Epidemiology

views updated May 21 2018

EPIDEMIOLOGY

Epidemiology is the indispensable basic science of public health. It provides the logical framework for the facts that enable public health officials to identify important public health problems and to delineate their dimensions. Epidemiologic methods are used to define these health problems; to classify, identify, and elucidate their causes; and to plan and evaluate rational control measures.

HISTORICAL DEVELOPMENT OF EPIDEMIOLOGY

In ancient times, epidemics and plagues were terrifying natural phenomena that cried out for a more rational explanation than that they were due to the wrath of god or the machinations of evil spirits. Hippocrates (c. 460377 b.c.e.) described many kinds of epidemics and in On Airs, Waters, Places and other writings. He offered empirical insights into environmental and behavioral factors that might be associated with certain kinds of disease. Although doctors and others engaged in the healing arts did not clearly understand the concept of contagion until several hundred years later, Fracastorius (c. 14781553) identified several ways that infections can be transmittedby direct contact, by what we now call droplet spread, and by contaminated clothing.

The science of epidemiology took root with empirical observations of epidemics and other causes of death. John Graunt (16201674), in London, complied the first mortality tables on England's bills of mortality. Statistical analyses of deaths due to childbed fever by Ignaz Semmelweiss (18181865) in Vienna in the early nineteenth century and of tuberculosis by Pierre Charles Alexandre Louis (17871872) in Paris demonstrated the power of numbers. In London, in 1848 and 1854, meticulous, logical examination of the facts and figures about cholera epidemics by John Snow (18131858) revealed the mode of communication of this deadly epidemic disease. Snow is regarded as the founder of modern epidemiology because of his use of such careful methods.

Until early in the twentieth century almost all epidemiology focused on communicable diseases, although Percivall Pott's (17141788) observations on cancer of the scrotum in chimney sweeps and James Lind's dietary experiment with fresh fruit to prevent scurvy (1975) were precursors of modern noncommunicable disease epidemiology and clinical trials, respectively. The use of epidemiology in studies of coronary heart disease and cancer in large-scale trials of many new preventive and therapeutic regimens, in nationwide surveys of health status, and in evaluation of health services came to the fore in the second half of the twentieth century. In the final quarter of the twentieth century, powerful computers, information technology, and more rigorous methodological approaches transformed epidemiology and made it a mandatory feature of clinical science as well as the most fundamental basic science of public health.

DEFINITION AND SCOPE

The word "epidemiology" was coined in the mid nineteenth century to describe the scientific study of epidemics. Its meaning has expanded over the years, and present-day epidemiology encompasses the study of all varieties of illness and injury as they affect defined groups of people. In 1983 a committee representing the International Epidemiological Association defined epidemiology as "the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to control of health problems." Study includes observation, surveillance, hypothesis-testing research projects, analysis of epidemiologic and other kinds of data, and certain other kinds of experiments. Distribution includes analysis of data according to the time scale over which events occur, the places where the events occur, and the categories of persons to whom they occur. Determinants are all the physical, biological, behavioral, social, and cultural factors that influence health. Health-related states or events include diseases, causes of death, behaviors such as the use of tobacco, reactions to preventive regimens, and provision and use of health services. Specified populations are those with identifiable characteristics such as known numbers and age groups. The ultimate aim and purpose of epidemiologyto promote, protect, and restore good healthis manifested in the "application of this study to control health problems."

Epidemiologists attempt to identify, measure, count, and control diseases, injuries, and causes of untimely death; and to relate these events to the associated inherited, environmental, and behavioral factors that cause or contribute to them. One of the great intellectual challenges of epidemiology is to dissect these factors and unravel their connections in order to identify exactly what is ultimately responsible for a particular disease or health problem.

RELATIONSHIP TO OTHER SCIENCES AND TECHNOLOGIES

The information used by epidemiologists comes from a diverse array of sources; draws on a wide range of sciences and technologies; and calls on the expertise of technologists and other people engaged in many kinds of crafts. Some connections are obviousthose with vital statistics, biostatistics, microbiology, immunology, and chemistry; with every clinical specialty from pediatrics to geriatrics and palliative care, and from family practice to hematology and neurosurgery. Other obvious connections are to the social and behavioral sciences, and, less obviously, to animal husbandry, wildlife biology, agricultural science, physics, atmospheric sciences, oceanography, engineering, town planning, education, law enforcement, communications technology, and the media. Epidemiology may be the most ecumenical of all the sciences. Probably no other branch of biomedical science has so many connections to such a wide range of other human activities.

RATES

The basis of all epidemiology is the comparison of groups of people. For these comparisons to be valid, it is necessary to convert raw numbers into rates. A rate is a fractionthe upper part (the numerator) is the number of people affected by the problem, event, or condition of interest; the lower part (the denominator) is the number of persons in the population who are at risk of experiencing the problem, event, or condition. Because the events normally continue over a long period, often indefinitely, rates are expressed in relation to a specified time. Since fractions are awkward to deal with, there is commonly a multiplier, and the rate, as shown in the following formula, is expressed in terms of so many per thousand, per hundred thousand, etc., in a specified time, usually a year, though shorter periods are used when circumstances warrant it:

In practice there are many variations in the ways rates are expressed, but the basic elements of events, population at risk, and time are common to all.

Rates have many uses. By comparing rates, epidemiologists can examine the experience of particular groups of people at specified times, in different cities, countries, or occupational groups. The observed differences are the basis for inferences about the reasons for these differences, and are used to test hypotheses about these reasons, possibly about the putative cause of a particular kind of cancer, for instance. In addition to the absolute requirement, for validity, of basing all comparisons on rates, another important use is in calculating the risks to individuals and groups of experiencing an event such as a heart attack, the occurrence of cancer, or traffic injury. Comparisons are often rendered invalid, or relatively unreliable, by differences among the populations being comparedoften because of failure to allow for various kinds of biases and confounding factors. A common problem stems from differences in the age composition of populations that are being compared. This problem is overcome by the procedure of age-adjustment. Another problem is that there may be important qualitative differences, such as health or employment status, between groups that are being compared.

The terms "incidence" and "prevalence" are often confused. Incidence refers to the number of new cases, events, or deaths, that occur in a specified time, usually one year. Prevalence refers to the total number of events or cases, both new and long-term, that are present at a particular point in time. Prevalence is therefore expressed as a number, not a rate, as there is no time dimension involved.

INVESTIGATING EPIDEMICS

An epidemic is the occurrence of a number of cases of a disease clearly in excess of normal expectation. This is usually a large number when the disease is one of the common infectious fevers, but even a single case of a dangerous contagious disease, such as typhoid, that has long been absent from a community should suffice to activate the highest level of epidemic surveillance and control measures. The occurrence of a small number of cases of a rare variety of cancer, closely clustered in time and space, may also signal an epidemic. Observational and analytic epidemiology blend in the investigation of epidemics. The investigation demands meticulous attention to detail in collecting information about all the cases of the condition, including mild and inconspicuous cases as well as those with florid manifestations, and must include details about all possible associated factors, such as dietary intake (this is especially important in outbreaks of food poisoning), occupation, living conditions, and unusual recent experiences. Particular attention is paid to the index casethe first identified case of a condition. In most infectious disease epidemics, this could be the case that introduced the infection into the affected community. Information is also gathered about healthy people in the same community, aimed at discovering why they have not been affected. Laboratory tests are used to confirm the diagnosis, identify the pathogenic organism, toxic chemical, or other agent that caused the disease; and to measure immunological responses among both sick and healthy people. Analyzing all this information often clarifies the nature and cause of an epidemic and points the way to appropriate control measures.

Investigating epidemics can be tedious because it needs to be so painstaking, even, seemingly, a boring routine task. But often it is as exciting as detective fiction. For example, an epidemic of typhoid in Aberdeen, Scotland, was traced eventually to a contaminated can of processed beef from Argentina. The can had been cooled in a river adjacent to the canning works. As the pressure inside the can fell when it cooled, a partial vacuum was created and typhoid bacilli in raw sewage in the water were sucked into the can through a minute hole.

Identifying the existence of an epidemic sometimes requires unusual vigilance and an ability to make connections among seemingly isolated events. An epidemic of lethal pneumonia among members of the American Legion who attended a convention in Philadelphia in 1976 and then returned to their hometowns before becoming ill, would not have come to light without rigorous scrutiny on the part of epidemic intelligence service officers of the Centers for Disease Control. Subsequent investigations led to the identification of Legionnaire's disease.

Techniques of molecular biology, notably DNA typing and the identification of biomarkers, have immensely enhanced the precision of epidemic investigation. It is now possible to trace the exact passage of an infectious agent such as the gonococcus or HIV (human immunodeficiency virus) as it is transmitted by direct contact from one individual to another among a group of people; or to show that coughing by a passenger with open pulmonary tuberculosis on a crowded airline flight can cause primary tuberculous infection of other passengers in the same compartment of that flight; or to determine how certain cancer-causing agents actually induce cancer. Books and articles in the popular press, notably the accounts by the journalist Berton Roueché in the New Yorker, and on some TV programs have communicated the excitement and challenge of epidemic investigations.

EPIDEMIOLOGIC METHODS

The application of several analytic methods of epidemiologic study has contributed substantially to scientists' understanding of disease causation, and therefore to control and prevention of many conditions of great public health importance. The available methods are observational epidemiology (the empirical study of naturally occurring events), analytic study, and, under carefully defined conditions and with all due ethical safeguards, human experimentation.

Observational Epidemiology. This method begins with surveillance of populations, using vital and health statisticsincluding analysis of death rates arranged by age, sex, locality, and cause of death. Other information is derived from notified cases of infectious diseases of public health importance, from registries of cancer or other diseases, and from hospital discharge statistics. Since 1957, the National Center for Health Statistics has conducted continuously a National Health Survey that has carried observational epidemiology to new levels of comprehensiveness.

It is often possible to make imaginative use of many other kinds of available information about defined population groups. Schools and many employers keep records of absences due to sickness, sometimes with reasons for these absences. Police and other law enforcement agencies keep records of calls to settle domestic disputes and of damage due to vandalism, which are useful indicators of social pathologies associated with local variations in the frequency of domestic violence, alcohol abuse, and broken families. All such sources of information combine to make it possible for epidemiologists and public health specialists to produce a multidimensional "community diagnosis." Serial measurements can indicate whether things are improving or getting worse, and in which ways these trends are moving for each of different indicators ranging from adolescent smoking behavior to reasons for long-term disability among the elderly.

Analytic Observational Studies. The possibilities of observational epidemiology are considerable, but not limitless. They are powerfully reinforced by analytic studies. The two main analytic methods are the case-control study and the cohort study.

Careful questioning of patients has enabled many doctors to make inferences about the influence of past experience on present disease. Percivall Pott, an eighteenth-century British physician, observed that cancer of the scrotum occurred among former chimney sweeps, and correctly inferred that it was associated with the accumulation of tar in the skin creases. Two hundred years later, in 1940, Norman Gregg, an ophthalmologist in Sydney, Australia, similarly inferred correctly that the cases he was seeing of congenital cataract must be associated with rubella (German measles), which their mothers had had during early pregnancy.

The case-control study is a systematic extension of routine medical history taking, in which the past histories of patients (the cases) suffering from the condition of interest are compared to the past histories of persons (the controls) who do not have the condition of interest, but who otherwise resemble the cases in such particulars as age and sex. Analysis of data about a series of cases and controls may show differences that are statistically significant. Sometimes only small numbers of cases are required to demonstrate significant differences between cases and controls. This makes the case-control study a suitable way to search for causes of rare conditions. For example, the discovery that a very rare form of liver cancer was strongly associated with occupational exposure to vinyl chloride required only four cases, and the fact that expectant mothers' use of artificial estrogens during early pregnancy can cause cancer of the vagina many years later in their daughters was based on a case-control study of eight cases. Although case-control studies can be flawed by the presence of biases that are often difficult or even impossible to eliminate, they are a valuable method of investigation because they can be done rapidly and at relatively little expense. The findings can be confirmed or refuted by more rigorous research methods such as cohort studies.

A cohort study is conducted by identifying individuals in a defined population who are exposed to varying levels of known or suspected risk for the condition of interest, such as cancer of the lung or coronary heart disease. The population is observed over a certain period, and the death and disease incidence rates among those exposed to varying and known levels of risk are compared. Cohort studies require large numbers, commonly many thousands, and prolonged observation, commonly years or even decades. They are therefore expensive, requiring a large and dedicated staff and maintenance of detailed records of very large numbers of people, only a small proportion of whom will ultimately fall ill and die of the condition of interest. Some cohort studies have become famous. The people of Framingham, Massachusetts, have been the subjects of cohort studies of coronary heart disease since 1948. In 1951, Richard Doll and Austin Bradford Hill began a cohort study of lung cancer in relation to tobacco smoking in a cohort of about 40,000 male British doctors. Later phases of this study have expanded to include risk factors for coronary heart disease and other chronic conditions; and by the late 1990s this study had yielded dramatic evidence of the relationship of tobacco smoking to cancers of many kindsand to coronary heart disease, chronic obstructive lung disease, and various other life-shortening chronic diseases.

It is possible to get results from a cohort study without waiting many years, if detailed information about exposure to risk factors at some time in the past is available in sufficient detail for a population of sufficient size. A method that permits reliable linking of past and present medical and other relevant records, such as a record linkage system, facilitates this approach. Record linkage is the process of relating information from two or more sets of recordscompiled years apart and sometimes by different agenciesabout the same individuals. A prerequisite is a way to identify individuals with a high degree of precision, such as a unique numbering system, or a system combining a sequence of digits for birthdate, birthplace, and sex; with alphabet letters or a phonetic code used for other details, such as the individual's mother's maiden name. Obviously the logistics of all this make it a costly method, but the yield can justify the expense. This method, known as an historical cohort study, has demonstrated the relationship of childhood cancer and developmental anomalies to prenatal maternal exposure to small diagnostic doses of X-rays. Record linkage and historical cohort studies have also demonstrated a relationship between birthweight and the occurrence of cardiovascular disease in middle age.

Experimental Epidemiology. In the 1920s, experimental epidemiology meant observing the passage of infectious pathogens in colonies of rodents, but such experiments are rarely necessary, and the meaning of the term has changed. Experiments in which the investigator studies the effects of intentional alteration or intervention in the course of a disease are now done on humans rather than experimental animals, usually using a randomized controlled-trial design.

The randomized controlled trial (RCT) is a form of human experimentation in which the subjects, usually patients, are randomly allocated to receive either a standard accepted therapeutic or preventive regimen, or an experimental regimen. The purpose of random allocation is to eliminate or minimize bias in the selection of subjects. This greatly enhances the validity of the results. Preferably, the subjects and those observing the trial's results should be unaware of which subjects are receiving the experimental and control regimens, thus eliminating the power of suggestion as a factor influencing the response of individuals to the regimen. There are very important ethical constraints on the conduct of randomized controlled trials. The only ethically acceptable justification for conducting a randomized controlled trial is uncertainty about which of the available regimens is the best, a state of affairs known as "equipoise." It is absolutely essential to obtain the genuinely informed consent of all human subjects on whom a trial is conducted.

CLINICAL EPIDEMIOLOGY AND EVIDENCE-BASED MEDICINE

In the final quarter of the twentieth century, physicians in clinical practice discovered the value of epidemiologic methods in enhancing the efficacy of treatment regimens, mainly through rigorous attention to the nature and quality of the evidence on which clinical decisions are based. Evidencebased medicine then moved into public health practice, where it is illuminating decisions about many aspects of public health practice, such as the most effective way to deploy public health nurses in a local health department.

OTHER RECENT ADVANCES

Epidemiology made spectacular progress in several other directions in the 1990s. One was in the application of molecular biology, resulting in what is sometimes called molecular epidemiology. Other advances have been made in genetic epidemiology, where the meeting of molecular genetics with public health, occupational and environmental health, and infant and child health has produced both exciting stories of great progress and difficult ethical and moral problems. What are scientists and physicians to do, for instance, with the newfound knowledge and technical capability to identify defective genes, especially genes that, in interaction with some environmental circumstances, can disqualify certain individuals from particular occupations and can render others ineligible for life insurance? Such dilemmas presage a testing time for society's values.

Another set of new challenges face epidemiologists who specialize in studies of risk management. The global environment is changing as the burden of greenhouse gases increases and leads to a rise in average global ambient temperatures, and remote sensing and climate models enable us to predict the likely future distribution of vector-borne diseases such as malaria, dengue, and schistosomiasis. A new realm of risk factor analysis is thus emerging, based on future health scenarios that incorporate climate models and in the most sophisticated applicationsinclude sets of models for future patterns of biodiversity, human settlements, and economic and industrial dynamics. In these ways epidemiologists are helping to plan the public health services that will be needed in the future.

John M. Last

(see also: Case-Control Study, Cohort Study, Cross-Sectional Study; Epidemiologic Transition; Graunt, John; Hippocrates of Cos; Mortality Rates; Notifiable Diseases; Pott, Percivall; Rates; Rates: Age-Adjusted; Record Linkage; Semmelweiss, Ignaz; Snow, John; Vital Statistics; and other articles on specific diseases mentioned herein )

Bibliography

Ashton, J., ed. (1994). The Epidemiological Imagination. Buckingham, UK: Open University Press.

Beaglehole, R.; Bonita, R.; and Kjellström, T. (1993). Basic Epidemiology. Geneva: World Health Organization.

Buck, C.; Llopis, A.; Nájera, E.; and Terris, M., eds. (1988). The Challenge of Epidemiology. Washington, DC: Pan American Health Organization.

Last, J. M., ed. (2000). A Dictionary of Epidemiology, 4th edition. New York: Oxford University Press.

Rothman, K. J., and Greenland, S., eds. (1998). Modern Epidemiology, 2nd edition. Philadelphia: Lippincott-Raven.

Roueché, B. (1954). Eleven Blue Men, and Other Narratives of Medical Detection. Boston: Little, Brown & Co.

Epidemiology

views updated May 21 2018

EPIDEMIOLOGY

Epidemiology is the study of the frequency, distribution, and determinants of disease in humans. Its aim is the prevention or effective control of disease. The term originated in the study of epidemics, rapidly spreading diseases that affect large numbers of a population (from the Greek epi meaning upon and demos meaning people). Epidemiology touches on ethics in two key areas: The need for competent and honest use of its information, and questions of responsibility raised by the global picture it presents of the health of humanity.

Speculation about the nature and causes of disease dates back to antiquity. The formal history of epidemiology, like that of statistics, begins with the systematic official recording of births and deaths in the seventeenth century, proceeding to the quantitative investigation of diseases with the emergence of scientific medicine in the nineteenth. Based on the theory of probability, statistical inference reached maturity in the early-twentieth century and gradually spread into a wide range of disciplines. Its application to medical research gave rise to biostatistics and contemporary epidemiology.

There is no clear division between the two fields. Epidemiology focuses more on public health issues and the need for valid population-based information, but it uses the theory and methods of biostatistics. Its practitioners tend to be individuals with primary interest and training in medicine or a related science, whereas biostatisticians come from mathematics. They work together as members of the medical research team, in the dynamic context of scientific advances and the latest information technology.

Modern Epidemiology

The mathematical approach to medicine, with the methodical tabulation of patient information on diseases and treatment outcomes, was introduced in the 1830s by the French physician Pierre C. A. Louis (1787–1872). As a notable result of his researches in Paris hospitals, his Numerical Method revealed the uselessness of bloodletting. Inspired by Louis, his British student William Farr (1807–1883) became the central figure in the development of vital statistics in England and the use of statistics to address public health concerns. Farr worked with John Snow (1813–1858), the physician who investigated the cholera epidemic sweeping through London in 1854. Snow's finding that the cholera poison was transmitted in contaminated water from the Broad Street pump was a milestone event in epidemiology and public health. Farr also provided guidance in statistics for Florence Nightingale (1820–1910) to support her work in hospital reform.

The existence of microbes was discovered in the late-seventeenth century by the Dutch lens grinder Antonie van Leeuwenhoek (1632–1723), who saw "animalcules, more than a million for each drop of water" through his microscope (Porter 1998, p. 225). The role of germs as causes of disease was established by Louis Pasteur (1822–1895), French chemist and founder of microbiology. Pasteur invented methods to isolate and culture bacteria, and to destroy them in perishable products by a heat treatment now called pasteurization. He found that inoculation by a weakened culture provided immunity, protection against the disease. This explained the earlier discovery of the English physician Edward Jenner (1749–1823) that vaccination with the milder cowpox protected against smallpox. (Vaccination comes from the Latin vacca meaning cow.) The German physician Robert Koch (1843–1910), founder of bacteriology, further developed techniques of isolating and culturing bacteria. He identified the germ causing anthrax in 1876, tuberculosis in 1882, and cholera in 1883. He contributed to the study of other major diseases, including plague, dysentery, typhoid fever, leprosy, and malaria.

Extensive public health measures of hygiene and immunization, along with the introduction of the sulfonamide drugs in the late 1930s and antibiotics in the 1940s, brought most infectious diseases under control. Attention turned to chronic diseases, by then the leading causes of morbidity and mortality—multicausal diseases with a long latency period and natural course. Two historic discoveries of the mid-twentieth century were tobacco use as a cause of lung cancer, and risk factors for heart disease. From the study of infectious and chronic diseases epidemiology has evolved into a multidimensional approach, defined by disease, exposure, and methods, with focus on new developments in medical science. Its many specialties include cancer, cardiovascular, and aging epidemiology, environmental, nutritional, and occupational epidemiology, clinical and pharmaco-epidemiology, and molecular and genetic epidemiology. With the sequencing of the human genome,

Table 1: Some Basic Terms of Epidemiology
SOURCE: Courtesy of Valerie Miké. Data in example from U.S. Census Bureau website and American Cancer Society (2004).
Measures of Morbidity and Mortality
• PREVALENCE (Burden of disease): Number of existing cases of a disease at a given point in time divided by the total population.
• INCIDENCE (Cumulative incidence, risk): Number of new cases of a disease during a given time period divided by the total population at risk.
• INCIDENCE RATE (Incidence density): Number of new cases of a disease during a given time period divided by the total person-time of observation.
• PERSON-TIME (usually person-years): Total disease-free time of all persons in the study, allowing for different starting dates and lengths of time observed
• CRUDE DEATH RATE: Number of deaths during a given time period divided by the total population.
• STANDARDIZED DEATH RATE: Crude death rate adjusted to control for age or other characteristic to allow valid comparisons using a standard population.
Example of Age-Adjusted Death Rates (2000 US Standard Population)
 AlaskaFloridaUnited States
Crude death rate/1,000 population (in 2000):4.610.38.9
Percent of population over age 65 (in 2000):5.717.612.4
Age-adjusted death rate/100,000 population (avg. for 1996–2000):   
Breast cancer25.225.627.7
Prostate cancer24.228.432.9
Prevalence, incidence, and death rates are expressed in units of a base (proportion mulitplied by base), usually per 1,000 or 100,000 population.
Table 2: Case-Control Study of Lung Cancer and Smoking
Smokers Lung CancerControlsOdds Ratio (ad/bc)
Historic study showing the association between cigarette smoking and lung cancer. No association would correspond to an odds ration of 1. P-values obtained by chi-square test for 2×2 tables.
SOURCE: Data from Doll and Hill (1950).
Males:Yes647(a)622(b)14.0
 No2(c)27(d)P<.00001
 Total649 649  
Females:Yes41(a)28(b)2.5
 No19(c)32(d)P<.05
 Total60 60  
Table 3: Cohort Study of Risk Factors for Coronary Heart Disease: Systolic Blood Pressure
Systolic BP (mmHg)Age 35–64Age 65–94
MenWomenMenWomen
Average annual incidence per 1,000 persons of coronary heart disease, by systolic blood pressure. Example of relative rist (RR): For men (35-64), systolic BP>180 relative to <120 mmHg, RR=22/7=3.1. No association would correspond to RR=1. Results of 30-year follow-up in historic Framingham Heart Study of risk factors for cardiovascular disease.
SOURCE: Adapted from Stokes et al. (1989).
<120731110
120–1391141913
140–1591672716
160–1792393415
>18022154931
Total Events516305244269

genetics is assuming increasing importance across all lines of inquiry. In its principles of studying human populations, epidemiology is related to psychology, sociology, and anthropology, all of which employ statistical inference.

Basic Concepts and Methods

Epidemiology may be descriptive or analytic. Descriptive epidemiology reports the general characteristics of a disease in a population. Its methods include case reports, correlational studies (to describe any association between potential risk factors and disease in a given database) and cross-sectional surveys (to determine prevalence of a disease and potential risk factors at a given point in time). Analytic epidemiology uses observational and experimental studies. The latter are clinical trials to test the effectiveness of interventions to treat or prevent a disease. But experimentation on humans is not ethically feasible for studying causes of disease. Observational research designs are thus the primary tools of epidemiology, the main types being case-control and cohort studies. After definition of some basic terms, these are discussed further below.

TABLE 4
Careful study is required to assess potential biases and confounding variables. General guidelines for establishing causality are provided by Hill's Criteria (Table 6).
Interpreting a Statistical Association
Possible Reasons for an Observed Statistical Association
SOURCE: Courtesy of Valerie Miké.
1.CHANCE: This is precisely the meaning of P-value, the probability that the observed outcome is due to chance.
2.BIAS: Systematic errors that distort the results, such as selection bias, recall bias, and observation bias.
3.CONFOUNDING: There is an extraneous, confounding variable (perhaps as yet unknown) that is related to the risk factor being studied and is an independent risk factor for the disease.
4.CAUSE-AND-EFFECT: The risk factor in the observed association is a cause of the disease.

MEASURES OF MORBIDITY AND MORTALITY. Some basic concepts of epidemiology are listed in Table 1. It is important to distinguish between the prevalence of a disease and its incidence. Prevalence signifies the amount of disease present at a point in time, such as the proportion of people with adult-onset diabetes in the United States on January 1, 2005. Incidence refers to new cases diagnosed during a given period of time, such as the proportion of U.S. adults diagnosed with diabetes in 2005. The denominator of incidence rate is person-time, a useful concept that allows for inclusion of subjects with different starting dates and lengths of time observed in a study. Causes of a disease can be investigated by observing incidence in a well-defined group of subjects without the disease, and patterns of disease incidence can be compared over time or populations.

Mortality is measured in terms of crude death rate, the actual proportion observed, or the standardized death rate, which involves adjustment for some characteristic. The example shows age-adjusted cancer death rates for the states of Alaska and Florida. Alaska has a much lower crude death rate than Florida, but its population is much younger. Both breast and prostate cancer are associated with older age, but after age-adjustment the two states are seen to have similar death rates for these two sites, both lower than the national average. The adjusted figures are meaningless in themselves, but provide for valid comparison of rates across groups and time. U.S. cancer death rates have been adjusted using the 2000 U.S. age distribution to make them comparable back to 1930 and ahead to the future.

OBSERVATIONAL RESEARCH DESIGNS: CASE-CONTROL AND COHORT STUDIES. A case-control study is retrospective: It identifies a group of people with the disease (cases) and selects a group as similar as possible to the cases but without the disease (controls). The aim is to determine the proportion of each group who were exposed to the risk factor of interest and compare them. Table 2 shows results of the case-control study of lung cancer and smoking reported in 1950 by Sir Richard Doll (b. 1912) and Sir Austin Bradford Hill (1897–1991), British pioneers of epidemiology and biostatistics. They identified 649 men and sixty women with lung cancer in twenty London hospitals and matched them with controls of the same age and sex but without lung cancer. The information they collected on all participants included their smoking history. The observed association, measured by the so-called odds ratio (the odds of smoking in cases over the odds of smoking in controls), was clearly statistically significant.

A cohort study is usually prospective. (It may be historical, if based on recorded past information.) It identifies a large group (cohort) of individuals who do not have the disease but for whom complete information is available concerning the risk factor(s) of interest; the cohort is then observed for the occurrence of the disease. A noted cohort design was the Framingham Heart Study, initiated by the U.S. Public Health Service in 1948 to identify risk factors for heart disease. Over 5,000 adult residents of Framingham, Massachusetts, men and women with negative test results for cardiovascular disease, agreed to join the study and undergo repeat testing at two-year intervals. The age and test measures at the start of each two-year period were used to classify subjects. Results of a thirty-year follow-up evaluation (part of a multivariate analysis including other risk factors and cardiovascular outcomes) are shown in Table 3, demonstrating a strong association between systolic blood pressure and incidence of coronary heart disease. Other suitable groups for cohort studies are members of professional groups, like doctors and nurses.

There are advantages and disadvantages pertaining to each research design, and the choice depends on the circumstances of the scientific question of interest. Any observed association then requires careful interpretation.

Association or Causation?

Possible reasons for an observed statistical association are listed in Table 4. Chance is simply the meaning of

TABLE 5
Proposed in 1884 by Robert Koch for bacteria, the original wording has been modified to include other microbes. Further versions use molecular biology as a tool to associate microbial agents with disease. Table is adapted from a leading textbook of medical microbiology.
Koch's Postulates for Establishing the Causes of Infectious Diseases, with Molecular Update
Koch's PostulatesMolecular Koch's Postulates*
*In addition, guidelines for establishing microbial disease causation in terms of the prevalence of the nucleic acid sequence of a putative pathogen in relation to disease status are given in the third column of the table from which this is taken.
SOURCE: Brooks et al. (2001), p. 134.
1.The microorganism should be found in all cases of the disease in question, and its distribution in the body should be in accordance with the lesions observed.1.The phenotype or property under investigation should be significantly associated with pathogenic strains of a species and not with nonpathogenic strains.
2.The microorganism should be grown in pure culture in vitro (or outside the body of the host) for several generations.2.Specific inactivation of the gene or genes associated with the suspected virulence trait should lead to a measurable decrease in pathogenicity or virulence.
3.When such a pure culture is inoculated into susceptible animal species, the typical disease must result.3.Reversion or replacement of the mutated gene with the wild type gene should lead to restoration of pathogenicity or virulence.
4.The microorganism must again be isolated from the lesions of such experimentally produced disease.  

the P-value, the probability that the association is due to chance. Bias refers to systematic errors that do not cancel out with larger sample size, but distort the results in one direction. For example, in a case-control study patients with the disease may be more likely to recall exposure to the risk factor than the controls, leading to recall bias. Bias is a serious problem in observational studies and needs to be assessed in the particular context of each research design. Confounding is the effect of an extraneous variable that is associated with the risk factor, but is also an independent risk factor for the disease. For example, an association between birth rank and Down's syndrome, the genetic disorder Trisomy 21 (an extra copy of chromosome 21) does not imply causality; the confounding variable is maternal age, which is associated with birth rank and is a known risk factor for the disease. There may also be confounding variables as yet unknown, but their potential effects must always be considered.

The establishment of causation is a long-debated problem in the philosophy of science. In the practical field of medicine, where life-and-death decisions must be made every day, there are guidelines to help assess the role of agents in the etiology of disease. When microbes were being identified as causes of devastating diseases in the late-nineteenth century, Robert Koch formulated postulates to prove that a particular microbe causes a given disease. Anticipated by his teacher Jacob Henle (1809–1885), these are also called Henle-Koch Postulates. They are shown in Table 5, along with current updates using molecular biology. The original version claims only necessary causation, not sufficient; the microorganism needs a susceptible host. Even more general, the molecular guidelines are expressed in terms of statistical association. But they are the organizing principle in contemporary studies of microbial etiology, crucial for the identification of newly emerging pathogens that may pose serious threats to public health.

Guidelines for establishing causality in observational studies are listed in Table 6. Formulated by Sir Austin Bradford Hill, they are based on criteria employed in the 1964 U.S. Surgeon General's Report to show that smoking causes lung cancer. Applied in a wider context, they are to be used primarily as an aid to exploration. In general there is no necessary or sufficient condition to establish causality from an observed association. Such conclusions result from a consensus of the scientific community.

Epidemiology and Ethics

The complex, probing methods of epidemiology yield tentative, partial, often conflicting results, replete with qualifications. Taken out of context by interest groups or the media, they can mislead and have harmful consequences. Their correct use requires professional competence and integrity. But beyond these issues of immediate concern, epidemiology plays a larger role. With its adjusted measures allowing comparison of health patterns over space and time, it provides a quantitative aerial video of the globe. Some of the images it presents are troubling.

TABLE 6
Formulated in 1965 by Sir Austin Bradford Hill, these are very general, tentative guidelines, with numerous exceptions and reservations. Aside from temporality, which may be considered part of the definition of causation, there is no necessary or sufficient criterion for establishing the causality of an observed association.
Hill's Criteria for Establishing Causality in Observational Studies
Aspects of Association to Consider
SOURCE: Hill (1965).
1.STRENGTH: Stronger associations more likely to be causal.
2.CONSISTENCY: Association is observed repeatedly in different populations under different circumstances.
3.SPECIFICITY: Disease outcome is specific to or characteristic of exposure.
4.TEMPORALITY: Exposure precedes disease.
5.BIOLOGIC GRADIENT: Monotone dose-response relationship (increase in exposure corresponds to increase in disease).
6.PLAUSIBILITY: Causal hypothesis is biologically plausible.
7.COHERENCE: Causal interpretation does not conflict with what is known about the natural history and biology of the disease.
8.EXPERIMENTAL EVIDENCE: Removal of putative cause in an intervention or prevention program results in reduction of disease incidence and mortality.
9.ANALOGY: Drug or chemical structurally similar to a known harmful agent may induce similar harmful effects.

There are now more obese than undernourished people living on earth, and their number is increasing rapidly in developing nations. According to a 2000 estimate of the World Health Organization (WHO), there are 220 million adults with Body Mass Index (BMI) <17, classified as undernourished, and over 300 million with BMI > 30, defined as obese. (BMI is weight in kilograms divided by height squared in meters.) This global epidemic of obesity, called globesity, brings with it the related conditions of diabetes, hypertension, and heart disease, and the problem is equally serious for children.

The harmful effects of tobacco have been known for half a century, and while the prevalence of smoking has been slowly declining in most industrialized nations, it has been rising steadily in the developing world. It is estimated that the number of smoking-related premature deaths worldwide, 5 million in 2000, will rise to 10 million per year by 2030, with 70 percent occurring in developing countries. Tobacco use will kill more people than the combined mortality due to malaria, pneumonia, tuberculosis, and diarrhea.

In the area of infectious diseases, after decades of exuberant optimism reality set in with the appearance of acquired immune deficiency syndrome (AIDS) in the 1980s. Homo sapiens lives in a sea of microbes and will never have total control. Vigilance for the emergence of disease-causing strains must be the aim, to detect outbreaks, identify pathogens and their mode of transmission, and seek control and prevention. Knowing the cause may not eliminate the disease, even when possible in principle, if (as with smoking) it hinges on human behavior. AIDS, for example, is preventable. Ongoing threats include new diseases from mutation or isolated animal reservoirs (Ebola, West Nile, severe acute respiratory syndrome [SARS]), resurgence of older strains, drug-resistance, targeted release through bioterrorism, and rapid spread through global travel.

At a WHO conference held in Geneva in November 2004, experts issued an urgent appeal for greater international cooperation, and called on governments to make pandemic preparedness part of their national security planning. Of particular concern was the new bird influenza strain A(H5N1), which could mutate and cause a pandemic on the scale of the influenza epidemic of 1918 that killed more than 20 million people. It is estimated that a new pandemic virus could spread around the world in less than six months, infecting 30 percent of the population and killing about 1 percent of those infected. The drug industry would have to prepare billions of doses of the influenza vaccine within weeks of an outbreak to halt its course. There are questions of what could possibly be feasible technologically, the huge investment needed, and the driving force to motivate the effort when it cannot be a matter of fiscal gain.

In March 2005 the British medical journal Lancet published four articles reporting on the appalling state of global infant health care. Four million babies die each year in the first month of life, nearly all in low- and middle-income nations. The highest numbers occur in south-central Asian countries, while the highest rates are generally in Sub-Saharan Africa. It is estimated that three-quarters of these deaths could be prevented with low-lost interventions. A similar number of babies are stillborn and 500,000 mothers die from pregnancy-related causes each year. The moral implications of this public health tragedy are overwhelming.

The problems humanity faces at the start of the twenty-first century are inseparable from dominant worldviews and the interplay of powerful economic and political forces. Epidemiology provides health-related information as a guide to action. Its proper use is an essential component of the Ethics of Evidence, proposed for dealing with the uncertainties of medicine in the framework of contemporary culture (Miké 1999, 2003). The Ethics of Evidence calls for integrating the best evidence of all relevant fields to promote human well-being, anchored in an inescapable moral dimension. Looking to the future, it urges all to be aware, to be informed, and to be responsible.

VALERIE MIKÉ

SEE ALSO Biostatistics;Health and Disease.

BIBLIOGRAPHY

Altman, Lawrence K. (2004). "Experts Urge Greater Effort on Vaccine for Bird Flu." New York Times, November 13,
p. A3.

American Cancer Society. (2004). Cancer Facts and Figures 2004. Atlanta, GA: Author. Includes report on worldwide effects of tobacco use.

Brooks, George F.; Janet S. Butel; and Stephen A. Morse. (2001). Jawetz, Melnick, & Adelberg's Medical Microbiology, 22nd edition. New York: McGraw-Hill.

Doll, Richard., and Austin Bradford Hill. (1950). "Smoking and Carcinoma of the Lung: Preliminary Report." British Medical Journal 2: 739–748.

Gail, Mitchell H., and Jacques Benichou, eds. (2000). Encyclopedia of Epidemiologic Methods. New York: John Wiley & Sons.

Hill, Austin Bradford. (1965). "The Environment and Disease: Association or Causation?" Proceedings of the Royal Society of Medicine 58: 295–300.

Hennekens, Charles H., and Julie F. Buring. (1987). Epidemiology in Medicine. Boston: Little, Brown.

Lawn, Joy E.; Simon Cousens; and Jelka Zupan. (2005). "Neonatal Survival 1: 4 Million Neonatal Deaths: When? Where? Why?" Lancet 365: 891–900. First report in the four-part series.

Lilienfeld, David E.; Paul D. Stolley; and Abraham M. Lilienfeld. (1994). Foundations of Epidemiology, 3rd edition. New York: Oxford University Press.

Miké, Valerie. (1999). "Outcomes Research and the Quality of Health Care: The Beacon of an Ethics of Evidence." Evaluation & the Health Professions 22: 3–32. Commentary by Edmund D. Pellegrino, "The Ethical Use of Evidence in Biomedicine," is included in this issue.

Miké, Valerie. (2003). "Evidence and the Future of Medicine." Evaluation & the Health Professions 26: 127–152.

Porter, Roy. (1998). The Greatest Benefit to Mankind: A Medical History of Humanity. New York: W. W. Norton.

Rothman, Kenneth J., and Sander Greenland. (2000). "Hill's Criteria for Causality." In Encyclopedia of Epidemiologic Methods, eds. Mitchell H. Gail, and Jacques Benichou. New York: John Wiley & Sons.

Stokes, Joseph III; William B. Kannel; Philip A. Wolf; et al. (1989). "Blood Pressure as a Risk Factor for Cardiovascular Disease: The Framingham Study—30 Years of Followup." Hypertension 13(Supplement I): 113–118.

INTERNET RESOURCE

Controlling the Global Obesity Epidemic. World Health Organization (WHO). Updated September 2003. Available from http://www.who.int/nut/obs.htm. From the organization's Nutrition pages.

Epidemiology

views updated Jun 27 2018

Epidemiology

Introduction

History and Scientific Foundations

Applications and Research

Impacts and Issues

Primary Source Connection

BIBLIOGRAPHY

Introduction

Epidemiology is the study of the causes and distribution of illness and injury. It constitutes the scientific underpinning of public health practice. According to noted British epidemiologist Sir Richard Doll (1912–2005), “Epidemiology is the simplest and most direct method of studying the causes of disease in humans, and many major contributions have been made by studies that have demanded nothing more than an ability to count, to think logically and to have an imaginative idea.” In practice, epidemiology is applied in the three main areas of public health: safety and injuries, chronic disease, and infectious disease. This article will emphasize examples and applications in infectious disease epidemiology.

History and Scientific Foundations

The first physician known to consider the fundamental concepts of disease causation was the ancient Greek Hippocrates (c.460—c.377 BC), when he wrote that medical thinkers should consider the climate and seasons, the air, the water that people use, the soil and people's eating, drinking and exercise habits in a region. Subsequently and until recent times, these causes of diseases were often considered, but not quantitatively measured. In 1662, John Graunt (1620–1674), a London haberdasher, published an analysis of the weekly reports of births and deaths in London, the first statistical description of population disease patterns. Among his findings, he noted a higher death rate for men than women, a high infant mortality rate, and seasonal variations in mortality. Graunt's study, with its meticulous counting and disease pattern description, set the foundation for modern public health practice.

Graunt's data collection and analytical methodology was furthered by the physician William Farr, who assumed responsibility for medical statistics for England and Wales in 1839 and set up a system for the routine collection of the numbers and causes of deaths. In analyzing statistical relationships between disease and such circumstances as marital status, occupations such as mining and working with earthenware, elevation above sea level and imprisonment, he addressed many of the basic methodological issues that contemporary epidemiologists deal with. These issues include defining populations at risk for disease and the relative disease risk between population groups, and considering whether associations between disease and the factors mentioned above might be caused by other factors, such as age, length of exposure to a condition, or overall health.

A generation later public health research came into its own as a practical tool when another British physician, John Snow (1813–1858), tested the hypothesis that a cholera epidemic in London was being transmitted by contaminated water. By examining death rates from cholera, he realized that they were significantly higher in areas supplied with water by the Lambeth and the Southwark and Vauxhall companies, which drew their water from a part of the Thames River that was grossly polluted with sewage. When the Lambeth Company changed the location of its water source to another part of the river that was relatively less polluted, rates of cholera in the areas served by that company declined, while no change occurred among the areas served by the Southwark and Vauxhall. Areas of London served by both companies experienced a cholera death rate that was intermediate between the death rates in the areas supplied by just one of the companies. The geographic pattern of infections was carefully recorded and plotted on a map of London. In recognizing the grand but simple natural experiment posed by the change in the Lambeth Company water source, Snow was able to make a uniquely valuable contribution to epidemiology and public health practice.

After Snow's seminal work, investigations by epidemiologists have come to include many chronic diseases with complex and often still unknown causal agents, and the methods of epidemiology have become similarly complex. Today researchers use genetics, molecular biology, and microbiology as investigative tools, and the methods used to establish relative disease risk make use of the most advanced statistical techniques available. Yet, reliance on meticulous counting and categorizing of cases and the imperative to think logically and avoid the pitfalls in mathematical relationships in medical data remain at the heart of all of the research used to show elevated disease risk in population subgroups and to prove that medical treatments are safe and effective.

Basic Epidemiological Concepts and Terms

The most basic concepts in epidemiology are the measures used to discover whether a statistical association exists between various factors and disease. These measures include various kinds of rates, proportions, and ratios. Mortality (death) and morbidity (disease) rates are the raw material that researchers use in establishing disease causation. Morbidity rates are most usefully expressed in terms of disease incidence (the rate with which members of a population or research sample contract a disease) and prevalence (the proportion of the group that has a disease over a given period of time).

WORDS TO KNOW

INCIDENCE: The number of new cases of a disease or injury that occur in a population during a specified period of time.

MORBIDITY: The term “morbidity” comes from the Latin word morbus, which means sick. In medicine it refers not just to the state of being ill, but also to the severity of the illness. A serious disease is said to have a high morbidity.

MORTALITY: Mortality is the condition of being susceptible to death. The term “mortality” comes from the Latin word mors, which means “death.” Mortality can also refer to the rate of deaths caused by an illness or injury, i.e., “Rabies has a high mortality.”

NOTIFIABLE DISEASES: Diseases that the law requires must be reported to health officials when diagnosed, including active tuberculosis and several sexually transmitted diseases; also called reportable diseases.

PREVALENCE: The actual number of cases of disease (or injury) that exist in a population.

SURVEILLANCE: The systematic analysis, collection, evaluation, interpretation, and dissemination of data. In public health, it assists in the identification of health threats and the planning, implementation, and evaluation of responses to those threats.

The most important task in epidemiology is the assessment or measurement of disease risk. The population at risk is the group of people that could potentially contract a disease, which can range from the entire world population (e.g., at risk for the flu) to a small group of people within a remote and isolated community (e.g., at risk for contracting a particular, ecologically restricted parasite). The most basic measure of a population group's risk for a disease is relative risk—the ratio of the prevalence of a disease in one group with particular biological, demographic, or behavioral characteristics to the prevalence in another group with different characteristics.

The simplest measure of relative risk is the odds ratio, which is the ratio of the odds that a person in one group has a disease to the odds that a person in a second, comparator group has the disease. The odds for contracting a disease are the ratio between the proportion of people in a population group that share particular characteristics that put them at risk for a disease to the proportion of people in a reference or control population (often the general population in a certain region or jurisdiction). For example, patients with chronic obstructive pulmonary disease (COPD), an inflammatory condition of the lungs associated with smoking and long exposure to air pollution, are at significantly greater risk of contracting community-acquired pneumonia (CAP) compared to a general population group matched on age and gender. Thus in a sample of subjects that includes both COPD patients and subjects who do not have COPD, epidemiologists expect that the odds ratio for the COPD patients contracting CAP would be significantly greater than 1.0.

The mortality rate is the ratio of the number of deaths in a population, either in total or disease-specific, to the total number of members of that population, and is usually given in terms of a large population denominator, so that the numerator can be expressed as a whole number. Thus, in 1982, the number of deaths from all causes was 1,973,000 and number of people in the United States was 231,534,000, yielding a death rate from all causes of 852.1 per 100,000 per year. That same year there were 1,807 deaths from tuberculosis yielding a disease-specific mortality rate of 7.8 per million per year.

Assessing disease frequency is more complex because of the factors of time and disease duration. For example, disease prevalence can be assessed at a point in time (point prevalence) or over a period of time, usually a year (period prevalence, annual prevalence). This is the prevalence that is usually measured in illness surveys that are reported to the public in the news. Researchers can also measure prevalence over an indefinite time period, as in the case of lifetime prevalence, which is the prevalence of a disease over the course of the entire lives of the people in the population under study up to the point in time when the researchers make the assessment. Researchers calculate this by determining for every person in the study sample whether or not he or she has ever had the disease, or by checking lifetime health records for everybody in the population for the occurrence of the disease, counting the occurrences, and then dividing by the number of people in the population.

The other basic measure of disease frequency is incidence, the number of cases of a disease that occur in a given period of time. Incidence is a critical statistic in describing the course of a fast-moving epidemic, in which medical decision-makers must know how quickly a disease is spreading. The incidence rate is the key to public health planning because it enables officials to understand what the prevalence of a disease is likely to be in the future. Prevalence is mathematically related to the cumulative incidence of a disease over a period of time as well as the expected duration of a disease, which can be a week in the case of the flu or a lifetime in the case of juvenile onset diabetes. Therefore, incidence not only indicates the rate of new disease cases, but is the basis of the rate of change of disease prevalence.

Epidemiologists use statistical analysis to discover associations between death and disease in populations and various factors—including environmental (e.g., pollution), demographic (age and gender), biological (e.g., body mass index or “BMI” and genetics), social (e.g., educational level), and behavioral (e.g., tobacco smoking, diet or type of medical treatment)—that could be implicated in causing disease.

Familiarity with basic concepts of probability and statistics is essential in understanding health care and epidemiological research. Statistical associations take into account the role of chance in contracting disease. Researchers compare disease rates for two or more population groups that vary in their environmental, genetic, pathogen exposure, or behavioral characteristics and observe whether a particular group characteristic is associated with a difference in rates that is unlikely to have occurred by chance alone.

Applications and Research

Applications in Public Health Practice

Certain concepts are basic to infectious disease epidemiology. These include the infectious agent, which is the organism that can develop within a human host and be passed along to other people via a particular mode of transmission, for example by air, food, or sexual intercourse. Infectious diseases have geographic scope or occurrence, and take a certain length of time to result in disease symptoms called the incubation period. After this incubation period, there is a period during which the individual can pass the infection along to others, called the period of communicability of the disease. The infectivity of a disease is the probability that an infected individual can pass the infection to an uninfected person, and the virulence of an infectious agent is the relative power and pathogenicity possessed by the organism. Populations of animals or human groups that harbor the infectious agent constitute a reservoir of the disease, and an organism such as a tick or insect that carries the infectious agent from such a reservoir to vulnerable individuals is called a vector.

Once the epidemic is underway, public health officials must begin attempts to control it even as they continue to gather epidemiological information about its cause and distribution. These control efforts consist of preventive measures for individuals and groups, which are measures designed to prevent further spread of the disease, and treatment in order to minimize the period of communicability of the infection, as well as reduce morbidity and mortality. Control of patient contacts and the immediate environment are foremost among such preventive measures, which can extend to patient isolation and observance of universal precautions, including handwashing, wearing of gloves and masks, and sterilization in dangerous instances. Epidemic measures, including the necessary abrogation of civil rights as in quarantines, are sometimes necessary to contain a communicable disease that has spread within an area, state, or nation. The epidemic may have disaster implications if effective preventive actions are not initiated, and the scope of actions can be international, requiring the coordination of disparate public health capabilities across national boundaries.

Screening Programs

Screening a community using relatively simple diagnostic tests is one of the most powerful tools that healthcare professionals and public health authorities have in preventing or combating disease. Familiar examples of screening include HIV testing to help prevent AIDS, tuberculin testing to screen for tuberculosis, and hepatitis C testing by insurers to detect subclinical infection that could result in liver cirrhosis over the long term. In undertaking a screening program, authorities must always judge whether the benefits of preventing the illness in question outweigh the costs and the number of cases that have been mistakenly identified, called false positives.

The ability of the test to identify true positives (sensitivity) and true negatives (specificity) makes screening a valuable prevention tool. However, the usefulness of the screening test is proportional to the disease prevalence in the population at risk. If the disease prevalence is very low, there are likely to be more false positives than true positives, which would cast doubt on the usefulness and the cost-effectiveness of the test. For example, if the prevalence of a disease in the population is only 2% and a test with a false positive rate of 4% is given to everyone (normally a good rate for a screening test), then individuals falsely identified as having the disease would be twice as frequent as individuals accurately identified with the disease. This would render the test results virtually useless. Public health officials deal with this situation by screening only population subgroups that have a high risk of contracting the disease. In infectious disease, screening tests are valuable for infections with a long latency period, which is the period of time during which an infected individual does not show disease symptoms, or which have a lengthy and ambiguous symptomatic period.

Clinical Trials

Clinical trials are the experimental branch of epidemiology in which scientific sampling with randomized selection of research subjects is combined with prospective study design and experimental controls involving a placebo or comparator active treatment control group. The statistical analysis used in clinical trials is similar to what is used in other types of epidemiological studies, usually simple counting of cases that improve or deteriorate and comparisons of morbidity and mortality rates between the trial treatment groups.

Clinical trials in infectious disease are most common when a significant follow-up period is available. One such trial was a rigorous test of the effectiveness of condoms in HIV/AIDS prevention. This experiment was reported in 1994 in the New England Journal of Medicine. Although in the United States and Western Europe the transmission of AIDS has been largely within certain high-risk groups, including drug users and homosexual males, worldwide the predominant mode of HIV transmission is heterosexual intercourse. The effectiveness of condoms to prevent HIV transmission is generally acknowledged, but even after more than 25 years of the growth of the epidemic, many people remain ignorant of the scientific support for their preventive value.

A group of European scientists conducted a prospective study of HIV negative subjects that had no risk factor for AIDS other than having a stable heterosexual relationship with an HIV infected partner. A sample of 304 HIV negative subjects (196 women and 108 men) was followed for an average of 20 months. During the trial 130 couples (42.8%) ended sexual relations, usually due to the illness or death of the HIV-infected partner. Of the remaining 256 couples that continued having exclusive sexual relationships, 124 couples (48.4%) consistently used condoms. None of the seronegative partners among these couples became infected with HIV. On the other hand, among the 121 couples that inconsistently used condoms, the seroconversion rate was 4.8 per 100 person-years.

Because none of the seronegative partners among the consistent condom-using couples became infected, this trial presents extremely powerful evidence of the effectiveness of condom use in preventing AIDS. On the other hand, there appear to be several main reasons why some of the couples did not use condoms consistently. Therefore, the main issue in the journal article shifts from the question of whether or not condoms prevent HIV infection—they clearly do—to the issue of why so many couples do not use condoms in view of the obvious risk. Couples with infected partners that got their infection through drug use were much less likely to use condoms than when the seropositive partner got infected through sexual relations. Couples with more seriously ill partners at the beginning of the study were significantly more likely to use condoms consistently. Finally, the longer the couple had been together before the start of the trial was positively associated with condom use.

Impacts and Issues

The control of infectious disease is an urgent mission for epidemiologists employed in various state and federal public health agencies and their partners in private industry and research foundations. The American Public Health Association (APHA) provides guidance for the epidemiology and control of more than 100 communicable diseases that confront public health practitioners at present.

Infectious disease epidemiology requires accurate and timely incidence and prevalence data such as is provided with comprehensive disease surveillance of usual and emerging diseases. Although the development of an organized surveillance system is critical to the provision of these data, the system's effectiveness depends on the willingness and ability of health care providers to detect, diagnose, and report the incidence of cases that the system is supposed to track. A reporting system functions at four levels: 1) the basic data is collected in the local community where the disease occurs; 2) the data are assembled at the district, state, or provincial levels; 3) information is aggregated under national auspices (e.g., the Centers for Disease Control and Prevention (CDC) in the United States); and 4) for certain prescribed diseases, the national health authority reports the disease information to the World Health Organization (WHO).

The reporting of cases at the local level is mandated for notifiable illnesses that come to the attention of healthcare providers. Case reports provide patient information, suspect organisms, and dates of onset with basis for diagnosis, consistent with patient privacy rights. Collective case reports are compiled at the district level by diagnosis stipulating the number of cases occurring within a prescribed time. Any unusual or group expression of illness that may be of public concern should be reported as an epidemic, whether the illness is included in the list of notifiable diseases and whether it is a well-known identified disease or an unknown clinical entity.

Because of the emergence or re-emergence of HIV/AIDS and resistant strains of tuberculosis, malaria, gonorrhea, and E. coli among others, infectious disease epidemiology, once thought to be waning in importance due to significant advances in public sanitation and immunization programs, has re-emerged as an urgent challenge. Infectious diseases currently threaten to destroy social order in some developing nations and pose extremely difficult public health problems even in the wealthiest societies. Hantavirus infections, thought to be a serious problem primarily in Asia, have emerged as an epidemic in the southwestern United States. Lyme disease continues to afflict ever larger populations in the Northeast United States; Ebola virus has jumped from monkeys to humans in Africa and pneumococci are becoming resistant to the antibiotics used to treat infections.

Air travel has created the situation in which travelers can return home from areas where particular pathogens are endemic within the incubation period of every infectious disease, which can potentially precipitate an epidemic.

Primary Source Connection

John Snow (1813–1858) was an English physician who made great advances in the understanding of both anesthetics and the spread of disease, especially cholera.

The first pandemic, which reached Great Britain in 1831, caused as much fear and panic as tuberculosis did in the early twentieth century and HIV/AIDS does today. The death rate from cholera was over 50 percent and medical opinion was sharply divided as to the cause. At the time, John Snow was a doctor's apprentice gaining his first experience with the disease, noting its symptoms of diarrhea and extreme dehydration.

The germ theory of disease, which holds that viruses and bacteria are the causative infectious agents of diseases such as yellow fever, smallpox, typhoid, cholera, and others, was in its infancy at this time. Some doctors accepted the hypothesis of contagion in which disease spreads from one person to another. Others assumed that “miasmata” or toxins in the air, spread disease.

Snow first began a serious scientific investigation of cholera transmission during the 1848 London epidemic. In his classic essay, On the Mode of Communication of Cholera, published on August 29, 1849, he postulated that polluted water was a source of cholera—especially water contaminated by the waste of an infected person, a not-uncommon occurrence at the time. When an outbreak erupted a few years later in central London at the end of August 1854, close to where Snow himself lived, he resumed his research.

The historical claim that Snow removed the pump handle himself—which would, of course, have stopped exposure to the contaminated water—has little evidence and may be a myth. Snow recommended its removal, but the actual removal was probably done by the local curate, Henry Whitehead, several days after the outbreak began.

It is partially thanks to John Snow's work in the Broad Street area that Britain suffered fewer major outbreaks of cholera after this time. An influential figure in medical circles, he had been elected president of the Medical Society of London in 1855. Fortunately for British public health, the successful proof of his theory on the transmission of cholera—from person to person via contaminated water— took hold, and the “environmental” theory eventually died away. Although the actual causative agent, the bacterium Vibrio cholerae, would not be identified until 1883, Snow's preventive methods worked. Indeed, they are still effective today, for despite the advent of vaccination and antibiotics, handwashing and the avoidance of contaminated food and water are still fundamental ways of preventing infection.

Because Snow based his investigation on the idea of germ theory, which French microbiologist Louis Pasteur (1822–1895) would later prove, he used a scientific approach and epidemiological study of cholera victims to validate his hypothesis. As his case notes amply demonstrate, much of his research was driven by his patients’ visible suffering.

See AlsoDemographics and Infectious Disease; Public Health and Infectious Disease; Notifiable Diseases.

BIBLIOGRAPHY

Books

Bennenson, A.S., ed. Control of Communicable Diseases Manual. 16th ed. Washington, DC: American Public Health Association, 1995.

Centers for Disease Control. Tuberculosis Statistics: States and Cities, 1984. Atlanta: Centers for Disease Control, 1985.

Graunt, J. Natural and Political Observations Made upon the Bills of Mortality. London, 1662. Reprinted by Johns Hopkins Press, 1939.

Hennekens, C.H., and J.E. Buring. Epidemiology in Medicine. Boston: Little, Brown, 1987.

Hippocrates. On Airs, Waters and Places. Shephard, David A.E. John Snow: Anaesthetist to a Queen and Epidemiologist to a Nation. Cornwall, Prince Edward Island, Canada: York Point, 1995.

Periodicals

De Vincenzi, I. “A Longitudinal Study of Human Immunodeficiency Virus Transmission by Heterosexual Partners.” New England Journal of Medicine 331 (August 11, 1994): 341–346.

UCLA. Department of Epidemiology. School of Public Health. “John Snow.” <http://www.ph.ucla.edu/epi/snow.html> (accessed March 30, 2007).

Kenneth LaPensee

Epidemiology

views updated May 29 2018

Epidemiology

BIBLIOGRAPHY

Epidemiology is a branch of ecology that includes both the sum of what is known concerning the differential distribution of disease throughout a population and the techniques for collecting and analyzing data dealing with the prevalence and incidence of disease among different social groups. While originally limited to the study of epidemics or the spread of contagious disease, epidemiology today covers all types of disease, degenerative as well as communicable, and all population characteristics—social and psychological as well as biological and physical—that may help to describe or explain the prevalence of disease.

Methods of epidemiology . In the broad sense of the term, epidemiology deals with the occurrence and distribution of disease among different population groups, whether human, animal, or plant. The discovery or description of these differences has been called descriptive, or comparative, epidemiology, whereas the analysis of the causal factors and conditions producing these differences is usually referred to as explanatory, or analytic, epidemiology. As epidemiology becomes increasingly concerned with the study of the origin and course of disease, rather than solely with its distribution, this distinction is gradually disappearing.

Because of its emphasis upon the relationship between environmental factors and disease, epidemiology is properly regarded as a major branch of human ecology, or “the study of the relations between man and his environment, both as it affects him and as he affects it” (Rogers 1960, p. vii). In general, three main sets of interacting factors form the focus of epidemiological interest: the host, or human individual varying in genetic resistance, susceptibility, and degree of immunity to the disease; the agent, or carrier of the disease, including any adverse process, whether it be an excess, deficiency, or interference of a microbial, toxic, or metabolic factor, and varying according to infectivity, virulence, and pathogenesis; and the environment, or surrounding medium, social as well as physical, which affects both the susceptibility of the host, the virulence of the agent or disease process, and the quantity and quality of contact between host and agent (Paul 1950, pp. 53-54). These three sets of factors do not exist in any simple one-to-one relationship but maintain a complex, ever-changing balance. The occurrence of disease, especially mass disease, is the result of a multiplicity of causal factors, each of which contributes to, rather than accounts for, the appearance of the disease.

Epidemiological knowledge consists of the available facts and theories concerning the relationships between these three factors and the various disease entities and health conditions. Social epidemiology, as a subdivision of epidemiology, concentrates on the social, as opposed to the physical or biological, factors in the incidence and prevalence of disease. In the case of the chronic, degenerative diseases and the mental and behavioral disorders, both of which constitute primary targets of modern epidemiology, distinctions between host, agent, and environmental factors and between social and biological or physical factors are becoming increasingly difficult to maintain.

As a research method, epidemiology refers to “the application of scientific principles to investigations of conditions affecting groups in the population [constructive epidemiology]” (Clark [1953] 1958, p. 65). Predominantly, this involves the observation of the occurrence of disease under natural conditions in whole populations, as opposed to clinical or laboratory investigations. Epidemiological method, for the most part, uses the research techniques of the population survey to discover the relationship between the occurrence of disease and the presence of various biological, physical, and social factors. The kind of “proof” that it tries, for the most part, to obtain is statistical association between the presumed “causal” factor and the occurrence of the disease. Dawber and Kannel (1963, pp. 433-434) have spoken of “macroscopic” studies, which correlate rates of a disease with other statistical measures for an area or population group (ecological correlations), as contrasted with “microscopic” studies, which correlate personal characteristics with the presence or absence of disease within the individual (individual correlations). Experimental epidemiology, involving the controlled introduction of epidemic conditions into populations of experimental animals in the laboratory (Greenwood 1932), field experiments to test the efficacy of various immunizing agents, or various types of preventive measures (MacMahon et al. 1960, pp. 268-279), represents an attempt to apply the experimental method to epidemiological problems.

Historical background . The scope of epidemiology, which was “originally concerned only with epidemics, … was extended first to include infectious diseases which do not ordinarily occur in epidemic form, such as leprosy, syphilis, and tuberculosis, and later to noninfectious diseases” (Doull 1952, p. 76). The birth of epidemiology as we know it may be traced back to England in the late seventeenth century, when John Graunt in 1662 developed the first mortality tables. However, it was not until the mid-nineteenth century that men like Johann Sussmilch and Adolphe Quetelet utilized these statistics to help identify etiological factors in disease. The major emphasis of epidemiology under such eminent pioneers as John Snow (cholera), Peter Panum (measles), William Budd (typhoid), and Kenneth Maxcy (endemic typhus) was upon the discovery of host, agent, and environmental factors associated with the spread of these highly contagious diseases, or what has been called “the mass-phenomena of infectious diseases” (see Frost 1910-1939).

The dramatic conquest of the infectious diseases in the present century, together with the growing importance of the chronic, degenerative diseases, soon made it apparent that epidemiology could no longer be restricted to epidemics. As a matter of fact, epidemiological studies of nutritional (James Lind on scurvy) and occupational (Henry B. Baker on lead colic) diseases had already demonstrated the applicability of epidemiological method to noninfectious diseases. The use of statistical associations based upon population surveys became one of the foremost methods for studying the occurrence of cancer, cardiovascular disease, and mental illness and for the difficult task of identifying specific etiological agents. Today, the value of epidemiological research for the study of all diseases is well established (James & Greenberg 1957).

Uses of epidemiology . As a standard tool of medical investigation, epidemiology has been brought to bear upon almost all aspects of the prevention and treatment of disease. Morris (1957) has listed seven fundamental applications: the determination of individual risks on the basis of morbidity tables and cohort analysis—for example, the chances of a forty-year-old male getting cancer; the securing of data on subclinical and undetected cases; the identification of syndromes or clusters of symptoms; the determination of historical trends of disease; the diagnosis of community health needs and resources; program planning, operation, and evaluation; and the search for causes of disease. Similar uses are described by Breslow (1957) for a large-scale epidemiological survey of chronic diseases in California. These include a demographic description of the changing population composition, a broad picture of the state of health and illness in the community, more extensive knowledge about disease prevalence, data on the utilization of health services, case rosters for follow-up investigations, and data on etiological factors. Thus, epidemiology provides a large portion of the scientific base for public health practice.

The diversity of these applications would suggest that epidemiological surveys are often combined, or confused, with general community health surveys. A survey that asks questions about health conditions and medical care of a population sample does not automatically become an epidemiological study. From a more rigorous point of view, the major contribution of epidemiological research should be in the development and testing of hypotheses concerning specific factors that may influence the distribution of some particular disease in a defined population. On the basis of existing knowledge, theory, or observation, the epidemiologist identifies subgroups of the population believed to have varying incidence rates of the disease being investigated. He then hypothesizes certain etiological factors related to the disease and also believed to differ among the subgroups being studied. By means of a field survey or the analysis of existing data, he then tests the direction and degree of association between the occurrence of the disease and the presence or absence of the group characteristic hypothesized as the etiological factor.

Epidemiology and social science . Epidemiology has theoretical and methodological ties to the social sciences. Both the epidemiologist and the social scientist are concerned with demography and ecology—the relationship of man to his environment (Fleck & lanni 1958). When the environment includes sociocultural factors as possible “causes” of disease, either indirectly (as in the case of poverty leading to malnutrition or unsanitary living conditions) or directly (as in the case of emotional disturbance leading to mental disease or addictive disorders, such as drinking and alcoholism or drug addiction), then all three basic components of epidemiology—host, agent, and environment—take on important social dimensions (King 1963). Epidemiology is becoming increasingly concerned with “the social component of environment … that part which results from the association of man with his fellow man … the attainments, beliefs, customs, traditions, and like features of a people” (Gordon 1952, pp. 124-125). In the current era of chronic, degenerative diseases, in which an individual’s whole way of life may become more important than any single infectious agent in the disease process, social factors become a primary target for epidemiological investigation.

Methodologically, both the epidemiologist and the social scientist rely heavily upon the population survey and field experiment. Similar problems of research design confront both groups, while technical considerations such as sampling, questionnaire construction, interviewing, and multivariate analysis are objects of mutual methodological interest (Wardwell & Bahnson 1964).

Recent research . All major diseases today are the subject of epidemiological research, and almost all of these include, at the minimum, such social groupings as sex, age, marital status and family composition, occupation, socioeconomic status, religion, and race. In addition, many studies are specifically aimed at the investigation of social factors, such as social stress, as possible etiological agents in the occurrence of the disease. Comprehensive reviews have been prepared by Clock and Lennard (1956) on hypertension, Graham (1960) on cancer, Mishler and Scotch (1963) on schizophrenia, Dawber and others (1959) on heart disease, Jaco (1960) and Hoch and Zubin (1961) on mental disease, Suchman and Scherzer (1960) on childhood accidents, King and Cobb (1958) on rheumatoid arthritis, among others. The state of knowledge in this field is advancing rapidly, and the findings of epidemiological surveys appear regularly in such periodicals as the American Journal of Public Health and the Journal of Chronic Diseases.

In general, these studies reveal a large number of significant differences in the occurrence of disease among different subgroups of the population (Pemberton 1963). For example, coronary artery disease is found to vary according to such sociocultural variables as occupation, economic status, race, and rural-urban residence. Cancer of the uterine cervix occurs much less frequently among Jewish women; men are more likely to incur cardiovascular disease; and mental illness is found more often among the lower socioeconomic groups. On a more psychological level, insecurity and stress tend to be associated with a higher incidence of mental illness, alcoholism, narcotics addiction, heart disease, arthritis, and a host of psychosomatic conditions (Leighton 1959). Perhaps the most famous of these epidemiological correlations deals with the association between smoking behavior and lung cancer (Dorn & Cutler 1958).

Some problems of research design . The major conceptual and methodological problems in epidemiological research stem from its dependence, by and large, upon associational evidence. The basic research design of epidemiological method consists in the comparison of two groups, each with varying rates of a disease, with respect to other characteristics hypothesized as explanatory of these varying disease rates. This is essentially an ex post facto form of survey research and one that may undertake demographic studies of existing vital statistics or several other types of study using data specially gathered for the purpose. These can be classified as being either retrospective studies, which secure data on different group characteristics hypothesized as etiological factors from at least two groups with varying rates of the disease being investigated, or prospective studies, which follow up groups of individuals with and without the hypothesized etiological characteristics in order to determine the differential development of the disease.

In all three study designs, the objective is the determination of a series of statistical associations from which etiological inferences may be drawn. These three types of design offer progressively more rigorous and plausible evidence of causality. The demographic method, relying as it does on ecological correlations, is the weakest, since variations in rates of occurrence between phenomena do not necessarily mean that these phenomena are related (Clausen & Kohn 1954); it is possible to have high ecological associations with little or no individual correlation. Retrospective studies do provide individual correlations, but there is often no way of knowing which of the two factors in an observed correlation came first. Prospective studies using a longitudinal study of cohorts are strongest, since these enable one to define the population at risk in advance of the development of disease and then to check one’s predictions over time [see COHORT ANALYSIS].

Smoking and lung cancer. The association between smoking and lung cancer provides an excellent example of the progression from demographic to retrospective and finally to prospective studies. The initial association was suggested by demographic comparisons showing a much higher incidence of lung cancer among men than women. Retrospective studies revealed a correlation between smoking histories and the occurrence of lung cancer. Finally, intensive prospective studies following up smokers and nonsmokers showed a higher development of lung cancer among the former. The continuing controversy today, however, demonstrates the further need and demand to prove, through experimental rather than epidemiological studies, that smoking can “cause” cancer.

Validity of epidemiological method. The inability of the epidemiologist to “randomize” his experimental and control groups and to alter deliberately the characteristics of his experimental group constitutes an intrinsic conceptual and methodological shortcoming that requires a continuing close working relationship between epidemiological and experimental research. Certain basic prerequisites must be satisfied if epidemiological method is to produce reliable and valid associations. First, the representativeness and generalizability of the sample from whom data are obtained must be ascertainable. This sample should include not only persons who are known to have the disease but also who are free of the disease. The definition of what is a “normal,” or disease-free, control group presents a particularly difficult problem for epidemiological study of the chronic diseases, since these may not become apparent until a fairly late stage. Second, the disease being studied must be defined in such a way that it can be reliably and validly diagnosed using field techniques. Errors due to false positives (the proportion of individuals classified as diseased among those truly not diseased) and false negatives (the proportion classified as not diseased among those truly diseased) can often lead to spurious associations (Rubin et al. 1956). Third, the hypothesized etiological factors must be similarly capable of objective definition and measurement. These are difficult conditions to meet, especially in relation to the chronic diseases, which often lack both clear-cut diagnostic criteria and well-developed theories of etiology and process (Pollack & Krueger 1960).

Future developments . Epidemiological method is bound to increase in importance as the search for etiological factors in the chronic diseases forces the medical researcher to supplement his laboratory experiments with field studies, both as source and proof of his hypotheses. The multiple nature of etiological factors (many, if not most, of which cannot be reproduced or controlled in the laboratory) will require greater reliance upon population surveys and field trials. Probabilities of disease will replace certainties, and associated conditions rather than specific causes will dominate the picture. Prominent among these conditions will be the cultural, social, and psychological forces that determine how man lives and which in later years influence the degenerative processes. Today we deal with these social factors on the most elementary level, that of descriptive group memberships. Tomorrow we may hope to be able to determine the dynamic factors underlying these group memberships and to develop and test specific hypotheses of how and why social factors relate to the origin and course of disease.

Edward A. Suchman

[See alsoDRINKING AND ALCOHOLISM; DRUGS, article onDRUG ADDICTION: SOCIAL ASPECTS; ECOLOGY, article onHUMAN ECOLOGY; PUBLIC HEALTH; VITAL STATISTICS; and the biographies ofGRAUNTandQUETELET.]

BIBLIOGRAPHY

Breslow, Lester 1957 Uses and Limitations of the California Health Survey for Studying the Epidemiology of Chronic Disease. American Journal of Public Health 47:168-172.

CLARK, E. GURNEY (1953) 1958 An Epidemiological Approach to Preventive Medicine. Chapter 3 in Hugh R. Leavell et al., Preventive Medicine for the Doctor in His Community: An Epidemiologic Approach. 2d ed. New York: McGraw-Hill.

Clausen, John A.; and KOHN, MELVIN L. 1954 The Ecological Approach in Social Psychiatry. American Journal of Sociology 60:140-151.

Dawber, Thomas R.; and KANNEL, WILLIAM B. 1963 Coronary Heart Disease as an Epidemiology Entity. American Journal of Public Health 53:433-437.

Dawber, Thomas R. et al. 1959 Some Factors Associated With the Development of Coronary Heart Disease. American Journal of Public Health 49:1349-1356.

Dorn, Harold F.; and CUTLER, SIDNEY J. 1958 Morbidity From Cancer in the United States. U.S. Public Health Service Publication No. 590; Public Health Monograph No. 56. Washington: Public Health Service.

Doull, James A. 1952 The Bacteriological Era (1876-1920). Pages 74-113 in Franklin H. Top (editor), The History of American Epidemiology. St. Louis, Mo.: Mosby.

Fleck, Andrew C.; and IANNI, FRANCIS A. J. 1958 Epidemiology and Anthropology: Some Suggested Affinities in Theory and Method. Human Organization 16, no. 4:38-40.

Frost, Wade Hampton (1910-1939) 1941 Papers of Wade Hampton Frost, M.D.: A Contribution to Epidemiological Method. Edited by Kenneth F. Maxcy. New York: Commonwealth Fund; Oxford Univ. Press. → These essays provide a brilliant description of the transition to modern epidemiology.

Glock, Charles Y.; and LENNARD, HENRY L. 1956 Studies in Hypertension. Journal of Chronic Diseases 5:178-196.

Gordon, John E. 1952 The Twentieth Century—Yesterday, Today, and Tomorrow (1920). Pages 114-167 in Franklin H. Top (editor), The History of American Epidemiology. St. Louis, Mo.: Mosby. → Contains a comprehensive bibliography and discussion of modern developments.

Graham, Saxon 1960 Social Factors in the Epidemiology of Cancer at Various Sites. New York Academy of Sciences, Annals 84:807-815.

Greenwood, Major 1932 Epidemiology, Historical and Experimental. Baltimore: Johns Hopkins Press; Oxford Univ. Press.

Hoch, Paul H.; and ZUBIN, JOSEPH (editors) 1961 Comparative Epidemiology of the Mental Disorders. Proceedings of the 49th annual meeting of the American Psychopathological Association, February 1959. New York: Grune & Stratton.

JACO, E. GARTLY 1960 The Social Epidemiology of Mental Disorders: A Psychiatric Survey of Texas. New York: Russell Sage Foundation.

JAMES, GEORGE; and GREENBERG, MORRIS 1957 The Medical Officer’s Bookshelf on Epidemiology and Evaluation. Part 1: Epidemiology. American Journal of Public Health 47:401-408. → Contains a brief review and bibliography on the epidemiology of various diseases.

King, Stanley H. 1963 Social Psychological Factors in Illness. Pages 99-121 in Howard E. Freeman et al. (editors), Handbook of Medical Sociology. Englewood Cliffs, N.J.: Prentice-Hall.

King, Stanley H.; and COBB, SIDNEY 1958 Psychosocial Factors in the Epidemiology of Rheumatoid Arthritis. Journal of Chronic Diseases 7:466-475.

Leighton, Alexander H. 1959 My Name Is Legion: Foundations for a Theory of Man in Relation to Culture. The Stirling County Study of Psychiatric Disorder and Sociocultural Environment, Vol. 1. New York: Basic Books. → Contains a theoretical discussion of social stress as a factor in mental illness.

MACMAHON, BRIAN; PUGH, THOMAS F.; and IPSEN, JOHANNES 1960 Epidemiologic Methods. Boston: Little. → Contains a critical review of current concepts and methods.

Mishler, Elliot G.; and SCOTCH, NORMAN A. 1963 Sociocultural Factors in the Epidemiology of Schizophrenia. Psychiatry 26:315-351.

Morris, Jeremy N. 1957 Uses of Epidemiology. Baltimore: Williams & Wilkins; Edinburgh: Livingstone.

Paul, John R. 1950 Epidemiology. Pages 52-62 in David E. Green and W. Eugene Knox (editors), Research in Medical Science. New York: Macmillan.

Pemberton, John (editor) 1963 Epidemiology: Reports on Research and Teaching, 1962. Oxford Univ. Press.

POLLACK, HERBERT; and KRUEGER, DEAN E. (editors) 1960 Epidemiology of Cardiovascular Diseases: Methodology. American Journal of Public Health 50 (Supplement): 1-124.

Rogers, Edward S. 1960 Human Ecology and Health: An Introduction for Administrators. New York: Macmillan.

RUBIN, THEODORE; ROSENBAUM, JOSEPH; and COBB, SIDNEY 1956 The Use of Interview Data for the Detection of Associations in Field Studies. Journal of Chronic Diseases 4:253-266.

Suchman, Edward A.; and SCHERZER, ALFRED L. 1960 Current Research in Childhood Accidents. Part 1 in Association for the Aid of Crippled Children, Two Reviews of Accident Research. New York: The Association.

U.S. SURGEON GENERAL’S ADVISORY COMMITTEE ON SMOKING AND HEALTH 1964 Smoking and Health. U.S. Department of Health, Education and Welfare, Public Health Service Publication No. 1103. Washington: Government Printing Office. → Contains a thorough analysis of the epidemiological evidence on smoking as a cause of cancer and other diseases.

Wardwell, Walter I.; and BAHNSON, CLAUS B. 1964 Problems Encountered in Behavioral Science Research in Epidemiological Studies. American Journal of Public Health 54:972-981.

Epidemiology

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EPIDEMIOLOGY

Epidemiology is the study of the distribution of disease and its determinants in human populations. Epidemiology usually takes place in an applied public health context. It focuses on the occurrence of disease by time, place, and person and seeks to identify and control outbreaks of disease through identification of etiological factors. Its approach is to identify associated risk factors and then work back to causes.

Historically, the focus of epidemiology was on large outbreaks, usually of infectious disease. The substance and methods of epidemiology have been applied to most forms of acute and chronic disease and many other physical and mental health conditions. Along with the broadening of the subject matter of epidemiology has come more focus on its methods. Along with the specialization of epidemiological methods has come the professional identification of persons as epidemiologists. In this entry, we address the origins, methodology, current topics, and professional issues related to epidemiology.


PROFESSIONAL ROLE

Epidemiology is the professional identification of an increasing number of persons who have received specialized training in departments of epidemiology in schools of public health. Many complete approved courses of study at the master's or doctoral level leading to an M.P.H., Dr. P.H., or Ph.D. with epidemiology as an area of concentration. Some schools offer the M.P.H. to physicians after an abbreviated course of study. Like most other developing professions, graduate epidemiologists are protective of their professional identification and would seek to differentiate their professional credentials from those who have found their ways to epidemiological roles from other educational backgrounds. The problem in this developing professionalism is how to define a unique intellectual content or theory of epidemiology, when the applied nature of the discipline demands that the latest theories and methods of investigating disease be incorporated into any ongoing investigation.


ORIGINS

Langmuir (Roeché 1967, p. xiii) traces the origins of epidemiology as far back as Hypocrites' report of an outbreak of mumps among Greek athletes, but the written history of mankind is full of major outbreaks of disease, which the practitioners of the time attempted to control with methods ranging from folk remedies and the available medicine, to religion and witchcraft, and even to civil and sanitary engineering. It was the careful and scientific observation of these outbreaks that led to the development of modern epidemiology.

Perhaps the most famous early epidemiological inquiry was John Snow's careful observation of the house-by-house locations of incident cases of cholera during epidemics in London in the 1840s and 1850s. Snow's correlation of new cases with some water supply systems, but not others, changed the conventional medical wisdom about how cholera was spread and did so before the microbial nature of the disease was discovered. Roeché's Annals of Epidemiology provides a number of examples of the application of epidemiological methods in relation to local outbreaks in the earlier part of the twentieth century. More recent well-known investigations have included those relating to Legionnaires' disease and AIDS.

Epidemiology as a discipline has grown along with the many associated disciplines of public health and medicine. Microbiology has identified the organisms and modes of transmission for many infectious diseases. Biochemistry, physiology, virology, and related basic medical sciences have provided the scientific background to support the development of the epidemiology of infectious disease. Other sciences ranging from genetics to sociology have contributed to the various specializations within epidemiology, which are broadly classified as infectious disease, chronic disease, cancer, cardiovascular disease, genetic, perinatal, reproductive, oral, occupational, environmental, air pollution, respiratory, nutritional, injury, substance abuse, psychiatric, social, and health care epidemiology as well as pharmaco-epidemiology.


A CONCEPTUAL PARADIGM

A typical paradigm in epidemiology focuses on the interaction of: host, agent, and environment. The host is typically a person but is sometimes another species or organism which provides a reservoir of infection that is subsequently transmitted to humans. In the presence of an epidemic, one tries to understand the characteristics of the host that provide susceptibility to the epidemic condition. Characteristics that are frequently considered are: (1) genetic characteristics; (2) biological characteristics, such as immunology, physiology, and anatomy; (3) demographic characteristics, such as age, sex, race, ethnicity, place of birth, and place of residence; (4) social and economic factors, such as socioeconomic status, education, and occupation; and (5) personal behaviors, such as diet, exercise, substance use, and use of health services.

The agents in this paradigm have classically been rats, lice, and insects. They may be biological, such as viruses or bacteria, as is the case in most infectious disease epidemiology. Typhus, cholera, smallpox, the Ebola virus, Legionnaires' disease, and AIDS follow this model. Chemical agents have also contributed to significant epidemics. Some have been physiological poisons such as the mercury once used in hatmaking, lead in old paint, water pipes, or moonshine liquor; others have been carcinogens such as tobacco or PCBs found as a contaminant in oil spread on roads. Recent focus has been on alcohol and other drugs of abuse. Other physical agents have included asbestos, coal dust, and radioactive fallout. Guns, automobiles, and industrial equipment are also agents of injury and mortality. Sometimes the "agent" has been a nutritive excess or deficiency, demonstrated in Goldberger's 1915 discovery that a deficiency of niacin, part of the vitamin B complex, causes pellagra. Similarly, stress and other elements of lifestyle have been investigated as contributors to cardiovascular disease. An element in the consideration of agents is the degree of exposure and whether the agent alone is a necessary or sufficient cause of the disorder.

The third element of this paradigm is the environment, which may promote the presence of an agent or increase host susceptibility to the agent. Many elements of the environment may be relevant to the disease process, including (1) the physical environment, such as climate, housing, and degree of crowding; (2) the biological environment, including plant and animal populations, especially humans; and (3) the demographic and socioeconomic environments of the host.

At the core of this simple paradigm is the potential for multiple paths of causation for an epidemic. Rarely is a single cause sufficient to ensure the onset of a disease or condition. Thus the approach considers alternative modes of transmission, such as the influence of a common agent versus transmission from host to host. For many agents there is an incubation period, with delayed onset after "infection" or contact with the agent. Further, exposure may lead to a spectrum of disease with variation in the type and severity of the response to the agent. An important element to observe in any outbreak is who is not affected and whether that is due to immunity or some other protective factor.


METHODOLOGY

Field Methods. The historical method of epidemiology began with the observation that an epidemic was present, with the initial response beginning with "shoe leather" investigation of who was affected and how. The initial approach focused on identified cases and their distribution over time and place, leading to a methodology that was often able to discern the risk factors for a disease even before a particular pathogen could be identified. The description of cases in terms of geography and environment as well as various demographic characteristics and exposures remains at the core of epidemiology.

Essential complements to epidemiologic field methods are careful clinical observation, measurement, and classification of the disorder, as well as laboratory identification of any pathogens and identification of potential risk factors for the observed disorder. This methodology is drawn from the methods of associated fields such as pathology, bacteriology, virology, immunology, and molecular genetics. Efforts at classification of pathogens have been augmented by the collection of libraries of reference specimens from past outbreaks.

A problem with the investigation of known outbreaks is that many types of epidemic may develop unobserved until a significant proportion of the population is affected. This has led to the development of surveillance strategies. Among these have been the reporting of multiple causes on death certificates and the mandatory reporting to the health department of many communicable diseases, such as tuberculosis and sexually transmitted diseases. The early detection and reporting of outbreaks make various public health interventions possible. Statistical analysis of mortality and morbidity has become a major component of the public health systems of most countries.

Case Registers. An extension to this approach involves case registers, in which identified mortality or morbidity is investigated and compiled in a statistical database, with subsequent investigation of the detailed context for each case. Case registers for particular types of diseases typically identify a case and then collect additional information through review of medical charts and direct field investigations and interviews. Although not as detailed as most case registers, large databases of treated disorders are gathered by various funders or providers of health services. These include the Health Care Finance Administration (Medicare and Medicaid) and various private insurance companies.

The systematic analysis of large databases, whether case registers or those of administrative agencies, makes it possible to monitor the prevalence of various conditions and to detect increases in prevalence or outbreaks long before they would be detected by individual clinicians. Analyses of mortality and morbidity are presented by most public health agencies. Typical methods include the presentation of rates of disorder, such as the number of cases per 100,000 population for geographic and demographic subpopulations. Analyses might ask whether rates are higher in one place compared to another, for a particular birth cohort, or for persons of a particular socioeconomic status. Such comparisons may be crude or adjusted for factors such as age and sex, which may bias such comparisons. Sometimes the analyses provide detailed age- and sex-specific comparisons or breakouts by other risk factors. Yet this approach is dependent on people with diseases being identified through the health system.

Prevalence Surveys. In order to discover the true prevalence of various conditions and risk factors, it is possible to conduct sample surveys of the population of a country or other geographic unit. This approach avoids potential reporting bias from the health care system and can identify conditions that might not otherwise be recognized or reported. Typically a representative sample of persons would be interviewed about their health, and sometimes various examinations or tests would be administered. Large comprehensive surveys of health and nutrition are conducted regularly by the National Center for Health Statistics. More specialized surveys of particular conditions such as blood pressure, substance use, and mental health have been conducted by federal, state, and private agencies. Because participation in most such surveys is voluntary, investigative procedures are usually limited to interviews and test procedures with little discomfort or risk. The limitation of prevalence surveys is that they are expensive and may have respondent selection biases. On the other hand, they have great potential for collecting detailed information about disorders and potential risk factors.

Case-Control Studies. The case-control method is used extensively in epidemiology. This approach typically starts with a sample of cases of a particular disorder and identifies one or more samples of persons who appear similar but who do not have the disorder. Careful comparison of the groups has potential for identifying risk factors associated with having the disorder or, alternatively, factors that are protective. The most important issue in designing case-control studies is the designation of an appropriate control group in such a way that the process selecting controls neither hides the real risk factors nor pinpoints apparent but false ones. Control groups are frequently designated by geographic or ecological variables and are often matched on individual characteristics such as age and sex. These methods are somewhat similar to those used in natural experiments, in which two groups differ on one or more risk factors and the rates of disorder are compared, but the case-control method starts with identified cases.

Cohort Studies. Unlike the prevalence survey and most case-control studies, which are cross-sectional or retrospective in nature, a cohort study endeavors to identify groups of persons who do not have the disorder or disorders in question and then follows them prospectively through the occurrence of the disease, with ascertainment of factors likely to contribute to the etiology of the disease. Such studies may start with a general sample of the population or may select groups based on the presence or absence of hypothesized risk factors prior to onset of the disorder. They then follow the samples for incident disorder. Unlike cross-sectional studies, cohort studies provide the possibility of determining causal order for risk factors and thus avoid the possibility that apparent risk factors are simply consequences of the disease. The main problem with true cohort studies is that they must last as long as it takes for the disease to develop, which may even take longer than the working life of the investigator. Sometimes, however, cohorts can be found that have been identified and assessed historically and thus can be compared in the present. Examples may be insurance groups, occupational groups, or even residents of certain areas. Then the task is to gather the information on exposure and relate it to health outcomes.

Experimental and Quasi-Experimental Methods. A true experiment is dependent on random assignment of persons or groups to conditions, but one would hardly assign a person to a condition known to produce a serious disease. Nonetheless, there are research designs that approximate true experiments. The most direct is an intervention study in which an intervention that cannot be provided to everyone is provided to one group but not another—or provided to the alternative group at a later time. A quasi-experimental design would identify a group that has been exposed to a risk factor and compare it to another that has not. If the factors that govern the initial exposure appear to be truly accidental, then the quasi-experiment may be nearly as random as a true experiment. In such circumstances or in true randomization, one can determine the effect of the risk factor on outcomes with little risk of the outcome determining the status of the risk factor.

Alternative Methods. There are a number of research designs found in epidemiology. Those presented above are typical but certainly not exhaustive of the alternatives. At the core of nearly all of these methods, however, is the identification of factors associated with the incidence or prevalence of particular types of disorder.


CURRENT ISSUES


In recent epidemiological literature there has been some concern about the future development of epidemiology. A part of this discussion focuses on the basic paradigm being used and whether it has shifted from an ecological approach consistent with the spread of infectious disease and related pathogens to individual risk factors that are more closely related to the current emphasis on chronic diseases. The growing influence of molecular and genetic methods increases this tendency. It has been suggested that this focus on individual and proximate causes blames the individual rather than fixing the prior cause. Some authors have suggested that epidemiology should regain its public health orientation by focusing more on ecological issues affecting the risk status of groups rather than on individual-level factors, and one suggested that the primary focus should be on fighting poverty. A more integrative approach has been suggested by Susser and Susser (1996a, 1996b), who criticize the field for continuing to rely on a multiple risk factor "black box" approach, which is of declining utility, in favor of an approach that encompasses multiple levels of organization and causes from the molecular to the societal.

A second area of concern, identified by Bracken (1998), is the relationship of epidemiology to corporate litigation when various rare disorders are related to sources of risk such as cellular telephones, breast implants, and the like. The issue is the extent to which epidemiologists can provide risk information to journalists and the public without undue burden from unbridled discovery and from the inconsistencies of findings of rare exposures related to rare diseases.

A third issue appears to be the search for professional identity in a discipline that has applicability across the full range of health professions, human and otherwise. The professional positions identified in a 1999 Internet search indicated that there is a continuing market for persons with epidemiological training but that these positions are distributed widely in departments supporting specific disciplines or located in various public health settings. Thus the job titles are often designated in a hyphenated form, such as psychiatric-epidemiologist, cancer-epidemiologist, and genetic-epidemiologist. For a more complete introduction to the principles and methods of epidemiology see Kleinbaum, Kupper, and Morgenstern (1982), Littlefeld and Stolley (1994), or MacMahon and Trichopolous (1996).


references

Ahlbom, Anders, and Staffan Norell 1990 Introduction toModern Epidemiology. Newton Lower Falls, Mass.: Epidemiology Resources, Inc.

Bracken, M. B. 1998 "Alarums False, Alarums Real: Challenges and Threats to the Future of Epidemiology." Annals of Epidemiology 8(2):79–82.

Friedman, Gary D. 1980 Primer of Epidemiology, 2nd ed. New York: McGraw-Hill.

Lilienfeld, David E., and Paul D. Stolley 1994 Foundations of Epidemiology. New York: Oxford University Press.

MacMahon, Brian, and Dimitrios Trichopoulos Epidemiology: Principles and Methods 2nd ed. Boston: Little, Brown.

Roueché, Berton 1967 Annals of Epidemiology. Boston: Little, Brown.

Susser M., and E. Susser 1996a "Choosing a Future for Epidemiology: I. Eras and Paradigms." American Journal of Public Health 86(5):630–632.

——1996b "Choosing a Future for Epidemiology: II. From Black Box to Chinese Boxes and Eco-Epidemiology." American Journal of Public Health 86(5):674–677.


Charles E. Holzer, III

Epidemiology

views updated May 23 2018

Epidemiology

Resources

Epidemiology is the study of the occurrence, frequency, and distribution of diseases in a given population. As part of this study, epidemiologistsscientists who investigate epidemics (widespread occurrence of a disease that occurs during a certain time)attempt to determine how the disease is transmitted, and what are the host(s) and environmental factor(s) that start, maintain, and/or spread the epidemic.

The primary focus of epidemiology are groups of persons, rather than individuals. The primary effort of epidemiologists is in determining the etiology (cause) of the disease and identifying measures to stop or slow its spread. This information, in turn, can be used to create strategies by which the efforts of health care workers and facilities in communities can be most efficiently allocated for this purpose.

In tracking a disease outbreak, epidemiologists may use any or all of three types of investigation: descriptive epidemiology, analytical epidemiology, and experimental epidemiology.

Descriptive epidemiology is the collection of all data describing the occurrence of the disease, and usually includes information about individuals infected, and the place and period during which it occurred. Such a study is usually retrospective, i.e., it is a study of an outbreak after it has occurred.

Analytical epidemiology attempts to determine the cause of an outbreak. Using the case control method, the epidemiologist can look for factors that might have preceded the disease. Often, this entails comparing a group of people who have the disease with a group that is similar in age, sex, socioeconomic status, and other variables, but does not have the disease. In this way, other possible factors, e.g., genetic or environmental, might be identified as factors related to the outbreak.

Using the cohort method of analytical epidemiology, the investigator studies two populations, one who has had contact with the disease-causing agent and another that has not. For example, the comparison of a group that received blood transfusions with a group that has not might disclose an association between blood transfusions and the incidence of a bloodborne disease, such as hepatitis B.

Experimental epidemiology tests a hypothesis about a disease or disease treatment in a group of people. This strategy might be used to test whether or not a particular antibiotic is effective against a particular disease-causing organism. One group of infected individuals is divided randomly so that some receive the antibiotic and others receive a placeboan inactive drug that is not known to have any medical effect. In this case, the antibiotic is the variable, i.e., the experimental factor being tested to see if it makes a difference between the two otherwise similar groups. If people in the group receiving the antibiotic recover more rapidly than those in the other group, it may logically be concluded that the variableantibiotic treatmentmade the difference. Thus, the antibiotic is effective.

Although the sudden appearance of dreaded diseases has plagued humanity for millennia, it was not until the nineteenth century that the field of epidemiology can be said to have been born. In 1854, the British physician John Snow (1813-1858) demonstrated the power of epidemiologic principles during an outbreak of cholera in London. Snow discovered that most of the victims of cholera he questioned obtained their drinking water from a well on Londons Broad Street. Moreover, most of the people afflicted with the disease drank from the polluted section of the Thames River, which ran through London. Snow arranged to have the Broad Street pump closed, preventing people from drinking water from that well. Subsequently, the cholera epidemic subsided.

Since the days of Snow, epidemiology has grown into a sophisticated science, which relies on statistics as well as interviews with disease victims. Today, epidemiologists study not only infectious diseases, such as cholera and malaria, but also noninfectious diseases, such as lung cancer and certain heart disorders.

In the process of studying the cause of an infectious disease, epidemiologists often view it in terms of the agent of infection (e.g., particular bacterium or virus), the environment in which the disease occurs (e.g., crowded slums), and the host (e.g., hospital patient). Thus, beta-hemolytic streptococci bacteria are the agent for acute rheumatic fever; but because not all persons infected with the organism develop the disease, the health of the host helps to determine how serious the disease will be for a particular person, or even, whether it will occur.

Among the important environmental factors that affect an epidemic of infectious diseases are poverty, overcrowding, lack of sanitation, and such uncontrollable factors as the season and climate.

Another way epidemiologists may view etiology of disease is as a web of causation. This web represents all known predisposing factors and their relations with each other and with the disease. For example, a web of causation for myocardial infarction (heart attack) can include diet, hereditary factors, cigarette smoking, lack of exercise, susceptibility to myocardial infarction, and hypertension. Each factor influences and is influenced by a variety of other factors.

By identifying specific factors and how they are ultimately related to the disease, it is sometimes possible to determine which preventive actions can be taken to reduce the occurrence of the disease. In the case of myocardial infarction, for example, these preventive actions might include a change in diet, treatment for hypertension, eliminating smoking, and beginning a regular schedule of exercise.

Epidemiologic investigations are largely mathematical descriptions of persons in groups, rather than individuals. The basic quantitative measurement in epidemiology is a count of the number of persons in the group being studied who have a particular disease; for example, epidemiologists may find 10 members of a village in the African village of Zaire suffer from infection with Ebola virus infection; or that 80 unrelated people living in an inner city area have tuberculosis.

Any description of a group suffering from a particular disease must be put into the context of the larger population. This shows what proportion of the population has the disease. The significance of 10 people out of a population of 1,000 suffering tuberculosis is vastly different, for example, than if those 10 people were part of a population of one million.

Thus one of the most important tasks of the epidemiologist is to determine the prevalence ratethe number of persons out of a particular population who have the disease:

Prevalence rate = number of persons with a disease/total number in group. Prevalence rate is like a snapshot of a population at a certain point in time, showing how many people in that population suffer from a particular disease. For example, the number of people on March 15 suffering infection from the parasite cryptosporidium in a town with a polluted water supply might be 37 out of a population of 80,000. Therefore, the prevalence rate on March 15 is 37/80,000.

A prevalence rate can represent any time period, e.g., day or hour; and it can refer to an event that happens to different persons at different times, such as complications that occur after drug treatment (on day five for some people or on day two for others).

The incidence rate is the rate at which a disease develops in a group over a period of time. Rather than being a snapshot, the incidence rate describes a continuing process that occurs over a particular period of time.

Incidence rate = total number per unit developing a disease over time /total number of persons. For example, the incidence rate of prostate cancer among men in a particular country might be 2% per year; or the number of children getting measles in a town might be 3% per day. Once a person has developed a lifelong disease, such as AIDS, he or she cannot be counted in the denominator of the incidence rate, since these people cannot get the disease again. The denominator refers only to those in the population who have not yet developed the disease.

Period prevalence measures the extent to which one or all diseases affects a group during the course of time, such as a year.

Period prevalence = number of persons with a disease during a period of time/total number in a group. In the case of a year, such as 1995, the period prevalence equals the prevalence at the beginning of 1995 plus the annual incidence during 1995.

Epidemiologists also measure attributable risk, which is the difference between two incidence rates of groups being compared, when those groups differ in some attribute that appears to cause that difference. For example, the lung cancer mortality rate among a particular population of non-smoking women 50 to 70 years old might be 20/100,000, while the mortality rate among woman in that age range who smoke might be 150/100,000. The difference between the two rates (150-20 = 130) is the risk that is attributable to smoking, if smoking is the only important difference between the groups regarding the development of lung cancer.

Epidemiologists arrange their data in various ways, depending on what aspect of the information they want to emphasize. For example, a simple graph of the annual occurrence of viral meningitis might show by the hills and valleys of the line in which years the number of cases increased or decreased. This might provide evidence of the cause and offer ways to predict when the incidence might rise again.

Bar graphs showing differences in rates among months of the year for viral meningitis might pinpoint a specific time of the year when the rate goes up, for example, in summertime. That, in turn, might suggest that specific summertime activities, such as swimming, might be involved in the spread of the disease.

One of the most powerful tools an epidemiologist can use is case reporting: reporting specific diseases to local, state and national health authorities, who accumulate the data. Such information can provide valuable leads as to where, when, and how a disease outbreak is spread, and help health authorities to determine how to halt the progression of an epidemic-one of the most important goals of epidemiology.

Often, epidemiologists are integrated into the public health structure of a local community, and work closely with public health officials to track and manage local outbreaks of disease. Other times, epidemiologists are part of larger national or international health organizations, and work to identify and track the emergence of new diseases worldwide. In either case, epidemiologists rely on observations and data collected at the source of an outbreak, and rapid dissemination of the data among colleagues. For example, when a dangerous pneumonia surfaced in February 2003 in China, Chinese authorities were at first hesitant to implement isolation procedures and investigate the outbreak. Within a month, the disease spread to a hospital in Viet Nam, where Carlo Urbani, an Italian medical epidemiologist working with the World Health Organization in Hanoi, recognized the influenzalike disease as unusual. Urbani worked at the hospital, collecting samples for testing, compiling data, instituting isolation and other infection control measures, and notifying health authorities worldwide. The disease was SARS (severe acute respiratory syndrome), and Urbani is credited with identifying and containing the epidemic. In mid-March, 2003, Urbani traveled to Thailand to present data to Centers for Disease Control and Prevention (CDC) officials. Feeling ill upon landing at the airport, Urbani again insisted upon isolating himself and for protective equipment for those coming in contact with him. He died of SARS two weeks later.

Resources

BOOKS

Nelson, K.E., C.M. Williams, and N.M.H. Graham. Infectious Disease Epidemiology: Theory and Practice Gaithersburg: Aspen Publishers, 2001.

Rothman, Kenneth J. Epidemiology: An Introduction New York: Oxford Univ. USA, 2002.

PERIODICALS

Perera, F.P., and I.B. Weinstein. Molecular Epidemiology: Recent Advances and Future Directions. Carcinogenesis 21 (2000): 517-524.

Phua, Kai-Lit, and Lee, Lai Kah. Meeting the Challenge of Epidemic Infectious Disease Outbreaks: An Agenda for Research. Journal of Public Health Policy. 26 (2005): 122-132.

Epidemics Of Meningococcal Disease. African Meningitis Belt, 2001. Weekly Epidemiological Record/World Health Organization 76, no. 37 (2001): 282-288.

OTHER

Olsen, Yorn, et al. Epidemiology and the Nobel Prize. International Epidemiological Association <http://www.dundee.ac.uk/iea/> (accessed November 25, 2006).

Marc Kusinitz

Epidemiology

views updated May 18 2018

Epidemiology

Epidemiology is the study of the occurrence, frequency, and distribution of diseases in a given population. As part of this study, epidemiologistsscientists who investigate epidemics (widespread occurrence of a disease that occurs during a certain time)attempt to determine how the disease is transmitted, and what are the host(s) and environmental factor(s) that start, maintain, and/or spread the epidemic.

Epidemiology can be an important facet of a forensic investigation. A recent infamous example occurred in the fall of 2001, when a number of letters containing spores of Bacillus anthracis, the agent that causes anthrax , were sent through the United States postal system. The illnesses and deaths that resulted prompted the near shut-down of the postal delivery system, and an investigation to find the sender(s) of the letters and the source of the bacterial spores. These investigations were rooted in epidemiology.

The primary focus of epidemiology is on groups of persons, rather than individuals. The primary effort of epidemiologists is in determining the etiology (cause) of the disease and identifying measures to stop or slow its spread. This information, in turn, can be used to create strategies by which the efforts of health care workers and facilities in communities can be most efficiently allocated for this purpose.

In tracking a disease outbreak, epidemiologists may use any or all of three types of investigation: descriptive epidemiology, analytical epidemiology, and experimental epidemiology.

Descriptive epidemiology is the collection of all data describing the occurrence of the disease, and usually includes information about individuals infected, and the place and period during which it occurred. Such a study is usually retrospective, i.e., it is a study of an outbreak after it has occurred. The 2001 anthrax investigation is one example.

Analytical epidemiology attempts to determine the cause of an outbreak. Using the case control method, the epidemiologist can look for factors that might have preceded the disease. Often, this entails comparing a group of people who have the disease with a group that is similar in age, sex, socioeconomic status, and other variables, but does not have the disease. In this way, other possible factors, e.g., genetic or environmental, might be identified as factors related to the outbreak.

Using the cohort method of analytical epidemiology, the investigator studies two populations, one who has had contact with the disease-causing agent and another that has not. For example, the comparison of a group that received blood transfusions with a group that has not might disclose an association between blood transfusions and the incidence of a blood borne disease, such as hepatitis B.

Experimental epidemiology tests a hypothesis about a disease or disease treatment in a group of people. This strategy might be used to test whether or not a particular antibiotic is effective against a particular disease-causing organism. One group of infected individuals is divided randomly so that some receive the antibiotic and others receive a placeboa "false" drug that is not known to have any medical effect. In this case, the antibiotic is the variable, i.e., the experimental factor being tested to see if it makes a difference between the two otherwise similar groups. If people in the group receiving the antibiotic recover more rapidly than those in the other group, it may logically be concluded that the variableantibiotic treatmentmade the difference. Thus, the antibiotic is effective.

In the process of studying the cause of an infectious disease, epidemiologists often view it in terms of the agent of infection (e.g., particular bacterium or virus), the environment in which the disease occurs (e.g., crowded slums), and the host (e.g., hospital patient). Another way epidemiologists may view etiology of disease is as a "web of causation." This web represents all known predisposing factors and their relations with each other and with the disease. For example, a web of causation for myocardial infarction (heart attack) can include diet, hereditary factors, cigarette smoking, lack of exercise, susceptibility to myocardial infarction, and hypertension. Each factor influences and is influenced by a variety of other factors.

Epidemiologic investigations are largely mathematical descriptions of persons in groups, rather than individuals. The basic quantitative measurement in epidemiology is a count of the number of persons in the group being studied who have a particular disease; for example, epidemiologists may find 10 members of a village in the African village of Zaire suffer from infection with Ebola virus infection; or that 80 unrelated people living in an inner city area have tuberculosis.

A fundamental underpinning of infectious epidemiology is the confirmation that a disease outbreak has occurred. Once this is done, the disease is followed with time. The pattern of appearance of cases of the disease can be tracked by developing what is known as an epidemic curve. This information is vital in distinguishing a natural outbreak from a deliberate and hostile act, for example. The appearance of a few cases at first with the number of cases increasing over time to a peak is indicative of a natural outbreak. The number of cases usually begins to subside as the population develops immunity to the infection (e.g., influenza). However, if a large number of cases occur in the same area at the same time, the source of the infection might not be natural. Examples include a food poisoning or a bioterrorist action where the accidental or deliberate release of organisms will be evident as a sudden appearance of a large number of cases at the same time.

Any description of a group suffering from a particular disease must be put into the context of the larger population. This shows what proportion of the population has the disease. The significance of ten people out of a population of 1,000 suffering tuberculosis is vastly different, for example, than if those ten people were part of a population of one million.

Thus one of the most important tasks of the epidemiologist is to determine the prevalence ratethe number of persons out of a particular population who have the disease (prevalence rate). A prevalence rate can represent any time period, e.g., day or hour; and it can refer to an event that happens to different persons at different times, such as complications that occur after drug treatment (on day five for some people or on day two for others).

The incidence rate is the rate at which a disease develops in a group over a period of time. Rather than being a snapshot, the incidence rate describes a continuing process that occurs over a particular period of time.

Period prevalence measures the extent to which one or all diseases affects a group during the course of time, such as a year.

Epidemiologists also measure attributable risk, which is the difference between two incidence rates of groups being compared, when those groups differ in some attribute that appears to cause that difference. For example, the lung cancer mortality rate among a particular population of non-smoking women 50 to 70 years old might be 20/100,000, while the mortality rate among woman in that age range who smoke might be 150/100,000. The difference between the two rates (150 20 = 130) is the risk that is attributable to smoking, if smoking is the only important difference between the groups regarding the development of lung cancer.

Epidemiologists arrange their data in various ways, depending on what aspect of the information they want to emphasize. For example, a simple graph of the annual occurrence of viral meningitis might show by the "hills" and "valleys" of the line in which years the number of cases increased or decreased. This might provide evidence of the cause and offer ways to predict when the incidence might rise again.

Bar graphs showing differences in rates among months of the year for viral meningitis might pinpoint a specific time of the year when the rate goes up, for example, in summertime. That, in turn, might suggest that specific summertime activities, such as swimming, might be involved in the spread of the disease.

One of the most powerful tools an epidemiologist can use is case reporting: reporting specific diseases to local, state, and national health authorities who accumulate the data. Such information can provide valuable leads as to where, when, and how a disease outbreak is spread, and help health authorities to determine how to halt the progression of an epidemicone of the most important goals of epidemiology.

Molecular epidemiology has been used to trace the cause of bacterial, viral, and parasitic diseases. This knowledge is valuable in developing a strategy to prevent further outbreaks of the microbial illness, since the probable source of a disease can be identified.

Molecular epidemiology arises from varied scientific disciplines, including genetics, epidemiology, and statistics. The strategies involved in genetic epidemiology encompass population studies and family studies. Sophisticated mathematical tools are now involved, and computer technology is playing a predominant role in the development of the discipline. Multidisciplinary collaboration is crucial to understanding the role of genetic and environmental factors in disease processes.

Much information can come from molecular epidemiology, even in the exact genetic cause of the malady is not known. For example, the identification of a malady in generations of related people can trace the genetic characteristic, and even help identify the original source of the trait. This approach is commonly referred to as genetic screening. The knowledge of why a particular malady appears in certain people, or why such people are more prone to a microbial infection than other members of the population, can reveal much about the nature of the disease in the absence of the actual gene whose defect causes the disease.

Various routes can spread infections (i.e., contact, air borne, insect borne, food and water intake, etc.). Likewise, the route of entry of an infectious microbe can also vary from microbe to microbe.

Laboratory analysis techniques can be combined with other techniques to provide information related to the spread of an outbreak. For example, microbiological data can be combined with geographic information systems (GIS ). GIS information has helped pinpoint the source of outbreaks. In addition to geographic based information, epidemiologists will use information including the weather on the days preceding an outbreak, mass transit travel schedules, and schedules of mass-participation events that occurred around the time of an outbreak to try an establish a pattern of movement or behavior to those who have been affected by the outbreak. Use of credit cards and bank debit cards can also help piece together the movements of those who subsequently became infected.

Reconstructing the movements of people is especially important when the outbreak is of an infectious disease. The occurrence of the disease over time can yield information as to the source of an outbreak.

Epidemiologists were among the first scientists to effectively utilize the Internet and email capabilities to effectively communicate regarding disease outbreaks. The International Society for Infectious Diseases sponsors PROMED, a global e-mail based electronic reporting system for outbreaks of emerging infectious diseases and toxins , which is open to all sources.

see also Anthrax, investigation of 2001 murders; Ebola virus; Pathogens; September 11, 2001, terrorist attacks (forensic investigations of).

Epidemiology

views updated Jun 11 2018

Epidemiology

Epidemiology is the study of the occurrence, frequency , and distribution of diseases in a given population. As part of this study, epidemiologists—scientists who investigate epidemics (widespread occurrence of a disease that occurs during a certain time)—attempt to determine how the disease is transmitted, and what are the host(s) and environmental factor(s) that start, maintain, and/or spread the epidemic .

The primary focus of epidemiology are groups of persons, rather than individuals. The primary effort of epidemiologists is in determining the etiology (cause) of the disease and identifying measures to stop or slow its spread. This information, in turn, can be used to create strategies by which the efforts of health care workers and facilities in communities can be most efficiently allocated for this purpose.

In tracking a disease outbreak, epidemiologists may use any or all of three types of investigation: descriptive epidemiology, analytical epidemiology, and experimental epidemiology.

Descriptive epidemiology is the collection of all data describing the occurrence of the disease, and usually includes information about individuals infected, and the place and period during which it occurred. Such a study is usually retrospective, i.e., it is a study of an outbreak after it has occurred.

Analytical epidemiology attempts to determine the cause of an outbreak. Using the case control method, the epidemiologist can look for factors that might have preceded the disease. Often, this entails comparing a group of people who have the disease with a group that is similar in age, sex, socioeconomic status, and other variables, but does not have the disease. In this way, other possible factors, e.g., genetic or environmental, might be identified as factors related to the outbreak.

Using the cohort method of analytical epidemiology, the investigator studies two populations, one who has had contact with the disease-causing agent and another that has not. For example, the comparison of a group that received blood transfusions with a group that has not might disclose an association between blood transfusions and the incidence of a bloodborne disease, such as hepatitis B.

Experimental epidemiology tests a hypothesis about a disease or disease treatment in a group of people. This strategy might be used to test whether or not a particular antibiotic is effective against a particular disease-causing organism . One group of infected individuals is divided randomly so that some receive the antibiotic and others receive a placebo—a "false" drug that is not known to have any medical effect. In this case, the antibiotic is the variable, i.e., the experimental factor being tested to see if it makes a difference between the two otherwise similar groups. If people in the group receiving the antibiotic recover more rapidly than those in the other group, it may logically be concluded that the variable—antibiotic treatment—made the difference. Thus, the antibiotic is effective.

Although the sudden appearance of dreaded diseases has plagued humanity for millennia, it was not until the nineteenth century that the field of epidemiology can be said to have been born. In 1854, the British physician John Snow (1813-1858) demonstrated the power of epidemiologic principles during an outbreak of cholera in London. Snow discovered that most of the victims of cholera he questioned obtained their drinking water from a well on London's Broad Street. Moreover, most of the people afflicted with the disease drank from the polluted section of the Thames River, which ran through London. Snow arranged to have the Broad Street pump closed, preventing people from drinking water from that well. Subsequently, the cholera epidemic subsided.

Since the days of Snow, epidemiology has grown into a very sophisticated science, which relies on statistics as well as interviews with disease victims. Today, epidemiologists study not only infectious diseases, such as cholera and malaria , but also noninfectious diseases, such as lung cancer and certain heart disorders.

In the process of studying the cause of an infectious disease, epidemiologists often view it in terms of the agent of infection (e.g., particular bacterium or virus ), the environment in which the disease occurs (e.g., crowded slums), and the host (e.g., hospital patient). Thus, beta-hemolytic streptococci bacteria are the agent for acute rheumatic fever ; but because not all persons infected with the organism develop the disease, the health of the host helps to determine how serious the disease will be for a particular person, or even, whether it will occur.

Among the important environmental factors that affect an epidemic of infectious diseases are poverty, over-crowding, lack of sanitation, and such uncontrollable factors as the season and climate.

Another way epidemiologists may view etiology of disease is as a "web of causation." This web represents all known predisposing factors and their relations with each other and with the disease. For example, a web of causation for myocardial infarction (heart attack) can include diet, hereditary factors, cigarette smoking, lack of exercise , susceptibility to myocardial infarction, and hypertension . Each factor influences and is influenced by a variety of other factors.

By identifying specific factors and how they are ultimately related to the disease, it is sometimes possible to determine which preventive actions can be taken to reduce the occurrence of the disease. In the case of myocardial infarction, for example, these preventive actions might include a change in diet, treatment for hypertension, eliminating smoking, and beginning a regular schedule of exercise.

Epidemiologic investigations are largely mathematical descriptions of persons in groups, rather than individuals. The basic quantitative measurement in epidemiology is a count of the number of persons in the group being studied who have a particular disease; for example, epidemiologists may find 10 members of a village in the African village of Zaire suffer from infection with Ebola virus infection; or that 80 unrelated people living in an inner city area have tuberculosis .

Any description of a group suffering from a particular disease must be put into the context of the larger population. This shows what proportion of the population has the disease. The significance of 10 people out of a population of 1,000 suffering tuberculosis is vastly different, for example, than if those 10 people were part of a population of one million.

Thus one of the most important tasks of the epidemiologist is to determine the prevalence rate—the number of persons out of a particular population who have the disease:

Prevalence rate = number of persons with a disease / total number in group. Prevalence rate is like a snapshot of a population at a certain point in time, showing how many people in that population suffer from a particular disease. For example, the number of people on March 15 suffering infection from the parasite cryptosporidium in a town with a polluted water supply might be 37 out of a population of 80,000. Therefore, the prevalence rate on March 15 is 37/80,000.

A prevalence rate can represent any time period, e.g., day or hour; and it can refer to an event that happens to different persons at different times, such as complications that occur after drug treatment (on day five for some people or on day two for others).

The incidence rate is the rate at which a disease develops in a group over a period of time. Rather than being a snapshot, the incidence rate describes a continuing process that occurs over a particular period of time.

Incidence rate = total number per unit developing a disease over time / total number of persons. For example, the incidence rate of prostate cancer among men in a particular country might be 2% per year; or the number of children getting measles in a town might be 3% per day. Once a person has developed a lifelong disease, such as AIDS , he or she cannot be counted in the denominator of the incidence rate, since these people cannot get the disease again. The denominator refers only to those in the population who have not yet developed the disease.

Period prevalence measures the extent to which one or all diseases affects a group during the course of time, such as a year.

Period prevalence = number of persons with a disease during a period of time / total number in group. In the case of a year, such as 1995, the period prevalence equals the prevalence at the beginning of 1995 plus the annual incidence during 1995.

Epidemiologists also measure attributable risk, which is the difference between two incidence rates of groups being compared, when those groups differ in some attribute that appears to cause that difference. For example, the lung cancer mortality rate among a particular population of non-smoking women 50 to 70 years old might be 20/100,000, while the mortality rate among woman in that age range who smoke might be 150/100,000. The difference between the two rates (150-20 = 130) is the risk that is attributable to smoking, if smoking is the only important difference between the groups regarding the development of lung cancer.

Epidemiologists arrange their data in various ways, depending on what aspect of the information they want to emphasize. For example, a simple graph of the annual occurrence of viral meningitis might show by the "hills" and "valleys" of the line in which years the number of cases increased or decreased. This might provide evidence of the cause and offer ways to predict when the incidence might rise again.

Bar graphs showing differences in rates among months of the year for viral meningitis might pinpoint a specific time of the year when the rate goes up, for example, in summertime. That, in turn, might suggest that specific summertime activities, such as swimming, might be involved in the spread of the disease.

One of the most powerful tools an epidemiologist can use is case reporting: reporting specific diseases to local, state and national health authorities, who accumulate the data. Such information can provide valuable leads as to where, when, and how a disease outbreak is spread, and help health authorities to determine how to halt the progression of an epidemic-one of the most important goals of epidemiology.


Resources

books

Cohn, Victor. News and Numbers. A Guide to Reporting Statistical Claims and Controversies in Health and Related Fields. Ames: Iowa State University Press, 1989.

Nelson, K.E., C.M. Williams, and N.M.H. Graham. InfectiousDisease Epidemiology: Theory and Practice Gaithersburg: Aspen Publishers, 2001.

periodicals

Perera, F.P., and I.B. Weinstein. "Molecular Epidemiology: Recent Advances and Future Directions." Carcinogenesis 21 (2000): 517-524.

"Pidemics Of Meningococcal Disease. African Meningitis Belt, 2001." Weekly Epidemiological Record / World Health Organization 76, no. 37 (2001): 282-288.


Marc Kusinitz

Epidemiology

views updated Jun 11 2018

Epidemiology

ANTONIO FARINA/

BRIAN D. HOYLE

Epidemiology is the study of the various factors that influence the occurrence, distribution, prevention, and control of disease, injury, and other health-related events in a defined human population. By the application of various analytical techniques including mathematical analysis of the data, the probable cause of an infectious out-break can be pinpointed. This connection between epidemiology and infection makes microorganisms an important facet of epidemiology, and gives epidemiologists a vital link in emergency planning for public health response to a biological attack.

Molecular epidemiology has been used to trace the cause of bacterial, viral, and parasitic diseases. This knowledge is valuable in developing a strategy to prevent further outbreaks of the microbial illness, since the probable source of a disease can be identified.

Furthermore, in the era of biological weapons use by individuals, organizations, and governments, epidemiological studies of the effect of exposure to infectious microbes has become more urgently important. Knowledge of the effect of a bioweapon on the battlefield may not extend to the civilian population that might also be secondarily affected by the weapons. Thus, epidemiology is an important tool in identifying and tracing the course of an infection.

Molecular and genetic basis of epidemiology. Genetic epidemiology studies could result in data that would enable forensic investigators to rapidly identify bioterrorism or biological warfare agents specifically engineered or vectored to affect certain subgroups within a larger population.

Molecular epidemiology arises from varied scientific disciplines, including genetics, epidemiology and statistics. The strategies involved in genetic epidemiology encompass population studies and family studies. Sophisticated mathematical tools are now involved, and computer technology is playing a predominant role in the development of the discipline. Multidisciplinary collaboration is crucial to understanding the role of genetic and environmental factors in disease processes.

Much information can come from molecular epidemiology even if the exact genetic cause of the malady is not known. For example, the identification of a malady in generations of related people can trace the genetic characteristic, and even help identify the original source of the trait. This approach is commonly referred to as genetic screening. The knowledge of why a particular malady appears in certain people, or why such people are more prone to a microbial infection than other members of the population, can reveal much about the nature of the disease in the absence of the actual gene whose defect causes the disease.

Differences in response to pathogens is often a complex interplay of various environmental and genetic factors that require sophisticated analytical tools and techniques to identify. Aided by advances in computer technology, scientists develop complex mathematical formulas for the analysis of epidemiological models, the description of the transmission of the disease, and genetic-environmental interactions. Sophisticated mathematical techniques are now used for assessing classification, diagnosis, prognosis and treatment of many diseases.

Population studies provide data that greatly impact public health programs and emergency responses. By means of several statistical tools, genetic epidemiologic studies evaluate risk factors, inheritance and possible models of inheritance. Different kinds of studies are based upon the number of people who participate and the method of sample collection (i.e., at the time of an outbreak or after an outbreak has occurred). A challenge for the investigator is to achieve a result able to be applied with as low a bias as possible to the general population. In other words, the goal of an epidemiological study of an infectious outbreak is to make the results from a few individuals applicable to the whole population.

A fundamental underpinning of infectious epidemiology is the confirmation that a disease outbreak has occurred. Once this is done, the disease is followed with time. The pattern of appearance of cases of the disease can be tracked by developing what is known as an epidemic curve. This information is vital in distinguishing a natural outbreak from a deliberate and hostile act, for example. In a natural outbreak the number of cases increases over time to a peak, after which the cases subside as immunity develops in the population. A deliberate release of organisms will be evident as a sudden appearance of a large number of cases at the same time.

Tracking diseases with technology. Many illnesses of epidemiological concern are caused by microorganisms. Examples include hemorrhagic fevers such as that caused by the Ebola virus. The determination of the nature of illness outbreaks due to these and other microorganisms involve microbiological and immunological techniques.

Various routes can spread infections (i.e., contact, air borne, insect borne, food and water intake, etc.). Likewise, the route of entry of an infectious microbe can also vary from microbe to microbe.

If an outbreak is recognized early enough, samples of the suspected cause as well as samples from the afflicted (i.e., sputum, feces) can be gathered for analysis. The analysis will depend on the symptoms. For example, in the case of a food poisoning, symptoms such as the rapid development of cramping, nausea with vomiting, and diarrhea after eating a hamburger would be grounds to consider Escherichia coli O157:H7 as the culprit. Analyses would likely include the examination for other known microbes associated with food poisoning (i.e., Salmonella ) in order to save time in identifying the organism.

Analysis can involve the use of conventional laboratory techniques (e.g., use of nonselective and selective growth media to detect bacteria). As well, more recent technological innovations can be employed. An example is the use of antibodies to a known microorganism that are complexed with a fluorescent particle. The binding of the antibody to the microbes can be detected by the examination of a sample using fluorescence microscopy or flow cytometry. Molecular techniques such as the polymerase chain reaction are employed to detect genetic material from a target organism. However, the expense of the techniques such as PCR tends to limit its use to more of a confirmatory role, rather than as an initial tool of an investigation. A considerable research effort is ongoing at U.S. National Laboratories to develop quicker, less expensive, and more portable PCR equipment that can be used by inspectors and investigators.

Another epidemiological tool is the determination of the antibiotic susceptibility and resistance of bacteria.

Such laboratory techniques can be combined with other techniques to provide information related to the spread of an outbreak. For example, microbiological data can be combined with geographic information systems (GIS). GIS information has helped pinpoint the source of outbreaks. In addition to geographic based information, epidemiologists will use information including the weather on the days preceding an outbreak, mass transit travel schedules and schedules of mass-participation events that occurred around the time of an outbreak to try and establish a pattern of movement or behavior to those who have been affected by the outbreak. Use of credit cards and bank debit cards can also help piece together the movements of those who subsequently became infected.

Reconstructing the movements of people is especially important when the outbreak is an infectious disease. The occurrence of the disease over time can yield information as to the source of an outbreak. For example, the appearance of a few cases at first with the number of cases increasing over time to a peak is indicative of a natural outbreak. The number of cases usually begins to subside as the population develops immunity to the infection (e.g., influenza). However, if a large number of cases occur in the same area at the same time, the source of the infection might not be natural. Examples include a food poisoning or a bioterrorist action.

Epidemiologists were among the first scientists to effectively utilize the Internet and email capabilities to effectively communicate regarding disease outbreaks. The International Society for Infectious Diseases sponsors PROMED, the global email based electronic reporting system for outbreaks of emerging infectious diseases and toxins, is open to all sources.

FURTHER READING:

BOOKS:

Trestrail, John H. Forensic Epidemiology. Loue, Sana, 1999.

PERIODICALS:

Epidemiology Program Office, CDC. "CDC's 50th Anniversary: History of CDC." Morbidity and Mortality Weekly Report no. 45 (1996): 52530.

ELECTRONIC:

Centers for Disease Control and Prevention. "About CDC." November 2, 2002. <http://www.cdc.gov/aboutcdc.htm> (28 December 2002).

International Society for Infectious Diseases. ProMED-mail. May, 2003. <http://www.promedmail.org/pls/askus/f?p=2400:1000'>(May 12, 2003).

SEE ALSO

Biological Weapons, Genetic Identification
Bioshield Project
Bioterrorism, Protective Measures
CDC (United States Centers for Disease Control and Prevention)
Communicable Diseases, Isolation, and Quarantine
Public Health Service (PHS), United States
World Health Organization (WHO)

Epidemiology

views updated May 11 2018

Epidemiology


Epidemiology, the study of epidemics, is sometimes called the medical aspect of ecology because it is the study of diseases in animal populations, including humans. The epidemiologist is concerned with the interactions of organisms and their environments as related to the presence of disease. Environmental factors of disease include geographical features, climate , and concentration of pathogens in soil and water. Epidemiology determines the numbers of individuals affected by a disease, the environmental circumstances under which the disease may occur, the causative agents, and the transmission of disease.

Epidemiology is commonly thought to be limited to the study of infectious diseases, but that is only one aspect of the medical specialty. The epidemiology of the environment and lifestyles has been studied since Hippocrates's time. More recently, scientists have broadened the worldwide scope of epidemiology to studies of violence, of heart disease due to lifestyle choices, and to the spread of disease because of environmental degradation .

Epidemiologists at the Epidemic Intelligence Service (EIS) of the Centers for Disease Control and Prevention have played important roles in landmark epidemiologic investigations. Those include the identification in 1955 of a lot of poliovirus vaccine, supposedly dead, that was contaminated with live polio virus ; an investigation of the definitive epidemic of Legionnaires' disease in 1976; identification of tampons as a risk factor for toxic-shock syndrome; and investigation of the first cluster of cases that came to be called acquired immunodeficiency syndrome (AIDS ). EIS officers are increasingly involved in the investigation of noninfectious disease problems, including the risk of injury associated with all-terrain vehicles and cluster deaths related to flour contaminated with parathion.

The epidemiological classification of disease deals with the incidence, distribution, and control of disorders of a population. Using the example of typhoid, a disease spread through contaminated food and water, scientists first must establish that the disease observed is truly caused by Salmonella typhosa, the typhoid organism. Investigators then must know the number of cases, whether the cases were scattered over the course of a year or occurred within a short period, and the geographic distribution. It is critical that the precise locations of the diseased patients be established. In a hypothetical case, two widely separated locations within a city might be found to have clusters of cases of typhoid arising simultaneously. It might be found that each of these clusters revolved around a family unit, suggesting that personal relationships might be important. Further investigation might disclose that all of the infected persons had dined at one time or at short intervals in a specific home, and that the person who had prepared the meal had visited a rural area, suffered a mild attack of the disease, and now was spreading it to family and friends by unknowing contamination of food.

One very real epidemic of cholera in the West African nation of Guinea-Bissau was tracked by CDC researchers using maps, interviews, and old-fashioned footwork door-to-door through the country. An investigator eventually tracked the source of the cholera outbreak to contaminated shellfish.

Epidemic diseases result from an ecological imbalance of some kind. Ecological imbalance, and hence, epidemic disease may be either naturally caused or induced by man. A breakdown in sanitation in a city, for example, offers conditions favorable for an increase in the rodent population, with the possibility that diseases may be introduced into and spread among the human population. In this case, an epidemic would result as much from an alteration in the environment as from the presence of a causative agent. For example, an increase in the number of epidemics of viral encephalitis, a brain disease, in man has resulted from the ecological imbalance of mosquitoes and wild birds caused by man's exploitation of lowland for farming. Driven from their natural habitat of reeds and rushes, the wild birds, important natural hosts for the virus that causes the disease, are forced to feed near farms; mosquitoes transmit the virus from birds to cattle to man.

Lyme disease, which was tracked by epidemiologists from man to deer to the ticks which infest deer, is directly related to environmental changes. The lyme disease spirochete probably has been infecting ticks for a long time; museum specimens of ticks collected on Long Island in the l940s were found to be infected. Since then, tick populations in the Northeast have increased dramatically, triggering the epidemic.

There are more ticks because many of the forests that had been felled in the Northeast have returned to forestland. Deer populations in those areas have exploded, close to concentrated human populations, as have the numbers of Ixodes dammini ticks which feed on deer. The deer do not become ill, but when a tick bite infects a human host, the result can be a devastating disease, including crippling arthritis and memory loss.

Disease detectives, as epidemiologists are called, are taking on new illnesses like heart disease and cancer , diseases that develop over a lifetime. In 1948, epidemiologists enrolled 5,000 people in Framingham, Massachusetts, for a study on heart disease. Every two years the subjects have undergone physicals and answered survey questions. Epidemiologists began to understand what factors put people at risk, such as high blood pressure, elevated cholesterol levels, smoking, and lack of exercise.

CDC epidemiologists are now tracking the pattern of violence, traditionally a matter for police. If a pattern is found, then young people who are at risk can be taught to stop arguments before they escalate to violence, or public health workers can recognize behaviors that lead to spouse abuse, or the warning signs of teenage suicide, for example.

In the 1980s, classic epidemiology discovered that a puzzling array of illnesses was linked, and it came to be known as AIDS. Epidemiologists traced the disease to sexual contact, then to contaminated blood supplies, then proved the AIDS virus could cross the placental barrier, infecting babies born to HIV-infected mothers.

The AIDS virus, called human immunodeficiency virus, may have existed for centuries in African monkeys and apes. Perhaps 40 years ago, this virus crossed from monkey to man, although researchers do not know how or why. African chimpanzees can be infected with HIV, but they don't develop the disease, suggesting that chimps have developed protective immunity. Eventually AIDS, over centuries, probably will develop into a less deadly disease in humans. But before then, researchers fear that new, more deadly, diseases will evolve.

As human communities change and create new ways for diseases to spread, viruses and bacteria constantly evolve as well. Rapidly increasing human populations prove a fertile breeding ground for microbes , and as the planet becomes more crowded, the distances that separate communities become smaller.

Epidemiology has become one of the important sciences in the study of nutritional and biotic diseases around the world. The United Nations supports, in part, a World Health Organization investigation of nutritional diseases.

Epidemiologists have also been called upon in times of natural emergencies. When Mount St. Helens erupted on May 18, 1980, CDC epidemiologists were asked to assist in an epidemiologic evaluation. The agency funded and assisted in a series of studies on the health effects of dust exposure, occupational exposure, and mental health effects of the volcanic eruption.

In 1990, CDC epidemiologists began research for the Department of Energy to study people who have been exposed to radiation. A major task of the study is to quantify exposures based on historical reconstructions of emissions from nuclear plant operations. Epidemiologists have undertaken a major thyroid disease study for those people exposed to radioactive iodine as a result of living near the Hanford Nuclear Reservation in Richland, Washington, during the l940s and l950s.

[Linda Rehkopf ]

RESOURCES

BOOKS

Friedman, G. D. Primer of Epidemiology. 3rd ed. New York: McGraw-Hill, 1987.

Goldsmith, J. R., ed. Environmental Epidemiology: Epidemiological Investigations of Community Environmental Problems. St. Louis: CRC Press, 1986.

Kopfler, F. C., and G. Craun, eds. Environmental Epidemiology. Chelsea, MI: Lewis, 1986.