Epidemiology is the study of factors affecting the health Health is generally defined as being "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity" according to the World Health Organization and illness It is sometimes considered a synonym for disease. Others maintain that fine distinctions exist. Some have described illness as the subjective perception by a patient of an objectively defined disease of populations, and serves as the foundation and logic Logic, from the Greek λογική is defined by the Penguin Encyclopedia to be "The formal systematic study of the principles of valid inference and correct reasoning". As a discipline, logic dates back to Aristotle, who established its fundamental place in philosophy. It became part of the classical trivium, a fundamental part of a of interventions made in the interest of public health Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals." [citation needed] It is concerned with threats to the overall health of a community based on population health and preventive medicine Preventive medicine or preventive care refers to measures taken to prevent illness or injury, rather than curing them. It can be contrasted not only with curative medicine, but also with public health methods . This takes place at primary, secondary and tertiary prevention levels. It is considered a cornerstone methodology of public health research, and is highly regarded in evidence-based medicine Evidence-based medicine aims to apply evidence gained from the scientific method to certain parts of medical practice. It seeks to assess the quality of evidence relevant to the risks and benefits of treatments (including lack of treatment). According to the Centre for Evidence-Based Medicine, "Evidence-based medicine is the conscientious, for identifying risk factors for disease A disease or medical condition is an abnormal condition of an organism that impairs bodily functions, associated with specific symptoms and signs. It may be caused by external factors, such as invading organisms, or it may be caused by internal dysfunctions, such as autoimmune diseases and determining optimal treatment approaches to clinical practice. In the study of communicable and non-communicable diseases, the work of epidemiologists ranges from outbreak Outbreak is a term used in epidemiology to describe an occurrence of disease greater than would otherwise be expected in a particular time and place. It may be small and localized group or impact upon thousands of people across an entire continent. Two linked cases of a rare infectious disease may be sufficient to constitute an outbreak. Outbreaks investigation to study design, data collection and analysis including the development of statistical models to test hypotheses and the documentation of results for submission to peer-reviewed journals. Epidemiologists rely on a number of other scientific disciplines, such as biology (to better understand disease processes), Geographic Information Science Geographic information science is the academic theory behind the development, use, and application of geographic information systems (GIS). It is concerned with GIS people, hardware, software, and geospatial data. GISc addresses fundamental issues raised by the use of GIS and related information technologies (Goodchild 1990, 1992; Wilson and (to store data and map disease patterns) and social science The social sciences comprise academic disciplines concerned with the study of the social life of human groups, animals and individuals including anthropology, archeology, communication studies, cultural studies, demography, economics, human geography, history, linguistics, media studies, political science, psychology, social work, and sociology disciplines (to better understand proximate and distal risk factors).

Etymology

Epidemiology, "the study of what is upon the people", is derived from the Greek terms epi = upon, among; demos = people, district; logos = study, word, discourse; suggesting that it applies only to human populations. But the term is widely used in studies of zoological populations (veterinary epidemiology), although the term 'epizoology Categories: Epidemiology | Demography | Public health | ' is available, and it has also been applied to studies of plant populations (botanical epidemiology).^[1]

History

The Greek physician Hippocrates Hippocrates of Cos or Hippokrates of Kos - Greek: Ἱπποκράτης; Hippokrátēs was an ancient Greek physician of the Age of Pericles, and was considered one of the most outstanding figures in the history of medicine. He is referred to as the "father of medicine" in recognition of his lasting contributions to the field as the is sometimes said to be the uncle of epidemiology. He is the first person known to have examined the relationships between the occurrence of disease and environmental influences. He coined the terms endemic In epidemiology, an infection is said to be endemic in a population when that infection is maintained in the population without the need for external inputs. For example, chickenpox is endemic (steady state) in the UK, but malaria is not. Every year, there are a few cases of malaria acquired in the UK, but these do not lead to sustained (for diseases usually found in some places but not in others) and epidemic In epidemiology, an epidemic occurs when new cases of a certain disease occur in a given human population, during a given period, substantially exceed what is "expected," based on recent experience (the number of new cases in the population during a specified period of time is called the "incidence rate"). (An epizootic is the (for disease that are seen at some times but not others).^[2]

One of the earliest theories on the origin of disease was that it was primarily the fault of human luxury. This was expressed by philosophers such as Plato Plato (Greek: Πλάτων, Plátōn, "broad") (428/427 BC[a] – 348/347 BC), was a Classical Greek philosopher, mathematician, writer of philosophical dialogues, and founder of the Academy in Athens, the first institution of higher learning in the Western world. Along with his mentor, Socrates, and his student, Aristotle, Plato helped^[3] and Rousseau Jean-Jacques Rousseau was a major philosopher, writer, and composer of the eighteenth-century Enlightenment, whose political philosophy influenced the French Revolution and the development of modern political and educational thought. His novel, Emile: or, On Education, which he considered his most important work, is a seminal treatise on the,^[4] and social critics like Jonathan Swift.^[5]

In the medieval Islamic world The Islamic Golden Age, also sometimes known as the Islamic Renaissance, is traditionally dated from the 7th to 13th centuries C.E., but has been extended to the 15th and 16th centuries by more recent scholarship. During this period, artists, engineers, scholars, poets, philosophers, geographers and traders in the Islamic world contributed to the, physicians In the history of medicine, Islamic medicine or Arabic medicine refers to medicine developed in the medieval Islamic civilization and written in Arabic, the lingua franca of the Islamic civilization. Despite these names, a significant number of scientists during this period were not Arab. Some consider the label "Arab-Islamic" as discovered the contagious nature of infectious disease An infectious disease is a clinically evident disease resulting from the presence of pathogenic microbial agents, including pathogenic viruses, pathogenic bacteria, fungi, protozoa, multicellular parasites, and aberrant proteins known as prions. These pathogens are able to cause disease in animals and/or plants. Infectious pathologies are usually. In particular, the Persian The Persian people are defined by the use of the Persian language as their mother tongue. However, the term Persian has also a supra-ethnic significance and has been historically referred to a part of Iranian peoples. The origin of the Persian people, at least in terms of language, is traced to the ancient Indo-Iranians (Aryans), who arrived in physician Avicenna Abū ‘Alī al-Ḥusayn ibn ‘Abd Allāh ibn Sīnā', known as Abū Alī Sīnā or Ibn Sīnā (Arabic: ابن سینا‎), and commonly known in English by his Latinized name Avicenna (Greek: Aβιτζιανός, Abitzianos), (c. 980 - 1037) was a Persian polymath and the foremost physician and philosopher of his time. He was also an astronomer,, considered a "father of modern medicine,"^[6] in The Canon of Medicine Also known as the Qanun, which means "law" in Arabic and Persian, the Canon of Medicine remained a medical authority up until the 18th century and early 19th century. It set the standards for medicine in Europe and the Islamic world, and is Avicenna's most renowned written work. Qanun was used at many medical schools—at University of (1020s), discovered the contagious nature of tuberculosis Tuberculosis is a common and often deadly infectious disease caused by mycobacteria, in humans mainly Mycobacterium tuberculosis . Tuberculosis usually attacks the lungs (as pulmonary TB) but can also affect the central nervous system, the lymphatic system, the circulatory system, the genitourinary system, the gastrointestinal system, bones, and sexually transmitted disease, and the distribution of disease A disease or medical condition is an abnormal condition of an organism that impairs bodily functions, associated with specific symptoms and signs. It may be caused by external factors, such as invading organisms, or it may be caused by internal dysfunctions, such as autoimmune diseases through water Water is a ubiquitous chemical substance that is essential for the survival of all known forms of life.[citation needed] In typical usage, water refers only to its liquid form or state, but the substance also has a solid state, ice, and a gaseous state, water vapor or steam. Water covers 71% of the Earth's surface. On Earth, it is found mostly in and soil As defined by J.S. Joffe in 1949, Soil is a natural body consisting of layers of mineral constituents of variable thicknesses, which differ from the parent materials in their morphological, physical, chemical, and mineralogical characteristics. In engineering, soil is referred to as regolith, or loose rock material. Soil differs from its parent.^[7] Avicenna stated that bodily secretion Secretion is the process of elaborating and releasing chemicals from a cell, a secreted chemical substance or amount of substance. In contrast to excretion, the substance may have a certain function, rather than being a waste product is contaminated by foul foreign earthly bodies The bacteria [bækˈtɪərɪə] (singular: bacterium)[α] are a large group of unicellular microorganisms. Typically a few micrometres in length, bacteria have a wide range of shapes, ranging from spheres to rods and spirals. Bacteria are ubiquitous in every habitat on Earth, growing in soil, acidic hot springs, radioactive waste, water, and deep before being infected.^[8] He introduced the method of quarantine Quarantine is voluntary or compulsory isolation, typically to contain the spread of something considered dangerous, often but not always disease. The word comes from the Italian language Italian quarantena, meaning forty day period as a means of limiting the spread of contagious disease.^[9] He also used the method of risk factor A risk factor is a variable associated with an increased risk of disease or infection. Risk factors are correlational and not necessarily causal, because correlation does not imply causation. For example, being young cannot be said to cause measles, but young people are more at risk as they are less likely to have developed immunity during a analysis, and proposed the idea of a syndrome In medicine and psychology, the term syndrome refers to the association of several clinically recognizable features, signs , symptoms (reported by the patient), phenomena or characteristics that often occur together, so that the presence of one feature alerts the physician to the presence of the others. In recent decades the term has been used in the diagnosis In medicine, diagnosis is the process of identifying a medical condition or disease by its signs, symptoms, and from the results of various diagnostic procedures. The conclusion reached through this process is called a diagnosis. The term "diagnostic criteria" designates the combination of signs, symptoms, and test results that allows of specific diseases.^[10]

When the Black Death (bubonic plague Bubonic plague is the best known manifestation of the bacterial disease plague, caused by the bacterium Yersinia pestis . The term "bubonic plague" was often used synonymously for plague, but it does in fact refer specifically to an infection that enters through the skin and travels through the lymphatics, as is often seen in flea-borne) reached Al Andalus in the 14th century, Ibn Khatima hypothesized that infectious diseases are caused by small "minute bodies" which enter the human body and cause disease. Another 14th century Andalusian-Arabian physician, Ibn al-Khatib (1313–1374), wrote a treatise called On the Plague, in which he stated how infectious disease can be transmitted through bodily contact and "through garments, vessels and earrings."^[8]

In the middle of the 16th century, a famous Italian doctor from Verona Verona is a city in Veneto, northern Italy, one of the seven provincial capitals in the region. It is one of the main tourist destinations in north-eastern Italy, thanks to its artistic heritage, several annual fairs, shows and operas, such as the lyrical season in the Arena, the ancient amphitheatre built by the Romans named Girolamo Fracastoro Girolamo Fracastoro (1478‑March 17, 1553) was an Venetian physician, scholar (in mathematics, geography and astronomy), poet and atomist was the first to propose a theory that these very small, unseeable, particles that cause disease were alive. They were considered to be able to spread by air, multiply by themselves and to be destroyable by fire. In this way he refuted Galen Aelius Galenus or Claudius Galenus , better known as Galen of Pergamum (Greek: Γαληνός, Galēnos), was a prominent Roman physician and philosopher of Greek origin, and probably the most accomplished medical researcher of the Roman period. His theories dominated and influenced Western medical science for well over a millennium. His account's theory of miasms The miasmatic theory of disease held that diseases such as cholera, chlamydia or the Black Death were caused by a miasma , a noxious form of "bad air". This concept has been supplanted by the germ theory of disease (poison gas in sick people). In 1543 he wrote a book De contagione et contagiosis morbis, in which he was the first to promote personal and environmental hygiene Hygiene, refers to the set of practices associated with the preservation of health and healthy living. Hygiene is a concept related to medicine as well as to personal and professional care practices related to most aspects of living although it is most often associated with cleanliness and preventative measures. In medicine, hygiene practices are to prevent disease. The development of a sufficiently powerful microscope by Anton van Leeuwenhoek Antonie Philips van Leeuwenhoek (born on October 24, 1632 – baptized on November 4, and buried on August 30, 1723) was a Dutch tradesman and scientist from Delft, the Netherlands. He is commonly known as "the Father of Microbiology", and considered to be the first microbiologist. He is best known for his work on the improvement of the in 1675 provided visual evidence of living particles consistent with a germ theory of disease The germ theory, also called the pathogenic theory of medicine, is a theory that proposes that microorganisms are the cause of many diseases. Although highly controversial when first proposed, it is now a cornerstone of modern medicine and clinical microbiology, leading to such important innovations as antibiotics and hygienic practices.

John Graunt John Graunt was one of the first demographers, though by profession he was a haberdasher. Born in London, Graunt, along with William Petty, developed early human statistical and census methods that later provided a framework for modern demography. He is credited with producing the first life table, giving probabilities of survival to each age, a professional haberdasher A haberdasher is a person who sells small articles for sewing, such as buttons, ribbons and zippers. In U.S. English, haberdasher is another term for a men's outfitter. A haberdasher's shop or the items sold therein are called haberdashery and serious amateur scientist, published Natural and Political Observations ... upon the Bills of Mortality in 1662. In it, he used analysis of the mortality rolls in London London is the capital of England and the United Kingdom. It has been an influential city for two millennia and its history goes back to its founding by the Romans. The city's core, the ancient City of London, still retains its limited medieval boundaries. However, since at least the nineteenth century, the name "London" has also referred before the Great Plague The Great Plague was a massive outbreak of disease in England that killed an estimated 100,000 people, 20% of London's population. The disease was historically identified as bubonic plague, an infection by the bacterium Yersinia pestis, transmitted through a flea vector. The 1665-1666 epidemic was on a far smaller scale than the earlier " to present one of the first life tables In actuarial science, a life table is a table which shows, for a person at each age, what the probability is that they die before their next birthday. From this starting point, a number of statistics can be derived and thus also included in the table: and report time trends for many diseases, new and old. He provided statistical evidence for many theories on disease, and also refuted many widespread ideas on them.

Dr. John Snow John Snow was a British physician and a leader in the adoption of anaesthesia and medical hygiene. He is considered to be one of the fathers of epidemiology, because of his work in tracing the source of a cholera outbreak in Soho, England, in 1854 is famous for his investigations into the causes of the 19th Century Cholera epidemics. He began with noticing the significantly higher death rates in two areas supplied by Southwark Company. His identification of the Broad Street Broadwick Street is a street in Soho, City of Westminster London. It runs for 0.18 mile (0.3km) approximately west-east between Marshall Street and Wardour Street, crossing Berwick Street pump as the cause of the Soho epidemic is considered the classic example of epidemiology. He used chlorine in an attempt to clean the water and had the handle removed, thus ending the outbreak. (It has been questioned as to whether the epidemic was already in decline when Snow took action.) This has been perceived as a major event in the history of public health Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals." [citation needed] It is concerned with threats to the overall health of a community based on population health and can be regarded as the founding event of the science of epidemiology.

Other pioneers include Danish physician P. A. Schleisner, who in 1849 related his work on the prevention of the epidemic of tetanus Tetanus, also called lockjaw, is a medical condition characterized by a prolonged contraction of skeletal muscle fibers. The primary symptoms are caused by tetanospasmin, a neurotoxin produced by the Gram-positive, obligate anaerobic bacterium Clostridium tetani. Infection generally occurs through wound contamination, and often involves a cut or neonatorum on the Vestmanna Islands in Iceland. Another important pioneer was Hungarian physician Ignaz Semmelweis, who in 1847 brought down infant mortality at a Vienna hospital by instituting a disinfection procedure. His findings were published in 1850, but his work was ill received by his colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon Joseph Lister 'discovered' antiseptics in 1865 in light of the work of Louis Pasteur.

In the early 20th century, mathematical methods were introduced into epidemiology by Ronald Ross, Anderson Gray McKendrick and others.

Another breakthrough was the 1954 publication of the results of a British Doctors Study, led by Richard Doll and Austin Bradford Hill, which lent very strong statistical support to the suspicion that tobacco smoking was linked to lung cancer.

• History of emerging infectious diseases

The profession

To date, few universities offer epidemiology as a course of study at the undergraduate level. Many epidemiologists are physicians, or hold other postgraduate degrees including a Master of Public Health (MPH), Master of Science or Epidemiology (MSc.). Doctorates include the Doctor of Public Health (DrPH), Doctor of Pharmacy (PharmD), Doctor of Philosophy (PhD), Doctor of Science (ScD), or for clinically trained physicians, Doctor of Medicine (MD) and Doctor of Veterinary Medicine (DVM) . In the United Kingdom, the title of 'doctor' is by long custom used to refer to general medical practitioners, whose professional degrees are usually those of Bachelor of Medicine and Surgery (MBBS or MBChB). As public health/health protection practitioners, epidemiologists work in a number of different settings. Some epidemiologists work 'in the field'; i.e., in the community, commonly in a public health/health protection service and are often at the forefront of investigating and combating disease outbreaks. Others work for non-profit organizations, universities, hospitals and larger government entities such as the Centers for Disease Control and Prevention (CDC), the Health Protection Agency, The World Health Organisation (WHO), or the Public Health Agency of Canada.

The practice

Epidemiologists employ a range of study designs from the observational to experimental and are generally categorized as descriptive, analytic (aiming to further examine known associations or hypothesized relationships), and experimental (a term often equated with clinical or community trials of treatments and other interventions). Epidemiological studies are aimed, where possible, at revealing unbiased relationships between exposures such as alcohol or smoking, biological agents, stress, or chemicals to mortality or morbidity. The identification of causal relationships between these exposures and outcomes is an important aspect of epidemiology. Modern epidemiologists use informatics as a tool.

The term 'epidemiologic triad' is used to describe the intersection of Host, Agent, and Environment in analyzing an outbreak.

As causal inference

Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships.

It is nearly impossible to say with perfect accuracy how even the most simple physical systems behave beyond the immediate future, much less the complex field of epidemiology, which draws on biology, sociology, mathematics, statistics, anthropology, psychology, and policy; "Correlation does not imply causation" is a common theme for much of the epidemiological literature. For epidemiologists, the key is in the term inference. Epidemiologists use gathered data and a broad range of biomedical and psychosocial theories in an iterative way to generate or expand theory, to test hypotheses, and to make educated, informed assertions about which relationships are causal, and about exactly how they are causal. Epidemiologists Rothman and Greenland emphasize that the "one cause - one effect" understanding is a simplistic mis-belief. Most outcomes, whether disease or death, are caused by a chain or web consisting of many component causes.

Bradford-Hill criteria

In 1965 Austin Bradford Hill detailed criteria for assessing evidence of causation.^[11] These guidelines are sometimes referred to as the Bradford-Hill criteria, but this makes it seem like it is some sort of checklist. For example, Phillips and Goodman (2004) note that they are often taught or referenced as a checklist for assessing causality, despite this not being Hill's intention.^[12] Hill himself said "None of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect hypothesis and none can be required sine qua non".^[11]

1. Strength: A small association does not mean that there is not a causal effect.^[11]
2. Consistency: Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.^[11]
3. Specificity: Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.^[11]
4. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).^[11]
5. Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.^[11]
6. Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).^[11]
7. Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that "... lack of such [laboratory] evidence cannot nullify the epidemiological affect on associations" ^[11].
8. Experiment: "Occasionally it is possible to appeal to experimental evidence" ^[11].
9. Analogy: The effect of similar factors may be considered^[11].

A useful mnemonic for remembering these criteria is 'ACCESS PTB'.

Legal interpretation

Epidemiological studies can only go to prove that an agent could have caused, but not that it did cause, an effect in any particular case:

"Epidemiology is concerned with the incidence of disease in populations and does not address the question of the cause of an individual’s disease. This question, sometimes referred to as specific causation, is beyond the domain of the science of epidemiology. Epidemiology has its limits at the point where an inference is made that the relationship between an agent and a disease is causal (general causation) and where the magnitude of excess risk attributed to the agent has been determined; that is, epidemiology addresses whether an agent can cause a disease, not whether an agent did cause a specific plaintiff’s disease."^[13]

In United States law, epidemiology alone cannot prove that a causal association does not exist in general. Conversely, it can be (and is in some circumstances) taken by US courts, in an individual case, to justify an inference that a causal association does exist, based upon a balance of probability.

Advocacy

As a public health discipline, epidemiologic evidence is often used to advocate both personal measures like diet change and corporate measures like removal of junk food advertising, with study findings disseminated to the general public in order to help people to make informed decisions about their health. Often the uncertainties about these findings are not communicated well; news articles often prominently report the latest result of one study with little mention of its limitations, caveats, or context. Epidemiological tools have proved effective in establishing major causes of diseases like cholera and lung cancer but have had problems with more subtle health issues, and several recent epidemiological results on medical treatments (for example, on the effects of hormone replacement therapy) have been refuted by later randomized controlled trials.^[14]

Population-based health management

Epidemiological practice and the results of epidemiological analysis make a significant contribution to emerging population-based health management frameworks.

Population-based health management encompasses the ability to:

• Assess the health states and health needs of a target population;
• Implement and evaluate interventions that are designed to improve the health of that population; and
• Efficiently and effectively provide care for members of that population in a way that is consistent with the community’s cultural, policy and health resource values.

Modern population-based health management is complex, requiring a multiple set of skills (medical, political, technological, mathematical etc.) of which epidemiological practice and analysis is a core component, that is unified with management science to provide efficient and effective health care and health guidance to a population. This task requires the forward looking ability of modern risk management approaches that transform health risk factors, incidence, prevalence and mortality statistics (derived from epidemiological analysis) into management metrics that not only guide how a health system responds to current population health issues, but also how a health system can be managed to better respond to future potential population health issues.

Examples of organizations that use population-based health management that leverage the work and results of epidemiological practice include Canadian Strategy for Cancer Control, Health Canada Tobacco Control Programs, Rick Hansen Foundation, Canadian Tobacco Control Research Initiative.^[15][16][17]

Each of these organizations use a population-based health management framework called Life at Risk that combines epidemiological quantitative analysis with demographics, health agency operational research and economics to perform:

• Population Life Impacts Simulations: Measurement of the future potential impact of disease upon the population with respect to new disease cases, prevalence, premature death as well as potential years of life lost from disability and death;
• Labour Force Life Impacts Simulations: Measurement of the future potential impact of disease upon the labour force with respect to new disease cases, prevalence, premature death and potential years of life lost from disability and death;
• Economic Impacts of Disease Simulations: Measurement of the future potential impact of disease upon private sector disposable income impacts (wages, corporate profits, private health care costs) and public sector disposable income impacts (personal income tax, corporate income tax, consumption taxes, publicly funded health care costs).

Types of studies

Case series

Case-series may refer to the qualititative study of the experience of a single patient, or small group of patients with a similar diagnosis, or to a statistical technique comparing periods during which patients are exposed to some factor with the potential to produce illness with periods when they are unexposed.

The former type of study is purely descriptive and cannot be used to make inferences about the general population of patients with that disease. These types of studies, in which an astute clinician identifies an unusual feature of a disease or a patient's history, may lead to formulation of a new hypothesis. Using the data from the series, analytic studies could be done to investigate possible causal factors. These can include case control studies or prospective studies. A case control study would involve matching comparable controls without the disease to the cases in the series. A prospective study would involve following the case series over time to evaluate the disease’s natural history.^[18]

The latter type, more formally described as self-controlled case-series studies, divide individual patient follow-up time into exposed and unexposed periods and use fixed-effects poisson regression processes to compare the incidence rate of a given outcome between exposed and unexposed periods. This technique has been extensively used in the study of adverse reactions to vaccination, and has been shown to provide statistical power comparable to that available in cohort studies.

Case control studies

Case control studies select subjects based on their disease status. A group of individuals that are disease positive (the "case" group) is compared with a group of disease negative individuals (the "control" group). The control group should ideally come from the same population that gave rise to the cases. The case control study looks back through time at potential exposures that both groups (cases and controls) may have encountered. A 2x2 table is constructed, displaying exposed cases (A), exposed controls (B), unexposed cases (C) and unexposed controls (D). The statistic generated to measure association is the odds ratio (OR), which is the ratio of the odds of exposure in the cases (A/C) to the odds of exposure in the controls (B/D), i.e. OR = (A/C) / (B/D) .

If the OR is clearly greater than 1, then the conclusion is "those with the disease are more likely to have been exposed," whereas if it is close to 1 then the exposure and disease are not likely associated. If the OR is far less than one, then this suggests that the exposure is a protective factor in the causation of the disease.

Case control studies are usually faster and more cost effective than cohort studies, but are sensitive to bias (such as recall bias and selection bias). The main challenge is to identify the appropriate control group; the distribution of exposure among the control group should be representative of the distribution in the population that gave rise to the cases. This can be achieved by drawing a random sample from the original population at risk. This has as a consequence that the control group can contain people with the disease under study when the disease has a high attack rate in a population.

Cohort studies

Cohort studies select subjects based on their exposure status. The study subjects should be at risk of the outcome under investigation at the beginning of the cohort study; this usually means that they should be disease free when the cohort study starts. The cohort is followed through time to assess their later outcome status. An example of a cohort study would be the investigation of a cohort of smokers and non-smokers over time to estimate the incidence of lung cancer. The same 2x2 table is constructed as with the case control study. However, the point estimate generated is the Relative Risk (RR), which is the probability of disease for a person in the exposed group, P_e = A / (A+B) over the probability of disease for a person in the unexposed group, P_u = C / (C+D), i.e. RR = P_e / P_u.

As with the OR, a RR greater than 1 shows association, where the conclusion can be read "those with the exposure were more likely to develop disease."

Prospective studies have many benefits over case control studies. The RR is a more powerful effect measure than the OR, as the OR is just an estimation of the RR, since true incidence cannot be calculated in a case control study where subjects are selected based on disease status. Temporality can be established in a prospective study, and confounders are more easily controlled for. However, they are more costly, and there is a greater chance of losing subjects to follow-up based on the long time period over which the cohort is followed.

Outbreak investigation

For information on investigation of infectious disease outbreaks, please see outbreak investigation.

Validity: precision and bias

Random error

Random error is the result of fluctuations around a true value because of sampling variability. Random error is just that: random. It can occur during data collection, coding, transfer, or analysis. Examples of random error include: poorly worded questions, a misunderstanding in interpreting an individual answer from a particular respondent, or a typographical error during coding. Random error affects measurement in a transient, inconsistent manner and it is impossible to correct for random error.

There is random error in all sampling procedures. This is called sampling error.

Precision in epidemiological variables is a measure of random error. Precision is also inversely related to random error, so that to reduce random error is to increase precision. Confidence intervals are computed to demonstrate the precision of relative risk estimates. The narrower the confidence interval, the more precise the relative risk estimate.

There are two basic ways to reduce random error in an epidemiological study. The first is to increase the sample size of the study. In other words, add more subjects to your study. The second is to reduce the variability in measurement in the study. This might be accomplished by using a more precise measuring device or by increasing the number of measurements.

Note, that if sample size or number of measurements are increased, or a more precise measuring tool is purchased, the costs of the study are usually increased. There is usually an uneasy balance between the need for adequate precision and the practical issue of study cost.

Systematic error

A systematic error or bias occurs when there is a difference between the true value (in the population) and the observed value (in the study) from any cause other than sampling variability. An example of systematic error is if, unbeknown to you, the pulse oximeter you are using is set incorrectly and adds two points to the true value each time a measurement is taken. The measuring device could be precise but not accurate. Because the error happens in every instance, it is systematic. Conclusions you draw based on that data will still be incorrect. But the error can be reproduced in the future (eg, by using the same mis-set instrument).

A mistake in coding that affects all responses for that particular question is another example of a systematic error.

The validity of a study is dependent on the degree of systematic error. Validity is usually separated into two components:

• Internal validity is dependent on the amount of error in measurements, including exposure, disease, and the associations between these variables. Good internal validity implies a lack of error in measurement and suggests that inferences may be drawn at least as they pertain to the subjects under study.

• External validity pertains to the process of generalizing the findings of the study to the population from which the sample was drawn (or even beyond that population to a more universal statement). This requires an understanding of which conditions are relevant (or irrelevant) to the generalization. Internal validity is clearly a prerequisite for external validity.

Selection bias

Selection bias is one of three types of bias that threatens the validity of a study. Selection bias is an inaccurate measure of effect which results from a systematic difference in the relation between exposure and disease between those who are in the study and those who should be in the study.

If one or more of the sampled groups does not accurately represent the population they are intended to represent, then the results of that comparison may be misleading.

Selection bias can produce either an overestimation or underestimation of the effect measure. It can also produce an effect when none actually exists.

An example of selection bias is volunteer bias. Volunteers may not be representative of the true population. They may exhibit exposures or outcomes which may differ from nonvolunteers (eg volunteers tend to be healthier or they may seek out the study because they already have a problem with the disease being studied and want free treatment).

Another type of selection bias is caused by non-respondents. For example, women who have been subjected to politically motivated sexual assault may be more fearful of participating in a survey measuring incidents of mass rape than non-victims, leading researchers to underestimate the number of rapes.

To reduce selection bias, you should develop explicit (objective) definitions of exposure and/or disease. You should strive for high participation rates. Have a large sample size and randomly select the respondents so that you have a better chance of truly representing the population.

Journals

A list of journals:^[19]

General journals

• American Journal of Epidemiology
• Epidemiologic Reviews
• Epidemiology (journal)
• International Journal of Epidemiology
• Annals of Epidemiology
• Journal of Epidemiology and Community Health
• European Journal of Epidemiology
• Emerging themes in epidemiology
• Epidemiologic Perspectives and Innovations
• Eurosurveillance

Specialty journals

• Cancer Epidemiology Biomarkers and Prevention
• Genetic epidemiology (journal)
• Journal of Clinical Epidemiology
• Paediatric Perinatal Epidemiology
• Epidemiology and Infection
• Pharmacoepidemiology and Drug Safety

Areas

By physiology/disease

• Infectious disease epidemiology
• Cardiovascular disease epidemiology
• Cancer epidemiology
• Neuroepidemiology
• Epidemiology of Aging
• Oral/Dental epidemiology
• Reproductive epidemiology
• Obesity/diabetes epidemiology
• Renal epidemiology
• Injury epidemiology
• Psychiatric epidemiology
• Veterinary epidemiology
• Epidemiology of zoonosis
• Respiratory Epidemiology
• Pediatric Epidemiology
• Quantitative parasitology

By methodological approach

• Environmental epidemiology
• Economic epidemiology
• Clinical epidemiology
• Conflict epidemiology
• Genetic epidemiology
• Molecular epidemiology
• Nutritional epidemiology
• Social epidemiology
• Lifecourse epidemiology
• Epi methods development / Biostatistics
• Meta-analysis
• Spatial epidemiology
• Tele-epidemiology
• Biomarker epidemiology
• Pharmacoepidemiology
• Primary care epidemiology
• Infection control and hospital epidemiology
• Public Health practice epidemiology
• Surveillance epidemiology (Clinical surveillance)
• Disease Informatics

See also

• Age adjustment
• Biostatistics
• Centers for Disease Control and Prevention in the United States
• Centre for Research on the Epidemiology of Disasters (CRED)
• European Centre for Disease Prevention and Control
• E-epidemiology
• Epidemiological methods
• Epidemic model
• Epi Info software program
• OpenEpi software program
• Hispanic paradox
• Landscape epidemiology
• Important publications in epidemiology
• Mathematical modelling in epidemiology
• Mendelian randomization
• Thousand Families Study, Newcastle upon Tyne
• Whitehall Study
• Epidemiological Transition
• Demographic Transition
• International Society for Pharmacoepidemiology
• Palaeoepidemiology

References

Notes

1. ^ Nutter, Jr., F.W. (1999). "Understanding the interrelationships between botanical, human, and veterinary epidemiology: the Ys and Rs of it all". Ecosys Health 5 (3): 131–40. doi:10.1046/j.1526-0992.1999.09922.x.
2. ^ "Changing Concepts: Background to Epidemiology". Duncan & Associates. http://www.duncan-associates.com/changing_concepts.pdf. Retrieved on 2008-02-03.
3. ^ "The Republic, by Plato". The Internet Classic Archive. http://classics.mit.edu/Plato/republic.4.iii.html. Retrieved on 2008-02-03.
4. ^ "A Dissertation on the Origin and Foundation of the Inequality of Mankind". Constitution Society. http://www.constitution.org/jjr/ineq_03.htm.
5. ^ Swift, Jonathan. "Gulliver's Travels: Part IV. A Voyage to the Country of the Houyhnhnms". http://www.jaffebros.com/lee/gulliver/bk4/chap4-7.html. Retrieved on 2008-02-03.
6. ^ Cesk, Cas Lek (1980). "The father of medicine, Avicenna, in our science and culture: Abu Ali ibn Sina (980-1037)" (in Czech). Becka J. 119 (1): 17–23.
7. ^ George Sarton, Introduction to the History of Science. (cf. Dr. A. Zahoor and Dr. Z. Haq (1997), Quotations From Famous Historians of Science, Cyberistan.
8. ^ ^{a b} Ibrahim B. Syed, Ph.D. (2002). "Islamic Medicine: 1000 years ahead of its times", Journal of the Islamic Medical Association '2', p. 2-9.
9. ^ Tschanz, David W. (August 2003). "Arab Roots of European Medicine". Heart Views (Qatar: The Gulf Heart Association) 4 (2). http://www.hmc.org.qa/hmc/heartviews/H-V-v4%20N2/9.htm.
10. ^ Goodman, Lenn Evan (2003). Islamic Humanism. Oxford University Press. pp. 155. ISBN 0195135806.
11. ^ ^{a b c d e f g h i j k} Hill, A.B. (1965). "The environment and disease: association or causation?". Proceedings of the Royal Society of Medicine 58: 295–300. http://www.edwardtufte.com/tufte/hill.
12. ^ Phillips, Carl V.; Karen J. Goodman (October 2004). "The missed lessons of Sir Austin Bradford Hill". Epidemiologic Perspectives and Innovations 1 (3): 3. doi:10.1186/1742-5573-1-3. http://www.epi-perspectives.com/content/1/1/3.
13. ^ Green, Michael D.; D. Michal Freedman, and Leon Gordis (PDF). Reference Guide on Epidemiology. Federal Judicial Centre. http://www.fjc.gov/public/pdf.nsf/lookup/sciman06.pdf/$file/sciman06.pdf. Retrieved on 2008-02-03.
14. ^ Taubes, Gary (2007-09-16). "Do we really know what makes us healthy?". New York Times. http://www.nytimes.com/2007/09/16/magazine/16epidemiology-t.html. Retrieved on 2007-09-18.
15. ^ Smetanin, P.; P. Kobak (October 2005). "Interdisciplinary Cancer Risk Management: Canadian Life and Economic Impacts" in 1st International Cancer Control Congress..
16. ^ Smetanin, P.; P. Kobak (July 2006). "A Population-Based Risk Management Framework for Cancer Control" (PDF) in The International Union Against Cancer Conference..
17. ^ Smetanin, P.; P. Kobak (July 2005). "Selected Canadian Life and Economic Forecast Impacts of Lung Cancer" (PDF) in 11th World Conference on Lung Cancer..
18. ^ Hennekens, Charles H.; Julie E. Buring (1987). Mayrent, Sherry L. (Ed.). ed. Epidemiology in Medicine. Lippincott, Williams and Wilkins. ISBN 978-0316356367.
19. ^ "Epidemiologic Inquiry: Impact Factors of leading epidemiology journals". Epidemiologic.org. http://www.epidemiologic.org/2006/10/impact-factors-of-epidemiology-and.html. Retrieved on 2008-02-03.

Bibliography

• Clayton, David and Michael Hills (1993) Statistical Models in Epidemiology Oxford University Press. ISBN 0-19-852221-5
• Last JM (2001). "A dictionary of epidemiology", 4th edn, Oxford: Oxford University Press. 5th. edn (2008), edited by Miquel Porta [1]
• Morabia, Alfredo. ed. (2004) A History of Epidemiologic Methods and Concepts. Basel, Birkhauser Verlag. Part I. [2] [3]
• Smetanin P., Kobak P., Moyer C., Maley O (2005) “The Risk Management of Tobacco Control Research Policy Programs” The World Conference on Tobacco OR Health Conference, July 12–15, 2006 in Washington DC.
• Szklo MM & Nieto FJ (2002). "Epidemiology: beyond the basics", Aspen Publishers, Inc.
• Rothman, Kenneth, Sander Greenland and Timothy Lash (2008). "Modern Epidemiology", 3rd Edition, Lippincott Williams & Wilkins. ISBN 0781755646, ISBN 978-0781755641
• Rothman, Kenneth (2002). "Epidemiology. An introduction", Oxford University Press. ISBN 0195135547, ISBN 978-0195135541

External links

• The Health Protection Agency
• The Collection of Biostatistics Research Archive
• Statistical Applications in Genetics and Molecular Biology
• The International Journal of Biostatistics
• Analytical Epidemiology
• BMJ - Epidemiology for the Uninitiated' (fourth edition), D. Coggon, PHD, DM, FRCP, FFOM, Geoffrey Rose DM, DSC, FRCP, FFPHM, DJP Barker, PHD, MD, FRCP, FFPHM, FRCOG, British Medical Journal
• Epidem.com - Epidemiology (peer reviewed scientific journal that publishes original research on epidemiologic topics)
• NIH.gov - 'Epidemiology' (textbook chapter), Philip S. Brachman, Medical Microbiology (fourth edition), US National Center for Biotechnology Information
  • UTMB.edu - 'Epidemiology' (plain format chapter), Philip S. Brachman, Medical Microbiology
• Monash Virtual Laboratory - Simulations of epidemic spread across a landscape
• EMER- Epizootic Diseases, Emerging and Re-emerging Diseases
• Umeå Centre for Global Health Research
• Epidemiology and Public Health Sciences, Umeå International School of Public Health

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