<p><strong>Epidemiology</strong> is the study of factors affecting the <a href="/wiki/Health" title="Health">health</a> and <a href="/wiki/Illness" title="Illness">illness</a> of populations, and serves as the foundation and <a href="/wiki/Logic" title="Logic">logic</a> of interventions made in the interest of <a href="/wiki/Public_health" title="Public health">public health</a> and <a href="/wiki/Preventive_medicine" title="Preventive medicine">preventive medicine</a>. It is considered a cornerstone methodology of public health research, and is highly regarded in <a href="/wiki/Evidence-based_medicine" title="Evidence-based medicine">evidence-based medicine</a> for identifying risk factors for <a href="/wiki/Disease" title="Disease">disease</a> and determining optimal treatment approaches to clinical practice.</p><p>The work of communicable and non-communicable disease epidemiologists ranges from <a href="/wiki/Outbreak" title="Outbreak">outbrea</a> investigation, to study design, data collection and analysis including the development of statistical models to test hypotheses and the 'writing-up' of results for submission to peer reviewed journals. Epidemiologists may draw on a number of other scientific disciplines such as biology in understanding disease processes and social science disciplines including sociology and philosophy in order to better understand proximate and distal risk factors.</p><p><a nameid="Etymology" idname="Etymology"></a></p>

<p>Epidemiology, &quot;the study of what is upon the people&quot;, is derived from the Greek terms <em>epi</em> = upon, among; <em>demos</em> = people, district; <em>logos</em> = 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 '<a href="/wiki/Epizoology" title="Epizoology">epizoology</a>' is available, and it has also been applied to studies of plant populations (botanical epidemiology); see Nutter 1999. It is also applied to studies of micro-organisms (microbial epidemiology).</p><p><a nameid="History_of_epidemiology" idname="History_of_epidemiology"></a></p>

<p>The Greek physician Hippocrates is sometimes said to be the &quot;father of epidemiology&quot;. He is the first person known to have examined the relationships between the occurrence of disease and environmental influences. He coined the terms <a href="/wiki/Endemic" title="Endemic">endemic</a> (for diseases usually found in some places but not in others) and <a href="/wiki/Epidemic" title="Epidemic">epidemic</a> (for disease that are seen at some times but not others. <a rel="nofollow" href="http://www.duncan-associates.com/changing_concepts.pdf" title="http://www.duncan-associates.com/changing_concepts.pdf" class="external autonumber">[2]</a></p><p>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 <a rel="nofollow" href="http://classics.mit.edu/Plato/republic.4.iii.html" title="http://classics.mit.edu/Plato/republic.4.iii.html" class="external autonumber">[3]</a> and Rousseau <a rel="nofollow" href="http://www.constitution.org/jjr/ineq_03.htm" title="http://www.constitution.org/jjr/ineq_03.htm" class="external autonumber">[4]</a>, and social critics like Jonathan Swift <a rel="nofollow" href="http://www.jaffebros.com/lee/gulliver/bk4/chap4-7.html" title="http://www.jaffebros.com/lee/gulliver/bk4/chap4-7.html" class="external autonumber">[5]</a>.</p><p>In the <a href="/wiki/Islamic_Golden_Age" title="Islamic Golden Age">medieval Islamic world</a>, <a href="/wiki/Islamic_medicine" title="Islamic medicine">Muslim physicians</a> discovered the contagious nature of <a href="/wiki/Infectious_disease" title="Infectious disease">infectious disease</a>. In particular, the <a href="/wiki/Persian_people" title="Persian people">Persian</a> physician <a href="/wiki/Avicenna" title="Avicenna">Avicenna</a>, considered a &quot;father of modern medicine&quot;,<sup id="_ref-Cesk_0" class="reference"><a hrefid="#_note_ref-Cesk" title="Cesk_0">[1]</a></sup> in <em><a href="/wiki/The_Canon_of_Medicine" title="The Canon of Medicine">The Canon of Medicine</a></em> (1020s), discovered the contagious nature of <a href="/wiki/Tuberculosis" title="Tuberculosis">tuberculosis</a> and <a href="/wiki/Sexually_transmitted_disease" title="Sexually transmitted disease">sexually transmitted disease</a>, and the distribution of <a href="/wiki/Disease" title="Disease">disease</a> through <a href="/wiki/Water" title="Water">water</a> and <a href="/wiki/Soil" title="Soil">soil</a>,<sup id="_ref-Sarton_0" class="reference"><a hrefid="#_note_ref-Sarton" title="Sarton_0">[2]</a></sup> stated that bodily <a href="/wiki/Secretion" title="Secretion">secretion</a> is contaminated by <a href="/wiki/Bacteria" title="Bacteria">foul foreign earthly bodies</a> before being infected,<sup id="_ref-Syed_0" class="reference"><a hrefid="#_note_ref-Syed" title="Syed_0">[3]</a></sup> introduced the method of <a href="/wiki/Quarantine" title="Quarantine">quarantine</a> as a means of limiting the spread of contagious disease,<sup id="_ref-Tschanz_0" class="reference"><a hrefid="#_note_ref-Tschanz" title="Tschanz_0">[4]</a></sup> the method of <a href="/wiki/Risk_factor" title="Risk factor">risk factor</a> analysis, and the idea of a <a href="/wiki/Syndrome" title="Syndrome">syndrome</a> in the <a href="/wiki/Diagnosis" title="Diagnosis">diagnosis</a> of specific diseases.<sup id="_ref-Goodman_0" class="reference"><a hrefid="#_note_ref-Goodman" title="Goodman_0">[5]</a></sup></p><p>When the <a href="/wiki/Black_Death" title="Black Death">Black Death</a> <a href="/wiki/Bubonic_plague" title="Bubonic plague">bubonic plague</a> reached <a href="/wiki/Al-Andalus" title="Al-Andalus">al-Andalus</a> in the 14th century, the <a href="/wiki/Arab" title="Arab">Arabian</a> physician <a href="/wiki/Islamic_medicine#Bacteriology.2C_epidemiology.2C_microbiology" title="Islamic medicine">Ibn Khatima</a> discovered that infectious diseases are caused by <a href="/wiki/Microorganism" title="Microorganism">microorganisms</a> which enter the human body. Another 14th century Andalusian-Arabian physician, <a href="/wiki/Islamic_medicine#Bacteriology.2C_epidemiology.2C_microbiology" title="Islamic medicine">Ibn al-Khatib</a> (1313-1374), wrote a treatise called <em>On the Plague</em>, in which he stated how infectious disease can be transmitted through bodily contact and &quot;through garments, vessels and earrings.&quot;<sup id="_ref-Syed_1" class="reference"><a hrefid="#_note_ref-Syed" title="Syed_1">[3]</a></sup></p><p>In the middle of the 16th century, a famous Italian doctor from <a href="/wiki/Florence" title="Florence">Florence</a> named <a href="/wiki/Girolamo_Fracastoro" title="Girolamo Fracastoro">Girolamo Fracastoro</a> was the first one who proposed a theory that very small, unseeable, live particles cause diseases. They were considered to be able to spread by air, multiply by themselves and to be destroyable by fire. In such a way he refuted <a href="/wiki/Galen" title="Galen">Galen</a>'s theory of miasms (poison gas in sick people). In <a href="/wiki/1543" title="1543">1543</a> he wrote a book &quot;<a href="/w/index.php?title=De_contagione_et_contagiosis_morbis&amp;action=edit" title="De contagione et contagiosis morbis" class="new">De contagione et contagiosis morbis</a>&quot;. At that time, based of his theory, he was the first to promote personal and environmental <a href="/wiki/Hygiene" title="Hygiene">hygiene</a>. This theory could not have been proven until the development of the first microscope by <a href="/wiki/Anton_van_Leeuwenhoek" title="Anton van Leeuwenhoek">Anton van Leeuwenhoek</a> in <a href="/wiki/1675" title="1675">1675</a>.</p>

<div class="thumbinner" style="widthWIDTH: 302px;" ><img class="thumbinnerthumbimage"><a hrefheight="/wiki/Image:Snow-cholera-map.jpg293" titlealt="Original map by Dr. John Snow showing the clusters of cholera cases in the London epidemic of 1854" class="image"><img width="300" height="293" border="0" src="http://upload.wikimedia.org/wikipedia/commons/thumb/c/c7/Snow-cholera-map.jpg/300px-Snow-cholera-map.jpg" alt="Original map by Dr. John Snow showing the clusters of cholera cases in the London epidemic of 1854" class="thumbimage" /></a>

<div style="float: right;" class="magnify"><a hrefstyle="/wiki/ImageFLOAT:Snow-cholera-map.jpgright" title><img height="Enlarge11" classalt="internal"><img width="15" height="11" src="/skins-1.5/common/images/magnify-clip.png" alt="" /></a></div>Original map by Dr. John Snow showing the <a href="/wiki/Cluster_%28epidemiology%29" title="Cluster (epidemiology)">clusters</a> of cholera cases in the London epidemic of 1854</div>

<p><a href="/wiki/John_Graunt" title="John Graunt">John Graunt</a>, a professional <a href="/wiki/Haberdasher" title="Haberdasher">haberdasher</a> and serious amateur scientist, published <em>Natural and Political Observations ... upon the Bills of Mortality</em> in <a href="/wiki/1662" title="1662">1662</a>. In it, he used analysis of the mortality rolls in <a href="/wiki/London" title="London">London</a> before the <a href="/wiki/Great_Plague_of_London" title="Great Plague of London">Great Plague</a> to present one of the first <a href="/wiki/Life_tables" title="Life tables">life tables</a> 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.</p><p>Dr. <a href="/wiki/John_Snow_%28physician%29" title="John Snow (physician)">John Snow</a> is famous for the suppression of an <a href="/wiki/1854" title="1854">1854</a> outbreak of <a href="/wiki/Cholera" title="Cholera">cholera</a> in London's <a href="/wiki/Soho" title="Soho">Soho</a> district. He identified the cause of the outbreak as a public water pump on <a href="/wiki/Broadwick_Street" title="Broadwick Street">Broad Street</a> 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 <a href="/wiki/Public_health" title="Public health">public health</a> and can be regarded as the founding event of the science of epidemiology.</p><p>Other pioneers include Danish physician <a href="/w/index.php?title=P._A._Schleisner&amp;action=edit" title="P. A. Schleisner" class="new">P. A. Schleisner</a>, who in <a href="/wiki/1849" title="1849">1849</a> related his work on the prevention of the epidemic of <a href="/wiki/Tetanus" title="Tetanus">tetanus</a> neonatorum on the <a href="/wiki/Vestmanna_Islands" title="Vestmanna Islands">Vestmanna Islands</a> in <a href="/wiki/Iceland" title="Iceland">Iceland</a>. Another important pioneer was <a href="/wiki/Hungary" title="Hungary">Hungarian</a> physician <a href="/wiki/Ignaz_Semmelweis" title="Ignaz Semmelweis">Ignaz Semmelweis</a>, who in <a href="/wiki/1847" title="1847">1847</a> brought down infant mortality at a Vienna hospital by instituting a disinfection procedure. His findings were published in <a href="/wiki/1850" title="1850">1850</a>, but his work was ill received by his colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon <a href="/wiki/Joseph_Lister" title="Joseph Lister">Joseph Lister</a> 'discovered' antiseptics in <a href="/wiki/1865" title="1865">1865</a> in light of the work of <a href="/wiki/Louis_Pasteur" title="Louis Pasteur">Louis Pasteur</a>.</p><p>In the early 20th century, mathematical methods were introduced into epidemiology by <a href="/wiki/Ronald_Ross" title="Ronald Ross">Ronald Ross</a>, <a href="/wiki/Anderson_Gray_McKendrick" title="Anderson Gray McKendrick">Anderson Gray McKendrick</a> and others.</p><p>Another breakthrough was the <a href="/wiki/1954" title="1954">1954</a> publication of the results of a <a href="/wiki/British_Doctors_Study" title="British Doctors Study">British Doctors Study</a>, led by <a href="/wiki/Richard_Doll" title="Richard Doll">Richard Doll</a> and <a href="/wiki/Austin_Bradford_Hill" title="Austin Bradford Hill">Austin Bradford Hill</a>, which lent very strong statistical support to the suspicion that <a href="/wiki/Tobacco_smoking" title="Tobacco smoking">tobacco smoking</a> was linked to <a href="/wiki/Lung_cancer" title="Lung cancer">lung cancer</a>.</p>

<li><a href="/wiki/History_of_emerging_infectious_diseases" title="History of emerging infectious diseases">History of emerging infectious diseases</a> </li>

<p><a nameid="The_profession_of_epidemiology" idname="The_profession_of_epidemiology"></a></p>

<p>To date, few <a href="/wiki/Universities" title="Universities">Universities</a> offer epidemiology as a course of study at undergraduate level. Many epidemiologists, therefore, are <a href="/wiki/Physicians" title="Physicians">physicians</a> or hold other postgraduate degrees including a <a href="/wiki/Master_of_Public_Health" title="Master of Public Health">Master of Public Health</a> (MPH), <a href="/wiki/Master_of_Science" title="Master of Science">Master of Science</a> or Epidemiology (MSc.) Other higher degrees confer the title of <a href="/wiki/Physician" title="Physician">Doctor</a> such as a <a href="/wiki/Doctor_of_Public_Health" title="Doctor of Public Health">Doctor of Public Health</a> (DrPH), <a href="/wiki/Doctor_of_Philosophy" title="Doctor of Philosophy">Doctor of Philosophy</a> (PhD), <a href="/wiki/Doctor_of_Science" title="Doctor of Science">Doctor of Science</a> (ScD) or for those clinically trained, <a href="/wiki/Doctor_of_Medicine" title="Doctor of Medicine">Doctor of Medicine</a> (MD). In the United Kingdom, the title of 'doctor' is a honorary one conferred to those having attained the professional degrees of <a href="/wiki/Bachelor_of_Medicine_and_Surgery" title="Bachelor of Medicine and Surgery">Bachelor of Medicine and Surgery</a> (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 <a href="/wiki/Centers_for_Disease_Control_and_Prevention" title="Centers for Disease Control and Prevention">Centers for Disease Control and Prevention</a> (CDC), Health Protection Agency or the Public Health Agency of Canada.</p><p><a nameid="The_practice_of_epidemiology" idname="The_practice_of_epidemiology"></a></p>

<p>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 <a href="/wiki/Exposure_Assessment#Exposure" title="Exposure Assessment">exposures</a> such as alcohol or smoking, <a href="/wiki/Infections" title="Infections">biological agents</a>, <a href="/wiki/Stress_%28medicine%29" title="Stress (medicine)">stress</a>, or <a href="/wiki/Chemical_compound" title="Chemical compound">chemicals</a> to <a href="/wiki/Death" title="Death">mortality</a> or <a href="/wiki/Morbidity" title="Morbidity">morbidity</a>. Identifying causal relationships between these exposures and outcomes are important aspects of epidemiology. Modern epidemiologist use <a href="/wiki/Disease_informatics" title="Disease informatics">disease informatics</a> as a tool.</p><p>The term 'epidemiologic triangle' is used to describe the intersection of <em>Host</em>, <em>Agent</em>, and <em>Environment</em> in analyzing an outbreak.</p><p><a nameid="Epidemiology_as_causal_inference" idname="Epidemiology_as_causal_inference"></a></p>

<p>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 <em>causal</em> 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 <a href="/wiki/Biology" title="Biology">biology</a>, <a href="/wiki/Sociology" title="Sociology">sociology</a>, <a href="/wiki/Mathematics" title="Mathematics">mathematics</a>, <a href="/wiki/Statistics" title="Statistics">statistics</a>, <a href="/wiki/Anthropology" title="Anthropology">anthropology</a>, <a href="/wiki/Psychology" title="Psychology">psychology</a>, and <a href="/wiki/Policy" title="Policy">policy</a>; &quot;<a href="/wiki/Correlation_does_not_imply_causation" title="Correlation does not imply causation">Correlation does not imply causation</a>,&quot; is a common theme to much of the epidemiologic literature. For epidemiologists, the key is in the term <a href="/wiki/Inference" title="Inference">inference</a>. 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 &quot;<strong>one cause - one effect</strong>&quot; understanding is a simplistic misbelief. Most outcomes &mdash; whether disease or death &mdash; are caused by a chain or web consisting of many component causes.</p><p><a nameid="Bradford-Hill_criteria" idname="Bradford-Hill_criteria"></a></p>

<p>In 1965 <a href="/wiki/Austin_Bradford_Hill" title="Austin Bradford Hill">Austin Bradford Hill</a> detailed criteria for assessing evidence of causation<sup id="_ref-bh65_0" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_0">[6]</a></sup>. These guidelines are sometimes referred to as the <em>Bradford-Hill criteria</em>, 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 <sup id="_ref-0" class="reference"><a hrefid="#_note_ref-0" title="">[7]</a></sup>. Hill himself said &quot;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&quot;<sup id="_ref-bh65_1" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_1">[6]</a></sup>.</p>

<li><strong>Strength</strong>: A small association does not mean that there is not a causal effect.<sup id="_ref-bh65_2" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_2">[6]</a></sup> </li> <li><strong>Consistency</strong>: Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.<sup id="_ref-bh65_3" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_3">[6]</a></sup> </li> <li><strong>Specificity</strong>: 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.<sup id="_ref-bh65_4" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_4">[6]</a></sup> </li> <li><strong>Temporality</strong>: 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).<sup id="_ref-bh65_5" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_5">[6]</a></sup> </li> <li><strong>Biological gradient</strong>: 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.<sup id="_ref-bh65_6" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_6">[6]</a></sup> </li> <li><strong>Plausibility</strong>: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).<sup id="_ref-bh65_7" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_7">[6]</a></sup> </li> <li><strong>Coherence</strong>: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that &quot;... lack of such [laboratory] evidence cannot nullify the epidemiological affect on associations&quot; <sup id="_ref-bh65_8" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_8">[6]</a></sup>. </li> <li><strong>Experiment</strong>: &quot;Occasionally it is possible to appeal to experimental evidence&quot; <sup id="_ref-bh65_9" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_9">[6]</a></sup>. </li> <li><strong>Analogy</strong>: The effect of similar factors may be considered<sup id="_ref-bh65_10" class="reference"><a hrefid="#_note_ref-bh65" title="bh65_10">[6]</a></sup>. </li>

<p><a nameid="Legal_interpretation_of_epidemiologic_studies" idname="Legal_interpretation_of_epidemiologic_studies"></a></p><h2><span class="editsection"></span><span class="mw-headline">Legal interpretation of epidemiologic studies</span></h2><p>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 <a href="/wiki/Probability" title="Probability">probability</a>. Strictly speaking, epidemiology can only go to prove that an agent could have caused but not that, in any particular case, it did cause: &quot;Epidemiology is concerned with the <a href="/wiki/Incidence_%28epidemiology%29" title="Incidence (epidemiology)">incidence</a> of disease in populations and does not address the question of the cause of an individual&rsquo;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&rsquo;s disease.&quot; <a rel="nofollow" href="http://www.fjc.gov/public/pdf.nsf/lookup/sciman06.pdf/$file/sciman06.pdf" title="http://www.fjc.gov/public/pdf.nsf/lookup/sciman06.pdf/$file/sciman06.pdf" class="external autonumber">[6]</a>)</p><p><a nameid="Epidemiology_and_advocacy" idname="Epidemiology_and_advocacy"></a></p>

<p>As a <a href="/wiki/Public_health" title="Public health">public health</a> discipline, epidemiologic evidence is often used to <a href="/wiki/Advocacy" title="Advocacy">advocate</a> both personal measures like diet change and corporate measures like removal of <a href="/wiki/Junk_food" title="Junk food">junk food</a> 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 <a href="/wiki/Cholera" title="Cholera">cholera</a> and <a href="/wiki/Lung_cancer" title="Lung cancer">lung cancer</a> but have had problems with more subtle health issues, and several recent epidemiological results on medical treatments (for example, on the effects of <a href="/wiki/Hormone_replacement_therapy" title="Hormone replacement therapy">hormone replacement therapy</a>) have been refuted by later <a href="/wiki/Randomized_controlled_trial" title="Randomized controlled trial">randomized controlled trials</a>.<sup id="_ref-1" class="reference"><a hrefid="#_note_ref-1" title="">[8]</a></sup></p><p><a nameid="Epidemiology_and_population-based_health_management" idname="Epidemiology_and_population-based_health_management"></a></p><h2><span class="editsection"></span><span class="mw-headline">Epidemiology and population-based health management</span></h2><p>Epidemiological practice and the results of epidemiological analysis make a significant contribution to emerging population-based health management frameworks.</p>

<li>assess the health states and health needs of a target population; </li> <li>implement and evaluate interventions that are designed to improve the health of that population; and </li> <li>efficiently and effectively provide care for members of that population in a way that is consistent with the community&rsquo;s cultural, policy and health resource values. </li>

<p>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.</p><p>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.<sup id="_ref-2" class="reference"><a hrefid="#_note_ref-2" title="">[9]</a></sup><sup id="_ref-3" class="reference"><a hrefid="#_note_ref-3" title="">[10]</a></sup><sup id="_ref-4" class="reference"><a hrefid="#_note_ref-4" title="">[11]</a></sup></p><p>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:</p>

<li>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; </li> <li>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; </li> <li>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). </li>

<p><a nameid="Types_of_studies" idname="Types_of_studies"></a></p>

<div class="noprint relarticle mainarticle"><em>Main article: <a href="/wiki/Study_design" title="Study design">Study design</a></em></div>

<p><a nameid="Case_series" idname="Case_series"></a></p>

<p>Case-series describe the experience of a single patient or a group of patients with a similar diagnosis. They are 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&rsquo;s natural history.<sup id="_ref-5" class="reference"><a hrefid="#_note_ref-5" title="">[12]</a></sup></p><p><a nameid="Case_control_studies" idname="Case_control_studies"></a></p>

<p>Case control studies select subjects based on their disease status. The study population is comprised of individuals that are disease positive. The control group should come from the same population that gave rise to the cases. The case control study looks back through time at potential exposures both populations (cases and controls) may have encountered. A 2x2 table is constructed, displaying exposed cases (A), the exposed controls (B), unexposed cases (C) and the unexposed controls(D). The statistic generated to measure association is the <a href="/wiki/Odds_ratio" title="Odds ratio">odds ratio</a> (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). This is equal to (A*D)/(B*C).</p>

<p>If the OR is clearly greater than 1, then the conclusion is &quot;those with the disease are more likely to have been exposed,&quot; 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.</p><p>Case control studies are usually faster and more cost effective than <a href="/wiki/Cohort_studies" title="Cohort studies">cohort studies</a>, 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.</p><p><a nameid="Cohort_studies" idname="Cohort_studies"></a></p>

<p>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 nonsmokers 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) [What is Relative Risk? How is it measured? How can values be interpreted? Link to statistical analysis? Explanation needed], which is the incidence of disease in the exposed group (A/A+B) over the incidence in the unexposed (C/C+D).</p>

<p>As with the OR, a RR greater than 1 shows association, where the conclusion can be read &quot;those with the exposure were more likely to develop disease.&quot;</p><p>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.</p><p><a nameid="Outbreak_investigation" idname="Outbreak_investigation"></a></p>

<dl><dd><em>For information on investigation of <a href="/wiki/Infectious_disease" title="Infectious disease">infectious disease</a> outbreaks, please see <a href="/wiki/Outbreak#Outbreak_Investigation" title="Outbreak">outbreak investigation</a>.</em> </dd></dl><p><a nameid="Measures" idname="Measures"></a></p>

<li>Measures of <a href="/w/index.php?title=Occurrence&amp;action=edit" title="Occurrence" class="new">occurrence</a>

<li><a href="/wiki/Incidence_%28epidemiology%29" title="Incidence (epidemiology)">Incidence</a> measures

<li><a href="/w/index.php?title=Incidence_density&amp;action=edit" title="Incidence density" class="new">Incidence density</a> (also known as <a href="/wiki/Incidence_rate" title="Incidence rate">Incidence rate</a>) (Szklo &amp; Nieto, 2000) </li> <li><a href="/wiki/Hazard_rate" title="Hazard rate">Hazard rate</a> </li> <li><a href="/wiki/Cumulative_incidence" title="Cumulative incidence">Cumulative incidence</a> </li>

<li><a href="/wiki/Prevalence" title="Prevalence">Prevalence</a> measures

<li><a href="/wiki/Point_prevalence" title="Point prevalence">Point prevalence</a> </li> <li><a href="/wiki/Period_prevalence" title="Period prevalence">Period prevalence</a> </li>

<li>Measures of <a href="/wiki/Association_%28statistics%29" title="Association (statistics)">association</a>

<li><a href="/wiki/Risk_ratio" title="Risk ratio">Risk ratio</a> </li> <li><a href="/w/index.php?title=Rate_ratio&amp;action=edit" title="Rate ratio" class="new">Rate ratio</a> </li> <li><a href="/wiki/Odds_ratio" title="Odds ratio">Odds ratio</a> </li> <li><a href="/wiki/Hazard_ratio" title="Hazard ratio">Hazard ratio</a> </li>

<li><a href="/w/index.php?title=Risk/rate/incidence_difference&amp;action=edit" title="Risk/rate/incidence difference" class="new">Risk/rate/incidence difference</a> </li> <li><a href="/wiki/Attributable_risk" title="Attributable risk">Attributable risk</a>

<li><a href="/w/index.php?title=Attributable_risk_in_exposed&amp;action=edit" title="Attributable risk in exposed" class="new">Attributable risk in exposed</a> </li> <li><a href="/w/index.php?title=Percent_attributable_risk&amp;action=edit" title="Percent attributable risk" class="new">Percent attributable risk</a> </li> <li><a href="/w/index.php?title=Levin%E2%80%99s_attributable_risk&amp;action=edit" title="Levin’s attributable risk" class="new">Levin&rsquo;s attributable risk</a> </li>

<li><a href="/wiki/Virulence" title="Virulence">Virulence</a> and <a href="/wiki/Infectivity" title="Infectivity">Infectivity</a> </li> <li><a href="/wiki/Mortality_rate" title="Mortality rate">Mortality rate</a> and <a href="/wiki/Morbidity" title="Morbidity">Morbidity</a> </li> <li><a href="/wiki/Case_fatality" title="Case fatality">Case fatality</a> </li> <li><a href="/wiki/Sensitivity_%28tests%29" title="Sensitivity (tests)">Sensitivity (tests)</a> and <a href="/wiki/Specificity_%28tests%29" title="Specificity (tests)">Specificity (tests)</a> </li>

<p><a nameid="Criticisms_of_the_validity_of_epidemiologic_conclusions" idname="Criticisms_of_the_validity_of_epidemiologic_conclusions"></a></p><h2><span class="editsection"></span><span class="mw-headline">Criticisms of the validity of epidemiologic conclusions</span></h2><p><a nameid="Random_error" idname="Random_error"></a></p>

<p>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 includ: poorly worded questions, a misunderstanding in interpreting an individual answer from a particular respondent, or a typographical error during coding. Random error effects measurement in a transient, inconsistent manner and it is impossible to correct for random error.</p><p>There is random error in all sampling procedures (this is called sampling error).</p><p>Precision in epidemiologic 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.</p><p>There are two basic ways to reduce random error in an epidemiologic 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 accurate measuring device or by increasing the number of measurements.</p><p>Note that if we increase the sample size, increase the number of measurements, or purchase a more precise measuring tool, we are usually driving up the costs of the study. There is usually an uneasy balance between the need for adequate precision and the practical issue of study cost.</p><p><a nameid="Systematic_error" idname="Systematic_error"></a></p>

<p>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, unbeknownst 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. 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).</p><p>A mistake in coding the effects *all* responses for that particular question is another example of a systematic error.</p><p>The validity of a study is dependent on the degree of systematic error. Validity is usually separated into two components:</p><p>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.</p><p>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.</p><p><a nameid="Selection_bias" idname="Selection_bias"></a></p>

<p>Selection bias is one of three types of bias that threatens the internal 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.</p><p>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.</p><p>Selection bias can produce either an overestimation or underestimation of the effect measure. It can also produce an effect when none actually exists.</p><p>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).</p><p>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.</p><p>To reduce selection bias, you should develop explicit (objective) definitions of exposure and/or disease. You should strive for high participation rates, for instance, by offering incentives to participants. Have a large sample size and randomly select the respondents so that you have a better chance of truly representing the population.</p><p><a nameid="Epidemiology_journals" idname="Epidemiology_journals"></a></p>

<p>A ranked list of journals: <a rel="nofollow" href="http://www.epidemiologic.org/2006/10/impact-factors-of-epidemiology-and.html" title="http://www.epidemiologic.org/2006/10/impact-factors-of-epidemiology-and.html" class="external text">Impact Factors of leading epidemiology journals</a></p><p><a nameid="General_epidemiology_journals" idname="General_epidemiology_journals"></a></p>

<li><a rel="nofollow" href="http://aje.oxfordjournals.org/" title="http://aje.oxfordjournals.org" class="external text">American Journal of Epidemiology</a> </li> <li><a rel="nofollow" href="http://epirev.oxfordjournals.org/" title="http://epirev.oxfordjournals.org" class="external text">Epidemiologic Reviews</a> </li> <li><a rel="nofollow" href="http://www.epidem.com/" title="http://www.epidem.com" class="external text">Epidemiology</a> </li> <li><a rel="nofollow" href="http://ije.oxfordjournals.org/" title="http://ije.oxfordjournals.org" class="external text">International Journal of Epidemiology</a> </li> <li><a rel="nofollow" href="http://www.elsevier.com/wps/find/journaldescription.cws_home/505746/description" title="http://www.elsevier.com/wps/find/journaldescription.cws_home/505746/description" class="external text">Annals of Epidemiology</a> </li> <li><a rel="nofollow" href="http://jech.bmj.com/" title="http://jech.bmj.com" class="external text">Journal of Epidemiology and Community Health</a> </li> <li><a rel="nofollow" href="http://www.springer.com/10654" title="http://www.springer.com/10654" class="external text">European Journal of Epidemiology</a> </li> <li><a rel="nofollow" href="http://www.ete-online.com/" title="http://www.ete-online.com" class="external text">Emerging Themes in Epidemiology</a> </li> <li><a rel="nofollow" href="http://www.epi-perspectives.com/" title="http://www.epi-perspectives.com" class="external text">Epidemiologic Perspectives and Innovations</a> </li> <li><a rel="nofollow" href="http://www.eurosurveillance.org/" title="http://www.eurosurveillance.org" class="external text">Eurosurveillance</a> </li>

<p><a nameid="Specialty_epidemiology_journals" idname="Specialty_epidemiology_journals"></a></p>

<li><a rel="nofollow" href="http://cebp.aacrjournals.org/" title="http://cebp.aacrjournals.org" class="external text">Cancer Epidemiology Biomarkers and Prevention</a> </li> <li><a rel="nofollow" href="http://www3.interscience.wiley.com/cgi-bin/jhome/35841" title="http://www3.interscience.wiley.com/cgi-bin/jhome/35841" class="external text">Genetic Epidemiology</a> </li> <li><a rel="nofollow" href="http://www.elsevier.com/wps/find/journaldescription.cws_home/525472/description" title="http://www.elsevier.com/wps/find/journaldescription.cws_home/525472/description" class="external text">Journal of Clinical Epidemiology</a> </li> <li><a rel="nofollow" href="http://www.blackwellpublishing.com/journal.asp?ref=0269-5022" title="http://www.blackwellpublishing.com/journal.asp?ref=0269-5022" class="external text">Paediatric Perinatal Epidemiology</a> </li> <li><a rel="nofollow" href="http://journals.cambridge.org/action/displayJournal?jid=HYG" title="http://journals.cambridge.org/action/displayJournal?jid=HYG" class="external text">Epidemiology and Infection</a> </li> <li><a rel="nofollow" href="http://eu.wiley.com/WileyCDA/WileyTitle/productCd-PDS.html" title="http://eu.wiley.com/WileyCDA/WileyTitle/productCd-PDS.html" class="external text">Pharmacoepidemiology and Drug Safety</a> </li>

<p><a nameid="Areas_of_epidemiology" idname="Areas_of_epidemiology"></a></p>

<p><a nameid="By_physiology.2Fdisease_area" idname="By_physiology.2Fdisease_area"></a></p>

<li>Infectious disease epidemiology </li> <li><a href="/wiki/Cardiovascular" title="Cardiovascular">Cardiovascular</a> disease epidemiology </li> <li><a href="/wiki/Cancer" title="Cancer">Cancer</a> epidemiology </li> <li>Neuroepidemiology </li> <li>Epidemiology of Aging </li> <li>Oral/Dental epidemiology </li> <li>Reproductive epidemiology </li> <li><a href="/wiki/Obesity" title="Obesity">Obesity</a>/<a href="/wiki/Diabetes" title="Diabetes">diabetes</a> epidemiology </li> <li>Renal epidemiology </li> <li>Injury epidemiology </li> <li>Psychiatric epidemiology </li> <li><a href="/wiki/Veterinary" title="Veterinary">Veterinary</a> epidemiology </li> <li>Epidemiology of <a href="/wiki/Zoonosis" title="Zoonosis">zoonosis</a> </li> <li>Respiratory Epidemiology </li>

<p><a nameid="By_methodological_approach" idname="By_methodological_approach"></a></p>

<li><a href="/wiki/Environmental_epidemiology" title="Environmental epidemiology">Environmental epidemiology</a> </li> <li><a href="/w/index.php?title=Clinical_epidemiology&amp;action=edit" title="Clinical epidemiology" class="new">Clinical epidemiology</a> </li> <li><a href="/wiki/Conflict_epidemiology" title="Conflict epidemiology">Conflict epidemiology</a> </li> <li>Genetic epidemiology </li> <li><a href="/wiki/Molecular_epidemiology" title="Molecular epidemiology">Molecular epidemiology</a> </li> <li><a href="/w/index.php?title=Nutritional_epidemiology&amp;action=edit" title="Nutritional epidemiology" class="new">Nutritional epidemiology</a> </li> <li><a href="/wiki/Social_epidemiology" title="Social epidemiology">Social epidemiology</a> </li> <li>Lifecourse epidemiology </li> <li>Epi methods development / <a href="/wiki/Biostatistics" title="Biostatistics">Biostatistics</a> </li> <li><a href="/wiki/Meta-analysis" title="Meta-analysis">Meta-analysis</a> </li> <li><a href="/wiki/Spatial_epidemiology" title="Spatial epidemiology">Spatial epidemiology</a> </li> <li><a href="/wiki/Tele-epidemiology" title="Tele-epidemiology">Tele-epidemiology</a> </li> <li>Biomarker epidemiology </li> <li>Pharmacoepidemiology </li> <li>Primary care epidemiology </li> <li><a href="/wiki/Infection_control_and_hospital_epidemiology" title="Infection control and hospital epidemiology">Infection control and hospital epidemiology</a> </li> <li>Public Health practice epidemiology </li> <li><a href="/wiki/Surveillance" title="Surveillance">Surveillance</a> epidemiology (<a href="/wiki/Clinical_surveillance" title="Clinical surveillance">Clinical surveillance</a>) </li> <li><a href="/wiki/Disease_Informatics" title="Disease Informatics">Disease Informatics</a> </li>

<p><a nameid="See_also" idname="See_also"></a></p>

<div style="-moz-column-count: 3;">

<li><a href="/wiki/Age_adjustment" title="Age adjustment">Age adjustment</a> </li> <li><a href="/wiki/Centers_for_Disease_Control_and_Prevention" title="Centers for Disease Control and Prevention">Centers for Disease Control and Prevention</a> in the United States </li> <li><a href="/wiki/E-epidemiology" title="E-epidemiology">E-epidemiology</a> </li> <li><a href="/wiki/Epidemiological_methods" title="Epidemiological methods">Epidemiological methods</a> </li> <li><a href="/wiki/Epi_Info" title="Epi Info">Epi Info</a> software program </li> <li><a href="/wiki/OpenEpi" title="OpenEpi">OpenEpi</a> software program </li> <li><a href="/wiki/Hispanic_paradox" title="Hispanic paradox">Hispanic paradox</a> </li> <li><a href="/wiki/List_of_publications_in_biology#Epidemiology" title="List of publications in biology">Important publications in epidemiology</a> </li> <li><a href="/wiki/Mathematical_modelling_in_epidemiology" title="Mathematical modelling in epidemiology">Mathematical modelling in epidemiology</a> </li> <li><a href="/wiki/Study_design" title="Study design">Study design</a> </li> <li><a href="/wiki/Thousand_Families_Study%2C_Newcastle_upon_Tyne" title="Thousand Families Study, Newcastle upon Tyne">Thousand Families Study, Newcastle upon Tyne</a> </li> <li><a href="/wiki/Whitehall_Study" title="Whitehall Study">Whitehall Study</a> </li> <li><a href="/wiki/Epidemiological_Transition" title="Epidemiological Transition">Epidemiological Transition</a> </li> <li><a href="/wiki/Demographic_Transition" title="Demographic Transition">Demographic Transition</a> </li> <li><a href="/wiki/International_Society_for_Pharmacoepidemiology" title="International Society for Pharmacoepidemiology">International Society for Pharmacoepidemiology</a> </li>

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<span style="fontFONT-sizeSIZE: 110%;"><a href="/wiki/Influenza" title="Influenza">Influenza</a></span></th>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;">Influenza</th> <td style="fontFONT-sizeSIZE: 95%; widthWIDTH: 100%; textTEXT-alignALIGN: left;"><a href="/wiki/Influenza_research" title="Influenza research">Research</a> - <a href="/wiki/Influenza_vaccine" title="Influenza vaccine">Vaccine</a> - <a href="/wiki/Avian_influenza" title="Avian influenza">Avian influenza</a> - <a href="/wiki/Influenza_treatment" title="Influenza treatment">Treatment</a> - <a href="/wiki/Influenza_Genome_Sequencing_Project" title="Influenza Genome Sequencing Project">Genome sequencing</a> - <a href="/wiki/Flu_season" title="Flu season">Season</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;">Influenza viruses</th> <td style="backgroundFONT-SIZE: 95%; BACKGROUND: rgb(247, 247, 247) none repeat scroll 0% 50%; fontWIDTH: 100%; TEXT-sizeALIGN: 95%left; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; width: 100%; text-align: left;"><a href="/wiki/Orthomyxoviridae" title="Orthomyxoviridae">Orthomyxoviridae</a> - <a href="/wiki/Influenzavirus_A" title="Influenzavirus A">Influenza A</a> - <a href="/wiki/Influenzavirus_B" title="Influenzavirus B">Influenza B</a> - <a href="/wiki/Influenzavirus_C" title="Influenzavirus C">Influenza C</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;">Subtypes of Influenza A virus</th> <td style="fontFONT-sizeSIZE: 95%; widthWIDTH: 100%; textTEXT-alignALIGN: left;"><a href="/wiki/H1N1" title="H1N1">H1N1</a> - <a href="/wiki/H1N2" title="H1N2">H1N2</a> - <a href="/wiki/H2N2" title="H2N2">H2N2</a> - <a href="/wiki/H3N1" title="H3N1">H3N1</a> - <a href="/wiki/H3N2" title="H3N2">H3N2</a> - <a href="/wiki/H3N8" title="H3N8">H3N8</a> - <a href="/wiki/H5N1" title="H5N1">H5N1</a> - <a href="/wiki/H5N2" title="H5N2">H5N2</a> - <a href="/wiki/H5N3" title="H5N3">H5N3</a> - <a href="/wiki/H5N8" title="H5N8">H5N8</a> - <a href="/wiki/H5N9" title="H5N9">H5N9</a> - <a href="/wiki/H7N1" title="H7N1">H7N1</a> - <a href="/wiki/H7N2" title="H7N2">H7N2</a> - <a href="/wiki/H7N3" title="H7N3">H7N3</a> - <a href="/wiki/H7N4" title="H7N4">H7N4</a> - <a href="/wiki/H7N7" title="H7N7">H7N7</a> - <a href="/wiki/H9N2" title="H9N2">H9N2</a> - <a href="/wiki/H10N7" title="H10N7">H10N7</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;"><a href="/wiki/H5N1" title="H5N1">H5N1</a></th> <td style="backgroundFONT-SIZE: 95%; BACKGROUND: rgb(247, 247, 247) none repeat scroll 0% 50%; fontWIDTH: 100%; TEXT-sizeALIGN: 95%left; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; width: 100%; text-align: left;"><a href="/wiki/H5N1_genetic_structure" title="H5N1 genetic structure">Genetic structure</a> - <a href="/wiki/Transmission_and_infection_of_H5N1" title="Transmission and infection of H5N1">Transmission and infection</a> - <a href="/wiki/Global_spread_of_H5N1" title="Global spread of H5N1">Global spread</a> - <a href="/wiki/H5N1_clinical_trials" title="H5N1 clinical trials">Clinical Trials</a> - <a href="/wiki/Human_mortality_from_H5N1" title="Human mortality from H5N1">Human mortality</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;"><a href="/wiki/Antiviral_drugs" title="Antiviral drugs">Antiviral drugs</a></th> <td style="fontFONT-sizeSIZE: 95%; widthWIDTH: 100%; textTEXT-alignALIGN: left;"><a href="/wiki/Arbidol" title="Arbidol">Arbidol</a> - <em><a href="/wiki/Adamantane" title="Adamantane">adamantane derivatives</a></em> (<a href="/wiki/Amantadine" title="Amantadine">Amantadine</a>, <a href="/wiki/Rimantadine" title="Rimantadine">Rimantadine</a>) - <em><a href="/wiki/Neuraminidase_inhibitor" title="Neuraminidase inhibitor">neuraminidase inhibitors</a></em> (<a href="/wiki/Oseltamivir" title="Oseltamivir">Oseltamivir</a>, <a href="/wiki/Peramivir" title="Peramivir">Peramivir</a>, <a href="/wiki/Zanamivir" title="Zanamivir">Zanamivir</a>)<br /> <em>Experimental</em> (<a href="/wiki/Peramivir" title="Peramivir">Peramivir</a>)</td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;"><a href="/wiki/Influenza_vaccine" title="Influenza vaccine">Influenza vaccines</a></th> <td style="backgroundFONT-SIZE: 95%; BACKGROUND: rgb(247, 247, 247) none repeat scroll 0% 50%; fontWIDTH: 100%; TEXT-sizeALIGN: 95%left; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; width: 100%; text-align: left;"><a href="/wiki/FluMist" title="FluMist">FluMist</a> - <a href="/wiki/Fluzone" title="Fluzone">Fluzone</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;"><a href="/wiki/Influenza_pandemic" title="Influenza pandemic">Influenza pandemics</a></th> <td style="fontFONT-sizeSIZE: 95%; widthWIDTH: 100%; textTEXT-alignALIGN: left;"><a href="/wiki/Asian_Flu" title="Asian Flu">Asian Flu</a> - <a href="/wiki/Hong_Kong_Flu" title="Hong Kong Flu">Hong Kong Flu</a> - <a href="/wiki/Spanish_flu" title="Spanish flu">Spanish flu</a> - <a href="/wiki/Fujian_flu" title="Fujian flu">Fujian flu</a> - <a href="/wiki/Pandemic_Severity_Index" title="Pandemic Severity Index">Pandemic Severity Index</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;">Outbreaks of <a href="/wiki/Avian_influenza" title="Avian influenza">Avian influenza</a></th> <td style="backgroundFONT-SIZE: 95%; BACKGROUND: rgb(247, 247, 247) none repeat scroll 0% 50%; fontWIDTH: 100%; TEXT-sizeALIGN: 95%left; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; width: 100%; text-align: left;"><a href="/wiki/Bird_flu_in_Croatia" title="Bird flu in Croatia">Croatia (2005)</a> - <a href="/wiki/Bird_flu_in_India" title="Bird flu in India">India (2006)</a> - <a href="/wiki/2007_Bernard_Matthews_H5N1_outbreak" title="2007 Bernard Matthews H5N1 outbreak">UK (2007)</a> - <a href="/wiki/2008_bird_flu_outbreak_in_West_Bengal" title="2008 bird flu outbreak in West Bengal">West Bengal (2008)</a></td>

<th style="backgroundBACKGROUND: rgb(221, 221, 255) none repeat scroll 0% 50%; WHITE-SPACE: nowrap; TEXT-ALIGN: right; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; white-space: nowrap; text-align: right;">Influenza in non-human mammals</th> <td style="fontFONT-sizeSIZE: 95%; widthWIDTH: 100%; textTEXT-alignALIGN: left;"><a href="/wiki/Canine_influenza" title="Canine influenza">Canine influenza</a> - <a href="/wiki/Equine_influenza" title="Equine influenza">Equine influenza</a> (<a href="/wiki/2007_Australian_equine_influenza_outbreak" title="2007 Australian equine influenza outbreak">2007 Australian outbreak</a>) - <a href="/wiki/Swine_flu" title="Swine flu">Swine flu</a></td>

<p><a nameid="References" idname="References"></a></p>

<li id="_note-Cesk"><strong><a href="#_ref-Cesk_0" title="">^</a></strong> Cas Lek Cesk (1980). &quot;The father of medicine, Avicenna, in our science and culture: Abu Ali ibn Sina (980-1037)&quot;, <em>Becka J.</em> <strong>119</strong> (1), p. 17-23. </li> <li id="_note-Sarton"><strong><a href="#_ref-Sarton_0" title="">^</astrong></strong> <a href="/wiki/George_Sarton" title="George Sarton">George Sarton</a>, <em>Introduction to the History of Science</em>.<br /> (<a href="/wiki/Cf." title="Cf.">cf.</a> cf. Dr. A. Zahoor and Dr. Z. Haq (1997), Quotations From Famous Historians of Science, Cyberistan. <a rel/li> <li id="nofollow_note-Syed" href="http://www.cyberistan.org/islamic>^ ^{<em><strong>a</Introl1.html" title="http:strong></em></www.cyberistan.org/islamic/Introl1.html" class="external text"sup> ^{<em>Quotations From Famous Historians of Science</astrong>, Cyberistan. b</listrong> <li id="_note-Syed">^ <a href="#_ref-Syed_0" title=""/em>}Ibrahim B. Syed, Ph.D. (2002). &quot;Islamic Medicine: 1000 years ahead of its times&quot;, <em><strong>a</strong></em></supem>Journal of the Islamic Medical Association</aem> <a href="#_ref-Syed_1" title="">^{<emstrong>2</strong>b, p. 2-9. </strongli> </emli id="_note-Tschanz"></supstrong>^</astrong> Ibrahim BDavid W. SyedTschanz, MSPH, Ph.D. PhD (2002August 2003). &quot;Islamic Arab Roots of European Medicine: 1000 years ahead of its times&quot;, <em>Heart Views<a href="/wiki/The_Islamic_Medical_Association_of_North_America" title="The Islamic Medical Association of North America">Journal of the Islamic Medical Associationem> </astrong>4</em> <strong>(2</strong>, p. 2-9. ). </li> <li id="_note-TschanzGoodman"><strong><a href="#_ref-Tschanz_0" title="">^</astrong></strong> David W. Tschanz, MSPH, PhD Lenn Evan Goodman (August 2003). &quot;Arab Roots of European Medicine&quot;, <em>Heart ViewsIslamic Humanism</em> <strong>4</strong> (2), p. 155, Oxford University Press, ISBN 0195135806. </li> <li id="_note-Goodmanbh65">^ <strongsup><a href="#_ref-Goodman_0" title=""em>^</strong>a></strong> Lenn Evan Goodman (2003), </em>Islamic Humanism} ^{<em>, p. 155, <a href="strong>b</wikistrong></Oxford_University_Press" title="Oxford University Press"em>} ^{<em><strong>Oxford University Pressc</astrong>, <a href="/w/index.php?title=Special:Booksources&amp;isbn=0195135806" class="internal"em>ISBN 0195135806</asup>. </lisup> <li id="_note-bh65"<em>^ <a href="#_ref-bh65_0" title=""strong>d<sup/strong></em>} ^{<em><strong>ae</strong></em>}</asup> <a href="#_ref-bh65_1" title=""em><supstrong><em><strong>bf</strong></em>}</a> <a href="#_ref-bh65_2" title="">^{<em><strong>cg</strong></em>}</a> <a href="#_ref-bh65_3" title=""><supsup><em><strong>dh</strong></em></sup></asup><em> <a href="#_ref-bh65_4" title=""strong>i</strong></em></sup>^{<em><strong>ej</strong></em>}</asup> <a href="#_ref-bh65_5" title="">^{<emem><strong>fk</strong></em>}</a> <a href="#_ref-bh65_6" title=""><sup>Hill AB. (1965). The environment and disease: association or causation? <em><strong>g</strong>Proceedings of the Royal Society of Medicine</em>, 58, 295-300. [1] </supli> </a> <a hrefli id="#_ref_note-bh65_7" title="0"><sup><em><strong>h^</strong>Phillips, CV &amp; Goodman KJ. (2004). The missed lessons of Sir Austin Bradford Hill. </em></supem>Epidemiologic Perspectives and Innovations</aem> , 1:3. </li> <a hrefli id="#_ref_note-bh65_8" title="1">^{<emstrong>^</strong>iTaubes G. &quot;Do we really know what makes us healthy?&quot;, </strongem>NY Times</em>, 2007-09-16. Retrieved on 2007-09-18.}</a> <a hrefspan class="#_ref-bh65_9" title="">^{<em><strong>j</strong></em>}</a> <a href="#_ref-bh65_10" title="">^{<em><strong>k</strong></em>}</a> Hill AB. (1965). The environment and disease: association or causation? <em>Proceedings of the Royal Society of Medicine</em>, 58, 295-300. <a rel="nofollow" href="http://www.edwardtufte.com/tufte/hill" title="http://www.edwardtufte.com/tufte/hill" class="external autonumber">[1]</a> </li> <li id="_note-0"><strong><a href="#_ref-0" title="">^</a></strong> Phillips, CV &amp; Goodman KJ. (2004). The missed lessons of Sir Austin Bradford Hill. <em>Epidemiologic Perspectives and Innovations</em>, 1:3. </li> <li id="_note-1"><strong><a href="#_ref-1" title="">^</a></strong> Taubes G. &quot;<a rel="nofollow" href="http://www.nytimes.com/2007/09/16/magazine/16epidemiology-t.html" title="http://www.nytimes.com/2007/09/16/magazine/16epidemiology-t.html" class="external text">Do we really know what makes us healthy?</a>&quot;, <em>NY Times</em>, <a href="/wiki/2007" title="2007">2007</a>-<a href="/wiki/September_16" title="September 16">09-16</a>. Retrieved on <a href="/wiki/2007" title="2007">2007</a>-<a href="/wiki/September_18" title="September 18Z3988">09-18</a>.<span title="ctx_ver=Z39.88-2004&amp;rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&amp;rft.type=newspaperArticle&amp;rft.subject=News&amp;rft.au=Taubes+G&amp;rft.title=Do+we+really+know+what+makes+us+healthy%3F&amp;rft.identifier=http%3A%2F%2Fwww.nytimes.com%2F2007%2F09%2F16%2Fmagazine%2F16epidemiology-t.html&amp;rft.source=NY+Times&amp;rft.date=%5B%5B2007-09-16%5D%5D" class="Z3988">&nbsp;</span> </li> <li id="_note-2"><strong><a href="#_ref-2" title="">^</a></strong> Smetanin P &amp; Kobak P (2005a) &ldquo;Interdisciplinary Cancer Risk Management&rdquo; 1st International Cancer Control Congress to be held October 23-26, 2005 in Vancouver, Canada. </li> <li id="_note-3"><strong><a href="#_ref-3" title="">^</a></strong> Smetanin P &amp; Kobak P (2005b) &ldquo;A Population-Based Risk Management Framework for Cancer Control&rdquo; The International Union Against Cancer Conference July 8-12, 2006 in Washington DC. </li> <li id="_note-4"><strong><a href="#_ref-4" title="">^</a></strong> Smetanin P &amp; Kobak P (2005c) &ldquo;Selected Canadian Life and Economic Forecast Impacts of Lung Cancer&rdquo; 11th World Conference on Lung Cancer in Barcelona, Spain on 3-6 July 2005. </li> <li id="_note-5"><strong><a href="#_ref-5" title="">^</a></strong> Hennekens C.H. and Buring, J.E. (1987) &sbquo; Epidemiology in Medicine.&trade; Mayrent, S.L (Ed.), Lippincott, Williams and Wilkins </li>

<li>Clayton, David and Michel Hills (1993) <em>Statistical Models in Epidemiology</em> Oxford University Press. <a href="/w/index.php?title=Special:Booksources&amp;isbn=0198522215" class="internal">ISBN 0-19-852221-5</a> </li>

<dl><dd> <dl><dd>A thorough introduction to the statistical analysis of epidemiological data, focussing on survival rates - their estimation, analysis and comparison. </dd></dl></dd></dl>

<li>Last JM (2001). &quot;A dictionary of epidemiology&quot;, 4th edn, Oxford: Oxford University Press. </li> <li>Morabia, Alfredo. ed. (2004) A History of Epidemiologic Methods and Concepts. Basel, Birkhauser Verlag. Part I. </li> <li>Nutter FW Jr (1999) &quot;Understanding the Interrelationships Between Botanical, Human, and Veterinary Epidemiology: The Ys and Rs of It All. Ecosystem Health 5 (3): 131-140&quot;. </li> <li>Smetanin P., Kobak P., Moyer C., Maley O (2005) &ldquo;The Risk Management of Tobacco Control Research Policy Programs&rdquo; The World Conference on Tobacco OR Health Conference, July 12-15, 2006 in Washington DC. </li> <li>Szklo MM &amp; Nieto FJ (2002). &quot;Epidemiology: beyond the basics&quot;, Aspen Publishers, Inc. </li>

<p><a nameid="External_links" idname="External_links"></a></p>

<li><a relclass="nofollowexternal text" hreftitle="http://www.hpa.org.uk/" titlerel="nofollow" href="http://www.hpa.org.uk" class="external text/">The Health Protection Agency</a> </li> <li><a relclass="nofollowexternal text" hreftitle="http://www.biostatsresearch.com/repository/" titlerel="nofollow" href="http://www.biostatsresearch.com/repository/" class="external text">The Collection of Biostatistics Research Archive</a> </li> <li><a relclass="nofollowexternal text" hreftitle="http://www.bepress.com/sagmb/" titlerel="nofollow" href="http://www.bepress.com/sagmb/" class="external text">Statistical Applications in Genetics and Molecular Biology</a> </li> <li><a relclass="nofollowexternal text" hreftitle="http://www.bepress.com/ijb/" titlerel="nofollow" href="http://www.bepress.com/ijb/" class="external text">The International Journal of Biostatistics</a> </li> <li><a relclass="nofollowexternal text" hreftitle="http://bmj.bmjjournals.com/epidem/epid.html" titlerel="nofollow" href="http://bmj.bmjjournals.com/epidem/epid.html" class="external text">BMJ</a> - 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, <em><a title="British Medical Journal" href="/wiki/British_Medical_Journal" title="British Medical Journal">British Medical Journal</a></em> </li> <li><a relclass="nofollowexternal text" hreftitle="http://www.epidem.com/" titlerel="nofollow" href="http://www.epidem.com" class="external text/">Epidem.com</a> - <em><a class="new" title="Epidemiology (journal)" href="/w/index.php?title=Epidemiology_%28journal%29&amp;action=edit" title="Epidemiology (journal)" class="new">Epidemiology</a></em> (peer reviewed scientific journal that publishes original research on epidemiologic topics) </li> <li><a relclass="nofollowexternal text" hreftitle="http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=mmed.chapter.631" titlerel="nofollow" href="http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=mmed.chapter.631" class="external text">NIH.gov</a> - 'Epidemiology' (textbook chapter), Philip S. Brachman, <em><a title="Medical Microbiology" href="/wiki/Medical_Microbiology" title="Medical Microbiology">Medical Microbiology</a></em> (fourth edition), US <a href="/wiki/National_Center_for_Biotechnology_Information" title="National Center for Biotechnology Information" href="/wiki/National_Center_for_Biotechnology_Information">National Center for Biotechnology Information</a> </li>

<li><a relclass="nofollowexternal text" hreftitle="http://gsbs.utmb.edu/microbook/" titlerel="nofollow" href="http://gsbs.utmb.edu/microbook/" class="external text">UTMB.edu</a> - 'Epidemiology' (plain format chapter), Philip S. Brachman, <em>Medical Microbiology</em> </li>

<li><a relclass="nofollowexternal text" hreftitle="http://vlab.infotech.monash.edu.au/simulations/cellular-automata/epidemic/" titlerel="nofollow" href="http://vlab.infotech.monash.edu.au/simulations/cellular-automata/epidemic/" class="external text">Monash Virtual Laboratory</a> - Simulations of epidemic spread across a landscape </li>