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The term epidemiology is now widely applied to cover the description and causation of not only epidemic, infectious disease, but of disease in general, including related conditions. Some examples of topics examined through epidemiology include as high blood pressure, mental illness and obesity. Therefore, this epidemiology is based upon how the ...
An epidemic curve, also known as an epi curve or epidemiological curve, is a statistical chart used in epidemiology to visualise the onset of a disease outbreak. It can help with the identification of the mode of transmission of the disease. It can also show the disease's magnitude, whether cases are clustered or if there are individual case ...
Human infectious diseases may be characterized by their case fatality rate (CFR), the proportion of people diagnosed with a disease who die from it (cf. mortality rate).It should not be confused with the infection fatality rate (IFR), the estimated proportion of people infected by a disease-causing agent, including asymptomatic and undiagnosed infections, who die from the disease.
It is discussed in further detail by Sperber and Hirschfeld for the cases of folkbiology, folksociology, and supernaturalism. [2] Here is an example: Think about a human cognitive sub-system that must have been very important for human cognitive evolution (i.e. a module with an innate basis); like the ability that allows humans to recognize and ...
Lung cancer is associated with the bacterium Chlamydia pneumoniae, [27] with human papillomaviruses, and with Merkel cell polyomavirus. [28] Leukemia. Adult T-cell leukemia can be caused by human T-cell leukemia virus-1. Mesothelioma is associated with simian virus 40, [29] especially in conjunction with asbestos exposure.
For example, smallpox eradication, with the last wild case in 1977, and certification of the eradication of indigenous transmission of 2 of the 3 types of wild poliovirus (type 2 in 2015, after the last reported case in 1999, and type 3 in 2019, after the last reported case in 2012). [29] The herd immunity level will be denoted q.
The number of infections equals the cases identified in the study or observed. An example would be HIV infection during a specific time period in the defined population. The population at risk are the cases appearing in the population during the same time period. An example would be all the people in a city during a specific time period.
Epidemiological (and other observational) studies typically highlight associations between exposures and outcomes, rather than causation. While some consider this a limitation of observational research, epidemiological models of causation (e.g. Bradford Hill criteria) [7] contend that an entire body of evidence is needed before determining if an association is truly causal. [8]