Epidemiological method: Difference between revisions

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== Measures ==

Epidemiologists are famous for their use of rates. Each measure serves to characterize the disease giving valuable information about contagiousness, incubation period, duration, and mortality of the disease.{{cn|date=August 2022}}

=== Measures of occurrence ===

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==Limitations==

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)<ref>{{cite journal | vauthors = Fedak KM, Bernal A, Capshaw ZA, Gross S | title = Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology | journal = Emerging Themes in Epidemiology | volume = 12 | pages = 14 | date = 2015-09-30 | pmid = 26425136 | pmc = 4589117 | doi = 10.1186/s12982-015-0037-4 | doi-access = free }}</ref> contend that an entire body of evidence is needed before determining if an association is truly causal.<ref>{{cite web | url = http://sphweb.bumc.bu.edu/otlt/MPH-Modules/EP/EP713_Causality/EP713_Causality_print.html | title = Causal Inference | publisher = Boston University School of Public Health |access-date=2018-04-01}}</ref> Moreover, many research questions are impossible to study in experimental settings, due to concerns around ethics and study validity. For example, the link between [[cigarette]] smoke and lung cancer was uncovered largely through observational research; however research ethics would certainly prohibit conducting a randomized trial of cigarette smoking once it had already been identified as a potential health threat.{{cn|date=August 2022}}

==See also==