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Epidemiology


Epidemiology is the study and analysis of the patterns, causes, and effects of health and disease conditions in defined populations. It is the cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences.

Major areas of epidemiological study include disease etiology, transmission, outbreak investigation, disease surveillance, forensic epidemiology and screening, biomonitoring, and comparisons of treatment effects such as in clinical trials. Epidemiologists rely on other scientific disciplines like biology to better understand disease processes, statistics to make efficient use of the data and draw appropriate conclusions, social sciences to better understand proximate and distal causes, and engineering for exposure assessment.


Cases Controls
Exposed A B
Unexposed C D
..... Cases Controls
Exposed 103 84
Unexposed 84 103
..... Cases Controls
Exposed 1732 1652
Unexposed 1652 1732
..... Case Non-case Total
Exposed A B (A + B)
Unexposed C D (C + D)

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

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