Epidemiology provides the scientific framework for understanding the distribution and determinants of health and disease in populations. This webinar offers a comprehensive introduction to the foundational concepts necessary for measuring and interpreting disease occurrence in public health research. Participants will begin with a clear definition of epidemiology and an overview of the types of variables commonly used in epidemiologic studies, including exposures, outcomes, and potential confounders.
The webinar will then introduce essential principles of hypothesis testing, including the interpretation of p-values and confidence intervals, enabling participants to critically assess statistical evidence in scientific literature. Core measures of disease frequency like incidence, prevalence, and mortality will be explained in detail, followed by a discussion of measures of association including relative risk, odds ratio, and attributable risk.
Special emphasis will be placed on understanding cause–effect relationships in epidemiology and evaluating the potential impact of exposures on disease burden through measures such as population attributable risk. The session will conclude by highlighting how accurate measurement of disease informs surveillance systems, guides prevention strategies, and supports evidence-based public health decision-making.
A webinar on understanding epidemiological disease measurement to interpret health data and support evidence-based decisions.
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