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    Area of Science:

    • Epidemiology
    • Public Health Research Methods

    Background:

    • Descriptive epidemiologic studies are crucial for understanding population health.
    • A clear framework is needed to guide the design and conduct of these studies.
    • Existing methods may lack standardization, potentially leading to biased results.

    Purpose of the Study:

    • To propose a structured framework for designing and conducting descriptive epidemiologic studies.
    • To ensure clarity in defining target populations, outcomes, measures of occurrence, and auxiliary variables.
    • To illustrate the framework's application and identify potential biases.

    Main Methods:

    • Development of a conceptual framework for descriptive studies.
    • Identification of key components: target population (person, place, time), outcome, measure of occurrence, and auxiliary variables.
    • Application of the framework to a real-world dataset on viral suppression in people with HIV in the US.

    Main Results:

    • The framework requires explicit definition of population, outcome, and measurement.
    • Application revealed potential biases related to missing data, measurement error, and loss to follow-up.
    • The framework aids in identifying and mitigating biases in descriptive studies.

    Conclusions:

    • A well-defined descriptive epidemiologic study requires precise articulation of its components.
    • The proposed framework enhances the rigor and transparency of descriptive study design.
    • Adherence to this framework can minimize biases and improve the reliability of health research findings.