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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
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Flattening Epidemic Curves and COVID-19: Policy Rationales, Inequality, and Racism.

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    Flattening epidemic curves, like during COVID-19, disproportionately harms essential workers and minority groups by increasing structural inequality. Societies must mitigate these harms despite the benefits of a flattened curve.

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    Area of Science:

    • Public Health
    • Epidemiology
    • Sociology

    Background:

    • Interventions to flatten epidemic curves are common during public health crises.
    • The U.S. COVID-19 pandemic provides a relevant context for analyzing these interventions.
    • Flattened curves may have unintended consequences on vulnerable populations.

    Purpose of the Study:

    • To examine rationales for and against flattening epidemic curves.
    • To analyze how flattened curves impact essential workers and minority populations.
    • To distinguish and explore forms of racism, particularly structural racism.

    Main Methods:

    • Review of rationales for and against epidemic curve flattening.
    • Analysis of the U.S. COVID-19 experience.
    • Distinction between simple, systemic, and structural racism.

    Main Results:

    • Flattened epidemic curves increase risks for essential workers, low-income, and minority populations.
    • Structural racism, characterized by a lack of intentionality, is exacerbated by flattened curves.
    • Societies prolonging epidemics through flattening incur ethical obligations.

    Conclusions:

    • Flattening epidemic curves can worsen structural inequality.
    • Societies have a responsibility to mitigate and compensate victims of inequality resulting from prolonged epidemics.