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on
1
Introduction
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Presentation
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Heterogeneity
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Sources of heterogeneity
5
Cities
6
Equity and social justice
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Fundamental insights
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Access to testing
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Contact rates
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Vaccine uptake
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Public health messaging
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Bivariate analysis
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Framing individuals as vectors
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No longer social inequalities
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Stigma
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Political correctness
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Consequences
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Principles of practice
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The importance of amplifying
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Ed Young
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Dr John OBrien
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Thank you
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Comments
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Simple but not too simple
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Model specification
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Mathematical modeling
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Field Institute
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Open Access
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Lab Website
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Mathematical background
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Mathematical epidemiology
32
Conclusion
Description:
Explore a thought-provoking colloquium on ethical considerations in epidemic modeling, focusing on HIV and COVID-19. Examine how terminology, assumptions, and interpretations can impact communities disproportionately affected by these diseases. Learn about the evolution of HIV modeling practices and the importance of partnering with affected communities. Analyze common analytic biases, simplifying assumptions, and potential misinterpretations in epidemic models. Discover best practices for de-stigmatizing language in health research and gain insights from discussions with communities about HIV and COVID-19 modeling results. Reflect on the potential impact of models on inequitable public health responses and consider ways to improve future approaches.

Do No Harm - Terminology, Assumptions, and Interpretation of Epidemic Models in Communities Most Affected

Fields Institute
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