Public Health Best Practices
Using Data To Capture and Change Structural Factors
Upstream factors are important for preventing and mitigating health disparities. We bring focus to how data can be used to capture these social and environmental factors, and how to incorporate them in models that affect change. Relevant Papers Zhao, Y., Paul, R., Reid, S., Vieira, C. C., Wolfe, C., Zhang, Y., & Chunara, R., 2024. Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts. Social Indicators Research. Zhang, M., Rahman, S., Mhasawade, V., & Chunara, R., 2024. Utilizing big data without domain knowledge impacts public health decision-making. Proceedings of the National Academy of Sciences of ...
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NSF CAREER: Learning from When, Where and by Whom Data is Generated for Advancing Public Health Studies (2019-2024)
This award is focused on developing new machine learning and data science approaches motivated by the need to improve data management and analysis in the public health domain. The project will also provide educational programs informed by best practices in research for public health practitioners, students, and community members in the context of data science and public health.
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Social Determinants and Risk Prediction
Social determinants play an important role in shaping noncommunicable disease. We are examining the role of social determinants in clinical risk prediction as well as appropriate modeling strategies for their integration.
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