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Statistical modeling is essential for evidence-based decision-making in public health, especially in sub-Saharan Africa, where the prevalence of both communicable and noncommunicable diseases remains high. This chapter serves as an introduction to the book “Statistical Modelling for Evidence-Based Public Health: Case Studies in HIV Epidemiology and Child and Maternal Health.” It outlines the book’s structure and key themes while highlighting the use of advanced statistical techniques to analyze disease patterns, monitor health interventions, and optimize health policies. By connecting data science with public health, this chapter underscores the importance of robust analytical methods in enhancing healthcare outcomes and guiding policy decisions in resource-limited settings.

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Advancing Evidence-Based Decision-Making in Public Health: The Critical Role of Practical Biostatistical Methods for Health Monitoring in Sub-Saharan Africa

  • 章节

  • 发表日期：

    2025年

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  • Tsirizani M. Kaombe,
  • Lawrence N. Kazembe,
  • Vincent Samuel Phiri,
  • Dzinkambani Kambalame,
  • Adamson Sinjani Muula

摘要

Statistical modeling is essential for evidence-based decision-making in public health, especially in sub-Saharan Africa, where the prevalence of both communicable and noncommunicable diseases remains high. This chapter serves as an introduction to the book “Statistical Modelling for Evidence-Based Public Health: Case Studies in HIV Epidemiology and Child and Maternal Health.” It outlines the book’s structure and key themes while highlighting the use of advanced statistical techniques to analyze disease patterns, monitor health interventions, and optimize health policies. By connecting data science with public health, this chapter underscores the importance of robust analytical methods in enhancing healthcare outcomes and guiding policy decisions in resource-limited settings.