University of Massachusetts Amherst

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Statistical Modeling in Global Health

October 2

Leontine Alkema, Biostatistics and Epidemiology

Title: Statistical Modeling in Global Health: A Selection of Recent Developments and Future Opportunities in Child, Maternal and Reproductive Health

Abstract: Are developing countries making progress in reducing child and maternal mortality? How do we assess whether girls’ mortality is elevated in countries where a preference for sons may exist? How can countries best monitor unmet need for contraceptive methods, and set targets for improving access? Questions like these require answers to inform the global health agenda in child, maternal and reproductive health. In this presentation, I will discuss some of the general challenges for answering such questions and give examples of statistical models that we used to provide answers. A Bayesian B-splines regression modelling approach to estimating child mortality and a Bayesian hierarchical time series model for assessing outlying child mortality gender ratios will be discussed in more detail. I will conclude with some future directions for “Stats in action” within global health research.

Bio: Leontine Alkema is Assistant Professor of Biostatistics at UMass Amherst. Her research focuses on the development of statistical models to assess and interpret demographic and population-level health trends and differentials, generally on a national level, for all countries in the world. She collaborates with various United Nations agencies to make available improved estimation methods and resulting estimates to diverse international audiences