November 16, 2015 | News | Suessmilch Lecture

Bayesian modeling approaches for family planning indicators and proximate determinants of fertility

On November 23 Leontine Alkema of the University of Massachusetts Amherst will give a talk at the MPIDR. She will explain a method used by the United Nations and Family Planning 2020 (FP2020) to estimate and project family planning indicators.

About the talk

Contraceptive prevalence and unmet need for family planning are important indicators that measure the degree to which women and their partners are able to prevent unintended pregnancies, and that can benchmark progress towards achieving universal access to reproductive health.

In this presentation, I will introduce a Bayesian hierarchical time series modeling approach that is used by the United Nations Population Division and the global partnership FP2020 to estimate and project family planning indicators at the national and subnational level. The presentation will outline the challenges regarding data sources and estimation, and discuss the approaches used to overcome these challenges. I will conclude with ongoing work on a Bayesian extended version of Bongaarts' proximate determinants model, aimed at providing new insights into abortion incidence and unintended pregnancies worldwide.

The applications will be used to highlight the role and potential of Bayesian methods for modeling demographic indicators.

About the person

Leontine Alkema is Assistant Professor of Biostatistics at the University of Massachusetts Amherst. Leontine Alkema received her M.Sc. in Applied Mathematics from Delft University of Technology in the Netherlands and her Ph.D. in Statistics from the University of Washington. She was a post-doctoral research fellow at Columbia University, a visiting Assistant Professor at UC Berkeley and Assistant Professor at the National University of Singapore before joining 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.