Bio:

Leontine Alkema is a Professor of Biostatistics at the University of Massachusetts Amherst. Dr. Alkema's research focuses on developing statistical models to understand trends and disparities in reproductive, maternal, and child health outcomes worldwide. She has created statistical methods for monitoring key global indicators, including under-five mortality rates, maternal mortality, contraceptive use and unmet needs, abortion incidence, and total fertility rates. Her work also aims to evaluate the impact of policies and programs on family planning and related outcomes. Dr. Alkema collaborates with various United Nations agencies, the World Health Organization, the FP2030 community, and the Guttmacher Institute to help make available improved estimation methods, software, and model-based estimates for diverse international audiences.

Abstract:

Population-level measures of demographic and health indicators over time are crucial for identifying disadvantaged groups, assessing progress, and informing resource allocation. However, monitoring can be complicated by the scarcity of high-quality data. In such cases, statistical models can integrate data from multiple sources to generate estimates and forecasts with associated uncertainties.

In this presentation, I will explore the necessity and application of statistical models for estimating and forecasting demographic and global health indicators. I will specifically focus on global estimation and forecasting of family planning indicators, such as modern contraceptive use and unmet contraceptive needs. I will introduce the Family Planning Estimation Tool (FPET), a Bayesian statistical model that is used in low- and middle-income countries to produce estimates and short-term forecasts of family planning indicators. Drawing on our experiences with FPET, I will discuss lessons learned and ongoing challenges in the broader field of statistical modeling for monitoring demographic and global health indicators.

This is joint work with Herbert Susmann, Evan Ray, Shauna Mooney, Niamh Cahill, Kristin Bietsch, Priya Emmart, Rebecca Rosenberg, John Stover, and Emily Sonneveldt.