Bio:

Jaline Gerardin is a computational epidemiologist with a background in mathematical modeling and translation to policy. She has worked with high-burden countries in using data and analytics to inform malaria strategic planning, including the application of models to predict intervention impact. Her work on model development has focused on transmission dynamics, effects of antimalarials, and using machine learning techniques to address computational tractability. Passionate about expanding the talent pool for analytics, Jaline has led a training program in applied malaria modeling that builds technical, scientific, and communication skills in the next generation of modelers and educators. She is a co-founder and the Executive Director of the Applied Malaria Modeling Network (AMMnet). Jaline was previously malaria team lead at the Institute for Disease Modeling and currently faculty at Northwestern University.

Abstract:

Sub-Saharan Africa faces a funding shock for health financing amidst a high health burden. Setting health priorities well, and improving service delivery, is more important than ever, and public health analytics and modeling can play a strong role. I present a data-to-action application of mathematical modeling embedded in existing malaria policy decision-making structures, illustrating the opportunities available to improve analytical rigor as well as remaining challenges.