Data, science and achieving the sustainable development goals
The United Nation’s Sustainable Development Goal 3 aims to ensure healthy lives and promote well-being for all at all ages. This goal includes reduction in maternal mortality to less than 70/100,000 live births, lowering child mortality below 25 deaths per 1,000 births and 30% reduction in premature deaths due to non-communicable disease by 2030. In order to meet these targets, we need information about who is dying, where and from what? This information is not easily available for the majority of deaths occurring in low and middle income countries. We are now understanding more, thanks to a major health information-strengthening effort.
This session discusses the data collection scale currently underway, where new data and analytics, and human-computer collaboration will provide comprehensive monitoring of efforts to bend the curve. It describes the Global Burden of Disease Study, an ongoing effort to integrate all available data and produce estimates of who is sick with what and where and can SDGs be attained given the current scale of interventions.
Abraham Flaxman: Planning Strategic Health Interventions from Global Burden of Disease Estimates
Abraham Flaxman, PhD, is an Associate Professor of Health Metrics Sciences at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. He is currently leading the development of a simulation platform to derive “what-if” results from Global Burden of Disease estimates and is engaged in methodological and operational research on verbal autopsy. Dr. Flaxman has previously designed software tools such as DisMod-MR that IHME uses to estimate the Global Burden of Disease, and the Bednet Stock-and-Flow Model, which has produced estimates of insecticide-treated net coverage in sub-Saharan Africa. This work uses Integrative Systems Modeling to combine a system dynamics model of process with a statistical model of data to bring together all available sources of information.