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Activity Number: 595 - Global Estimates of Morbidity and Mortality
Type: Invited
Date/Time: Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract #300485
Title: Making Inference in Global Health When There Is Limited (Or No) Data
Author(s): Bethany Hedt-Gauthier*
Companies: Harvard Medical School
Keywords: Global health; program evaluation; data quality; health equity

Health programs in low- and middle-income countries (LMICs) must make data-driven decisions to optimize implementation and outcomes. However, data for these programs are sparse and the data that do exist are often of limited quality. This talk will review the data sources most commonly available for program implementation and evaluation in LMICs, with a focus on sub-Saharan Africa. The talk will also discuss the opportunities and pitfalls of “borrowing” data from other contexts to fill in the information gaps, an approach commonly used in global health inference. Finally, the talk will conclude with recommendations to statisticians on how to best fill the information and methods void that currently exists in global health.

Authors who are presenting talks have a * after their name.

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