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Obtaining Accurate Estimates of Subnational Vaccine Coverage

Joshua Warren and Daniel Weinberger of Yale University in the U.S. will develop an analytical framework to improve local estimates of vaccine coverage in low- to middle-income countries. Current estimates can be unreliable, due to errors and biases in record-keeping and difficulties in estimating local population sizes, and are further complicated when children are vaccinated outside of their home administrative district. They will develop advanced spatial analytical methods including bias adjustments that take these issues into account and can generate more reliable local estimates also from poor quality data. They will collect higher quality survey data on vaccine coverage and population sizes from selected locations to calibrate and ultimately validate the estimates. Their approach can be used in other low-income settings to improve vaccine coverage.

More information about Innovations in Immunization Data Management, Use, and Improved Process Efficiency (Round 21)

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The Bill & Melinda Gates Foundation is part of the Grand Challenges partnership network. Visit www.grandchallenges.org to view the map of awarded grants across this network and grant opportunities from partners.