Pascal Geldsetzer of Stanford University in the U.S. will develop a computational tool to support health campaigns in low- and middle-income countries that can predict the number and location of the people that need targeting. They will use freely available databases, including the Demographic and Health Surveys (DHS), covering over 10 million households and high-resolution population estimates to estimate the percentage of children under 5-years-old who are un- or under-vaccinated within each 30m by 30m area. They will then use algorithms to determine the optimal numbers and locations of campaign posts needed to ensure a desired vaccination coverage within a given budget. This work will lay the foundation for developing a simple Android application to help managers increase the impact of health campaigns.
More information about Innovations for Improving the Impact of Health Campaigns (Round 24)