Mapping COVID-19 vaccine hesitancy drivers using machine learning enhanced geospatial data

We will share how we are using machine learning (ML) enhanced geospatial data to 1) map levels of COVID-19 vaccine hesitancy, 2) model the underlying drivers of hesitancy based on Confidence, Convenience, and Complacency, and 3) segment populations based on the unique combinations of these drivers down to the 1km2 across Ethiopia, Ghana, Kenya, Malawi, Mali, Nigeria, Rwanda, South Africa, Uganda, and Zambia. We are delivering data via a custom web-based dashboard/application to inform risk communication and community engagement (RCCE) and social behavior change (SBC) efforts among a wide variety of implementing partners working to increase COVID-19 vaccine uptake.

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