Geohealth monitoring

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The Pandemic Recovery Survey aims to study the impacts of COVID-19 across the world and to assist public health officials in focusing their efforts to recover from the pandemic and allocate resources. It includes questions about people’s access to health information, support, and care, their confidence in vaccines, household financial and food (in)security as well as their socio-demographic characteristics. People from 21 countries around the globe are invited to participate via Facebook.

The University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey, in partnership with Facebook is a partnership between Facebook and academic institutions. The survey is available in 56 languages. A representative sample of Facebook users is invited on a daily basis to report on topics including, for example, symptoms, social distancing behavior, vaccine acceptance, mental health issues, and financial constraints. Facebook provides weights to reduce nonresponse and coverage bias. Country and region-level statistics are published daily via public API and dashboards, and microdata is available for researchers via data use agreements. Over half a million responses are collected daily.

DemeNumberSelector is an R package designed to automatically determine the optimized number of demes for a gene flow method known as estimated effective migration surfaces.

SparseSampleFiltering is a set of Python scripts designed to filter out high spatial uncertainty contours from estimated effective migration surfaces caused by sparse sample locations.