We find ourselves in a global pandemic, referred to as COVID-19. There is much research underway on all aspects of the pandemic, including to slow its spread, improve diagnostic tests and develop a vaccine. Population Data Science has a unique part to play because of the availability of large-scale datasets on the general population or on specific cohorts, such as age groups, geographic regions, particular health conditions or socio-economic levels.

The datasets are being used in many ways, such as to contribute to mapping infection patterns, identifying at risk groups, modelling likely case numbers and predicting when risks might reduce. In some cases, additional datasets such as virus surveillance data, symptom tracking, and other study data are augmenting routine health and administrative datasets. As well as studies involving data analysis, the pandemic is influencing how data are used under these circumstances, including what our policies should be, how to engage effectively with the public and how to manage data governance to preserve robustness and simultaneously expedite data access.

Developing a Data Integrated COVID-19 Tracking System for Decision-Making and Public Use

Alexander Krusina, Oscar Chen, Lucia Otero Varela, Chelsea Doktorchik, Vince Avati, Søren Knudsen, Danielle Southern, Cathy Eastwood, Nishan Sharma, Tyler Williamson
Published online: Sep 28, 2020