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University of Cambridge > Talks.cam > Worms and Bugs > LSOA level risk model and early detection system; a framework to incorporate mobility, vaccination, health background, land use factors, and socioeconomic and demographic characteristics in evaluating COVID19 prevalence and risk
LSOA level risk model and early detection system; a framework to incorporate mobility, vaccination, health background, land use factors, and socioeconomic and demographic characteristics in evaluating COVID19 prevalence and riskAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Dr Ciara Dangerfield. ONS Dara Science Campus is developing a COVID19 risk model and early detection system at spatially aggregated LSOA level. The aim is to create a framework where the impact of NPIs (e.g. through examining changes in mobility indicators) can be evaluated after controlling for land use characteristics, vaccination rate, and socioeconomic and demographic factors. The model also aims to predict the spatial distribution of the near future risks and detect the outliers as potential area of concerns. This talk is part of the Worms and Bugs series. This talk is included in these lists:
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