Modeling and Predicting the Spread of Covid-19 : Comparative Results for the United States, the Philippines, and South Africa

Dasgupta, Susmita ; Wheeler, David

World Bank, Washington, DC

关键词: CORONAVIRUS;    COVID-19;    PANDEMIC;    INFECTION DATA;    EPIDEMIC SPREAD;   

DOI  :  10.1596/1813-9450-9419
RP-ID  :  WPS9419

学科分类：社会科学、人文和艺术（综合）

来源: World Bank Open Knowledge Repository

【 摘 要 】

A model of Covid-19 transmission amonglocations within a country has been developed that is (1)implementable anywhere spatially-disaggregated Covid-19infection data are available; (2) scalable for locations ofdifferent sizes, from individual regions to countries ofcontinental scale; (3) reliant solely on data that are freeand open to public access; (4) grounded in a rigorous,proven methodology; and (5) capable of forecasting futurehotspots with enough accuracy to provide useful alerts.Applications to the United States, the Philippines, andSouth Africa's Western Cape province demonstrate themodel's usefulness. The model variables includeindicators of interactions among infected residents, locallyand at a greater distance, with infection dynamics capturedby a Gompertz growth model.The model results for all threecountries suggest that local infection growth is affected bythe scale of infections in relatively distant places.Forecasts of hotspots 14 and 28 days in advance, using onlyinformation available on the first day of the forecast,indicate an imperfect but nonetheless informativeidentification of actual hotspots.