Modeling and predicting the spread of Covid-19 : comparative results for the United States, the Philippines, and South Africa / Susmita Dasgupta, David Wheeler
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: World Bank E-Library Archive | Policy research working paper ; 9419Publisher: [Washington, DC, USA] : World Bank Group, Development Economics, Development Research Group & Urban, Disaster Risk Management, Resilience and Land Global Practice, October 2020Description: 1 Online-Ressource (circa 24 Seiten) : IllustrationenSubject(s): Genre/Form: Additional physical formats: Erscheint auch als: Modeling and Predicting the Spread of Covid-19: Comparative Results for the United States, the Philippines, and South Africa. Druck-Ausgabe Washington, D.C : The World Bank, 2020DOI: DOI: 10.1596/1813-9450-9419Online resources: Summary: A model of Covid-19 transmission among locations within a country has been developed that is (1) implementable anywhere spatially-disaggregated Covid-19 infection data are available; (2) scalable for locations of different sizes, from individual regions to countries of continental scale; (3) reliant solely on data that are free and open to public access; (4) grounded in a rigorous, proven methodology; and (5) capable of forecasting future hotspots with enough accuracy to provide useful alerts. Applications to the United States, the Philippines, and South Africa's Western Cape province demonstrate the model's usefulness. The model variables include indicators of interactions among infected residents, locally and at a greater distance, with infection dynamics captured by a Gompertz growth model. The model results for all three countries suggest that local infection growth is affected by the scale of infections in relatively distant places. Forecasts of hotspots 14 and 28 days in advance, using only information available on the first day of the forecast, indicate an imperfect but nonetheless informative identification of actual hotspotsPPN: PPN: 1743508247Package identifier: Produktsigel: ZDB-110-WBL | ZDB-1-WBA | ZDB-110-WBONo physical items for this record
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