Author: Vir Bannerjee Bulchandani; Saumya Shivam; Sanjay Moudgalya; S L Sondhi
Title: Digital Herd Immunity and COVID-19 Document date: 2020_4_18
ID: k8xuv5xy_50
Snippet: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.15.20066720 doi: medRxiv preprint sufficiently expressive to model complicated features of COVID-19 spreading and control, for example presymptomatic transmission, as distinct from asymptomatic transmission, and recursive contact tracing. Using this model we obtained predictions for realistic COVID-19 parameter values, finding that in ord.....
Document: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.15.20066720 doi: medRxiv preprint sufficiently expressive to model complicated features of COVID-19 spreading and control, for example presymptomatic transmission, as distinct from asymptomatic transmission, and recursive contact tracing. Using this model we obtained predictions for realistic COVID-19 parameter values, finding that in order for a contact-tracing app to be effective, the fraction of app take-up among a given population would need to lie between 75% and 95%, depending on the frequency of asymptomatic transmission.
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