Author: Luca Ferretti; Chris Wymant; Michelle Kendall; Lele Zhao; Anel Nurtay; David G Bonsall; Christophe Fraser
Title: Quantifying dynamics of SARS-CoV-2 transmission suggests that epidemic control and avoidance is feasible through instantaneous digital contact tracing Document date: 2020_3_12
ID: bc9retcq_22
Snippet: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.03.08.20032946 doi: medRxiv preprint (33) suggest that in practice manual contact tracing can only improve on this to a limited extent: it is too slow, and cannot be scaled up once the epidemic grows beyond the early phase, due to limited personnel. Using mobile phones to measure infectious disease contact networks has been proposed previously (.....
Document: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.03.08.20032946 doi: medRxiv preprint (33) suggest that in practice manual contact tracing can only improve on this to a limited extent: it is too slow, and cannot be scaled up once the epidemic grows beyond the early phase, due to limited personnel. Using mobile phones to measure infectious disease contact networks has been proposed previously (34-36). Considering our quantification of SARS-CoV-2 transmission, we suggest that this approach, with a mobile phone App implementing instantaneous contact tracing, could reduce transmission enough to achieve R < 1 and sustained epidemic suppression, stopping the virus from spreading further. We have developed a web interface to explore the uncertainty in our modelling assumptions (25). This will also serve as an ongoing resource as new data becomes available and as the epidemic evolves.
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