Author
Hart, W
Maini, P
Thompson, R
Journal title
eLife
DOI
10.7554/eLife.65534
Volume
10
Last updated
2024-03-10T09:44:35.253+00:00
Abstract
<br><strong>Background<br></strong>
Understanding changes in infectiousness during SARS-COV-2 infections is critical to assess the effectiveness of public health measures such as contact tracing.
<br><strong>Methods<br></strong>
Here, we develop a novel mechanistic approach to infer the infectiousness profile of SARS17 COV-2 infected individuals using data from known infector-infectee pairs. We compare estimates of key epidemiological quantities generated using our mechanistic method with analogous estimates generated using previous approaches.
<br><strong>Results<br></strong>
The mechanistic method provides an improved fit to data from SARS-CoV-2 infector infectee pairs compared to commonly used approaches. Our best-fitting model indicates a high proportion of presymptomatic transmissions, with many transmissions occurring shortly before the infector develops symptoms.
<br><strong>Conclusions<br></strong>
High infectiousness immediately prior to symptom onset highlights the importance of continued contact tracing until effective vaccines have been distributed widely, even if contacts from a short time window before symptom onset alone are traced.
<br><strong>Funding<br></strong>
Engineering and Physical Sciences Research Council (EPSRC).
Symplectic ID
1174071
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Publication type
Journal Article
Publication date
26 Apr 2021
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