Background: Understanding changes in infectiousness during SARS-COV-2 infections is critical to assess the effectiveness of public health measures such as contact tracing.
Methods: Here, we develop a novel mechanistic approach to infer the infectiousness profile of SARS-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.
Results: 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.
Conclusions: 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.
Funding: Engineering and Physical Sciences Research Council (EPSRC).
All data generated or analysed during this study are included in the manuscript and supporting files. A source data file has been provided for Figure 2, containing the SARS-CoV-2 transmission pair data used in our analyses. These data were originally reported in references (3,10,29-31), and the combined data were also considered in reference (4). Code for reproducing our results is available at https://github.com/will-s-hart/COVID-19-Infectiousness-Profile.
- William Stephen Hart
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Jennifer Flegg, The University of Melbourne, Australia
© 2021, Hart et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.