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Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events
SARS-CoV-2 is difficult to contain because many transmissions occur during the pre-symptomatic phase of infection. Moreover, in contrast to influenza, while most SARS-CoV-2 infected people do not transmit the virus to anybody, a small percentage secondarily infect large numbers of people. We designe...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536880/ https://www.ncbi.nlm.nih.gov/pubmed/33024978 http://dx.doi.org/10.1101/2020.08.07.20169920 |
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author | Goyal, Ashish Reeves, Daniel B. Cardozo-Ojeda, E. Fabian Schiffer, Joshua T. Mayer, Bryan T. |
author_facet | Goyal, Ashish Reeves, Daniel B. Cardozo-Ojeda, E. Fabian Schiffer, Joshua T. Mayer, Bryan T. |
author_sort | Goyal, Ashish |
collection | PubMed |
description | SARS-CoV-2 is difficult to contain because many transmissions occur during the pre-symptomatic phase of infection. Moreover, in contrast to influenza, while most SARS-CoV-2 infected people do not transmit the virus to anybody, a small percentage secondarily infect large numbers of people. We designed mathematical models of SARS-CoV-2 and influenza which link observed viral shedding patterns with key epidemiologic features of each virus, including distributions of the number of secondary cases attributed to each infected person (individual R(0)) and the duration between symptom onset in the transmitter and secondarily infected person (serial interval). We identify that people with SARS-CoV-2 or influenza infections are usually contagious for fewer than one day congruent with peak viral load several days after infection, and that transmission is unlikely below a certain viral load. SARS-CoV-2 super-spreader events with over 10 secondary infections occur when an infected person is briefly shedding at a very high viral load and has a high concurrent number of exposed contacts. The higher predisposition of SARS-CoV-2 towards super-spreading events is not due to its 1–2 additional weeks of viral shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks than a person infected with influenza, likely due to aerosolization of virus. Our results support policies that limit crowd size in indoor spaces and provide viral load benchmarks for infection control and therapeutic interventions intended to prevent secondary transmission. |
format | Online Article Text |
id | pubmed-7536880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-75368802020-10-07 Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events Goyal, Ashish Reeves, Daniel B. Cardozo-Ojeda, E. Fabian Schiffer, Joshua T. Mayer, Bryan T. medRxiv Article SARS-CoV-2 is difficult to contain because many transmissions occur during the pre-symptomatic phase of infection. Moreover, in contrast to influenza, while most SARS-CoV-2 infected people do not transmit the virus to anybody, a small percentage secondarily infect large numbers of people. We designed mathematical models of SARS-CoV-2 and influenza which link observed viral shedding patterns with key epidemiologic features of each virus, including distributions of the number of secondary cases attributed to each infected person (individual R(0)) and the duration between symptom onset in the transmitter and secondarily infected person (serial interval). We identify that people with SARS-CoV-2 or influenza infections are usually contagious for fewer than one day congruent with peak viral load several days after infection, and that transmission is unlikely below a certain viral load. SARS-CoV-2 super-spreader events with over 10 secondary infections occur when an infected person is briefly shedding at a very high viral load and has a high concurrent number of exposed contacts. The higher predisposition of SARS-CoV-2 towards super-spreading events is not due to its 1–2 additional weeks of viral shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks than a person infected with influenza, likely due to aerosolization of virus. Our results support policies that limit crowd size in indoor spaces and provide viral load benchmarks for infection control and therapeutic interventions intended to prevent secondary transmission. Cold Spring Harbor Laboratory 2020-09-28 /pmc/articles/PMC7536880/ /pubmed/33024978 http://dx.doi.org/10.1101/2020.08.07.20169920 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/It is made available under a CC-BY-NC-ND 4.0 International license (http://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Article Goyal, Ashish Reeves, Daniel B. Cardozo-Ojeda, E. Fabian Schiffer, Joshua T. Mayer, Bryan T. Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title | Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title_full | Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title_fullStr | Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title_full_unstemmed | Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title_short | Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events |
title_sort | wrong person, place and time: viral load and contact network structure predict sars-cov-2 transmission and super-spreading events |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536880/ https://www.ncbi.nlm.nih.gov/pubmed/33024978 http://dx.doi.org/10.1101/2020.08.07.20169920 |
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