Academic Journal

Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events

التفاصيل البيبلوغرافية
العنوان: Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events
المؤلفون: Ashish Goyal, Daniel B Reeves, E Fabian Cardozo-Ojeda, Joshua T Schiffer, Bryan T Mayer
المصدر: eLife, Vol 10 (2021)
بيانات النشر: eLife Sciences Publications Ltd
سنة النشر: 2021
المجموعة: Directory of Open Access Journals: DOAJ Articles
مصطلحات موضوعية: SARS-CoV-2, epidemiology, mathematical modeling, viral dynamics, Medicine, Science, Biology (General), QH301-705.5
الوصف: SARS-CoV-2 is difficult to contain because many transmissions occur during pre-symptomatic infection. Unlike influenza, most SARS-CoV-2-infected people do not transmit while a small percentage infect large numbers of people. We designed mathematical models which link observed viral loads with epidemiologic features of each virus, including distribution of transmissions attributed to each infected person and duration between symptom onset in the transmitter and secondarily infected person. We identify that people infected with SARS-CoV-2 or influenza can be highly contagious for less than 1 day, congruent with peak viral load. SARS-CoV-2 super-spreader events occur when an infected person is shedding at a very high viral load and has a high number of exposed contacts. The higher predisposition of SARS-CoV-2 toward super-spreading events cannot be attributed to additional weeks of shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks, likely due to aerosolization.
نوع الوثيقة: article in journal/newspaper
اللغة: English
تدمد: 2050-084X
Relation: https://elifesciences.org/articles/63537; https://doaj.org/toc/2050-084X; e63537; https://doaj.org/article/008fe4290c394c67af594a260723aec4
DOI: 10.7554/eLife.63537
الاتاحة: https://doi.org/10.7554/eLife.63537
https://doaj.org/article/008fe4290c394c67af594a260723aec4
رقم الانضمام: edsbas.DBCBBE70
قاعدة البيانات: BASE
الوصف
تدمد:2050084X
DOI:10.7554/eLife.63537