Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events
- Fred Hutchinson Cancer Research Center, United States
Abstract
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 one 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 towards 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.
Data availability
The original data and code is shared at: https://github.com/ashish2goyal/SARS_CoV_2_Super_Spreader_Event
Article and author information
Author details
Funding
National Institute of Allergy and Infectious Diseases (R01 AI121129-05S1)
- Joshua T Schiffer
Council of State and Territorial Epidemiologists (Inform Public Health Decision Making Funding Opportunity)
- Joshua T Schiffer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Goyal 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.
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Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events
eLife 10:e63537.
https://doi.org/10.7554/eLife.63537
Further reading
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- Medicine
- Microbiology and Infectious Disease
- Epidemiology and Global Health
- Immunology and Inflammation
eLife has published articles on a wide range of infectious diseases, including COVID-19, influenza, tuberculosis, HIV/AIDS, malaria and typhoid fever.
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- Epidemiology and Global Health
Background:
Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.
Methods:
This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera–Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.
Results:
About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of –0.19 (95% CI −0.34, –0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.
Conclusions:
Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.
Funding:
This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.
