Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions

Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, including serial interval distributions-i.e., the time between illness onset in successive cases in a...

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Published inScience Vol. 369; no. 6507; pp. 1106 - 1109
Main Authors Ali, Sheikh Taslim, Wang, Lin, Lau, Eric H Y, Xu, Xiao-Ke, Du, Zhanwei, Wu, Ye, Leung, Gabriel M, Cowling, Benjamin J
Format Journal Article Web Resource
LanguageEnglish
Published United States The American Association for the Advancement of Science 28.08.2020
American Association for the Advancement of Science
Subjects
Basic Reproduction Number
Betacoronavirus
China - epidemiology
Coronaviridae
Coronavirus Infections - epidemiology
Coronavirus Infections - transmission
Coronaviruses
Cough
COVID-19
Disease transmission
Epidemiology
Forecasting
Herd immunity
Humans
Incidence
Infections
Intervals
Medicine
Pandemics
Parameter estimation
Patient Isolation
Pneumonia, Viral - epidemiology
Pneumonia, Viral - transmission
Reproduction
Respiratory diseases
SARS-CoV-2
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Signs and symptoms
Time Factors
Viral diseases
Viruses
China
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Summary:Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, including serial interval distributions-i.e., the time between illness onset in successive cases in a transmission chain-and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 shortened substantially from 7.8 to 2.6 days within a month (9 January to 13 February 2020). This change was driven by enhanced nonpharmaceutical interventions, particularly case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve our ability to assess transmission dynamics, forecast future incidence, and estimate the impact of control measures.
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These authors contributed equally to this work.
ISSN:0036-8075
1095-9203
1095-9203
DOI:10.1126/science.abc9004