A reconstruction of early cryptic COVID spread

To respond better to future pandemics, we must understand how the SARS-CoV-2 virus dispersed so rapidly. A model of COVID-19 spread sheds light on cryptic transmission, undetected by surveillance efforts, in early 2020. Modelling undetected cases of infection at the start of the pandemic.

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Bibliographic Details
Published inNature (London) Vol. 600; no. 7887; pp. 40 - 41
Main Authors Cauchemez, Simon, Bosetti, Paolo
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 02.12.2021
Nature Publishing Group
Subjects
631/326/596/4130
692/700/478/174
Biological models (mathematics)
Coronaviruses
COVID-19
Disease transmission
Epidemiology
Health surveillance
Humanities and Social Sciences
Humans
Infections
Lethality
multidisciplinary
News And Views
Pandemics
Phylogeny
Randomness
SARS-CoV-2
Science
Severe acute respiratory syndrome coronavirus 2
Viral diseases
Viral infections
Viruses
Italy
France
United States > US
China
Europe
Epidemiology
SARS-CoV-2
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Abstract To respond better to future pandemics, we must understand how the SARS-CoV-2 virus dispersed so rapidly. A model of COVID-19 spread sheds light on cryptic transmission, undetected by surveillance efforts, in early 2020. Modelling undetected cases of infection at the start of the pandemic.
AbstractList Davis et al. used the Global Epidemic and Mobility (GLEAM) model, which has both stochastic (incorporating elements of randomness) and mechanistic (including defined principles about the biological and social mechanisms associated with viral infection and transmission) components to simulate virus spread on a global scale2. The model also captures biological aspects of SARS-CoV-2 transmission, clinical features (such as lethality for each age group analysed) and the timing of non-pharmaceutical containment measures, such as lockdowns. Methods that calibrate these models to both epidemiological and virus-sequencing data could improve their performance for 'now-casting' and forecasting viral spread, as well as for assessing the effects of policies in real time.
To respond better to future pandemics, we must understand how the SARS-CoV-2 virus dispersed so rapidly. A model of COVID-19 spread sheds light on cryptic transmission, undetected by surveillance efforts, in early 2020. Modelling undetected cases of infection at the start of the pandemic.
Author Cauchemez, Simon
Bosetti, Paolo
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Cites_doi 10.1016/j.cell.2020.04.021
10.1016/j.jocs.2010.07.002
10.1038/s41586-021-04130-w
10.1093/bioinformatics/bty407
10.1038/s41562-021-01079-8
10.1126/science.abf2946
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Snippet To respond better to future pandemics, we must understand how the SARS-CoV-2 virus dispersed so rapidly. A model of COVID-19 spread sheds light on cryptic...
Davis et al. used the Global Epidemic and Mobility (GLEAM) model, which has both stochastic (incorporating elements of randomness) and mechanistic (including...
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Coronaviruses
COVID-19
Disease transmission
Epidemiology
Health surveillance
Humanities and Social Sciences
Humans
Infections
Lethality
multidisciplinary
News And Views
Pandemics
Phylogeny
Randomness
SARS-CoV-2
Science
Severe acute respiratory syndrome coronavirus 2
Viral diseases
Viral infections
Viruses
Title A reconstruction of early cryptic COVID spread
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