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1 Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
2 Collège Doctoral, Sorbonne Université, Paris, France.
3 Infections Antimicrobials Modelling Evolution (IAME) UMR 1137, University of Paris, Paris, France.
4 Emerging Diseases Epidemiology Unit, Institut Pasteur, Paris, France.
5 PACRI Unit, Conservatoire National des Arts et Métiers, Paris, France.
6 National Reference Center for Respiratory Viruses, Department of Virology, Infective Agents Institute, North Hospital Network, Lyon, France.
7 Virpath Laboratory, International Center of Research in Infectiology, INSERM U1111, CNRS-UMR 5308, École Normale Supérieure de Lyon, Université Claude Bernard Lyon, Lyon University, Lyon, France.
8 INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
1 Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
2 Collège Doctoral, Sorbonne Université, Paris, France.
3 Infections Antimicrobials Modelling Evolution (IAME) UMR 1137, University of Paris, Paris, France.
4 Emerging Diseases Epidemiology Unit, Institut Pasteur, Paris, France.
5 PACRI Unit, Conservatoire National des Arts et Métiers, Paris, France.
6 National Reference Center for Respiratory Viruses, Department of Virology, Infective Agents Institute, North Hospital Network, Lyon, France.
7 Virpath Laboratory, International Center of Research in Infectiology, INSERM U1111, CNRS-UMR 5308, École Normale Supérieure de Lyon, Université Claude Bernard Lyon, Lyon University, Lyon, France.
8 INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
We used a mathematical model to evaluate the impact of mass testing in the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Under optimistic assumptions, one round of mass testing may reduce daily infections by up to 20-30%. Consequently, very frequent testing would be required to control a quickly growing epidemic if other control measures were to be relaxed. Mass testing is most relevant when epidemic growth remains limited through a combination of interventions.
Keywords:
Covid-19; SARS-CoV-2; epidemic; mass testing.
Conflict of interest: YY has received honoraria for presentations at workshops and consultancy honoraria from Abbvie, Gilead, Merck, J&J and ViiV health care before 2017; there are no conflicts of interest to declare after 2017.
Figures
Figure 1
Expected number of daily SARS-CoV-2…
Figure 1
Expected number of daily SARS-CoV-2 infections with monthly or biweekly testing campaigns, by…
Figure 1
Expected number of daily SARS-CoV-2 infections with monthly or biweekly testing campaigns, by date and percentage of population tested, France, 4 January–1 May 2021
Figure 2
Impact of a single mass…
Figure 2
Impact of a single mass testing campaign for SARS-CoV-2 on (A) reduction of…
Figure 2
Impact of a single mass testing campaign for SARS-CoV-2 on (A) reduction of daily infections 10 days after mass testing and (B) number of days to return to pre-mass testing epidemiological situation, France, 4 January–1 May 2021
Figure 3
Expected maximum number of daily…
Figure 3
Expected maximum number of daily SARS-CoV-2 infections as a function of the number…
Figure 3
Expected maximum number of daily SARS-CoV-2 infections as a function of the number of days between consecutive campaigns and the proportion of the population tested in each campaign, for different doubling times, France, 4 January–1 May 2021
Figure 4
Frequency of mass testing campaigns…
Figure 4
Frequency of mass testing campaigns necessary to keep the number of daily SARS-CoV-2…
Figure 4
Frequency of mass testing campaigns necessary to keep the number of daily SARS-CoV-2 infections below 40,000, as a function of the proportion of the population tested in each campaign, for different modelling assumptions, France, 4 January–1 May 2021
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