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Model-based evaluation of alternative reactive class closure strategies against COVID-19.
Liu, Quan-Hui; Zhang, Juanjuan; Peng, Cheng; Litvinova, Maria; Huang, Shudong; Poletti, Piero; Trentini, Filippo; Guzzetta, Giorgio; Marziano, Valentina; Zhou, Tao; Viboud, Cecile; Bento, Ana I; Lv, Jiancheng; Vespignani, Alessandro; Merler, Stefano; Yu, Hongjie; Ajelli, Marco.
  • Liu QH; College of Computer Science, Sichuan University, Chengdu, China.
  • Zhang J; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Peng C; Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
  • Litvinova M; Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
  • Huang S; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Poletti P; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Trentini F; College of Computer Science, Sichuan University, Chengdu, China.
  • Guzzetta G; Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
  • Marziano V; Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy.
  • Zhou T; Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
  • Viboud C; Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
  • Bento AI; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Lv J; Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
  • Vespignani A; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Merler S; College of Computer Science, Sichuan University, Chengdu, China.
  • Yu H; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Ajelli M; Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Nat Commun ; 13(1): 322, 2022 01 14.
Article in English | MEDLINE | ID: covidwho-1625443
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ABSTRACT
There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, we developed a data-driven computational model of SARS-CoV-2 transmission. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 17.3% (95%CI 8.0-26.8%), due to the low probability of timely identification of infections in the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Depending on the contribution of schools to transmission, this strategy can greatly reduce COVID-19 burden even when school contribution to transmission and immunity in the population is low. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to be rolled out.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Schools / Quarantine / Models, Statistical / SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-021-27939-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Schools / Quarantine / Models, Statistical / SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-021-27939-5