Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools

Akira Endo (遠藤彰), COVID-19 Working Group Cmmid, Mitsuo Uchida (内田満夫), Yang Liu (刘扬), Katherine E. Atkins, Adam J. Kucharski and Sebastian Funk
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Akira Endo (遠藤彰): a Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; c The Alan Turing Institute, London NW1 2DB, United Kingdom;; d School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki 852-8523, Japan;; e Japan Society for the Promotion of Science, Tokyo 102-0083, Japan;
COVID-19 Working Group Cmmid: b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;
Mitsuo Uchida (内田満夫): f Graduate School of Medicine, Gunma University, Gunma 371-8511, Japan;
Yang Liu (刘扬): a Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;
Katherine E. Atkins: a Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; g Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh EH16 4UX, United Kingdom
Adam J. Kucharski: a Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;
Sebastian Funk: a Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;; b The Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom;

Proceedings of the National Academy of Sciences, 2022, vol. 119, issue 37, e2203019119

Abstract: Interventions to control coronavirus disease 2019 (COVID-19) in school settings often assume that simply limiting the number of students attending reduces the potential for disease spread. However, using a mathematical model parameterized with a detailed dataset of seasonal influenza in Japanese primary schools, we find that interventions that focus only on reducing the number of students in class at any moment in time (e.g., reduced class sizes and staggered attendance) may not be effective. We propose two approaches for pandemic management in school settings: a routine “preemptive” approach that attempts to keep the within-school reproduction number low by, for example, regular screening and cohorting and a “responsive” approach where fixed-period class closures are employed upon detection of a symptomatic case.

Keywords: influenza; school; mathematical model; class size; social network (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:119:y:2022:p:e2203019119

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