气候变化领域集成服务门户(CCPortal): Model-based evaluation of alternative reactive class closure strategies against COVID-19

CCPortal

DOI	10.1038/s41467-021-27939-5
	Model-based evaluation of alternative reactive class closure strategies against COVID-19
	Liu Q.-H.; Zhang J.; Peng C.; Litvinova M.; Huang S.; Poletti P.; Trentini F.; Guzzetta G.; Marziano V.; Zhou T.; Viboud C.; Bento A.I.; Lv J.; Vespignani A.; Merler S.; Yu H.; Ajelli M.
发表日期	2022
ISSN	2041-1723
卷号	13 期号:1
英文摘要	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. © 2022, The Author(s).
语种	英语
scopus关键词	antigen; closure; COVID-19; disease transmission; immunity; probability; computer simulation; diagnosis; epidemiology; growth, development and aging; human; immunology; Italy; legislation and jurisprudence; mass screening; organization and management; pathogenicity; prevention and control; quarantine; school; statistical model; student; Computer Simulation; COVID-19; COVID-19 Serological Testing; Humans; Italy; Mass Screening; Models, Statistical; Physical Distancing; Quarantine; SARS-CoV-2; Schools; Students
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251253
作者单位	College of Computer Science, Sichuan University, Chengdu, China; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China; Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, United States; Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy; Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, United States; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, ...
推荐引用方式 GB/T 7714	Liu Q.-H.,Zhang J.,Peng C.,et al. Model-based evaluation of alternative reactive class closure strategies against COVID-19[J],2022,13(1).
APA	Liu Q.-H..,Zhang J..,Peng C..,Litvinova M..,Huang S..,...&Ajelli M..(2022).Model-based evaluation of alternative reactive class closure strategies against COVID-19.Nature Communications,13(1).
MLA	Liu Q.-H.,et al."Model-based evaluation of alternative reactive class closure strategies against COVID-19".Nature Communications 13.1(2022).