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      Determining the optimal strategy for reopening schools, the impact of test and trace interventions, and the risk of occurrence of a second COVID-19 epidemic wave in the UK: a modelling study.

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          Abstract

          As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.

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          Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020

          Kenji Mizumoto, Katsushi Kagaya, Alexander Zarebski … (2020)
          On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking. As at 20 February, 634 persons on board tested positive for the causative virus. We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5–20.2%). Most infections occurred before the quarantine start.
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            Age-dependent effects in the transmission and control of COVID-19 epidemics

            Nicholas Davies, Petra Klepac, Yang Liu … (2020)
            The COVID-19 pandemic has shown a markedly low proportion of cases among children1-4. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from China, Italy, Japan, Singapore, Canada and South Korea. We estimate that susceptibility to infection in individuals under 20 years of age is approximately half that of adults aged over 20 years, and that clinical symptoms manifest in 21% (95% credible interval: 12-31%) of infections in 10- to 19-year-olds, rising to 69% (57-82%) of infections in people aged over 70 years. Accordingly, we find that interventions aimed at children might have a relatively small impact on reducing SARS-CoV-2 transmission, particularly if the transmissibility of subclinical infections is low. Our age-specific clinical fraction and susceptibility estimates have implications for the expected global burden of COVID-19, as a result of demographic differences across settings. In countries with younger population structures-such as many low-income countries-the expected per capita incidence of clinical cases would be lower than in countries with older population structures, although it is likely that comorbidities in low-income countries will also influence disease severity. Without effective control measures, regions with relatively older populations could see disproportionally more cases of COVID-19, particularly in the later stages of an unmitigated epidemic.
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              Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study

              Qifang Bi, Yongsheng Wu, Shujiang Mei … (2020)
              Summary Background Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures. Methods From Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk. Findings Cases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20–22). Cases were isolated on average 4·6 days (95% CI 4·1–5·0) after developing symptoms; contact tracing reduced this by 1·9 days (95% CI 1·1–2·7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6·27 [95% CI 1·49–26·33] for household contacts and 7·06 [1·43–34·91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11·2% (95% CI 9·1–13·8), and children were as likely to be infected as adults (infection rate 7·4% in children <10 years vs population average of 6·6%). The observed reproductive number (R) was 0·4 (95% CI 0·3–0·5), with a mean serial interval of 6·3 days (95% CI 5·2–7·6). Interpretation Our data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control. Funding Emergency Response Program of Harbin Institute of Technology, Emergency Response Program of Peng Cheng Laboratory, US Centers for Disease Control and Prevention.
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                Author and article information

                Journal
                Journal ID (iso-abbrev): Lancet Child Adolesc Health
                Title: The Lancet. Child & adolescent health
                Publisher: Elsevier BV
                ISSN (Electronic): 2352-4650
                ISSN (Print): 2352-4642
                Publication date (Electronic): November 2020
                Volume: 4
                Issue: 11
                Affiliations
                [1 ] Department of Applied Health Research and Institute for Global Health, University College London, London, UK; The Queen's College, University of Oxford, Oxford, UK. Electronic address: j.panovska-griffiths@ucl.ac.uk.
                [2 ] Institute for Disease Modeling, Bellevue, WA, USA; Complex Systems Group, School of Physics, University of Sydney, Sydney, NSW, Australia.
                [3 ] Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark; Burnet Institute, Melbourne, VIC, Australia.
                [4 ] Institute for Disease Modeling, Bellevue, WA, USA.
                [5 ] UCL Great Ormond St Institute of Child Health, London, UK.
                [6 ] Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.
                Article
                Publisher Item ID: S2352-4642(20)30250-9
                DOI: 10.1016/S2352-4642(20)30250-9
                PMC ID: 7398659
                PubMed ID: 32758453
                SO-VID: 1583d67d-8307-4d26-b45f-85d6131942dc
                Copyright © Copyright © 2020 Elsevier Ltd. All rights reserved.
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