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10.1016/S1473-3099(20)30162-6

http://scihub22266oqcxt.onion/10.1016/S1473-3099(20)30162-6
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32213332!7158571!32213332
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suck abstract from ncbi


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pmid32213332      Lancet+Infect+Dis 2020 ; 20 (6): 678-688
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  • Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study #MMPMID32213332
  • Koo JR; Cook AR; Park M; Sun Y; Sun H; Lim JT; Tam C; Dickens BL
  • Lancet Infect Dis 2020[Jun]; 20 (6): 678-688 PMID32213332show ga
  • BACKGROUND: Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful. METHODS: We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R(0)] of 1.5, 2.0, or 2.5) and assuming 7.5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R(0) value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22.7%, 30.0%, 40.0%, and 50.0%) to compare outbreak sizes under the same control measures. FINDINGS: For the baseline scenario, when R(0) was 1.5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000-320 000), corresponding to 7.4% (IQR 6.5-8.5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000-776 000) when R(0) was 2.0, corresponding to 19.3% (17.8-20.6) of the Singaporean population, and 1 207 000 cases (1 164 000-1 249 000) when R(0) was 2.5, corresponding to 32% (30.9-33.1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99.3% (IQR 92.6-99.9) when R(0) was 1.5, by 93.0% (81.5-99.7) when R(0) was 2.0, and by 78.2% (59.0 -94.4) when R(0) was 2.5. Assuming increasing asymptomatic fractions up to 50.0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R(0) of 1.5. INTERPRETATION: Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines. FUNDING: Singapore Ministry of Health, Singapore Population Health Improvement Centre.
  • |*Models, Statistical[MESH]
  • |Basic Reproduction Number[MESH]
  • |Betacoronavirus[MESH]
  • |COVID-19[MESH]
  • |Communicable Disease Control/*methods[MESH]
  • |Computer Simulation[MESH]
  • |Coronavirus Infections/*prevention & control/transmission[MESH]
  • |Humans[MESH]
  • |Influenza, Human/prevention & control[MESH]
  • |Pandemics/*prevention & control[MESH]
  • |Pneumonia, Viral/*prevention & control/transmission[MESH]
  • |Quarantine[MESH]
  • |SARS-CoV-2[MESH]
  • |Schools[MESH]
  • |Singapore/epidemiology[MESH]


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