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      Institutional, not home-based, isolation could contain the COVID-19 outbreak

      , , ,
      The Lancet
      Elsevier BV

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          Abstract

          In the absence of vaccines, non-pharmaceutical interventions such as physical distancing, intensive contact tracing, and case isolation remain frontline measures in controlling the spread of severe acute respiratory syndrome coronavirus 2. 1 In Wuhan, China, these measures were implemented alongside city lockdown, mass quarantine, and school closure during the coronavirus disease 2019 (COVID-19) outbreak in January and February, 2020. 2 Critical to Wuhan's success, cases identified through liberal testing, regardless of symptom profile, were immediately isolated in purpose-built shelters, as delays in isolation from symptom onset increase transmission risk substantially. 3 European countries and the USA have mostly followed these measures, except, in most cases, only people with severe symptoms are being admitted to hospital, whereas people with mild symptoms are asked to self-isolate at home. Test kit shortages and limited health-care facility capacity have also led to unconfirmed cases self-isolating at home. Compliance with home isolation, however, is partial. In Israel, 57% of people with unconfirmed infection did not self-isolate because they were not financially compensated 4 and because the lay public is not informed on how to keep strict isolation measures at home. We modelled and compared two types of isolation measures: institution-based isolation and home-based isolation. The former is modelled after China, with isolation of confirmed cases in quarantine facilities 5 resulting in no further onward within-household transmission, and the quarantining of contacts with legal enforcement. Once quarantined, contact rates are reduced by 75% in the household and by 90% in the community. We contrasted this with home-based isolation, modelled after Europe and the USA, where home isolation of confirmed cases is the current policy. This approach is assumed to cause a 50% reduction in contact within the home and a 75% reduction in contact in the community. Contact cases have an overall reduced interaction at an assumed contact rate of 50%. No reduction in transmission is assumed to occur for asymptomatic infections because asymptomatic cases are not being identified and isolated. We used GeoDEMOS-R, 6 an agent-based respiratory illness simulation model that estimates the total number of infections through time and measures the effects of quarantining, physcial distancing, and school closure on a city population. A different calibration procedure, 7 however, was used to estimate the number of infections over time. We assumed a basic reproduction number of 2 for the initial 4-week phase of the COVID-19 epidemic, with a subsequent decrease in the effective reproduction number due to the implementation of physical distancing control measures. The model represents a large city of 4 million residents, modelled upon the city-state of Singapore. Relative to the baseline with no control measures (figure ), our models showed that home-based isolation causes an 8-day delay (IQR 5–11) in the epidemic peak, with a corresponding reduction of 7100 cases (IQR 6800–7400) at this peak and 190 000 cases averted throughout the epidemic (IQR 185 000–194 000). Institution-based isolation created a peak delay of 18 days and a reduction of 18 900 cases (18 700–19 100). A total of 546 000 cases (IQR 540 000–550 000) are averted throughout the epidemic, representing roughly a 57% reduction in comparison to 20% reduction through home-based isolation. Figure Number of new infections (A) and cumulative infections (B) within 7 months under the baseline control measures (black), home-based isolation (blue), and institution-based isolation (red) These results show the need for institution-based isolation to reduce household and community transmission. They also provide theoretical support for the approach successfully implemented in Wuhan, where fangcang isolation shelters were established for all infected and potentially exposed individuals. 5 These shelters provided triage, basic medical care, frequent monitoring, rapid referrals, and essential living and social engagements for the wellbeing of those isolated. Crucially, the fangcang obviated most of the risk of within-household transmission, which frequently occurs as viral loads can be high for mild infections. 8 Home-based isolation, which is reliant on personal compliance, will therefore inevitably lead to increased transmission. Although cities within Europe and the USA might not be able to create make-shift isolation centres similar to those in Wuhan, due to a lack of social acceptability or negative public perceptions, other strategies should be considered to reduce transmission, such as repurposing hotels or dormitories. We urge policy makers in countries with or facing overburdened health-care facilities 9 to consider such measures as countries emerge from lockdowns.

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          Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

          Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R 0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R 0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R 0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R 0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R 0 of 2·5 more than 70% of contacts had to be traced, and for an R 0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R 0 was 1·5. For R 0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.
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            Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak

            Public health measures were decisive in controlling the SARS epidemic in 2003. Isolation is the separation of ill persons from non-infected persons. Quarantine is movement restriction, often with fever surveillance, of contacts when it is not evident whether they have been infected but are not yet symptomatic or have not been infected. Community containment includes measures that range from increasing social distancing to community-wide quarantine. Whether these measures will be sufficient to control 2019-nCoV depends on addressing some unanswered questions.
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              Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

              Summary 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.
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                Author and article information

                Journal
                The Lancet
                The Lancet
                Elsevier BV
                01406736
                April 2020
                April 2020
                Article
                10.1016/S0140-6736(20)31016-3
                dee1c1f4-ec05-42f8-b01a-922b0a87ebce
                © 2020

                https://www.elsevier.com/tdm/userlicense/1.0/

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