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

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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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          Most cited references 4

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          Comparative estimation of the reproduction number for pandemic influenza from daily case notification data.

          The reproduction number, R, defined as the average number of secondary cases generated by a primary case, is a crucial quantity for identifying the intensity of interventions required to control an epidemic. Current estimates of the reproduction number for seasonal influenza show wide variation and, in particular, uncertainty bounds for R for the pandemic strain from 1918 to 1919 have been obtained only in a few recent studies and are yet to be fully clarified. Here, we estimate R using daily case notifications during the autumn wave of the influenza pandemic (Spanish flu) in the city of San Francisco, California, from 1918 to 1919. In order to elucidate the effects from adopting different estimation approaches, four different methods are used: estimation of R using the early exponential-growth rate (Method 1), a simple susceptible-exposed-infectious-recovered (SEIR) model (Method 2), a more complex SEIR-type model that accounts for asymptomatic and hospitalized cases (Method 3), and a stochastic susceptible-infectious-removed (SIR) with Bayesian estimation (Method 4) that determines the effective reproduction number Rt at a given time t. The first three methods fit the initial exponential-growth phase of the epidemic, which was explicitly determined by the goodness-of-fit test. Moreover, Method 3 was also fitted to the whole epidemic curve. Whereas the values of R obtained using the first three methods based on the initial growth phase were estimated to be 2.98 (95% confidence interval (CI): 2.73, 3.25), 2.38 (2.16, 2.60) and 2.20 (1.55, 2.84), the third method with the entire epidemic curve yielded a value of 3.53 (3.45, 3.62). This larger value could be an overestimate since the goodness-of-fit to the initial exponential phase worsened when we fitted the model to the entire epidemic curve, and because the model is established as an autonomous system without time-varying assumptions. These estimates were shown to be robust to parameter uncertainties, but the theoretical exponential-growth approximation (Method 1) shows wide uncertainty. Method 4 provided a maximum-likelihood effective reproduction number 2.10 (1.21, 2.95) using the first 17 epidemic days, which is consistent with estimates obtained from the other methods and an estimate of 2.36 (2.07, 2.65) for the entire autumn wave. We conclude that the reproduction number for pandemic influenza (Spanish flu) at the city level can be robustly assessed to lie in the range of 2.0-3.0, in broad agreement with previous estimates using distinct data.
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            Self-Isolation Compliance In The COVID-19 Era Influenced By Compensation: Findings From A Recent Survey In Israel: A cross sectional study of the adult population of Israel to assess public attitudes toward the COVID-19 outbreak and self-isolation.

            To contain the novel coronavirus disease (COVID-19) pandemic, health and government authorities have imposed sweeping self-quarantine orders for communities worldwide. Health officials assume that the public will have high rates of compliance. However, studies suggest that a major obstacle to compliance for household quarantine is concern about loss of income. A cross-sectional study of the adult population of Israel was conducted in the last week of February 2020 to assess public attitudes toward the COVID-19 outbreak. In particular, public compliance rates with self-quarantine were assessed, depending on whether lost wages would be compensated for. When compensation was assumed, the compliance rate was 94 percent. When compensation was removed, the compliance rate dropped to less than 57 percent. This study demonstrated that providing people with assurances about their livelihoods during self-quarantine is an important component of compliance with public health regulations.
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              Deciphering the power of isolation in controlling COVID-19 outbreaks

               Yan Niu,  Fujie Xu (2020)
              Isolation of cases and contacts has long been a strategy in the fight against infectious diseases; however, its effectiveness has varied. The modelling study by Joel Hellewell and colleagues 1 qualitatively explored the parameters that determine whether isolation of cases and contacts can successfully contain COVID-19 outbreaks after importation of travel-related cases and initial transmissions. Initial outbreak sizes were among the key determinants for the success of isolation. 2 months ago, the world knew almost nothing about COVID-19, and Wuhan—the epicentre of the outbreak—did not have the luxury of early detection and response. Challenged by the reality that earlier opportunities had been missed, China launched a costly public health response in Wuhan, which involved many tactics besides isolation of cases and contacts, including lockdown of the city and mass quarantine, social distancing mandates, school closures, and intense case finding and contact tracing by the medical and public health professionals who were mobilised across the country to come to Wuhan.2, 3, 4 The approach in Wuhan and the nearby cities in Hubei Province took exceptional measures in response to the outbreak, because there was evidence of high-level community transmission and widespread nosocomial infections. 5 As of Feb 11, 2020, 3019 COVID-19 cases among health workers had been reported, with at least five deaths.5, 6 In many regions outside of China, decision makers and the medical community still have the opportunity of early detection and response. 2 The Article by Hellewell and colleagues gives us a clearer sense of how quickly the window for early response is closing: when the number of initial cases increases to 40, the probability of failure to control is high, at 80% even with 80% of contacts traced and isolated. Based on the early experience in Wuhan, the number of COVID-19 cases could increase from 20 to 40 cases within 3 days (from Jan 6–8, 2020), and outbreak sizes doubled in every 7·4 days on average, highlighting the urgency of early detection and rapid response. 7 In Hellewell and colleagues' model, transmission before symptoms, even when the percentage is moderate, at 15–30%, had a marked effect on probability to control. 1 Unlike the severe acute respiratory syndrome virus, where almost all onward transmissions occur after symptom onset, 8 we now know that transmission of COVID-19 virus can occur before symptom onset. In the fifth version of Chinese guidelines governing contact tracing, it defined close contacts as “those who have been in close contact since 2 days before the onset of symptoms in suspected and confirmed cases, or 2 days prior to an asymptomatic confirmed case,” which reflects our current understanding that secondary transmission of COVID-19 virus is possible at least 2 days before symptom onset. 9 However, the efficiency of transmission remains uncertain, and seroprevalence studies among different contacts will be important. Transmission by people with no or mild symptoms can dampen the power of the isolation strategy because of reduced likelihood of isolating all cases and tracing all contacts. The identification and testing of potential cases need to be as extensive as is permitted by health care and diagnostic testing capacity—including the identification, testing, and isolation of suspected cases with no or mild disease (eg, influenza-like illness). Another major challenge to the completeness in case isolation is that nucleic acid testing—the main tool for case identification—has a variable rate of false-negative results; so even symptomatic cases could be set free, and thus weakening the feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Aiming to improve the completeness of isolation to curb all transmissions, Hubei province revised the case definition between Feb 5 and 18, 2020, and added clinically diagnosed cases, which eliminated the requirement for a positive nucleic acid test. 10 The development of better tests is a research priority internationally. With more research and high-tech groups joining the fight, we might also see advances in contact tracing. In this fight against COVID-19, control measures such as isolation and contact tracing might indeed gain more power, thanks to modern technology. This online publication has been corrected. The corrected version first appeared at thelancet.com/lancetgh on March 26, 2020
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                Author and article information

                Contributors
                Journal
                Lancet
                Lancet
                Lancet (London, England)
                Elsevier Ltd.
                0140-6736
                1474-547X
                29 April 2020
                29 April 2020
                Affiliations
                [a ]Department of Disease Control, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
                [b ]Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
                Article
                S0140-6736(20)31016-3
                10.1016/S0140-6736(20)31016-3
                7190294
                © 2020 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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