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      Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19)

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          Abstract

          The number of novel coronavirus (COVID-19) cases worldwide continues to grow, and the gap between reports from China and statistical estimates of incidence based on cases diagnosed outside China indicates that a substantial number of cases are underdiagnosed (Nishiura et al., 2020a). Estimation of the asymptomatic ratio—the percentage of carriers with no symptoms—will improve understanding of COVID-19 transmission and the spectrum of disease it causes, providing insight into epidemic spread. Although the asymptomatic ratio is conventionally estimated using seroepidemiological data (Carrat et al., 2008, Hsieh et al., 2014), the collection of these data requires significant logistical effort, time, and cost. Instead, we propose a method of estimating the asymptomatic ratio by using information on Japanese nationals who were evacuated from Wuhan, China on charter flights. Figure 1 illustrates the flow of the evacuation process. By February 6, 2020 a total of N = 565 citizens had been evacuated. Among them, pN = 63 (11.2%) were considered symptomatic upon arrival based on (1) temperature screening before disembarkation, and (2) face-to-face interviews eliciting information on symptoms including fever, cough, and other non-specific symptoms consistent with COVID-19. Reverse transcription PCR (RT-PCR) testing was performed for all passengers, and m = 4 asymptomatic and n = 9 symptomatic passengers tested positive for COVID-19. Figure 1 Flow diagram of symptom screening and viral testing for passengers on chartered evacuation flights from Wuhan, China to Japan. The flow of Japanese residents evacuating from Wuhan and screened in Japan. A total of N passengers were evaluated, of whom a fraction p were symptomatic upon arrival. Among symptomatic and asymptomatic individuals, n and m persons, respectively, tested positive for the virus by RT-PCR. Figure 1 Employing a Bayes theorem, the asymptomatic ratio is defined as P r ( a s y m p t o m a t i c   |   i n f e c t i o n ) = Pr i n f e c t i o n   |   a s y m p t o m a t i c P r ( a s y m p t o m a t i c ) P r ( i n f e c t i o n ) , which can be calculated as m/(n + m), as seen in Figure 1. Using a binomial distribution, the asymptomatic ratio among evacuees was thus estimated to be 30.8% (95% confidence interval 7.7–53.8%). On March 6, 2020, a minimum of 30 days had elapsed since the citizens had departed from Wuhan – a length of observation sufficiently longer than the COVID-19 incubation period (Li et al., 2020, Linton et al., 2020). Thus, there was very little probability that the four virus-positive asymptomatic individuals would develop symptoms. In general, asymptomatic infections cannot be recognized if they are not confirmed by RT-PCR or other laboratory testing, and symptomatic cases may not be detected if they do not seek medical attention (Nishiura et al., 2020b). Estimates such as this therefore provide important insight by using a targeted population to assess the prevalence of asymptomatic viral shedding (Kupferschmidt and Cohen, 2020). It should be noted that the limited sensitivity of RT-PCR does not affect the estimate of the asymptomatic ratio, because the sensitivity is cancelled out from the right-hand side of the equation. However, a weakness of this study is that age-dependence and other aspects of heterogeneity were ignored, because the samples relied on Japanese evacuees from Wuhan. Despite the small sample size, this estimation indicates that perhaps less than a half of COVID-19-infected individuals are asymptomatic. This ratio is slightly smaller than that for influenza, which has been estimated at 56–80% (Hsieh et al., 2014) using similar definitions for symptomatic individuals. There is great need for further studies on the prevalence of asymptomatic COVID-19 infections to guide epidemic control efforts. Ethical approval Not required. Conflict of interest We declare that we have no conflict of interest.

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          Most cited references 7

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          Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

           Qun Li,  Xuhua Guan,  Peng Wu (2020)
          Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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            Time lines of infection and disease in human influenza: a review of volunteer challenge studies.

            The dynamics of viral shedding and symptoms following influenza virus infection are key factors when considering epidemic control measures. The authors reviewed published studies describing the course of influenza virus infection in placebo-treated and untreated volunteers challenged with wild-type influenza virus. A total of 56 different studies with 1,280 healthy participants were considered. Viral shedding increased sharply between 0.5 and 1 day after challenge and consistently peaked on day 2. The duration of viral shedding averaged over 375 participants was 4.80 days (95% confidence interval: 4.31, 5.29). The frequency of symptomatic infection was 66.9% (95% confidence interval: 58.3, 74.5). Fever was observed in 37.0% of A/H1N1, 40.6% of A/H3N2 (p = 0.86), and 7.5% of B infections (p = 0.001). The total symptoms scores increased on day 1 and peaked on day 3. Systemic symptoms peaked on day 2. No such data exist for children or elderly subjects, but epidemiologic studies suggest that the natural history might differ. The present analysis confirms prior expert opinion on the duration of viral shedding or the frequency of asymptomatic influenza infection, extends prior knowledge on the dynamics of viral shedding and symptoms, and provides original results on the frequency of respiratory symptoms or fever.
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              Is Open Access

              Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

              The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.
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                Author and article information

                Contributors
                Journal
                Int J Infect Dis
                Int. J. Infect. Dis
                International Journal of Infectious Diseases
                The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
                1201-9712
                1878-3511
                14 March 2020
                May 2020
                14 March 2020
                : 94
                : 154-155
                Affiliations
                Graduate School of Medicine, Hokkaido University, Sapporo, 060-8638, Japan
                Osaka Institute of Public Health, Osaka, 537-0025, Japan
                Graduate School of Medicine, Hokkaido University, Sapporo, 060-8638, Japan
                Author notes
                [* ]Corresponding author at: Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan. nishiurah@ 123456med.hokudai.ac.jp
                Article
                S1201-9712(20)30139-9
                10.1016/j.ijid.2020.03.020
                7270890
                32179137
                © 2020 The Author(s)

                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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                Infectious disease & Microbiology

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