Literature DB >> 32033064

The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights.

Hiroshi Nishiura1,2, Tetsuro Kobayashi1, Yichi Yang1, Katsuma Hayashi1, Takeshi Miyama3, Ryo Kinoshita1, Natalie M Linton1, Sung-Mok Jung1, Baoyin Yuan1, Ayako Suzuki1, Andrei R Akhmetzhanov1.   

Abstract

From 29 to 31 January 2020, a total of 565 Japanese citizens were evacuated from Wuhan, China on three chartered flights. All passengers were screened upon arrival in Japan for symptoms consistent with novel coronavirus (2019-nCoV) infection and tested for presence of the virus. Assuming that the mean detection window of the virus can be informed by the mean serial interval (estimated at 7.5 days), the ascertainment rate of infection was estimated at 9.2% (95% confidence interval: 5.0, 20.0). This indicates that the incidence of infection in Wuhan can be estimated at 20,767 infected individuals, including those with asymptomatic and mildly symptomatic infections. The infection fatality risk (IFR)-the actual risk of death among all infected individuals-is therefore 0.3% to 0.6%, which may be comparable to Asian influenza pandemic of 1957-1958.

Entities:  

Keywords:  ascertainment; diagnosis; epidemiology; importation; statistical inference; travel

Year:  2020        PMID: 32033064      PMCID: PMC7074297          DOI: 10.3390/jcm9020419

Source DB:  PubMed          Journal:  J Clin Med        ISSN: 2077-0383            Impact factor:   4.241


1. Introduction

As the epidemic of novel coronavirus (2019-nCoV) unfolded, the government of China has decided to implement countainment measures, including discontinuation of ordinary flights to and from Wuhan Tianhe International Airport even during the Chinese New Year holidays. The impact of such a dramatic restriction on human migration on the epidemic dynamics of 2019-nCoV will be soon visually identifiable, but this change made it difficult to update the cumulative incidence estimate using exported case data outside China [1]. Presently, exponential growth of confirmed cases has continued in China, but a substantial number of infections may have missed being diagnosed and reported. In the face of travel restrictions to and from Wuhan, the government of Japan offered Japanese citizens in Wuhan the option to be evacuated on specially chartered flights from 29 to 31 January 2020. A total of 565 Japanese citizens boarded three different flights and were evacuated. As of 2 February 2020, healthy individuals are quarantined with movement restrictions and brought under medical observation at designated hotels and dormitories. An additional 63 individuals who were determined to have symptoms consistent with 2019-nCoV infection upon arrival in Japan were all admitted to hospitals. The evacuation procedures involved in these flights have offered a unique opportunity for evaluation of the rate of underascertainment of 2019-nCoV cases in China. Here, we report the estimated rate of underascertainment and an update on current incidence in Wuhan.

2. Statistical Estimation

There were two interesting features of the evacuation process conducted by Japanese authorities. First, all 565 passengers were screened for symptoms upon arrival. Prior to disembarkation, the quarantine officers used portable thermoscanners to screen the temperature. In the following, all passengers were interviewed regarding whether they have any symptoms suggestive of upper raspiratory tract infection, including fever and cough. Of the 565 passengers, 63 were symptomatic. Second, the passengers were tested for presence of 2019-nCoV using reverse transcription polymerase chain reaction (RT-PCR), and eight passengers (1.4%) were determined to have the virus. Importantly, most of the individuals positive for the virus were asymptomatic (five passengers), while only the other three had symptoms consistent with 2019-nCoV infection, indicating that the dataset generated from this process can help investigate the full spectrum of infection including mild and asymptomatic infections. Let n and c(t) be the population size of Wuhan (11 million) and the cumulative number of cases in Wuhan by time t. As of 29 January 2020, there were 1905 confirmed cases reported from Wuhan. Suppose that q is the fraction of underascertained infected individuals and T is the detection window for the virus. While T is assumed as 10.0 days elsewhere [2] and even longer in an earlier study [1], the mean serial interval has recently been estimated at 7.5 days [3]. Another modeling study estimated the mean infectious period to be 3.6 days [4]. Here we set the serial interval to be 7.5 days as the default, and 3.6 and 10.0 days as the possible range of uncertainty. The balance equation for the risk of infection is thus written: It should be noted that all Japanese evacuees resided in Wuhan City, and citizens living in other cities in Hubei were not included on the flights. Hence, the population size n is not the catchment population of the Wuhan airport but the population size of Wuhan City. The likelihood function to estimate q is: Subsequently, the cumulative incidence can be estimated by: .

3. Estimate of the Incidence of “Infection”

Assuming that the mean detection window of the virus can be informed by the mean serial interval, here set at 7.5 days [3] (Table 1), the ascertainment rate was estimated to be 9.2% (95% confidence interval [CI]: 5.0, 20.0). Allowing the serial interval to vary from 3.6 to 10.0 days, the ascertainment rate ranged from 4.4% (95% CI: 2.4, 9.6) to 12.2% (95% CI: 6.6, 26.7). An ascertainment rate of 9.2% indicates that there are approximately 20,767 infected individuals (95% CI: 9528, 38,421) in Wuhan City as of 29 January 2020.
Table 1

Exportation events and estimated incidence in China.

Detection Window (Days)Ascertainment Rate (%)Incidence in Wuhan as on 29 January 2020 (Persons)
3.64.4 (2.4, 9.6)43,265 (19,849, 80,043)
7.59.2 (5.0, 20.0)20,767 (9528, 38,421)
10.012.2 (6.6, 26.7)15,575 (7146, 28,816)

The 95% confidence interval derived from profile likelihood is given in the parentheses. The estimated incidence represents infection, inclusive of mild and asymptomatic ones.

Laboratory testing of all evacuated passengers upon arrival in Japan offered an important opportunity to explicitly quantify the ascertainment rate using the number of both symptomatic ana asymptomatic infected evacuees for the calculatoin. In other words, if we assume that about 9.2% (95% CI: 5.0, 20.0) of cases have been diagnosed and reported by the Chinese government, the remaining 90.8% (80.0% or 95.0%) did not result in notification. This could be due to a variety of reasons including asymptomatic infection, mild illness, underdiagnosis and underreporting. The derived estimate is key in interpreting the severity of the 2019-nCoV infection. Presently, the case fatality risk among confirmed cases (cCFR) has been estimated to be in the order of 3%–6% [5]. However, the risk of death among all infected individuals is likely much smaller. With our estimate of ~10% ascertainment, the actual risk of death is therefore 0.3% to 0.6% among all infected individuals (abbreviated as iCFR or IFR) [6], which may be comparable to the Asian influenza pandemic of 1957–1958. However, it should be noted that quoted values of IFR may be oversestimated if the ascertainment rate is biased due to difficulties in detection of 2019-nCoV using RT-PCR (e.g., very short detection window of the virus during the course of infection). Clarifying the full spectrum of disease is of utmost importance to understanding the expected burden of the ongoing epidemic to the world. The meticulous effort of screening and testing Japanese passengers on evacuation flights indicated that about 90% of infections were not initially ascertained as cases, which must be kept in mind when analyzing the confirmed case data in China.
  4 in total

1.  Infection fatality risk of the pandemic A(H1N1)2009 virus in Hong Kong.

Authors:  Jessica Y Wong; Peng Wu; Hiroshi Nishiura; Edward Goldstein; Eric H Y Lau; Lin Yang; S K Chuang; Thomas Tsang; J S Malik Peiris; Joseph T Wu; Benjamin J Cowling
Journal:  Am J Epidemiol       Date:  2013-03-03       Impact factor: 4.897

2.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

3.  Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases.

Authors:  Sung-Mok Jung; Andrei R Akhmetzhanov; Katsuma Hayashi; Natalie M Linton; Yichi Yang; Baoyin Yuan; Tetsuro Kobayashi; Ryo Kinoshita; Hiroshi Nishiura
Journal:  J Clin Med       Date:  2020-02-14       Impact factor: 4.241

4.  The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020.

Authors:  Hiroshi Nishiura; Sung-Mok Jung; Natalie M Linton; Ryo Kinoshita; Yichi Yang; Katsuma Hayashi; Tetsuro Kobayashi; Baoyin Yuan; Andrei R Akhmetzhanov
Journal:  J Clin Med       Date:  2020-01-24       Impact factor: 4.241

  4 in total
  86 in total

Review 1.  Coronavirus Disease 2019-COVID-19.

Authors:  Kuldeep Dhama; Sharun Khan; Ruchi Tiwari; Shubhankar Sircar; Sudipta Bhat; Yashpal Singh Malik; Karam Pal Singh; Wanpen Chaicumpa; D Katterine Bonilla-Aldana; Alfonso J Rodriguez-Morales
Journal:  Clin Microbiol Rev       Date:  2020-06-24       Impact factor: 26.132

2.  A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures.

Authors:  Heewon Kang; Kyung-Duk Min; Seonghee Jeon; Ju-Yeun Lee; Sung-Il Cho
Journal:  Sci Rep       Date:  2022-06-09       Impact factor: 4.996

3.  Safety and immunogenicity of mRNA-LNP COVID-19 vaccine CVnCoV in Latin American adults: A phase 2 randomized study.

Authors:  Xavier Sáez-Llorens; Claudio Lanata; Elaine Aranguren; Carlos R Celis; Rubelio Cornejo; Rodrigo DeAntonio; Lucie Ecker; Diegi Garrido; Ana I Gil; Marina Gonzales; Morgan Hess-Holtz; Geert Leroux-Roels; Helga Junker; Sarah-Katharina Kays; Sven D Koch; Sandra Lazzaro; Philipp Mann; Gianluca Quintini; Barkha Srivastava; Dominik Vahrenhorst; Philipp von Eisenhart-Rothe; Olaf-Oliver Wolz; Lidia Oostvogels
Journal:  Vaccine X       Date:  2022-07-01

4.  Prediction of daily and cumulative cases for COVID-19 infection based on reproductive number (R0) in Karnataka: a data-driven analytics.

Authors:  Kuralayanapalya Puttahonnappa Suresh; Sharanagouda S Patil; Bharath Prasad Cholanayakanahalli Thyagaraju; Srikantha Gowda Ramkrishnappa; Divakar Hemadri; S Chandrashekara
Journal:  Sci Rep       Date:  2021-05-12       Impact factor: 4.379

5.  Estimation of the Actual Incidence of Coronavirus Disease (COVID-19) in Emergent Hotspots: The Example of Hokkaido, Japan during February-March 2020.

Authors:  Andrei R Akhmetzhanov; Kenji Mizumoto; Sung-Mok Jung; Natalie M Linton; Ryosuke Omori; Hiroshi Nishiura
Journal:  J Clin Med       Date:  2021-05-28       Impact factor: 4.241

Review 6.  Systematic Review on Outbreaks of SARS-CoV-2 on Cruise, Navy and Cargo Ships.

Authors:  Ann-Christin Kordsmeyer; Natascha Mojtahedzadeh; Jan Heidrich; Kristina Militzer; Thomas von Münster; Lukas Belz; Hans-Joachim Jensen; Sinan Bakir; Esther Henning; Julian Heuser; Angelina Klein; Nadine Sproessel; Axel Ekkernkamp; Lena Ehlers; Jens de Boer; Scarlett Kleine-Kampmann; Martin Dirksen-Fischer; Anita Plenge-Bönig; Volker Harth; Marcus Oldenburg
Journal:  Int J Environ Res Public Health       Date:  2021-05-13       Impact factor: 3.390

7.  A report on incidence of COVID-19 among febrile patients attending a malaria clinic.

Authors:  Subhasish Kamal Guha; Malabika Biswas; Bishal Gupta; Alisha Acharya; Supriya Halder; Bibhuti Saha; Moytrey Chatterjee; Pratip Kumar Kundu; Ardhendu Kumar Maji
Journal:  Trop Parasitol       Date:  2021-05-14

8.  Forecast of the Outbreak of COVID-19 Using Artificial Neural Network: Case Study Qatar, Spain, and Italy.

Authors:  Moayyad Shawaqfah; Fares Almomani
Journal:  Results Phys       Date:  2021-06-21       Impact factor: 4.476

Review 9.  Challenges with the proposed approach in enhancing the accessibility of antimalarial activities during COVID 19 pandemic.

Authors:  Ravi Kant; Poonam Yadav; Mahendra Singh; Mahendra Kumar Meena
Journal:  J Infect Public Health       Date:  2021-07-06       Impact factor: 3.718

10.  Death by political party: The relationship between COVID-19 deaths and political party affiliation in the United States.

Authors:  Jingjing Gao; Benjamin J Radford
Journal:  World Med Health Policy       Date:  2021-05-05
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.