Hokkaido University · Medicine
히로시 시바타 교수의 연구실은 감염병 역학과 전파 역학을 중심으로, 신종 코로나바이러스 감염증(COVID-19)의 임상적· epidemiological 특성과 전파 역학을 정량적으로 분석하는 데 전문성을 가진다. 주요 연구 방향은 잠복기, serial interval, 임상 증상 발현 시점, 그리고 무증상 감염 비율과 같은 전파 역학적 파rameter를 추정하는 데 중점을 두고 있으며, 특히 감염자의 전파 시점과 감염 확산의 초기 단계에서의 역학적 특성을 규명하는 데 기여해왔다. 이는 감염 예방 전략 수립과 공중보건 정책 수립에 실질적인 기초 자료를 제공한다.
Figures are computed from collected data and may differ slightly.
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% confid
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., 2020aNishiura H. Jung S.M. Linton N.M. Kinoshita R. Yang Y. Hayashi K. et al.The extent of transmission of novel coronavirus in Wuhan, China.J Clin Med. 2020; 9 (pii: E330)https://doi.org/10.3390/jcm9020330Crossref Scopus (
The serial interval of COVID-19 is close to or shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias.
A cluster of pneumonia cases linked to a novel coronavirus (2019-nCoV) was reported by China in late December 2019. Reported case incidence has now reached the hundreds, but this is likely an underestimate. As of 24 January 2020, with reports of thirteen exportation events, we estimate the cumulative incidence in China at 5502 cases (95% confidence interval: 3027, 9057). The most plausible number of infections is in the order of thousands, rather than hundreds, and there is a strong indication t
The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction nu
Abstract Objective To identify common features of cases with novel coronavirus disease (COVID-19) so as to better understand what factors promote secondary transmission including superspreading events. Methods A total of 110 cases were examined among eleven clusters and sporadic cases, and investigated who acquired infection from whom. The clusters included four in Tokyo and one each in Aichi, Fukuoka, Hokkaido, Ishikawa, Kanagawa and Wakayama prefectures. The number of secondary cases generated
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). Th
Abstract 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 9
A total of 565 Japanese citizens were evacuated from Wuhan, China to Japan. All passengers were screened for symptoms and also undertook reverse transcription polymerase chain reaction testing, identifying 5 asymptomatic and 7 symptomatic passengers testing positive for 2019-nCoV. We show that the screening result is suggestive of the asymptomatic ratio at 41.6%.
Abstract Objective To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs. Methods We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset ( n =28) and a subset of pairs with highest certainty in reporting ( n =18). In addition, we adjust
On 16 May 2009, Japan confirmed its first three cases of new influenza A(H1N1) virus infection without a history of overseas travel, and by 1 June, 361 cases, owing to indigenous secondary transmission, have been confirmed. Of these, 287 cases (79.5%) were teenagers (i.e. between 10 and 19 years of age). The reproduction number is estimated at 2.3 (95% confidence interval: 2.0, 2.6). The average number of secondary transmissions involving minors (those under 20 years of age) traced back to infec
In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertai
The impact of the drastic reduction in travel volume within mainland China in January and February 2020 was quantified with respect to reports of novel coronavirus (COVID-19) infections outside China. Data on confirmed cases diagnosed outside China were analyzed using statistical models to estimate the impact of travel reduction on three epidemiological outcome measures: (i) the number of exported cases, (ii) the probability of a major epidemic, and (iii) the time delay to a major epidemic. From
To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death mus
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