To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of ...199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
The complex and unprecedented Ebola epidemic ongoing in West Africa has highlighted the need to review the epidemiological characteristics of Ebola Virus Disease (EVD) as well as our current ...understanding of the transmission dynamics and the effect of control interventions against Ebola transmission. Here we review key epidemiological data from past Ebola outbreaks and carry out a comparative review of mathematical models of the spread and control of Ebola in the context of past outbreaks and the ongoing epidemic in West Africa. We show that mathematical modeling offers useful insights into the risk of a major epidemic of EVD and the assessment of the impact of basic public health measures on disease spread. We also discuss the critical need to collect detailed epidemiological data in real-time during the course of an ongoing epidemic, carry out further studies to estimate the effectiveness of interventions during past outbreaks and the ongoing epidemic, and develop large-scale modeling studies to study the spread and control of viral hemorrhagic fevers in the context of the highly heterogeneous economic reality of African countries.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Epidemiological surveillance of HIV infection in Japan involves two technical problems for directly applying a classical backcalculation method, i.e., (i) all AIDS cases are not counted over time and ...(ii) people diagnosed with HIV have received antiretroviral therapy, extending the incubation period. The present study aimed to address these issues and estimate the HIV incidence and the proportion of diagnosed HIV infections, using a simple statistical model.
From among Japanese nationals, yearly incidence data of HIV diagnoses and patients with AIDS who had not previously been diagnosed as HIV positive, from 1985 to 2017, were analyzed. Using the McKendrick partial differential equation, general convolution-like equations were derived, allowing estimation of the HIV incidence and the time-dependent rate of diagnosis. A likelihood-based approach was used to obtain parameter estimates.
Assuming that the median incubation period was 10.0 years, the cumulative number of HIV infections was estimated to be 29,613 (95% confidence interval (CI): 29,059, 30,167) by the end of 2017, and the proportion of diagnosed HIV infections was estimated at 80.3% (95% CI 78.7%-82.0%). Allowing the median incubation period to range from 7.5 to 12.3 years, the estimate of the proportion diagnosed can vary from 77% to 84%.
The proportion of diagnosed HIV infections appears to have not yet reached 90% among Japanese nationals. Compared with the peak incidence from 2005-2008, new HIV infections have clearly been in a declining trend; however, there are still more than 1,000 new HIV infections per year in Japan. To increase the diagnosed proportion of HIV infections, it is critical to identify people who have difficulty accessing consultation, testing, and care, and to explore heterogeneous patterns of infection.
Background: A measles outbreak involving 60 cases occurred in Yamagata, Japan in 2017. Using two different mathematical models for different datasets, we aimed to estimate measles transmissibility ...over time and explore any heterogeneous transmission patterns.Methods: The first model relied on the temporal distribution for date of illness onset for cases, and a generation-dependent model was applied to the data. Another model focused on the transmission network. Using the illness-onset date along with the serial interval and geographical location of exposure, we reconstructed a transmission network with 19 unknown links. We then compared the number of secondary transmissions with and without clinical symptoms or laboratory findings.Results: Using a generation-dependent model (assuming three generations other than the index case), the reproduction number (R) over generations 0, 1, and 2 were 25.3, 1.3, and <0.1, respectively, explicitly yielding the transmissibility over each generation. The network data enabled us to demonstrate that both the mean and the variance for the number of secondary transmissions per primary case declined over time. Comparing primary cases with and without secondary transmission, high viral shedding was the only significant determinant (P < 0.01).Conclusions: The R declined abruptly over subsequent generations. Use of network data revealed the distribution of the number of secondary transmissions per primary case and also allowed us to identify possible secondary transmission risk factors. High viral shedding from the throat mucosa was identified as a potential predictor of secondary transmission.
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FFLJ, NUK, ODKLJ, UL, UM, UPUK
Using numbers of SARS-CoV-2 variants detected in Japan as at 13 June 2021, relative instantaneous reproduction numbers (R
RI
) of the R.1, Alpha, and Delta variants with respect to other strains ...circulating in Japan were estimated at 1.25, 1.44, and 1.95. Depending on the assumed serial interval distributions, R
RI
varies from 1.20–1.32 for R.1, 1.34–1.58 for Alpha, and 1.70–2.30 for Delta. The frequency of Delta is expected to take over Alpha in Japan before 23 July 2021.
Background: As the COVID-19 pandemic spread, the Japanese government declared a state of emergency on April 7, 2020 for seven prefectures, and on April 16, 2020 for all prefectures. The Japanese ...Prime Minister and governors requested people to adopt self-restraint behaviors, including working from home and refraining from visiting nightlife spots. However, the effectiveness of the mobility change due to such requests in reducing the spread of COVID-19 has been little investigated. The present study examined the association of the mobility change in working, nightlife, and residential places and the COVID-19 outbreaks in Tokyo, Osaka, and Nagoya metropolitan areas in Japan. Methods: First, we calculated the daily mobility change in working, nightlife, and residential places compared to the mobility before the outbreak using mobile device data. Second, we estimated the sensitivity of mobility changes to the reproduction number by generalized least squares. Results: Mobility change had already started in March, 2020. However, mobility reduction in nightlife places was particularly significant due to the state of emergency declaration. Although the mobility in each place type was associated with the COVID-19 outbreak, the mobility changes in nightlife places were more significantly associated with the outbreak than those in the other place types. There were regional differences in intensity of sensitivity among each metropolitan area. Conclusions: Our findings indicated the effectiveness of the mobility changes, particularly in nightlife places, in reducing the outbreak of COVID-19.
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FFLJ, NUK, ODKLJ, UL, UM, UPUK
The present study aimed to estimate the infection fatality risk (IFR) and ascertainment bias of SARS-CoV-2 for six epidemic waves in Japan from February 2020 to January 2022. We used two types of ...datasets: (i) surveillance-based datasets containing the cumulative numbers of confirmed cases and deaths in each epidemic wave and (ii) seroepidemiological datasets conducted in a serial cross-sectional manner. Smoothing spline function was employed to reconstruct the age-specific cumulative incidence of infection. We found that IFR was highest during the first wave, and the second highest during the fourth wave, caused by the Alpha variant. Once vaccination became widespread, IFR decreased considerably among adults aged 40 years plus during the fifth wave caused by the Delta variant, although the epidemic size of fifth wave was the largest before the Omicron variant emerged. We also found that ascertainment bias was relatively high during the first and second waves and, notably, RT-PCR testing capacity during these early periods was limited. Improvements in the ascertainment were seen during the third and fourth waves. Once the Omicron variant began spreading, IFR diminished while ascertainment bias was considerably elevated.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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