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Abstract Background Japan implemented strict border control measures and all incoming passengers were subject to entry screening with reverse transcription–polymerase chain reaction or antigen testing. From late 2020, exit screening within 72 h of departure to Japan also became mandatory. In this study, we evaluated the effectiveness of the exit screening policy in Japan by analyzing airport screening data from October 2020 to April 2022. Methods In addition to assessing entry screening data over time of passengers from the United Kingdom, we examined the prevalence of coronavirus disease 2019 (COVID-19) in the United Kingdom based on the Office of National Statistics infection survey. We constructed a statistical model that described entry screening positivity over time using Office of National Statistics prevalence data as the explanatory variable. Ideally, the time-dependent patterns of entry screening and Office of National Statistics prevalence data should resemble each other; however, we found that, sometimes, they were different and regarded the difference to statistically partly reflect the effectiveness of exit screening. Results The average proportion positive in one month before mandatory exit screening was implemented among Japanese passengers was 0.67% (95% confidence interval [CI]: 0.45, 0.98), whereas the proportion positive decreased to 0.49% (95% CI: 0.21, 1.15) in the first month of exit screening. Adjusting for time-dependent prevalence at the origin, we concluded that exit screening contributed to reducing passenger positivity by 59.3% (95% CI: 19.6, 81.3). The overall positivity values among passengers during the Delta and Omicron variant periods were 3.46 times and 1.46 times that during the pre-Delta variant period, respectively. Conclusions We used a simplistic statistical model and empirical data from passengers arriving in Japan from the United Kingdom to support that exit screening helped to reduce the proportion positive by 59%. Although the proportion positive later increased considerably and precluded preventing the introduction of imported cases, submitting a certificate for a negative test result contributed to reducing the positivity among travelers.

Although epidemiological surveillance of COVID-19 has been gradually downgraded globally, the transmission of COVID-19 continues. It is critical to quantify the transmission dynamics of COVID-19 using multiple datasets including wastewater virus concentration data. Herein, we propose a comprehensive method for estimating the effective reproduction number using wastewater data. The wastewater virus concentration data, which were collected twice a week, were analyzed using daily COVID-19 incidence data obtained from Takamatsu, Japan between January 2022 and September 2022. We estimated the shedding load distribution (SLD) as a function of time since the date of infection, using a model employing the delay distribution, which is assumed to follow a gamma distribution, multiplied by a scaling factor. We also examined models that accounted for the temporal smoothness of viral load measurement data. The model that smoothed temporal patterns of viral load was the best fit model (WAIC = 2795.8), which yielded a mean estimated distribution of SLD of 3.46 days (95% CrI: 3.01–3.95 days). Using this SLD, we reconstructed the daily incidence, which enabled computation of the effective reproduction number. Using the best fit posterior draws of parameters directly, or as a prior distribution for subsequent analyses, we first used a model that assumed temporal smoothness of viral load concentrations in wastewater, as well as infection counts by date of infection. In the subsequent approach, we examined models that also incorporated weekly reported case counts as a proxy for weekly incidence reporting. Both approaches enabled estimations of the epidemic curve as well as the effective reproduction number from twice-weekly wastewater viral load data. Adding weekly case count data reduced the uncertainty of the effective reproduction number. We conclude that wastewater data are still a valuable source of information for inferring the transmission dynamics of COVID-19, and that inferential performance is enhanced when those data are combined with weekly incidence data.

Despite the global implementation of COVID-19 mitigation measures, the disease continues to maintain transmission. Although mask wearing became one of the key measures for preventing the transmission of COVID-19 early in the pandemic period, many countries have relaxed the mandatory or recommended wearing of masks. The objective of the present study was to estimate the epidemiological impact of removing the mask-wearing recommendation in Japan. We developed a model to assess the consequences of declining mask-wearing coverage after the government revoked its recommendation in February 2023. The declining mask-wearing coverage was estimated using serial cross-sectional data, and a mathematical model was devised to determine the age-specific incidence of COVID-19 using the observed case count in Tokyo from week of October 3, 2022 to October 30, 2023. We explored model-based counterfactual scenarios to measure hypothetical situations in which the mask-wearing coverage decreases or increases relative to the observed coverage. The results show that mask-wearing coverage declined from 97% to 69% by the week of October 30, 2023, and that if the mask-wearing recommendation had continued, 427 lives could have been saved in Tokyo. If the mask-wearing coverage had declined to 25% of the observed level, the model suggests there might have been 1587 additional deaths. Thus, revoking the mask-wearing recommendation had a substantial epidemiological impact. In future pandemics, our proposed approach could provide a real-time quantification of the effects of relaxing countermeasures.

Background: Rubella remains a public health challenge in Japan, impeding the attainment of herd immunity. Despite vaccination efforts since 1976, persistent outbreaks reveal a susceptibility gap in male adults born before 1995. Seroepidemiological surveys are pivotal in evaluating population immunity and identifying at-risk groups. Methods: This study aims to pinpoint high-risk areas for potential rubella outbreaks in Japan by merging seroepidemiological data from 2020 with population census information. Various data sources, including spatial demographic data, reported rubella and congenital rubella syndrome (CRS) cases, and traveler lodging statistics, were employed. Geospatial information for Japan's 230,300 small geographic areas was analyzed, and HI (hemagglutination inhibition) titers were examined by age and sex. Seroconversion was defined as an HI titer ≥ 1:32 or 1:16, indicating protective immunity. Geospatial maps illustrated the distribution of susceptible individuals per square kilometer, emphasizing high-risk urban areas like Tokyo and Osaka. Demographic shifts in the working-age population were assessed. Results: Susceptible individuals cluster in densely populated urban centers, persisting despite demographic changes. The study highlights areas at risk of increased susceptibility, particularly with an HI titer cut-off of 1:16. Foreign travelers pose potential rubella importation risks as travel volume to Japan rises. To prevent epidemics and congenital rubella syndrome burden, achieving and sustaining herd immunity in high-risk areas is crucial. Conclusions: This study offers a comprehensive assessment of vulnerability in densely populated Japanese regions. Integrating population statistics with seroepidemiological data enhances our understanding of population immunity, guiding resource allocation for supplementary vaccination planning. To avert rubella epidemics, high-risk locations must bolster indirect protection through herd immunity, ultimately preventing congenital rubella syndrome.

Objectives: To reconstruct age-structured case counts of COVID-19 using sentinel reporting, which replaced universal reporting of COVID-19 from May 2023 in Japan. Methods: Using COVID-19 sentinel data stratified by discrete age groups in selected prefectures and referring to universal case count data up to May 8, 2023, we fitted a statistical model to handle weekly growth rates as a function of age and time so as to convert sentinel data to case counts after cessation of universal reporting. Results: The age distribution of cases in sentinel reporting was significantly biased toward younger age groups compared to universal reporting. When comparing the epidemic size of the 9th wave (May 8 to September 18, 2023) to the 8th wave (October 3, 2022 to April 10, 2023), using the wave-on-wave ratio of total cumulative sentinel cases led to a significant underestimation of the wave-on-wave in Tokyo (0.975, vs 1.461 by universal reporting) and Okinawa (1.299, vs 1.472). The estimates of growth rates, scaling factors between universal and sentinel cases, and expected universal case count showed robustness to changes in the ending week of the data period. Conclusion: Our model quantified COVID-19 dynamics, comparably to universal reporting that ended in May 2023, enabling detailed and up-to-date health burden analysis using sentinel reports. The cumulative incidence was greater than that suggested from sentinel data in Tokyo, Nara, and Okinawa. Per-population burdens among children were particularly high in Osaka and Nara, indicating a strong bias in sentinel reporting toward pediatric cases.

Background: Stringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures. Methods: Immune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained. Results: Accounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged ≥ 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older. Conclusions: Our estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.

Abstract Background The Japanese government has instituted border control measures against COVID-19, including entry and exit screening of people arriving from overseas. We sought to evaluate the effectiveness of the exit screening policy in Japan in reducing the risk of importing COVID-19 cases among travelers from Asian and Pacific countries. Methods The study period was stratified based on the timing of exit screening: (i) the control period (the pre-exit screening period from 25 October 2020 to 16 January 2021), (ii) the time period with the Alpha variant from 17 January to 10 April 2021, and (iii) the time period with the Delta variant from 2 May to 2 October 2021. Incidence data in the countries of origin were used to adjust for the risk of infection among travelers. The positivity rate of entry screening in Japan was compared among the three different study periods, adjusting for the risk of infection in the country of origin. Results The adjusted relative risk of positivity was greatly reduced and substantially below the value of 1 during the Alpha variant period compared with the control period. Although the relative risks increased when comparing the Delta variant period against control, the estimate remained below 1, except for among travelers from India and Myanmar. The relative risk reduction was greatest in high-income countries, with estimates of 100% and 96% risk reduction during the Alpha and Delta variant periods, respectively, followed by upper-middle-income countries with estimates of 90% and 76%, respectively. Conclusions Even in the presence of the Alpha and Delta variants, exit screening clearly reduced the risk of infection among travelers arriving from Asian and Pacific nations. As the testing relies on the country of origin, the effectiveness varied greatly by the socioeconomic income status and epidemiological situation of those countries. Test standardization and quality assurance may be required in low- and middle-income countries.

Introduction Current traveller health surveillance is ‘top-down’. Mobile-based surveillance could capture infection symptoms in real time. We aimed to evaluate the spectrum of illness in travellers using a mobile app-based system.Methods This study (ClinicalTrials.gov NCT04672577) used an application called Infection Tracking in Travellers (ITIT) that records travel-related illness symptoms with associated geolocation and weather data. The free ITIT app is available in 14 languages. Participants were recruited globally from April 2022 to July 2023. Participants >18 years of age travelled internationally and provided electronic consent. Incentives included the provision of travel health information imported from the WHO website. Symptoms were recorded with daily pop-up questionnaires and symptom severity was assessed using a Likert scale. Two post-travel questionnaires were administered. Logistic mixed models examined factors relating to symptom presence, and a random forest model examined symptom impact.Results 609 participants were recruited until July 2023. Participants had an average age of 37 years (18–79), and an average travel duration of 26 days (2–281). Most participants were travelling for leisure/tourism (401; 66%), followed by ‘visiting friends and relatives’ (99; 16%) and business travel (80; 13%). All continents were visited by at least one traveller. Of 470 registered trips, symptoms were reported on 163 trips (35%). Gastrointestinal symptoms were reported on 87 trips (19%) and respiratory symptoms on 81 trips (17%). The most important factors in predicting the presence of symptoms were duration of travel, travelling in winter and high humidity. Diarrhoea, headache and nausea were symptoms with most impact on daily activities. Post-travel questionnaires showed that 12% of surveyed participants experienced symptoms with several episodes of self-treatment. Two diagnoses were recorded: Lyme disease and amoebic dysentery.Conclusion The digital tool ITIT successfully captures the spectrum of travel-related illness. This detailed epidemiology is crucial for outbreak detection and for the formulation of travel medicine guidelines.Trial registration number NCT04672577.

At the end of 2022, a total of 20,003 diagnoses of human immunodeficiency virus (HIV) infection and 8,983 cases of acquired immunodeficiency syndrome (AIDS) among Japanese nationals, and 3,860 HIV diagnoses and 1,575 AIDS cases among foreign residents, had been notified to the government in Japan. This study updates the estimate of HIV incidence, including during the COVID-19 pandemic. It aimed to reconstruct the incidence of HIV and understand how the disruption caused by COVID-19 affected the epidemiology of HIV. Using a median incubation period of 10.0 years, the number of undiagnosed HIV infections was estimated to be 3,209 (95% confidence interval (CI): 2,642, 3,710) at the end of 2022. This figure has declined steadily over the past 10 years. Assuming that the median incubation period was 10.0 years, the proportion of diagnosed HIV infections, including surviving AIDS cases, was 89.3% (95% CI: 87.8%, 91.0%). When AIDS cases were excluded, the proportion was 86.2% (95% CI: 84.3%, 88.3%). During the COVID-19 pandemic, the estimated annual diagnosis rate was slightly lower than during earlier time intervals, at around 16.5% (95% CI: 14.9%, 18.1%). Japan may already have achieved diagnostic coverage of 90%, given its 9% increment in the diagnosed proportion during the past 5 years. The incidence of HIV infection continued to decrease even during the COVID-19 pandemic from 2020 to 2022, and the annual rate of diagnosis decreased slightly to 16.5%. Monitoring the recovery of diagnosis along with the effective reproduction number is vital in the future.

Abstract Background A major epidemic of COVID-19 caused by the Delta variant (B.1.617.2) occurred in India from March to July 2021, resulting in 19 million documented cases. Given the limited healthcare and testing capacities, the actual number of infections is likely to have been greater than reported, and several modelling studies and excess mortality research indicate that this epidemic involved substantial morbidity and mortality. Methods To estimate the incidence during this epidemic, we used border entry screening data in Japan to estimate the daily incidence and cumulative incidence of COVID-19 infection in India. Analysing the results of mandatory testing among non-Japanese passengers entering Japan from India, we calculated the prevalence and then backcalculated the incidence in India from February 28 to July 3, 2021. Results The estimated number of infections ranged from 448 to 576 million people, indicating that 31.8% (95% confidence interval (CI): 26.1, 37.7) – 40.9% (95% CI: 33.5, 48.4) of the population in India had experienced COVID-19 infection from February 28 to July 3, 2021. In addition to obtaining cumulative incidence that was consistent with published estimates, we showed that the actual incidence of COVID-19 infection during the 2021 epidemic in India was approximately 30 times greater than that based on documented cases, giving a crude infection fatality risk of 0.47%. Adjusting for test-negative certificate before departure, the quality control of which was partly questionable, the cumulative incidence can potentially be up to 2.3–2.6 times greater than abovementioned estimates. Conclusions Our estimate of approximately 32–41% cumulative infection risk from February 28 to July 3, 2021 is roughly consistent with other published estimates, and they can potentially be greater, given an exit screening before departure. The present study results suggest the potential utility of border entry screening data to backcalculate the incidence in countries with limited surveillance capacity owing to a major surge in infections.

Mobility restrictions were widely practiced to reduce contact with others and prevent the spatial spread of COVID-19 infection. Using inter-prefectural mobility and epidemiological data, a statistical model was devised to predict the number of imported cases in each Japanese prefecture. The number of imported cases crossing prefectural borders in 2020 was predicted using inter-prefectural mobility rates based on mobile phone data and prevalence estimates in the origin prefectures. The simplistic model was quantified using surveillance data of cases with an inter-prefectural travel history. Subsequently, simulations were carried out to understand how imported cases vary with the mobility rate and prevalence at the origin. Overall, the predicted number of imported cases qualitatively captured the observed number of imported cases over time. Although Hokkaido and Okinawa are the northernmost and the southernmost prefectures, respectively, they were sensitive to differing prevalence rate in Tokyo and Osaka and the mobility rate. Additionally, other prefectures were sensitive to mobility change, assuming that an increment in the mobility rate was seen in all prefectures. Our findings indicate the need to account for the weight of an inter-prefectural mobility network when implementing countermeasures to restrict human movement. If the mobility rates were maintained lower than the observed rates, then the number of imported cases could have been maintained at substantially lower levels than the observed, thus potentially preventing the unnecessary spatial spread of COVID-19 in late 2020.

Many countries struggled with suppressing the incidence of COVID-19 caused by SARS-CoV-2 Omicron variant (B.1.1.529). As the epidemic size of COVID-19 in 2022 became bigger than earlier years in Japan, the present study aimed to estimate life expectancy at birth at the end of 2022, using provisional death datasets in Aichi and Fukui prefectures. We collected monthly death count from 2019 to the end of 2022, computing the period life table. While the life expectancy at birth in Aichi, 2019 was 84.6 years, it was very slightly extended to 84.7 years in 2020 and 2021, followed by a shortening for nearly 0.4 years in 2022. In Fukui, monotonous extension pattern was seen, i.e., 85.5 years in 2019, 85.6 in 2020, followed by 85.8 and 86.2 years in 2021 and 2022, respectively. Although decades-long trend of extending life expectancy at birth was partly discontinued from 2020 due to the pandemic at the national level, we have shown that the pandemic impact was still small in Japan by the end of 2022. First Omicron wave occurred shortly after primary series vaccination, and even real time booster program was underway during that wave. Different demographic consequences between Aichi and Fukui are explained by differential epidemic sizes prior to vaccination.

Background: The number of people undergoing voluntary HIV testing has abruptly decreased since 2020. The geographical heterogeneity of HIV infection and the impact of COVID-19 on the diagnosis of HIV at regional level are important to understand. This study aimed to estimate the HIV incidence by geographical region and understand how the COVID-19 pandemic influenced diagnosis of HIV. Methods: We used an extended back-calculation method to reconstruct the epidemiological dynamics of HIV/AIDS by geographical region. We used eight regions: Tokyo, the capital of Japan, Hokkaido plus Tohoku, Kanto plus Koshinetsu (excluding Tokyo), Hokuriku, Tokai, Kinki, Chugoku plus Shikoku, and Kyushu plus Okinawa. Four different epidemiological measurements were evaluated: (i) estimated HIV incidence, (ii) estimated rate of diagnosis, (iii) number of undiagnosed HIV infections, and (iv) proportion of HIV infections that had been diagnosed. Results: The incidence of HIV/AIDS during the COVID-19 pandemic from 2020 to 2022 increased in all regions except Kanto/Koshinetsu (51.3 cases/year), Tokyo (183.9 cases/year), Hokuriku (1.0 cases/year), and Tokai (43.1 cases/year). The proportion of HIV infections that had been diagnosed only exceeded 90% in Tokyo (91.7%, 95% confidence interval (CI): 90.6, 93.3), Kanto/Koshinetsu (91.0%, 95% CI: 87.3, 97.8), and Kinki (92.5%, 95% CI: 90.4, 95.9). The proportion of infections that had been diagnosed was estimated at 83.3% (95% CI: 75.1, 98.7) in Chugoku/Shikoku and 80.5% (95% CI: 73.9, 91.0) in Kyusyu/Okinawa. Conclusions: In urban regions with major metropolitan cities, including Tokyo, Kinki, and Kanto/Koshinetsu, the number of undiagnosed HIV infections is substantial. However, the proportion of undiagnosed infections was estimated to be smaller than in other regions. The diagnosed proportion was the lowest in Kyusyu/Okinawa (80.5%), followed by Chugoku/Shikoku and Hokkaido/Tohoku. The level of diagnosis in those regional prefectures may have been more influenced and damaged by the COVID-19 pandemic than in urban settings.

Abstract Background Many countries, including high-income nations, struggled to control epidemic waves caused by the Omicron variant (B.1.1.529), which had an antigenically distinct evolution. Evaluating the direct and indirect effects of vaccination during the Omicron waves is essential to assess virus control policies. The present study assessed the population impacts of a vaccination program during the sixth wave caused by BA.1 and BA.2 from January to May 2022, in Tokyo. Methods We analyzed the primary series and booster vaccination coverages and the confirmed cases stratified by vaccination history. We estimated the number of COVID-19 cases that were directly and indirectly prevented by vaccination. To estimate the direct impact, we used a statistical model that compared risks between unvaccinated and vaccinated individuals. A transmission model employing the renewal process was devised to quantify the total effect, given as the sum of the direct and indirect effects. Results Assuming that the reporting coverage of cases was 25%, mass vaccination programs, including primary and booster immunizations, directly averted 640,000 COVID-19 cases (95% confidence interval: 624–655). Furthermore, these programs directly and indirectly prevented 8.5 million infections (95% confidence interval: 8.4–8.6). Hypothetical scenarios indicated that we could have expected a 19% or 7% relative reduction in the number of infections, respectively, compared with the observed number of infections, if the booster coverage had been equivalent to that of the second dose or if coverage among people aged 10–49 years had been 10% higher. If the third dose coverage was smaller and comparable to that of the fourth dose, the total number of infections would have increased by 52% compared with the observed number of infections. Conclusions The population benefit of vaccination via direct and indirect effects was substantial, with an estimated 65% reduction in the number of SARS-CoV-2 infections compared with counterfactual (without vaccination) in Tokyo during the sixth wave caused by BA.1 and BA.2.

Abstract Japan implemented its nationwide vaccination program against COVID-19 in 2021, immunizing more than one million people (approximately 1%) a day. However, the direct and indirect impacts of the program at the population level have yet to be fully evaluated. To assess the vaccine effectiveness during the Delta variant (B.1.617.2) epidemic in 2021, we used a renewal process model. A transmission model was fitted to the confirmed cases from 17 February to 30 November 2021. In the absence of vaccination, the cumulative numbers of infections and deaths during the study period were estimated to be 63.3 million (95% confidence interval [CI] 63.2–63.6) and 364,000 (95% CI 363–366), respectively; the actual numbers of infections and deaths were 4.7 million and 10,000, respectively. Were the vaccination implemented 14 days earlier, there could have been 54% and 48% fewer cases and deaths, respectively, than the actual numbers. We demonstrated the very high effectiveness of COVID-19 vaccination in Japan during 2021, which reduced mortality by more than 97% compared with the counterfactual scenario. The timing of expanding vaccination and vaccine recipients could be key to mitigating the disease burden of COVID-19. Rapid and proper decision making based on firm epidemiological input is vital.

Abstract Chronic pancreatitis (CP) is a disease characterized by the inflammation and destruction of pancreatic tissue, leading to the replacement of functional tissue with fibrotic tissue. The regenerating gene (Reg) family proteins have recently been implicated in the repair and regeneration of inflamed pancreatic tissue, though the exact mechanisms of their involvement in the pathogenesis of CP are not yet fully understood. To investigate the role of Reg family proteins in CP, we generated global knockout mice (Reg −/− ) for Reg1-3 (Reg1,2,3a,3b,3d,3g) genes using the CRISPR/Cas9 system. We then investigated the effect of Reg family protein deficiency in a genetic model of CP (X-SPINK1) mice by knocking out Reg1-3 genes. We examined pancreatic morphology, inflammatory cytokines expression, and activation of pancreatic stellate cells (PSCs) at different ages. Reg −/− mice showed no abnormalities in general growth and pancreas development. Deficiency of Reg1-3 in CP mice led to a reduction in pancreatic parenchymal loss, decreased deposition of collagen, and reduced expression of proinflammatory cytokines. Additionally, Reg proteins were found to stimulate PSCs activation. Overall, our study suggests that Reg1-3 deficiency can lead to the remission of CP and Reg family proteins could be a potential therapeutic target for the treatment of CP.

Background: A highly pathogenic avian influenza (HPAI) A (H5N1) virus has been detected in domestic and wild animals worldwide. The incidence of HPAI infections in sea mammals has been increasing, as is the number of stranded marine mammals linked to H5N1 viral clade 2.3.4.4(b). In this study, we investigated a stranding event involving dolphins and human–dolphin contact, and investigated the potential risk of animal-to-human H5N1 transmission with a survey of exposure on the Tsurigasaki coast, Japan. Methods: We performed a non-random, convenient-sample-based, survey on Tsurigasaki beach where around 30 melon-headed whales were stranded on April 3, 2023. Face-to-face (n = 25) and telephone (n = 1) interviews among surfers took place on April 7 and 8. A nasal swab for quick antigen testing was taken from those who wished to be tested (n = 13), to detect infections with influenza A virus. Results: Although there was no confirmatory diagnosis of H5N1 in either humans or dolphins (while n = 3 dolphins were autopsied), we found that a large number of surfers had touched the dolphins with their bare hands while attempting to rescue them, and that some surfers were directly exposed to dolphin blood and body fluids in the ocean. Conclusions: The adequate communication of risk is required to minimize the threat of viral transmission at this particular human–animal interface. Administrative and legal responses to cross-species transmission, including guidelines via one health frameworks, a rapid evaluation process of ethical approval, and the systematic involvement of experts in infectious disease, must be urgently formulated.

Before reopening society in December 2022, China had not achieved sufficiently high vaccination coverage among people aged 80 years and older, who are vulnerable to severe infection and death owing to COVID-19. Suddenly ending the zero-COVID policy was anticipated to lead to substantial mortality. To investigate the mortality impact of COVID-19, we devised an age-dependent transmission model to derive a final size equation, permitting calculation of the expected cumulative incidence. Using an age-specific contact matrix and published estimates of vaccine effectiveness, final size was computed as a function of the basic reproduction number, R0. We also examined hypothetical scenarios in which third-dose vaccination coverage was increased in advance of the epidemic, and also in which mRNA vaccine was used instead of inactivated vaccines. Without additional vaccination, the final size model indicated that a total of 1.4 million deaths (half of which were among people aged 80 years and older) were anticipated with an assumed R0 of 3.4. A 10% increase in third-dose coverage would prevent 30,948, 24,106, and 16,367 deaths, with an assumed second-dose effectiveness of 0%, 10%, and 20%, respectively. With mRNA vaccine, the mortality impact would have been reduced to 1.1 million deaths. The experience of reopening in China indicates the critical importance of balancing pharmaceutical and non-pharmaceutical interventions. Ensuring sufficiently high vaccination coverage is vital in advance of policy changes.

Abstract Japanese government initially enforced restrictions on outpatient attendances among febrile individuals suspected of having COVID-19, asking everyone to remain at home for at least 4 days from the onset of fever. This restriction was cancelled on 8 May 2020, and a new antiviral, remdesivir, was approved from 7 May 2020. To investigate how this policy change influenced the prognosis of people with COVID-19, we estimated the case fatality risk as a function of the date of illness onset from April to June 2020. We used an interrupted time-series analysis model with an intervention date of 8 May 2020, and estimated time-dependent case fatality risk by age group. The case fatality risk showed a decreasing trend in all groups, and models were favored accounting for an abrupt causal effect, i.e., immediate decline in fatality risk. The trend was estimated at − 1.1% (95% CI [confidence interval]: − 3.9, 3.0) among people aged 60–69 years, − 7.2% (95% CI − 11.2, − 2.4) among those aged 70–79 years, − 7.4% (95% CI − 14.2, 0.2) among those aged 80–89 years, and − 10.3% (95% CI − 21.1, 2.7) among those aged 90 and over. Early diagnosis and treatment greatly contributed to reducing the case fatality risk.

Abstract 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.

IntroductionHeatstroke mortality is highest among older adults aged 65 years and older, and the risk is even doubled among those aged 75 years and older. The incidence of heatstroke is expected to increase in the future with elevated temperatures owing to climate change. In the context of a super-aged society, we examined possible adaptation measures in Japan that could prevent heatstroke among older people using an epidemiological survey combined with mathematical modeling.MethodsTo identify possible interventions, we conducted a cross-sectional survey, collecting information on heatstroke episodes from 2018 to 2019 among people aged 75 years and older. Responses were analyzed from 576 participants, and propensity score matching was used to adjust for measurable confounders and used to estimate the effect sizes associated with variables that constitute possible interventions. Subsequently, a weather-driven statistical model was used to predict heatstroke-related ambulance transports. We projected the incidence of heatstroke-related transports until the year 2100, with and without adaptation measures.ResultsThe risk factor with the greatest odds ratio (OR) of heatstroke among older adults was living alone (OR 2.5, 95% confidence interval: 1.2–5.4). Other possible risk factors included an inability to drink water independently and the absence of air conditioning. Using three climate change scenarios, a more than 30% increase in the incidence of heatstroke-related ambulance transports was anticipated for representative concentration pathways (RCP) 4.5 and 8.5, as compared with a carbon-neutral scenario. Given 30% reduction in single living, a 15% reduction in the incidence of heatstroke is expected. Given 70% improvement in all three risk factors, a 40% reduction in the incidence can be expected.ConclusionPossible adaptation measures include providing support for older adults living alone, for those who have an inability to drink water and for those without air conditioning. To be comparable to carbon neutrality, future climate change under RCP 2.6 requires achieving a 30% relative reduction in all three identified risks at least from 2060; under RCP 4.5, a 70% reduction from 2050 at the latest is needed. In the case of RCP 8.5, the goal of heatstroke-related transports approaching RCP 1.9 cannot be achieved.

In Japan, major and minor bimodal seasonal patterns of varicella have been observed. To investigate the underlying mechanisms of seasonality, we evaluated the effects of the school term and temperature on the incidence of varicella in Japan. We analyzed epidemiological, demographic and climate datasets of seven prefectures in Japan. We fitted a generalized linear model to the number of varicella notifications from 2000 to 2009 and quantified the transmission rates as well as the force of infection, by prefecture. To evaluate the effect of annual variation in temperature on the rate of transmission, we assumed a threshold temperature value. In northern Japan, which has large annual temperature variations, a bimodal pattern in the epidemic curve was observed, reflecting the large deviation in average weekly temperature from the threshold value. This bimodal pattern was diminished with southward prefectures, gradually shifting to a unimodal pattern in the epidemic curve, with little temperature deviation from the threshold. The transmission rate and force of infection, considering the school term and temperature deviation from the threshold, exhibited similar seasonal patterns, with a bimodal pattern in the north and a unimodal pattern in the south. Our findings suggest the existence of preferable temperatures for varicella transmission and an interactive effect of the school term and temperature. Investigating the potential impact of temperature elevation that could reshape the epidemic pattern of varicella to become unimodal, even in the northern part of Japan, is required.

The purpose of the present study was to develop a transmission model of COVID-19 cases with and without a contact history to understand the meaning of the proportion of infected individuals with a contact history over time. We extracted epidemiological information regarding the proportion of coronavirus disease 2019 (COVID-19) cases with a contact history and analyzed incidence data stratified by the presence of a contact history in Osaka from January 15 to June 30, 2020. To clarify the relationship between transmission dynamics and cases with a contact history, we used a bivariate renewal process model to describe transmission among cases with and without a contact history. We quantified the next-generation matrix as a function of time; thus, the instantaneous (effective) reproduction number was calculated for different periods of the epidemic wave. We objectively interpreted the estimated next-generation matrix and replicated the proportion of cases with a contact p(t) over time, and we examined the relevance to the reproduction number. We found that p(t) does not take either the maximum or minimum value at a threshold level of transmission with R(t)=1.0. With R(t) < 1 (subcritical level), p(t) was a decreasing function of R(t). Qualitatively, the minimum p(t) was seen in the domain with R(t) > 1. An important future implication for use of the proposed model is to monitor the success of ongoing contact tracing practice. A decreasing signal of p(t) reflects the increasing difficulty of contact tracing. The present study findings indicate that monitoring p(t) would be a useful addition to surveillance.

With continuing emergence of new SARS-CoV-2 variants, understanding the proportion of the population protected against infection is crucial for public health risk assessment and decision-making and so that the general public can take preventive measures. We aimed to estimate the protection against symptomatic illness caused by SARS-CoV-2 Omicron variants BA.4 and BA.5 elicited by vaccination against and natural infection with other SARS-CoV-2 Omicron subvariants. We used a logistic model to define the protection rate against symptomatic infection caused by BA.1 and BA.2 as a function of neutralizing antibody titer values. Applying the quantified relationships to BA.4 and BA.5 using two different methods, the estimated protection rate against BA.4 and BA.5 was 11.3% (95% confidence interval [CI]: 0.01–25.4) (method 1) and 12.9% (95% CI: 8.8–18.0) (method 2) at 6 months after a second dose of BNT162b2 vaccine, 44.3% (95% CI: 20.0–59.3) (method 1) and 47.3% (95% CI: 34.1–60.6) (method 2) at 2 weeks after a third BNT162b2 dose, and 52.3% (95% CI: 25.1–69.2) (method 1) and 54.9% (95% CI: 37.6–71.4) (method 2) during the convalescent phase after infection with BA.1 and BA.2, respectively. Our study indicates that the protection rate against BA.4 and BA.5 are significantly lower compared with those against previous variants and may lead to substantial morbidity, and overall estimates were consistent with empirical reports. Our simple yet practical models enable prompt assessment of public health impacts posed by new SARS-CoV-2 variants using small sample-size neutralization titer data to support public health decisions in urgent situations.

Abstract Background It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death. Methods We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated. Results The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients

Objectives: Elucidating the infection dynamics that lead to severe respiratory syncytial virus (RSV) pneumonia and hospitalization among young children are critical. We explored the role of infection parity as well as age in months for RSV-associated hospitalization among young children in Japan. Methods: We used a sequential transmission catalytic model to capture the transmission mechanisms of RSV among infants in an endemic state. We investigated data on the age-dependent seroprevalence and incidence rate of hospitalization in Japan, and jointly estimated the age-specific risk of hospitalization during primary RSV infection and relative risk of hospitalization during secondary infection in children aged

Abstract Background In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020. Methods We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign. Results Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign. Conclusions The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited.

The basic reproduction number, $ R_0 $, plays a central role in measuring the transmissibility of an infectious disease, and it thus acts as the fundamental index for planning control strategies. In the present study, we apply a branching process model to meticulously observed contact tracing data from Wakayama Prefecture, Japan, obtained in early 2020 and mid-2021. This allows us to efficiently estimate $ R_0 $ and the dispersion parameter $ k $ of the wild-type COVID-19, as well as the relative transmissibility of the Delta variant and relative transmissibility among fully vaccinated individuals, from a very limited data. $ R_0 $ for the wild type of COVID-19 is estimated to be 3.78 (95% confidence interval [CI]: 3.72–3.83), with $ k = 0.236 $ (95% CI: 0.233–0.240). For the Delta variant, the relative transmissibility to the wild type is estimated to be 1.42 (95% CI: 0.94–1.90), which gives $ R_0 = 5.37 $ (95% CI: 3.55–7.21). Vaccine effectiveness, determined by the reduction in the number of secondary transmissions among fully vaccinated individuals, is estimated to be 91% (95% CI: 85%–97%). The present study highlights that basic reproduction numbers can be accurately estimated from the distribution of minor outbreak data, and these data can provide further insightful epidemiological estimates including the dispersion parameter and vaccine effectiveness regarding the prevention of transmission.

COVID-19 vaccine effectiveness against death in Japan remains unknown. Furthermore, although evidence indicates that healthcare capacity influences case-fatality risk (CFR), it remains unknown whether this relationship is mediated by age. With a modeling study, we analyzed daily COVID-19 cases and deaths during January–August 2021 by using Tokyo surveillance data to jointly estimate COVID-19 vaccine effectiveness against death and age-specific CFR. We also examined daily healthcare operations to determine the association between healthcare burden and age-specific CFR. Among fully vaccinated patients, vaccine effectiveness against death was 88.6% among patients 60–69 years of age, 83.9% among patients 70–79 years of age, 83.5% among patients 80–89 years of age, and 77.7% among patients >90 years of age. A positive association of several indicators of healthcare burden with CFR among patients >70 years of age suggested an age-dependent effect of healthcare burden on CFR in Japan.

ABSTRACT: Objectives: COVID-19 vaccination in Japan started on February 17, 2021. Because the timing of vaccination and the risk of severe COVID-19 greatly varied with age, the present study aimed to monitor the age-specific fractions of the population who were immune to SARS-CoV-2 infection after vaccination. Methods: Natural infection remained extremely rare, accounting for less than 5% of the population by the end of 2021; thus, we ignored natural infection-induced immunity and focused on vaccine-induced immunity. We estimated the fraction of the population immune to infection by age group using vaccination registry data from February 17, 2021, to October 17, 2021. We accounted for two important sources of delay: (i) reporting delay and (ii) time from vaccination until immune protection develops. Results: At the end of the observation period, the proportion of individuals still susceptible to SARS-CoV-2 infection substantially varied by age and was estimated to be ≥90% among people aged 0–14 years, in contrast to approximately 20% among the population aged ≥65 years. We also estimated the effective reproduction number over time using a next-generation matrix while accounting for differences in the proportion immune to infection by age. Conclusion: The COVID-19 immune landscape greatly varied by age, and a substantial proportion of young adults remained susceptible. Vaccination contributed to a marked decrease in the reproduction number.

Background The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. Objective We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020–2021 into age-specific and cause of death-specific contributions. Methods We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019–21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. Results From 2019–2020, Japan’s national level life expectancy across the entire population was extended by 0.24 years. From 2020–2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020–2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020–2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life expectancy, whereas respiratory diseases did not. Conclusion The decades-long increasing trend in life expectancy was suspended by the COVID-19 pandemic. However, life expectancy changes from 2019–2020 and 2020–2021 were small in Japan. This may be attributable to the small epidemiological impact of COVID-19 during this time period, but nonetheless, the negative impact of COVID-19 on life expectancy was indicated in the present study. The chance of death accelerated in older people in 2021, but a smaller number of deaths than usual among infants and working age adults contributed to extended life expectancy, and the change in the cause of death structure under the COVID-19 pandemic also significantly contributed to shortening life expectancy.

BackgroundMobility data are crucial for understanding the dynamics of coronavirus disease 2019 (COVID-19), but the consistency of the usefulness of these data over time has been questioned. The present study aimed to reveal the relationship between the transmissibility of COVID-19 in Tokyo, Osaka, and Aichi prefectures and the daily night-time population in metropolitan areas belonging to each prefecture.MethodsIn Japan, the de facto population estimated from GPS-based location data from mobile phone users is regularly monitored by Ministry of Health, Labor, and Welfare and other health departments. Combined with this data, we conducted a time series linear regression analysis to explore the relationship between daily reported case counts of COVID-19 in Tokyo, Osaka, and Aichi, and night-time de facto population in downtown areas estimated from mobile phone location data, from February 2020 to May 2022. As an approximation of the effective reproduction number, the weekly ratio of cases was used. Models using night-time population with lags ranging from 7 to 14 days were tested. In time-varying regression analysis, the night-time population level and the daily change in night-time population level were included as explanatory variables. In the fixed-effect regression analysis, the inclusion of either the night-time population level or daily change, or both, as explanatory variables was tested, and autocorrelation was adjusted by introducing first-order autoregressive error of residuals. In both regression analyses, the lag of night-time population used in best fit models was determined using the information criterion.ResultsIn the time-varying regression analysis, night-time population level tended to show positive to neutral effects on COVID-19 transmission, whereas the daily change of night-time population showed neutral to negative effects. The fixed-effect regression analysis revealed that for Tokyo and Osaka, regression models with 8-day-lagged night-time population level and daily change were the best fit, whereas in Aichi, the model using only the 9-day-lagged night-time population level was the best fit using the widely applicable information criterion. For all regions, the best-fit model suggested a positive relationship between night-time population and transmissibility, which was maintained over time.ConclusionOur results revealed that, regardless of the period of interest, a positive relationship between night-time population levels and COVID-19 dynamics was observed. The introduction of vaccinations and major outbreaks of Omicron BA. Two subvariants in Japan did not dramatically change the relationship between night-time population and COVID-19 dynamics in three megacities in Japan. Monitoring the night-time population continues to be crucial for understanding and forecasting the short-term future of COVID-19 incidence.

The Omicron variant spreads fastest as ever among the severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) we had so far. The BA.1 and BA.2 sublineages of Omicron are circulating worldwide and it is urgent to evaluate the transmission advantages of these sublineages. Using a mathematical model describing trajectories of variant frequencies that assumes a constant ratio in mean generation times and a constant ratio in effective reproduction numbers among variants, trajectories of variant frequencies in Denmark from November 22, 2021 to February 26, 2022 were analyzed. We found that the mean generation time of Omicron BA.1 is 0.44–0.46 times that of Delta and the effective reproduction number of Omicron BA.1 is 1.88–2.19 times larger than Delta under the epidemiological conditions at the time. We also found that the mean generation time of Omicron BA.2 is 0.76–0.80 times that of BA.1 and the effective reproduction number of Omicron BA.2 is 1.25–1.27 times larger than Omicron BA.1. These estimates on the ratio of mean generation times and the ratio of effective reproduction numbers have epidemiologically important implications. The contact tracing for Omicron BA.2 infections must be done more quickly than that for BA.1 to stop further infections by quarantine. In the Danish population, the control measures against Omicron BA.2 need to reduce 20–21% of additional contacts compared to that against BA.1.

Objectives: To explore a potential country-based ecological link between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) infection and an apparent current global outbreak of severe hepatitis of unknown etiology among children. Methods: We examined country-level statistical associations between reported detection of one or more unexplained severe hepatitis cases in children and the cumulative number of Omicron (B.1.1.529) cases in 38 Organisation for Economic Co-operation and Development (OECD) member countries plus Romania. Results: At least one focal hepatitis case was detected in 12 of the 39 countries included in our analysis. Numbers of confirmed Omicron cases reported in these 12 countries ranged from 4.4 to 11.9 million. Among the remaining 27 countries, this measure ranged from 0.5 to 5.5 million cases. Countries which reported focal hepatitis cases experienced higher precedent population burdens of Omicron cases relative to those which did not report any such hepatitis cases (p=0.013). Conclusion: Prior exposure to Omicron variant (B.1.1.529) may be associated with an increased risk for severe hepatitis among children, indicating a critical need to conduct cofactor studies.

In response to the coronavirus disease 2019 (COVID-19) pandemic, Japan conducted mass vaccination. Seventy-two million doses of vaccine (i.e., for 36 million people if a double dose is planned per person) were obtained, with initial vaccination of the older population (≡ 65 years). Because of the limited number of vaccines, the government discussed shifting the plan to administering only a single dose so that younger individuals (

Japan successfully implemented a mass vaccination program for coronavirus disease 2019 (COVID-19), immunizing more than 1 million persons a day by July 2021. Given the COVID-19 vaccination capacity limitations, an urgent question was raised regarding whether it would be better to (ⅰ) complete double-dose COVID-19 vaccination among healthcare personnel and older adults before beginning double-dose vaccination of younger adults (double-dose strategy) or (ⅱ) allocate a single dose of COVID-19 vaccine to all adults regardless of age before administering the second dose (single-dose-first strategy). We used an age-structured susceptible-infectious-recovered (SIR) compartment model to compare the effectiveness of possible COVID-19 vaccination strategies and the length of public health and social measures (PHSM) to minimize the cumulative COVID-19 disease risk and death toll. Our results indicate that if the single-dose-first strategy was taken, an estimated total of 1,387,078 persons, i.e., 263,315 children, 928,518 young adults, and 195,245 older adults, would develop COVID-19, resulting in 15,442 deaths. In contrast, if the double-dose strategy was taken instead, an estimated total of 1,900,172 persons, i.e., 377,107 children, 1,315,927 young adults, and 207,138 older adults, would develop COVID-19, yielding 17,423 deaths. Real-time investigation favored the disease transmission blocking option, i.e., single-dose vaccination strategy. Applying the single-dose-first strategy should yield a smaller epidemic size than applying the double-dose strategy; however, for both strategies, PHSM will be essential by the time second-dose COVID-19 vaccination is complete among all adults.

Public health and social measures (PHSMs) targeting the coronavirus disease 2019 (COVID-19) pandemic have potentially affected the epidemiological dynamics of endemic infectious diseases. In this study, we investigated the impact of PHSMs for COVID-19, with a particular focus on varicella dynamics in Japan. We adopted the susceptible-infectious-recovered type of mathematical model to reconstruct the epidemiological dynamics of varicella from Jan. 2010 to Sep. 2021. We analyzed epidemiological and demographic data and estimated the within-year and multi-year component of the force of infection and the biases associated with reporting and ascertainment in three periods: pre-vaccination (Jan. 2010–Dec. 2014), pre-pandemic vaccination (Jan. 2015–Mar. 2020) and during the COVID-19 pandemic (Apr. 2020–Sep. 2021). By using the estimated parameter values, we reconstructed and predicted the varicella dynamics from 2010 to 2027. Although the varicella incidence dropped drastically during the COVID-19 pandemic, the change in susceptible dynamics was minimal; the number of susceptible individuals was almost stable. Our prediction showed that the risk of a major outbreak in the post-pandemic era may be relatively small. However, uncertainties, including age-related susceptibility and travel-related cases, exist and careful monitoring would be required to prepare for future varicella outbreaks.

Following the emergence and worldwide spread of coronavirus disease 2019 (COVID-19), each country has attempted to control the disease in different ways. The first patient with COVID-19 in Japan was diagnosed on 15 January 2020, and until 31 October 2020, the epidemic was characterized by two large waves. To prevent the first wave, the Japanese government imposed several control measures such as advising the public to avoid the 3Cs (closed spaces with poor ventilation, crowded places with many people nearby, and close-contact settings such as close-range conversations) and implementation of "cluster buster" strategies. After a major epidemic occurred in April 2020 (the first wave), Japan asked its citizens to limit their numbers of physical contacts and announced a non-legally binding state of emergency. Following a drop in the number of diagnosed cases, the state of emergency was gradually relaxed and then lifted in all prefectures of Japan by 25 May 2020. However, the development of another major epidemic (the second wave) could not be prevented because of continued chains of transmission, especially in urban locations. The present study aimed to descriptively examine propagation of the COVID-19 epidemic in Japan with respect to time, age, space, and interventions implemented during the first and second waves. Using publicly available data, we calculated the effective reproduction number and its associations with the timing of measures imposed to suppress transmission. Finally, we crudely calculated the proportions of severe and fatal COVID-19 cases during the first and second waves. Our analysis identified key characteristics of COVID-19, including density dependence and also the age dependence in the risk of severe outcomes. We also identified that the effective reproduction number during the state of emergency was maintained below the value of 1 during the first wave.

Although the Japanese government removed mask-wearing requirements in 2023, relatively high rates of mask wearing have continued in Japan. We aimed to assess psychological reasons and the strength of habitual mask wearing in Japan. An Internet-based cross-sectional survey was conducted with non-random participant recruitment. We explored the frequency of mask usage, investigating psychological reasons for wearing masks. A regression analysis examined the association between psychological reasons and the frequency of mask wearing. The habitual use of masks was assessed in the participant’s most frequently visited indoor space and public transport using the self-report habit index. The principal component analysis with varimax rotation revealed distinct habitual characteristics. Among the 2640 participants surveyed from 6 to 9 February 2023, only 4.9% reported not wearing masks at all. Conformity to social norms was the most important reason for masks. Participants exhibited a slightly higher degree of habituation towards mask wearing on public transport compared to indoor spaces. The mask-wearing rate was higher in females than in males, and no significant difference was identified by age group. Daily mask wearing in indoor spaces was characterized by two traits (automaticity and behavioral frequency). A high mask-wearing frequency has been maintained in Japan during the social reopening transition period. Mask wearing has become a part of daily habit, especially on public transport, largely driven by automatic and frequent practice.

ABSTRACT: Background: Following an outbreak of coronavirus disease 2019 (COVID-19) on the cruise ship Diamond Princess, passengers and crew were followed-up to determine prognosis. This study examined the epidemiological determinants of COVID-19 natural history using these follow-up data. Methods: Infection status, diagnosis, clinical symptoms and prognosis were analysed for all passengers and crew members on the Diamond Princess. In addition, the risk of infection associated with exposure within cabin rooms, as well as the risks of various clinical manifestations of disease, along with their epidemiological determinants, were analysed. Results: The adjusted odds ratio (aOR) of infection for individuals tested by polymerase chain reaction on or after 12 February 2020 compared with individuals tested before this date was 0.53 [95% confidence interval (CI) 0.39–0.72], reflecting decreased transmission during onboard quarantine. Among infected individuals, older age was associated with elevated odds of symptomatic illness (aOR 1.01, 95% CI 1.00–1.02), severe disease (aOR 1.08, 95% CI 1.05–1.12) and death (aOR 1.12, 95% CI 1.05–1.21). Conclusions: Severe COVID-19 disease, death and symptomatic illness were more frequent among older individuals on the Diamond Princess. Older elderly cases (age ≥80 years) had the highest risks of severe disease and death. Inter-room transmission was prevented successfully by the onboard quarantine.

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

Forecasting future epidemics helps inform policy decisions regarding interventions. During the early coronavirus disease 2019 epidemic period in January–February 2020, limited information was available, and it was too challenging to build detailed mechanistic models reflecting population behavior. This study compared the performance of phenomenological and mechanistic models for forecasting epidemics. For the former, we employed the Richards model and the approximate solution of the susceptible–infected–recovered (SIR) model. For the latter, we examined the exponential growth (with lockdown) model and SIR model with lockdown. The phenomenological models yielded higher root mean square error (RMSE) values than the mechanistic models. When using the numbers from reported data for February 1 and 5, the Richards model had the highest RMSE, whereas when using the February 9 data, the SIR approximation model was the highest. The exponential model with a lockdown effect had the lowest RMSE, except when using the February 9 data. Once interventions or other factors that influence transmission patterns are identified, they should be additionally taken into account to improve forecasting.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly spread across the globe. The variant of concern (VOC) 202012/01 (B.1.1.7, also known as the alpha variant) bearing the N501Y mutation emerged in late 2020. VOC 202012/01 was more transmissible than existing SARS-CoV-2 variants and swiftly became dominant in many regions. More than 150 cases of VOC 202012/01 were reported in Japan by 26 February 2021. During the very early stage of introduction, only a subset arose from domestic transmission. If the reproduction number R (i.e., the average number of secondary transmission events caused by a single primary case) is greater than 1, the corresponding proportion should converge to 1 in a short period of time, and thus it is critical to understand the transmissibility of VOC 202012/01 based on travel history information. The present study aimed to estimate R of VOC 202012/01 using overseas travel history information. A mathematical model was developed to capture the relationship between travel history and R. We obtained travel history data for each confirmed case of VOC 202012/01 infection from 26 December 2020 to 26 February 2021. Maximum likelihood estimation was used to estimate R, accounting for right censoring during real-time estimation. In the baseline scenario, R was estimated at 2.11 (95% confidence interval: 1.63, 2.94). By 26 February 2021, an average of nine generations had elapsed since the first imported case. If the generation time of VOC 202012/01 was assumed to be longer, R was increased, consistent with estimates of R from case data. The estimated R of VOC 202012/01 in Japan exceeded 1 on 26 February 2021, suggesting that domestic transmission events caused a major epidemic. Moreover, because our estimate of R was dependent on generation time and ascertainment biases, continuous monitoring of contact tracing data is crucial to decipher the mechanisms of increased VOC 202012/01 transmissibility.

In Japan, a prioritized COVID-19 vaccination program using Pfizer/BioNTech messenger RNA (mRNA) vaccine among healthcare workers commenced on February 17, 2021. As vaccination coverage increases, clusters in healthcare and elderly care facilities including hospitals and nursing homes are expected to be reduced. The present study aimed to explicitly estimate the protective effect of vaccination in reducing cluster incidence in those facilities. A mathematical model was formulated using three pieces of information: (1) the incidence of clusters in facilities from October 26, 2020 to June 27, 2021; (2) the incidence of confirmed COVID-19 cases during the same period; and (3) vaccine doses among healthcare workers from February 17 to June 27, 2021, extracted from the national Vaccination System database. We found that the estimated proportion at risk in healthcare and elderly care facilities declined substantially as the vaccination coverage among healthcare workers increased; the greater risk reduction was observed in healthcare facilities, at 0.10 (95% confidence interval (CI): 0.04–0.16) times that in the pre-vaccination period, while that in elderly care facilities was 0.34 (95% CI: 0.24–0.43) times that in the earlier period. The averted numbers of clusters in healthcare facilities and elderly care facilities were estimated to be 247 (95% CI: 210–301) and 279 (95% CI: 218–354), respectively. Prioritized vaccination among healthcare workers had a marked impact on preventing the incidence of clusters in facilities.

Objectives: The effective reproduction number (Rt) has been critical for assessing the effectiveness of countermeasures during the coronavirus disease 2019 (COVID-19) pandemic. Conventional methods using reported incidences are unable to provide timely Rt data due to the delay from infection to reporting. Our study aimed to develop a framework for predicting Rt in real time, using timely accessible data — i.e. human mobility, temperature, and risk awareness. Methods: A linear regression model to predict Rt was designed and embedded in the renewal process. Four prefectures of Japan with high incidences in the first wave were selected for model fitting and validation. Predictive performance was assessed by comparing the observed and predicted incidences using cross-validation, and by testing on a separate dataset in two other prefectures with distinct geographical settings from the four studied prefectures. Results: The predicted mean values of Rt and 95% uncertainty intervals followed the overall trends for incidence, while predictive performance was diminished when Rt changed abruptly, potentially due to superspreading events or when stringent countermeasures were implemented. Conclusions: The described model can potentially be used for monitoring the transmission dynamics of COVID-19 ahead of the formal estimates, subject to delay, providing essential information for timely planning and assessment of countermeasures.

Severe acute respiratory coronavirus 2 (SARS-CoV-2) infections have been associated with substantial presymptomatic transmission, which occurs when the generation interval—the time between infection of an individual with a pathogen and transmission of the pathogen to another individual—is shorter than the incubation period—the time between infection and symptom onset. We collected a dataset of 257 SARS-CoV-2 transmission pairs in Japan during 2020 and jointly estimated the mean incubation period of infectors (4.8 days, 95 % CrI: 4.4–5.1 days), mean generation interval to when they infect others (4.3 days, 95 % credible interval [CrI]: 4.0–4.7 days), and the correlation (Kendall’s tau: 0.5, 95 % CrI: 0.4–0.6) between these two epidemiological parameters. Our finding of a positive correlation and mean generation interval shorter than the mean infector incubation period indicates ample infectiousness before symptom onset and suggests that reliance on isolation of symptomatic COVID-19 cases as a focal point of control efforts is insufficient to address the challenges posed by SARS-CoV-2 transmission dynamics.

The Tokyo 2020 Olympic and Paralympic Games represent the most diverse international mass gathering event held since the start of the coronavirus disease 2019 (COVID-19) pandemic. Postponed to summer 2021, the rescheduled Games were set to be held amidst what would become the highest-ever levels of COVID-19 transmission in the host city of Tokyo. At the same time, the Delta variant of concern was gaining traction as the dominant viral strain and Japan had yet to exceed fifteen percent of its population fully vaccinated against COVID-19. To quantify the potential number of secondary cases that might arise during the Olympic Games, we performed a scenario analysis using a multitype branching process model. We considered the different contributions to transmission of Games accredited individuals, the general Tokyo population, and domestic spectators. In doing so, we demonstrate how transmission might evolve in these different groups over time, cautioning against any loosening of infection prevention protocols and supporting the decision to ban all spectators. If prevention measures were well observed, we estimated that the number of new cases among Games accredited individuals would approach zero by the end of the Games. However, if transmission was not controlled our model indicated hundreds of Games accredited individuals would become infected and daily incidence in Tokyo would reach upwards of 4,000 cases. Had domestic spectators been allowed (at 50% venue capacity), we estimated that over 250 spectators might have arrived infected to Tokyo venues, potentially generating more than 300 additional secondary infections while in Tokyo/at the Games. We also found the number of cases with infection directly attributable to hypothetical exposure during the Games was highly sensitive to the local epidemic dynamics. Therefore, reducing and maintaining transmission levels below epidemic levels using public health measures would be necessary to prevent cross-group transmission.

To deal with the risk of emerging diseases with many unknowns, close and timely collaboration and communication between science experts and policymakers are crucial to developing and implementing an effective science-based intervention strategy. The Expert Meeting, an ad hoc medical advisory body, was established in February 2020 to advise Japan’s COVID-19 Response Headquarters. The group played an important role in the policymaking process, promoting timely situation awareness and developing science-based proposals on interventions that were promptly reflected in government actions. However, this expert group may have been overly proactive in taking on the government’s role in crisis management. For the next stage of managing the coronavirus disease pandemic and future pandemics, the respective roles of the government and its advisory bodies need to be clearly defined. Leadership and strategic risk communication by the government are key.

Abstract Background Surgical site infections (SSI) are the most common healthcare-associated infection, and gastrointestinal surgery is frequently followed by a high incidence of SSI. Epidemiological analysis of the temporal trends in SSI following gastrointestinal surgery has yet to be performed in Japan. Our purpose was to descriptively investigate these trends. Methods Extracting national surveillance data from the Japan Nosocomial Infections Surveillance (JANIS) system, we analyzed the frequency of SSI events following gastrointestinal surgery, which consisted of seven surgical procedures, from 2012–2017. We calculated the standardized infection ratio to compute risk-adjusted SSI frequency, and used the trend test to detect time-dependent changes. Results The frequency of SSI events, except for those associated with surgery of the upper gastrointestinal tract, revealed a decreasing time-dependent trend. The use of laparoscopic surgery increased dramatically over time (p

Summary: Background: In Japan, vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was initiated on 17 February 2021, mainly using messenger RNA vaccines and prioritizing health care professionals. Whereas nationwide vaccination alleviated the coronavirus disease 2019 (COVID-19)-related burden, the population impact has yet to be quantified in Japan. We aimed to estimate the numbers of COVID-19 cases and deaths prevented that were attributable to the reduced risk among vaccinated individuals via a statistical modeling framework. Methods: We analyzed confirmed cases registered in the Health Center Real-time Information-sharing System on COVID-19 (3 March–30 November 2021) and publicly reported COVID-19-related deaths (24 March–30 November 2021). The vaccination coverage over this time course, classified by age and sex, was extracted from vaccine registration systems. The total numbers of prevented cases and deaths were calculated by multiplying the daily risk differences between unvaccinated and vaccinated individuals by the population size of vaccinated individuals. Findings: For both cases and deaths, the averted numbers were estimated to be the highest among individuals aged 65 years and older. In total, we estimated that 564,596 (95% confidence interval: 477,020–657,525) COVID-19 cases and 18,622 (95% confidence interval: 6522–33,762) deaths associated with SARS-CoV-2 infection were prevented owing to vaccination during the analysis period (i.e., fifth epidemic wave, caused mainly by the Delta variant). Female individuals were more likely to be protected from infection following vaccination than male individuals whereas more deaths were prevented in male than in female individuals. Interpretation: The vaccination program in Japan led to substantial reductions in the numbers of COVID-19 cases and deaths (33% and 67%, respectively). The preventive effect will be further amplified during future pandemic waves caused by variants with shared antigenicity. Funding: This project was supported by the Japan Science and Technology Agency; the Japan Agency for Medical Research and Development; the Japan Society for the Promotion of Science; and the Ministry of Health, Labour and Welfare.