Regional variations in HIV diagnosis in Japan before and during the COVID-19 pandemic.

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.

Vaccine-induced reduction of COVID-19 clusters in school settings in Japan during the epidemic wave caused by B.1.1.529 (Omicron) BA.2, 2022.

Clusters of COVID-19 in high-risk settings, such as schools, have been deemed a critical driving force of the major epidemic waves at the societal level. In Japan, the vaccination coverage among students remained low up to early 2022, especially for 5-11-year-olds. The vaccination of the student population only started in February 2022. Given this background and considering that vaccine effectiveness against school transmission has not been intensively studied, this paper proposes a mathematical model that links the occurrence of clustering to the case count among populations aged 0-19, 20-59, and 60+ years of age. We first estimated the protected (immune) fraction of each age group either by infection or vaccination and then linked the case count in each age group to the number of clusters via a time series regression model that accounts for the time-varying hazard of clustering per infector. From January 3 to May 30, 2022, there were 4,722 reported clusters in school settings. Our model suggests that the immunity offered by vaccination averted 226 (95% credible interval: 219-232) school clusters. Counterfactual scenarios assuming elevated vaccination coverage with faster roll-out reveal that additional school clusters could have been averted. Our study indicates that even relatively low vaccination coverage among students could substantially lower the risk of clustering through vaccine-induced immunity. Our results also suggest that antigenically updated vaccines that are more effective against the variant responsible for the ongoing epidemic may greatly help decrease not only the incidence but also the unnecessary loss of learning opportunities among school-age students.

Epidemiological impact of revoking mask-wearing recommendation on COVID-19 transmission in Tokyo, Japan.

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.

Assessing exit screening of SARS-CoV-2 in Japan: an analysis of the airport screening data of passengers from the United Kingdom, 2020-2022.

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.

Science-based exit from stringent countermeasures against COVID-19: Mortality prediction using immune landscape between 2021 and 2022 in Japan.

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.

Reconstructing the age-structured case count of COVID-19 from sentinel surveillance data in Japan: A modeling study.

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.

HIV incidence before and during the COVID-19 pandemic in Japan.

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.

Evaluation of the exit screening policy among travelers arriving from Asian and pacific nations.

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.

Identifying the population susceptible to rubella in Japan, 2020: Fine-scale risk mapping.

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.

Estimating the effective reproduction number of COVID-19 from population-wide wastewater data: An application in Kagawa, Japan.

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.

Decomposing mechanisms of COVID-19 mortality in empirical datasets: A modeling study.

Our objective was to decompose mortality mechanisms during the coronavirus disease 2019 (COVID-19) pandemic to estimate direct, indirect, and associated deaths from COVID-19. Given the confirmatory diagnosis of COVID-19, a death event that was not necessarily caused by respiratory complications but stemmed from other complications was categorized as an indirect death from COVID-19. Associated deaths occurred in patients who did not have COVID-19 but died during the surge in COVID-19 cases when overwhelming pressure was exerted on the healthcare system. Analyzing the sixth wave (i.e., the first epidemic wave of the Omicron B.1.1.529 variant from January to May 2022), decomposition was achieved using the binomial and Poisson sampling process models fitted to two pieces of data (i.e., COVID-19 death certificate and excess data by major cause of death). The total numbers of direct, indirect, and associated deaths during the sixth wave in Osaka were estimated at 1,071; 948; and 2,157; respectively. The number of associated deaths was greater than the sum of direct and indirect deaths. We further observed that the composition of indirect and associated deaths differed by major cause of death, and deaths caused by circulatory disease included a greater proportion of indirect deaths compared with deaths by other causes. The goals of healthcare services for endemic COVID-19 include the sustainable provision of services to avoid preventable deaths. Therefore, gaining an in-depth understanding of mechanisms that lead to excess death is vital for improving future pandemic response efforts.

Public holidays increased the transmission of COVID-19 in Japan, 2020-2021: a mathematical modelling study.

OBJECTIVES: Although the role of specific holidays in modifying transmission dynamics of infectious diseases has received some research attention, the epidemiological impact of public holidays on the transmission of coronavirus disease 2019 (COVID-19) remains unclear. METHODS: To assess the extent of increased transmission frequency during public holidays, we collected COVID-19 incidence and mobility data in Hokkaido, Tokyo, Aichi, and Osaka from February 15, 2020 to September 30, 2021. Models linking the estimated effective reproduction number (Rt) with raw or adjusted mobility, public holidays, and the state of emergency declaration were developed. The best-fit model included public holidays as an essential input variable, and was used to calculate counterfactuals of Rt in the absence of holidays. RESULTS: During public holidays, on average, Rt increased by 5.71%, 3.19%, 4.84%, and 24.82% in Hokkaido, Tokyo, Aichi, and Osaka, respectively, resulting in a total increase of 580 (95% confidence interval [CI], 213 to 954), 2,209 (95% CI, 1,230 to 3,201), 1,086 (95% CI, 478 to 1,686), and 5,211 (95% CI, 4,554 to 5,867) cases that were attributable to the impact of public holidays. CONCLUSIONS: Public holidays intensified the transmission of COVID-19, highlighting the importance of considering public holidays in designing appropriate public health and social measures in the future.

Reconstructing the COVID-19 incidence in India using airport screening data in Japan.

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.

Reconstruction and analysis of the transmission network of African swine fever in People's Republic of China, August 2018-September 2019.

Introduction of African swine fever (ASF) to China in mid-2018 and the subsequent transboundary spread across Asia devastated regional swine production, affecting live pig and pork product-related markets worldwide. To explore the spatiotemporal spread of ASF in China, we reconstructed possible ASF transmission networks using nearest neighbour, exponential function, equal probability, and spatiotemporal case-distribution algorithms. From these networks, we estimated the reproduction numbers, serial intervals, and transmission distances of the outbreak. The mean serial interval between paired units was around 29 days for all algorithms, while the mean transmission distance ranged 332 -456 km. The reproduction numbers for each algorithm peaked during the first two weeks and steadily declined through the end of 2018 before hovering around the epidemic threshold value of 1 with sporadic increases during 2019. These results suggest that 1) swine husbandry practices and production systems that lend themselves to long-range transmission drove ASF spread; 2) outbreaks went undetected by the surveillance system. Efforts by China and other affected countries to control ASF within their jurisdictions may be aided by the reconstructed spatiotemporal model. Continued support for strict implementation of biosecurity standards and improvements to ASF surveillance is essential for halting transmission in China and spread across Asia.

Survey of exposure to stranded dolphins in Japan to investigate an outbreak of suspected infection with highly pathogenic avian influenza (H5N1) clade 2.3.4.4(b) in humans.

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.

Life-expectancy changes from 2019 to 22: A case study of Japan using provisional death count.

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.

Epidemiological impact of travel enhancement on the inter-prefectural importation dynamics of COVID-19 in Japan, 2020.

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.

Habitual Mask Wearing as Part of COVID-19 Control in Japan: An Assessment Using the Self-Report Habit Index.

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.

Assessing the COVID-19 vaccination program during the Omicron variant (B.1.1.529) epidemic in early 2022, Tokyo.

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.

Evaluating the COVID-19 vaccination program in Japan, 2021 using the counterfactual reproduction number.

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.