Estimating global changes in routine childhood vaccination coverage during the COVID-19 pandemic, 2020-2021.

OBJECTIVES: The COVID-19 pandemic has disrupted the distribution of routine immunizations globally. Multi-country studies assessing a wide spectrum of vaccines and their coverage rates are needed to determine global performance in achieving vaccination goals. METHODS: Global vaccine coverage data for 16 antigens were obtained from WHO/UNICEF Estimates of National Immunization Coverage. Tobit regression was performed for all country-antigen pairs for which data were continuously available between 2015-2020 or 2015-2021 to predict vaccine coverage in 2020/2021. Vaccines for which multi-dose data were available were assessed to determine whether vaccine coverage for subsequent doses were lower than that of first doses. RESULTS: Vaccine coverage was significantly lower-than-predicted for 13/16 antigens in 2020 and all assessed antigens in 2021. Lower-than-predicted vaccine coverage was typically observed in South America, Africa, Eastern Europe, and Southeast Asia. There was a statistically significant coverage drop for subsequent doses of the diphtheria-tetanus-pertussis, pneumococcus, and rotavirus vaccines compared to first doses in 2020 and 2021. CONCLUSION: The COVID-19 pandemic exerted larger disruptions to routine vaccination services in 2021 than in 2020. Global efforts will be needed to recoup vaccine coverage losses sustained during the pandemic and broaden vaccine access in areas where coverage was previously inadequate.

Changes in cerebrovascular disease-related deaths and their location during the COVID-19 pandemic in Japan

Objective The COVID-19 pandemic placed an enormous strain on healthcare systems and raised concerns for delays in the management of patients with acute cerebrovascular events. In this study, we investigated cerebrovascular excess deaths in Japan. Study design Vital mortality statistics from January 2012 to May 2022 were obtained from the Japanese Ministry of Health, Labour and Welfare. Methods Using quasi-Poisson regression models, we estimated the expected weekly number of cerebrovascular deaths in Japan from January 2020 through May 2022 by place of death. Estimates were calculated for deaths in all locations, as well as for deaths in hospitals, in geriatric health service facilities, and at home. The age subgroups of ≥75 and <75 years were also considered. Weeks with a statistically significant excess of cerebrovascular deaths were determined when the weekly number of observed deaths exceeded the upper bound of 97.5% prediction interval. Results Excess deaths were noted in June 2021 and became more pronounced from February 2022 onwards. The trend was notable among those aged ≥75 years and for those who died in hospitals. With respect to the location of deaths, the excess was significant in geriatric health services facilities from April 2020 to June 2021, while no evidence of excess hospital deaths was observed during the same period. Conclusions Beginning in late 2021, excess cerebrovascular deaths coincided with the spread of the Omicron variant and may be associated with increased healthcare burden. In 2020, COVID-19 altered the geography of cerebrovascular deaths, with fewer people dying in hospitals and more dying in geriatric health service facilities and at home.

Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo.

BACKGROUND: On April 7, 2020, the Japanese government declared a state of emergency regarding the novel coronavirus (COVID-19). Given the nation-wide spread of the coronavirus in major Japanese cities and the rapid increase in the number of cases with untraceable infection routes, large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan is urgently required. METHODS: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And AN care seeking) was developed to surveil the Japanese epidemiological situation in real-time. COOPERA asked questions regarding personal information, location, preventive actions, COVID-19 related symptoms and their residence. Empirical Bayes estimates of the age-sex-standardized incidence rate and disease mapping approach using scan statistics were utilized to identify the geographical distribution of the symptoms in Tokyo and their spatial correlation r with the identified COVID-19 cases. FINDINGS: We analyzed 353,010 participants from Tokyo recruited from 27th March to 6th April 2020. The mean (SD) age of participants was 42.7 (12.3), and 63.4%, 36.4% or 0.2% were female, male, or others, respectively. 95.6% of participants had no subjective symptoms. We identified several geographical clusters with high spatial correlation (r = 0.9), especially in downtown areas in central Tokyo such as Shibuya and Shinjuku. INTERPRETATION: With the global spread of COVID-19, medical resources are being depleted. A new system to monitor the epidemiological situation, COOPERA, can provide insights to assist political decision to tackle the epidemic. In addition, given that Japan has not had a strong lockdown policy to weaken the spread of the infection, our result would be useful for preparing for the second wave in other countries during the next flu season without a strong lockdown. FUNDING: The present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009).

Recent changes in the reporting of STIs in Japan during the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has had variable effects on the rates of STIs reported across the globe. This study sought to assess how the number of STI reports changed during the pandemic in Japan. METHODS: We used national infectious disease surveillance data from the National Institute of Infectious Diseases (Tokyo, Japan) for the period between January 2013 and December 2021. We compared reported rates of chlamydia, gonorrhoea, condyloma acuminata and genital herpes, as well as total notifications for HIV/AIDS and syphilis during the pandemic versus previous years in Japan. We used a quasi-Poisson regression to determine whether any given week or month between January 2018 and December 2021 had a significant excess or deficit of STIs. Notification values above or below the 95% upper and lower prediction thresholds were considered as statistically significant. The start of the pandemic was defined as January 2020. RESULTS: Chlamydia generally remained within predicted range during the pandemic period. Reporting of gonorrhoea was significantly higher than expected throughout early-to-mid 2021 but otherwise generally remained within predicted range prior to 2021. Condyloma, herpes and HIV/AIDS reporting were transiently significantly lower than expected throughout the pandemic period, but no significant periods of higher-than-expected reporting were detected. Syphilis showed widespread evidence of significantly lower-than-predicted reporting throughout 2020 but eventually reversed, showing significantly higher-than-predicted reporting in mid-to-late 2021. CONCLUSIONS: The COVID-19 pandemic was associated with variable changes in the reporting of STIs in Japan. Higher-than-predicted reporting was more likely to be observed in the later phases of the pandemic. These changes may have been attributable to pandemic-related changes in sexual behaviour and decreased STI clinic attendance and testing, but further research on the long-term impact of the pandemic on STIs is necessary.

Inter-prefectural Travel and Network Connectedness During the COVID-19 Pandemic in Japan.

BACKGROUND: Increases in human mobility have been linked to rises in novel coronavirus disease 2019 (COVID-19) transmission. The pandemic era in Japan has been characterized by changes in inter-prefectural mobility across state of emergency (SOE) declarations and travel campaigns, but they have yet to be characterized. METHODS: Using Yahoo Japan mobility data extracted from the smartphones of more than 10 million Japanese residents, we calculated the monthly number of inter-prefectural travel instances, stratified by residential prefecture and destination prefecture. We then used this adjacency matrix to calculate two network connectedness metrics, closeness centrality and effective distance, that reliably predict disease transmission. RESULTS: Inter-prefectural mobility and network connectedness decreased most considerably during the first SOE, but this decrease dampened with each successive SOE. Mobility and network connectedness increased during the Go To Travel campaign. Travel volume between distant prefectures decreased more than travel between prefectures with geographic proximity. Closeness centrality was found to be negatively correlated with the rate of COVID-19 infection across prefectures, with the strength of this association increasing in tandem with the infection rate. Changes in effective distance were more visible among geographically isolated prefectures (Hokkaido and Okinawa) than among metropolitan, central prefectures (Tokyo, Aichi, Osaka, and Fukuoka). CONCLUSION: The magnitude of reductions in human mobility decreased with each subsequent state of emergency, consistent with pandemic fatigue. The association between network connectedness and rates of COVID-19 infection remained visible throughout the entirety of the pandemic period, suggesting that inter-prefectural mobility may have contributed to disease spread.

Effect of the Tokyo 2020 Summer Olympic Games on COVID-19 incidence in Japan: a synthetic control approach.

BACKGROUND: The Tokyo 2020 Summer Olympic Games (23 July-8 August 2021) were held in the middle of Japan's fifth wave of COVID-19, when the number of cases was on the rise, and coincided with the fourth state of emergency implemented by the host city, Tokyo. AIM: This study aimed to assess whether the hosting of the Games was associated with a change in the number of COVID-19 cases in Japan using a synthetic control method. METHODS: A weighted average of control countries with a variety of predictors was used to estimate the counterfactual trajectory of daily COVID-19 cases per 1 000 000 population in the absence of the Games in Japan. Outcome and predictor data were extracted using official and open sources spanning several countries. The predictors comprise the most recent country-level annual or daily data accessible during the Games, including the stringency of the government's COVID-19 response, testing capacity and vaccination capacity; human mobility index; electoral democracy index and demographic, socioeconomic, health and weather information. After excluding countries with missing data, 42 countries were ultimately used as control countries. RESULTS: The number of observed cases per 1 000 000 population on the last day of the Games was 109.2 (7-day average), which was 115.7% higher than the counterfactual trajectory comprising 51.0 confirmed cases per 1 000 000 population. During the Olympic period (since 23 July), the observed cumulative number of cases was 61.0% higher than the counterfactual trajectory, comprising 143 072 and 89 210 confirmed cases (p=0.023), respectively. The counterfactual trajectory lagged 10 days behind the observed trends. CONCLUSIONS: Given the increasing likelihood that new emerging infectious diseases will be reported in the future, we believe that the results of this study should serve as a sentinel warning for upcoming mega-events during COVID-19 and future pandemics.

Excess deaths from non-COVID-19-related causes in Japan and 47 prefectures from January 2020 through May 2021 by place of death.

Excess deaths, including all-causes mortality, were confirmed for the first time in Japan in April 2021. However, little is known about the indirect effects of COVID-19 on the number of non-COVID-19-related deaths. We then estimated the excess deaths from non-COVID-19-related causes in Japan and its 47 prefectures from January 2020 through May 2021 by place of death. Vital statistical data on deaths were obtained from the Ministry of Health, Labour and Welfare. Using quasi-Poisson regression models, we estimated the expected weekly number of deaths due to all-causes excluding COVID-19 (non-COVID-19) and due to respiratory disease, circulatory disease, malignant neoplasms, and senility. Estimates were made separately for deaths in all locations, as well as for deaths in hospitals and clinics, in nursing homes and elderly care facilities, and at home. We defined a week with excess deaths as one in which the observed number of deaths exceeded the upper bound of the two-sided 95% prediction interval. Excess death was expressed as a range of differences between the observed and expected number of deaths and the 95% upper bound of the two-sided predictive interval. The excess percentage was calculated as the number of excess deaths divided by the expected number of deaths. At the national level, excess deaths from non-COVID-19-related all-causes were observed during April 19 to May 16, 2021. The largest excess percentage was 2.73-8.58% (excess deaths 689-2161) in the week of May 3-9. Similar trends were observed for all four cause categories. The cause-of-death categories which contributed to the excesses showed heterogeneity among prefectures. When stratified by place of death, excess mortality tended to be observed in nursing homes and elderly care facilities for all categories, in hospitals and clinics for circulatory disease, and at home for respiratory disease, malignant neoplasms, and senility. A caution is necessary that for the lastest three months (March-May 2021), adjusted data were used to account for possible reporting delays.

Changes in Health Care Access during the COVID-19 Pandemic: Estimates of National Japanese Data, June 2020-October 2021.

The COVID-19 pandemic has disrupted health care access around the world, both for inpatients and outpatients. We applied a quasi-Poisson regression to national, monthly data on the number of outpatients, number of inpatients, length of average hospital stay, and the number of new hospitalizations from March 2015 to October 2021 to assess how these outcomes changed between June 2020 to October 2021. The number of outpatient visits were lower-than-predicted during the early phases of the pandemic but normalized by the fall of 2021. The number of inpatients and new hospitalizations were lower-than-predicted throughout the pandemic, and deficits in reporting continued to be observed in late 2021. The length of hospital stays was within the predicted range for all beds, but when stratified by bed type, was higher than predicted for psychiatric beds, lower-than-predicted for tuberculosis beds, and showed variable changes in long-term care insurance beds. Health care access in Japan was impacted by the COVID-19 pandemic.

Changes in Health Care Access during the COVID-19 Pandemic: Estimates of National Japanese Data, June 2020–October 2021

The COVID-19 pandemic has disrupted health care access around the world, both for inpatients and outpatients. We applied a quasi-Poisson regression to national, monthly data on the number of outpatients, number of inpatients, length of average hospital stay, and the number of new hospitalizations from March 2015 to October 2021 to assess how these outcomes changed between June 2020 to October 2021. The number of outpatient visits were lower-than-predicted during the early phases of the pandemic but normalized by the fall of 2021. The number of inpatients and new hospitalizations were lower-than-predicted throughout the pandemic, and deficits in reporting continued to be observed in late 2021. The length of hospital stays was within the predicted range for all beds, but when stratified by bed type, was higher than predicted for psychiatric beds, lower-than-predicted for tuberculosis beds, and showed variable changes in long-term care insurance beds. Health care access in Japan was impacted by the COVID-19 pandemic.

Distributed lag interrupted time series model for unclear intervention timing: effect of a statement of emergency during COVID-19 pandemic.

BACKGROUND: Interrupted time series (ITS) analysis has become a popular design to evaluate the effects of health interventions. However, the most common formulation for ITS, the linear segmented regression, is not always adequate, especially when the timing of the intervention is unclear. In this study, we propose a new model to overcome this limitation. METHODS: We propose a new ITS model, ARIMAITS-DL, that combines (1) the Autoregressive Integrated Moving Average (ARIMA) model and (2) distributed lag functional terms. The ARIMA technique allows us to model autocorrelation, which is frequently observed in time series data, and the decaying cumulative effect of the intervention. By contrast, the distributed lag functional terms represent the idea that the intervention effect does not start at a fixed time point but is distributed over a certain interval (thus, the intervention timing seems unclear). We discuss how to select the distribution of the effect, the model construction process, diagnosing the model fitting, and interpreting the results. Further, our model is implemented as an example of a statement of emergency (SoE) during the coronavirus disease 2019 pandemic in Japan. RESULTS: We illustrate the ARIMAITS-DL model with some practical distributed lag terms to examine the effect of the SoE on human mobility in Japan. We confirm that the SoE was successful in reducing the movement of people (15.0-16.0% reduction in Tokyo), at least between February 20 and May 19, 2020. We also provide the R code for other researchers to easily replicate our method. CONCLUSIONS: Our model, ARIMAITS-DL, is a useful tool as it can account for the unclear intervention timing and distributed lag effect with autocorrelation and allows for flexible modeling of different types of impacts such as uniformly or normally distributed impact over time.

Characterising reasons for reversals of COVID-19 vaccination hesitancy among Japanese people: One-year follow-up survey.

Background: Vaccine hesitancy is a global public health threat. We present unique data that characterises those who experienced reversals of COVID-19 vaccination hesitancy in Japan. Methods: We administered a questionnaire on vaccination intention among 30053 Japanese adults aged 20 years or older before the COVID-19 vaccination was available to the general population (first survey) and conducted a follow-up survey on vaccination status one year later in February 2022 (second survey). Those who responded in the first survey that they did not intend to be vaccinated or were unsure and then responded in the second survey that they were vaccinated or intend to be vaccinated were asked about the reasons for their change of heart. Based on previous literature and expert opinion, 31 reasons for changing vaccination intention were compiled and respondents were asked to choose which among them applied to themselves, with multiple responses possible. Based on the results of those responses, each individual was then clustered using the Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction technique and Ordering Points To Identify the Clustering Structure (OPTICS) algorithm. We then identified unique characteristics among each of the sub-populations (clusters). Findings: In the second survey we received 19195 responses (response rate 63.9%), of which 8077 responded 'no' or 'not sure' in the first survey regarding their intention to be vaccinated. Of these, 5861 responded having received or intending to receive the vaccine (72.6%). We detected six and five sub-populations (clusters) among the 'no' group and 'not sure' group, respectively. The clusters were characterized by perceived benefits of vaccination, including the COVID-19 vaccine, awareness of the COVID-19 vaccination status of those close to them, recognition of the social significance of COVID-19 vaccination for the spread of infection, and dispelled concerns about short-term adverse reactions and the safety of the COVID-19 vaccine. Work and personal relationship reasons were also found to be a unique overarching reason for vaccination changes of heart only among those who did not intend to vaccinate. Interpretation: Those who changed their intention to accept COVID-19 vaccination as well as their unique characteristics as detailed in this study will be important entry points when discussing how to promote vaccination to those who are hesitant to vaccinate in the future. Funding: The present work was supported in part by a grant from the Kanagawa Prefectural Government of Japan and by AIST government subsidies.

Factors associated with reversals of COVID-19 vaccination willingness: Results from two longitudinal, national surveys in Japan 2021-2022.

Background: Research characterizing changes of heart with respect to vaccine intention is scarce, and very little research considers those who were initially vaccine willing but became hesitant. Here, we sought to assess the factors related to reversals of vaccine willingness. Methods: We conducted a longitudinal, national survey on vaccination intention among Japanese adults aged 20 years or older, with the first questionnaire performed in February-March 2021 (N = 30,053) and the follow-up in February 2022 (N = 19,195, response rate 63.9%). The study population comprised those who reported vaccine willingness in the first survey, with the outcome variable being development of vaccine hesitancy at follow-up. We performed a regression analysis of vaccination status using sociodemographic, health-related, psychologic/attitudinal, and information-related variables as predictors. We used the sparse group minimax concave penalty (MCP) to select the optimum group of covariates for the logistic regression. Findings: Of 11,118 (57.9%) respondents who previously expressed interest in vaccination, 10,684 (96.1%) and 434 (3.9%) were in the vaccine willing and hesitant groups, respectively. Several covariates were found to significantly predict vaccine hesitancy, including marital status, influenza vaccine history, COVID-19 infection/testing history, engagement in COVID-19 preventive measures, perceived risks/benefits of the COVID-19 vaccine, and attitudes regarding vaccination policies and norms. The use of certain information sources was also associated with vaccine hesitancy. Interpretation: Sociodemographic, health-related, psychologic/attitudinal, and information-related variables predicted the development of vaccine hesitancy among those with prior willingness. Most of these predictors were also associated with vaccination status. Funding: The present work was supported in part by a grant from the Kanagawa Prefectural Government of Japan and by AIST government subsidies.

Pre- and post-COVID-19 all-cause mortality of Japanese citizens versus foreign residents living in Japan, 2015-2021.

Immigrants in Japan face multiple health care challenges. There is limited research addressing how all-cause mortality differs between foreign residents and Japanese citizens, including the impact of the COVID-19 pandemic. We assessed whether all-cause mortality rates between Japanese citizens and foreign residents living in Japan differ, and whether these differentials changed after the start of the COVID-19 pandemic. We conducted a cross-sectional analysis using vital statistical data of all deaths among citizens and foreign residents that occurred within Japanese borders aggregated every 6 months between January 1, 2015 and June 30, 2021. Data were used to calculate sex-, region-, and 20-year age group-specific standardized mortality rates using the direct method based on the population distribution of Japanese citizens in 2021 by sex, region, and 20-year age groups. Chi-squared tests and linear regression were used to assess whether the pandemic was associated with changes in mortality rates among groups and changes in the mortality differentials between citizens and non-citizens, respectively. All-cause mortality increased monotonically with age for men and women. Men had higher mortality than women, regardless of age or nationality. All-cause mortality is lower among immigrants than Japanese citizens between the ages of 20-59, but higher under the age of 20 and over the age of 59. The pandemic was associated with significant changes in mortality in most groups, but no statistically significant changes in the mortality differentials between immigrants and Japanese citizens were detected. Young immigrants are generally healthier than their Japanese counterparts, in line with the healthy migrant hypothesis. Younger migrants are at higher risk of mortality, possibly due to increased vulnerability to psychologic stress. Older migrant mortality converged with citizen mortality, consistent with acculturation that occurs with longer duration of residence. The pandemic did not exacerbate health inequities for foreign residents with respect to mortality.

Changes in marriage, divorce and births during the COVID-19 pandemic in Japan.

INTRODUCTION: Marriage, divorce and fertility are declining in Japan. There is concern that the COVID-19 pandemic may have accelerated the decrease in marriages and births while increasing the number of divorces. Changes in partnership behaviours and fertility have significant implications for mental health, well-being and population demographics. METHODS: Japanese vital statistical data were collected for December 2011-May 2021. We used the Farrington algorithm on the daily numbers of marriages, divorces and births (per month) in order to determine whether any given month between January 2017 and May 2021 had a significant excess or deficit. Analyses were conducted at the national and regional levels. RESULTS: During the pandemic, significant deficits in the national number of marriages were noted in January 2020, April 2020, May 2020, July 2020, September 2020 and April 2021. Regional marriage patterns reflected national trends. Divorces were noted to be in deficit during April 2020, May 2020 and May 2021 at the country level. Regional analyses mirrored national divorce trends with the exception of Shikoku, which showed no deficits during the pandemic. Significant deficits in the number of total births were noted in December 2020, January 2021 and February 2021. Regionally, birth deficits were concentrated in Chubu, Kansai and Kanto. After the start of the pandemic, no significant excesses in marriages, divorces or births were noted at the national or regional level. CONCLUSIONS: Marriages and divorces declined during the pandemic in Japan, especially during state of emergency declarations. There were decreased births between December 2020 and February 2021, approximately 8-10 months after the first state of emergency, suggesting that couples altered their pregnancy intention in response to the pandemic. Metropolitan regions were more affected by the pandemic than their less metropolitan counterparts.

Factors associated with the risk perception of COVID-19 infection and severe illness: A cross-sectional study in Japan.

Understanding COVID-19 risk perception may help inform public health messaging aimed at encouraging preventive measures and improving countermeasures against the pandemic. We conducted an online survey of 29,708 Japanese adults in February 2021 and estimated the associations between COVID-19 risk perception and a broad array of individual factors. Two logistic regressions were constructed to estimate factors associated with the risk perception of COVID-19 (defined as responding that one might become infected within the next 6 months), and of severe illness among those who responded that they might become infected (defined as responding that one would become severely ill). After adjusting for covariates, those with a higher perceived risk of the COVID-19 vaccine had higher odds of risk perception for both infection and severe illness. Interestingly, those with higher odds of risk perception of being infected were more likely to report obtaining their information from healthcare workers whereas those with lower odds were more likely to report obtaining their information from the Internet or the government; those with lower odds of risk perception of being severely ill were more likely to report obtaining their information from the Internet. The higher the trust level in the government as a COVID-19 information source, the lower the odds of both risk perception of being infected and becoming severely ill. The higher the trust levels in social networking services as a COVID-19 information source, the higher the odds of risk perception of becoming severely ill. Public health messaging should address the factors identified in our study.

Identification of optimum combinations of media channels for approaching COVID-19 vaccine unsure and unwilling groups in Japan.

BACKGROUND: Optimizing media campaigns for those who were unsure or unwilling to take coronavirus disease (COVID-19) vaccines is required urgently to effectively present public health messages aimed at increasing vaccination coverage. We propose a novel framework for selecting tailor-made media channels and their combinations for this task. METHODS: An online survey was conducted in Japan during February to March, 2021, with 30,053 participants. In addition to their sociodemographic characteristics, it asked the attitude toward vaccination and information sources (i.e., media channels) for COVID-19 issues. Multinomial logic regression was fitted to estimate the combinations of the media channels and their odds ratio (OR) associated with vaccination attitudes. FINDINGS: The proportion of respondents who were unsure or unwilling to take the vaccination was skewed toward younger generation: 58.1% were aged under 35, while 28.1% were 65 years or older. Media channels such as "Non-medical and Non-TV" and "Non-medical and Non-government" were associated with the unsure group: OR (95% Confidence intervals, (CI)) = 1.75 (1.62, 1.89) and 1.53 (1.44, 1.62), respectively. In addition, media channels such as "Newspapers or the Novel Coronavirus Expert Meeting", "Medical or Local government", and "Non-TV" were associated with the unwilling group: OR (95% CI) were 2.00 (1.47, 2.75), 3.13 (2.58, 3.81), and 2.25 (1.84, 2.77), respectively. INTERPRETATION: To effectively approach COVID-19 vaccine unsure and unwilling groups, generation-specific online and offline media campaigns should be optimized to the type of vaccine attitude. FUNDING: Funded by the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009) and the Japan Agency for Medical Research and Development (AMED) (JP20fk0108535).

Reduced mortality during the COVID-19 outbreak in Japan, 2020: a two-stage interrupted time-series design.

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to be a major global health burden. This study aims to estimate the all-cause excess mortality occurring in the COVID-19 outbreak in Japan, 2020, by sex and age group. METHODS: Daily time series of mortality for the period January 2015-December 2020 in all 47 prefectures of Japan were obtained from the Ministry of Health, Labour and Welfare, Japan. A two-stage interrupted time-series design was used to calculate excess mortality. In the first stage, we estimated excess mortality by prefecture using quasi-Poisson regression models in combination with distributed lag non-linear models, adjusting for seasonal and long-term variations, weather conditions and influenza activity. In the second stage, we used a random-effects multivariate meta-analysis to synthesize prefecture-specific estimates at the nationwide level. RESULTS: In 2020, we estimated an all-cause excess mortality of -20 982 deaths [95% empirical confidence intervals (eCI): -38 367 to -5472] in Japan, which corresponded to a percentage excess of -1.7% (95% eCI: -3.1 to -0.5) relative to the expected value. Reduced deaths were observed for both sexes and in all age groups except those aged <60 and 70-79 years. CONCLUSIONS: All-cause mortality during the COVID-19 outbreak in Japan in 2020 was decreased compared with a historical baseline. Further evaluation of cause-specific excess mortality is warranted.

Geographically weighted generalized Farrington algorithm for rapid outbreak detection over short data accumulation periods.

The demand for rapid surveillance and early detection of local outbreaks has been growing recently. The rapid surveillance can select timely and appropriate interventions toward controlling the spread of emerging infectious diseases, such as the coronavirus disease 2019 (COVID-19). The Farrington algorithm was originally proposed by Farrington et al (1996), extended by Noufaily et al (2012), and is commonly used to estimate excess death. However, one of the major challenges in implementing this algorithm is the lack of historical information required to train it, especially for emerging diseases. Without sufficient training data the estimation/prediction accuracy of this algorithm can suffer leading to poor outbreak detection. We propose a new statistical algorithm-the geographically weighted generalized Farrington (GWGF) algorithm-by incorporating both geographically varying and geographically invariant covariates, as well as geographical information to analyze time series count data sampled from a spatially correlated process for estimating excess death. The algorithm is a type of local quasi-likelihood-based regression with geographical weights and is designed to achieve a stable detection of outbreaks even when the number of time points is small. We validate the outbreak detection performance by using extensive numerical experiments and real-data analysis in Japan during COVID-19 pandemic. We show that the GWGF algorithm succeeds in improving recall without reducing the level of precision compared with the conventional Farrington algorithm.

Effect of emergency declaration on mental health during the COVID-19 pandemic in Japan: A social network service-based difference-in-differences approach.

Strong lockdowns to control COVID-19 pandemic have been enforced globally and strongly restricted social activities with consequent negative effects on mental health. Japan has effectively implemented a unique voluntary policy to control COVID-19, but the mental health impact of the policy has not been examined on a large scale. In this study, we examined the effect of the first declaration on the mental health of affected residents. We used population-level questionnaire data of 17,400 people living under the state of emergency and 9208 who were not through a social-networking-service app and applied a difference-in-differences regression model to estimate the causal effect of the declaration of the state of emergency on psychological wellbeing, stratified by job category. No statistically significant effect of the declaration was observed among all job categories. This suggests that residents' psychological situation has gradually changed, possibly influenced by other factors such as the surrounding environment, rather than the declaration itself. Given that Japan has a unique policy to control COVID-19 instead of a strict lockdown, our results showed the Japanese-style policy may serve as a form of harm reduction strategy, to control the epidemic with minimal psychological harm, and enable a policy that balances disease control and mental health. Caution is necessary that this study used self-reported data from a limited time period before and after the first declaration in April 2020.