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.

Trends in Healthcare Access in Japan during the First Wave of the COVID-19 Pandemic, up to June 2020.

We evaluated the impact of the new coronavirus disease (COVID-19) on healthcare access in Japan in terms of the number of outpatients and hospitalized patients as well as the length of hospital stays, during the first wave of the pandemic, up to June 2020. This observational study evaluated the monthly average number of outpatients per day at hospitals, the average number of hospitalized patients per day, and the average length of hospital stays per patient, from December 2010 to June 2020, using the hospital reports data, which are open aggregated data on the utilization of hospitals from the Ministry of Health, Labour and Welfare. These numbers were compared with those from the same period of previous years, using a quasi-Poisson regression model. We found a nationwide decrease in the number of outpatients in general hospitals and hospitalized patients, particularly in long-term care beds in Japan, as well as the excess length of hospital stays among psychiatric care patients during the first wave of the COVID-19. This limited access to healthcare demonstrated the importance of the long-term health monitoring of vulnerable populations and the need for urgent management support to healthcare facilities in preparation for possible prolonged pandemics in the future.

Excess All-Cause Deaths during Coronavirus Disease Pandemic, Japan, January-May 20201.

To provide insight into the mortality burden of coronavirus disease (COVID-19) in Japan, we estimated the excess all-cause deaths for each week during the pandemic, January-May 2020, by prefecture and age group. We applied quasi-Poisson regression models to vital statistics data. Excess deaths were expressed as the range of differences between the observed and expected number of all-cause deaths and the 95% upper bound of the 1-sided prediction interval. A total of 208-4,322 all-cause excess deaths at the national level indicated a 0.03%-0.72% excess in the observed number of deaths. Prefecture and age structure consistency between the reported COVID-19 deaths and our estimates was weak, suggesting the need to use cause-specific analyses to distinguish between direct and indirect consequences of COVID-19.

Assessing the regional impact of Japan's COVID-19 state of emergency declaration: a population-level observational study using social networking services.

OBJECTIVE: On 7 April 2020, the Japanese government declared a state of emergency in response to the novel coronavirus outbreak. To estimate the impact of the declaration on regional cities with low numbers of COVID-19 cases, large-scale surveillance to capture the current epidemiological situation of COVID-19 was urgently conducted in this study. DESIGN: Cohort study. SETTING: Social networking service (SNS)-based online survey conducted in five prefectures of Japan: Tottori, Kagawa, Shimane, Tokushima and Okayama. PARTICIPANTS: 127 121 participants from the five prefectures surveyed between 24 March and 5 May 2020. INTERVENTIONS: An SNS-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was launched. It asks questions regarding postcode, personal information, preventive actions, and current and past symptoms related to COVID-19. PRIMARY AND SECONDARY OUTCOME MEASURES: Empirical Bayes estimates of age-sex-standardised incidence rate (EBSIR) of symptoms and the spatial correlation between the number of those who reported having symptoms and the number of COVID-19 cases were examined to identify the geographical distribution of symptoms in the five prefectures. RESULTS: 97.8% of participants had no subjective symptoms. We identified several geographical clusters of fever with significant spatial correlation (r=0.67) with the number of confirmed COVID-19 cases, especially in the urban centres of prefectural capital cities. CONCLUSIONS: Given that there are still several high-risk areas measured by EBSIR, careful discussion on which areas should be reopened at the end of the state of emergency is urgently required using real-time SNS system to monitor the nationwide epidemic.

Trends in emergency transportation due to heat illness under the new normal lifestyle in the COVID-19 era, in Japan and 47 prefectures.

In Japan, in response to the spread of the new coronavirus disease (COVID-19), a 'new normal' in the era of the COVID-19 was proposed by the government, which calls for thorough wearing of masks as an infection control measure in the era of the COVID-19, but related heat illness has been a great concern this summer. We applied quasi-Poisson regression models to the daily number of emergency transportations due to heat illness from 2008 to 2020 from the Fire and Disaster Management Agency, Ministry of Internal Affairs and Communications, Japan, to estimate the expected weekly number of emergency transportations from heat illness, with adjustment for their long-term trend and the weather conditions, including temperatures. We found that, at the national level, the number of heat illness emergency transports did not significantly increase or decrease from the annual trend in 2020. By prefecture, on the other hand, there were some prefectures in which the number of heat illness emergency transports was less than the average year, and most of them were in the week of August 10-16. By age group, the number of heat illness emergency transports in the 0-17 and 18-64 age groups was particularly low in some prefectures, and by severity, those in mild cases was particularly low. A caution is necessary that there is a possibility that a decrease in cases possibly associated with COVID-19 measures, such as, outdoor activity restrictions at schools/universities and cancellation of public events, may offset the possible increase in heat illness cases occurring elsewhere associated with wearing masks. Given that the end of the COVID-19 pandemic is not expected yet, continuous and appropriate awareness-raising activities to prevent heat-related illness remain important.

An assessment of self-reported COVID-19 related symptoms of 227,898 users of a social networking service in Japan: Has the regional risk changed after the declaration of the state of emergency?

BACKGROUND: In the absence of widespread testing, symptomatic monitoring efforts may allow for understanding the epidemiological situation of the spread of coronavirus disease 2019 (COVID-19) in Japan. We obtained data from a social networking service (SNS) messaging application that monitors self-reported COVID-19 related symptoms in real time in Fukuoka Prefecture, Japan. We aimed at not only understanding the epidemiological situation of COVID-19 in the prefecture, but also highlighting the usefulness of symptomatic monitoring approaches that rely on self-reporting using SNS during a pandemic, and informing the assessment of Japan's emergency declaration over COVID-19. METHODS: We analysed symptoms data (fever over 37.5° and a strong feeling of weariness or shortness of breath), reported voluntarily via SNS chatbot by 227,898 residents of Fukuoka Prefecture during March 27 to May 3, 2020, including April 7, when a state of emergency was declared. We estimated the spatial correlation coefficient between the number of the self-reported cases of COVID-19 related symptoms and the number of PCR confirmed COVID-19 cases in the period (obtained from the prefecture website); and estimated the empirical Bayes age- and sex-standardised incidence ratio (EBSIR) of the symptoms in the period, compared before and after the declaration. The number of symptom cases was weighted by age and sex to reflect the regional population distribution according to the 2015 national census. FINDINGS: Of the participants, 3.47% reported symptoms. There was a strong spatial correlation of 0.847 (p < 0.001) at municipality level between the weighted number of self-reported symptoms and the number of COVID-19 cases for both symptoms. The EBSIR at post-code level was not likely to change remarkably before and after the declaration of the emergency, but the gap in EBSIR between high-risk and low-risk areas appeared to have increased after the declaration. INTERPRETATION: While caution is necessary as the data was limited to SNS users, the self-reported COVID-19 related symptoms considered in the study had high epidemiological evaluation ability. In addition, though based on visual assessment, after the declaration of the emergency, regional containment of the infection risk might have strengthened to some extent. SNS, which can provide a high level of real-time, voluntary symptom data collection, can be used to assess the epidemiology of a pandemic, as well as to assist in policy assessments such as emergency declarations. 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).