Search

Objective This paper provides an in-depth examination of public attitudes towards salt reduction across seven culturally diverse countries: the USA, the UK, France, Japan, Indonesia, Thailand, and Brazil.Design Cross-sectional regression analysis with questionnaire data.Setting An analysis of questionnaire study in seven countries.Participants The study’s questionnaire collected responses from 7090 participants across seven countries with the mean age of respondents being 46.06 years (SD 16.96). The gender distribution encompassed 3473 men (49.12%), 3582 women (50.66%), 24 non-binary individuals (0.34%) and 11 who identified as ‘other’ (0.16%).Primary and secondary outcome measures Attitudes toward sodium reduction were measured on a seven-point Likert scale.Results Regression analysis revealed significant associations between attitudes towards sodium reduction and various factors across countries. Gender was a significant factor in France, with women showing less awareness than men (coefficient −0.123, 95% CI −0.237 to −0.008). Age was a significant factor in Japan and Thailand, with older generations exhibiting stronger awareness. Occupation was a significant factor in France (grocery, 0.678, 0.229 to 1.127) and Japan (food service, 0.792, 0.300 to 1.283). In France (0.090, 0.033 to 0.146) and Brazil (0.092, 0.040 to 0.144), attitudes towards reducing sugar intake were positively associated with sodium reduction attitudes. Government interventions showed varying impacts, with positive associations in Thailand (0.004, 0.001 to 0.008) and negative associations in France (−0.003 –0.005 to −0.000).Conclusion Our study reveals a complex array of factors shaping attitudes towards sodium reduction across seven countries. These findings support the need for nuanced, country-specific approaches in formulating sodium reduction strategies. Future research should validate these findings, explore further determinants and understand how attitudes translate into dietary behaviours.

Background: Chronic contained rupture (CCR) of abdominal aortic aneurysm (AAA) is a rare subtype of AAA rupture with a chronic course. CCR-AAA may mimic other diseases in terms of symptoms and morphology. Case report: A 64-year-old man was incidentally found to have an AAA and a retroperitoneal mass lesion on computed tomography (CT) during his medical checkup. He had no history of abdominal or back symptoms and was hemodynamically stable. Contrast-enhanced CT revealed a nubby cauliflower-like, nonenhanced mass in the retroperitoneum continuous with the aneurysm. Magnetic resonance imaging revealed the mass to have an internal low-signal area branching off from the abdominal aorta on a T1-weighted image. Positron emission tomography-CT revealed enhanced fluorine-18-fluorodeoxyglucose accumulation on the margin of the mass. The differential diagnoses included CCR-AAA, infectious aortic aneurysm, or AAA with a retroperitoneal malignant tumor. The mass lesion was resected at the same time as the open AAA repair. Histopathological examination revealed that the mass comprised granulation tissue associated with ruptured AAA and did not include a malignant tumor. The patient was diagnosed with CCR-AAA based on these results and had an uneventful postoperative course. Conclusions: Reaching a definitive diagnosis of CCR-AAA based on preoperative examinations was difficult, and simultaneous mass resection was required. Because CCR-AAA can rupture completely, mass resection may be helpful option for early diagnosis and patient salvage.

Autologous-engineered artificial tissues constitute an ideal alternative for radical surgery in terms of natural anticoagulation, self-repair, tissue regeneration, and the possibility of growth. Previously, we focused on the development and practical application of artificial tissues using “in-body tissue architecture (iBTA)”, a technique that uses living bodies as bioreactors. This study aimed to further develop iBTA by fabricating tissues with diverse shapes and evaluating their physical properties. Although the breaking strength increased with tissue thickness, the nominal breaking stress increased with thinner tissues. By carving narrow grooves on the outer periphery of an inner core with narrow grooves, we fabricated approximately 2.2 m long cord-shaped tissues and net-shaped tissues with various designs. By assembling the two inner cores inside the branched stainless-steel pipes, a large graft with branching was successfully fabricated, and its aortic arch replacement was conducted in a donor goat without causing damage. In conclusion, by applying iBTA technology, we have made it possible, for the first time, to create tissues of various shapes and designs that are difficult using existing tissue-engineering techniques. Thicker iBTA-induced tissues exhibited higher rupture strength; however, rupture stress was inversely proportional to thickness. These findings broaden the range of iBTA-induced tissue applications.

The increasing burden of lifestyle-related diseases highlights the need to address unhealthy dietary habits. This study aims to explore the latest dietary patterns in Japan following the COVID-19 pandemic, focusing on trends in health-promoting food choices. A web-based survey was conducted among 27,154 Japanese adults, selected via quota sampling to mirror national demographics. The study evaluated dietary diversity, measured through the Dietary Variety Score (Outcome 1), and the prioritization of nutritional and health considerations in food selection, assessed via a Likert scale (Outcome 2). Uniform Manifold Approximation and Projection (UMAP) and Ordering Points To Identify the Clustering Structure (OPTICS) algorithms were used to delineate patterns in health-centric food selections. OPTICS clustering revealed four distinct clusters for each outcome. Cluster 3, with a diverse diet, comprised older, predominantly female individuals with higher well-being and lower social isolation compared to Cluster 4, which lacked distinct dietary patterns. Cluster 3 also engaged more in snacking, treat foods, home cooking, and frozen meals. Similarly, a divide emerged between those prioritizing dietary considerations (Cluster C) and those indifferent to such aspects (Cluster D). The findings underscore the need for holistic post-COVID-19 public health initiatives addressing socioeconomic and cultural barriers to healthier dietary practices.

BackgroundSelf-tracking smartphone apps have emerged as promising tools to encourage healthy behaviors. In this longitudinal study, we used gym use data from members of a major fitness club that operates gyms throughout Japan from January 2014 to December 2019. ObjectiveOur objective was to assess the extent to which a health and fitness self-tracking mobile app introduced to gym members on January 1, 2018, contributed to their weight loss. The app allows users to input information regarding diet, sleep, weight, and gym exercise so that they can receive personalized feedback from an artificial intelligence chatbot to improve their health behaviors. MethodsWe used linear regression to quantify the association between app use and weight loss. The primary outcome of the study was the weight loss achieved by each gym user, which was calculated as the difference between their initial and final weights in kilograms, as recorded in the app. Individuals who did not attend the gym or failed to use the mobile app at least twice during the study period were excluded from the analysis. The model accounted for age, gender, distance between the gym and the member’s residence, average weekly number of times a member used the gym, user’s gym membership length in weeks, average weekly number of times a member input information into the app, and the number of weeks that the app was used at least once. ResultsData from 26,589 participants were analyzed. Statistically significant associations were detected between weight loss and 2 metrics related to app use: the average weekly frequency of use and the total number of weeks in which the app was used at least once. One input per week was found to be associated with a loss of 62.1 (95% CI 53.8-70.5) g, and 1 week of app use was associated with 21.7 (95% CI 20.5-22.9) g of weight loss from the day of the first input to that of the final input to the app. Furthermore, the average number of times that a member used the gym weekly was also shown to be statistically significantly associated with weight loss: 1 use per week was associated with 255.5 (95% CI 228.5-282.6) g of weight loss. ConclusionsThis empirical study demonstrated a significant association between weight loss among gym members and not only the frequency of weekly gym use but also the use of a health and fitness self-tracking app. However, further work is needed to examine the mechanisms through which mobile apps affect health behaviors and to identify the specific app features that are most effective in promoting weight loss.

Abstract Objective: Excessive salt intake raises blood pressure and increases the risk of non-communicable diseases (NCD), such as CVD, chronic kidney disease and stomach cancer. Reducing the Na content of food is an important public health measure to control the NCD. This study quantifies the amount of salt reduced by using umami substances, i.e. glutamate, inosinate and guanylate, for adults in the USA. Design: The secondary data analysis was performed using data of the US nationally representative cross-sectional dietary survey, the National Health and Nutrition Examination Survey (NHANES) 2017–2018. Per capita daily salt intake corresponding to the NHANES food groups was calculated in the four hypothetical scenarios of 0 %, 30 %, 60 % and 90 % market share of low-Na foods in the country. The salt reduction rates by using umami substances were estimated based on the previous study results. Setting: The USA Participants: 4139 individuals aged 20 years and older in the USA Results: Replacing salt with umami substances could help the US adults reduce salt intake by 7·31–13·53 % (7·50–13·61 % for women and 7·18–13·53 % for men), which is equivalent to 0·61–1·13 g/d (0·54–0·98 g/d for women and 0·69–1·30 g/d for men) without compromising the taste. Approximately, 21·21–26·04 % of the US adults could keep their salt intake below 5 g/d, the WHO’s recommendation in the scenario where there is no low-Na product on the market. Conclusions: This study provides essential information that the use of umami substances as a substitute for salt may help reduce the US adults’ salt intake.

This study investigated six-month outcomes of first models of ascending aortic replacement. The molds used to produce the Biotube were implanted subcutaneously in goats. After 2–3 months, the molds were explanted to obtain the Biotubes (inner diameter, 12 mm; wall thickness, 1.5 mm). Next, we performed ascending aortic replacement using the Biotube in five allogenic goats. At 6 months, the animals underwent computed tomography (CT) and histologic evaluation. As a comparison, we performed similar surgeries using glutaraldehyde-fixed autologous pericardial rolls or pig-derived heterogenous Biotubes. At 6 months, CT revealed no aneurysmalization of the Biotube or pseudoaneurysm formation. The histologic evaluation showed development of endothelial cells, smooth muscle cells, and elastic fibers along the Biotube. In the autologous pericardium group, there was no evidence of new cell development, but there was calcification. The histologic changes observed in the heterologous Biotube group were similar to those in the allogenic Biotube group. However, there was inflammatory cell infiltration in some heterologous Biotubes. Based on the above, we could successfully create the world’s first Biotube-based ascending aortic replacement models. The present results indicate that the Biotube may serve as a scaffold for aortic tissue regeneration.

Biotubes are autologous tubular tissues developed within a patient’s body through in-body tissue architecture, and they demonstrate high potential for early clinical application as a vascular replacement. In this pilot study, we used large animals to perform implantation experiments in preparation for preclinical testing of Biotube. The biological response after Biotube implantation was histologically evaluated. The designed Biotubes (length: 50 cm, internal diameter: 4 mm, and wall thickness: 0.85 mm) were obtained by embedding molds on the backs of six goats for a predetermined period (1–5 months). The same goats underwent bypass surgery on the carotid arteries using Biotubes (average length: 12 cm). After implantation, echocardiography was used to periodically monitor patency and blood flow velocity. The maximum observation period was 6 months, and tissue analysis was conducted after graft removal, including the anastomosis. All molds generated Biotubes that exceeded the tensile strength of normal goat carotid arteries, and eight randomly selected Biotubes were implanted. Thrombotic occlusion occurred immediately postoperatively (1 tube) if anticoagulation was insufficient, and two tubes, with insufficient Biotube strength (2 months without aneurysm formation. The spots far from the anastomosis became stenosed within 3 months (3 tubes) when Biotubes had a wide intensity distribution, but the shape of the remaining two tubes remained unchanged for 6 months. The entire length of the bypass region was walled with an αSMA-positive cell layer, and an endothelial cell layer covered most of the lumen at 2 months. Complete endothelial laying of the luminal surface was obtained at 3 months after implantation, and a vascular wall structure similar to that of native blood vessels was formed, which was maintained even at 6 months. The stenosis was indicated to be caused by fibrin adhesion on the luminal surface, migration of repair macrophages, and granulation formation due to the overproliferation of αSMA-positive fibroblasts. We revealed the importance of Biotubes that are homogeneous, demonstrate a tensile strength > 5 N, and are implanted under appropriate antithrombotic conditions to achieve long-term patency of Biotube. Further, we clarified the Biotube regeneration process and the mechanism of stenosis. Finally, we obtained the necessary conditions for a confirmatory implant study planned shortly.

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.

Abstract 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.

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.

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.

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.

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.

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.

Abstract The international spread of COVID-19 infection has attracted global attention, but the impact of local or domestic travel restriction on public transportation network remains unclear. Passenger volume data for the domestic public transportation network in Japan and the time at which the first confirmed COVID-19 case was observed in each prefecture were extracted from public data sources. A survival approach in which a hazard was modeled as a function of the closeness centrality on the network was utilized to estimate the risk of importation of COVID-19 in each prefecture. A total of 46 prefectures with imported cases were identified. Hypothetical scenario analyses indicated that both strategies of locking down the metropolitan areas and restricting domestic airline travel would be equally effective in reducing the risk of importation of COVID-19. While caution is necessary that the data were limited to June 2020 when the pandemic was in its initial stage and that no other virus spreading routes have been considered, domestic travel restrictions were effective to prevent the spread of COVID-19 on public transportation network in Japan. Instead of lockdown that might seriously damage the economy, milder travel restrictions could have the similar impact on controlling the domestic transmission of COVID-19.

Abstract Background In Japan, the latest estimates of excess all-cause deaths through January to July 2020 showed that the overall (direct and indirect) mortality burden from the Coronavirus Disease 2019 (COVID-19) in Japan was relatively low compared to Europe and the United States. However, consistency between the reported number of COVID-19 deaths and excess all-cause deaths was limited across prefectures, suggesting the necessity of distinguishing the direct and indirect consequences of COVID-19 by cause-specific analysis. To examine whether deaths from road injuries decreased during the COVID-19 pandemic in Japan, consistent with a possible reduction of road transport activity connected to Japan’s state of emergency declaration, we estimated the exiguous deaths from road injuries in each week from January to September 2020 by 47 prefectures. Methods To estimate the expected weekly number of deaths from road injuries, a quasi-Poisson regression was applied to daily traffic fatalities data obtained from Traffic Accident Research and Data Analysis, Japan. We set two thresholds, point estimate and lower bound of the two-sided 95% prediction interval, for exiguous deaths, and report the range of differences between the observed number of deaths and each of these thresholds as exiguous deaths. Results Since January 2020, in a few weeks the observed deaths from road injuries fell below the 95% lower bound, such as April 6–12 (exiguous deaths 5–21, percent deficit 2.82–38.14), May 4–10 (8–23, 21.05–43.01), July 20–26 (12–29, 30.77–51.53), and August 3–9 (3–20, 7.32–34.41). However, those less than the 95% lower bound were also observed in weeks in the previous years. Conclusions The number of road traffic fatalities during the COVID-19 pandemic in Japan has decreased slightly, but not significantly, in several weeks compared with the average year. This suggests that the relatively small changes in excess all-cause mortality observed in Japan during the COVID-19 pandemic could not be explained simply by an offsetting reduction in traffic deaths. Considering a variety of other indirect effects, evaluating an independent, unbiased measure of COVID-19-related mortality burden could provide insight into the design of future broad-based infectious disease counter-measures and offer lessons to other countries.

Background: The World Health Organization declared the novel coronavirus outbreak (COVID-19) to be a pandemic on March 11, 2020. Large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan would improve preparation for and prevention of a massive outbreak. Methods: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was developed using the LINE app to evaluate the current Japanese epidemiological situation. LINE users could participate in the system either though a QR code page in the prefectures’ websites or a banner at the top of the LINE app screen. COOPERA asked participants questions regarding personal information, preventive actions, and non-specific symptoms related to COVID-19 and their duration. We calculated daily cross correlation functions between the reported number of infected cases confirmed using polymerase chain reaction and the symptom-positive group captured by COOPERA. Results: We analyzed 206,218 participants from three prefectures reported between March 5 and 30, 2020. The mean age of participants was 44.2 (standard deviation, 13.2) years. No symptoms were reported by 96.93% of participants, but there was a significantly positive correlation between the reported number of COVID-19 cases and self-reported fevers, suggesting that massive monitoring of fever might help to estimate the scale of the COVID-19 epidemic in real time. Conclusions: COOPERA is the first real-time system being used to monitor trends in COVID-19 in Japan and provides useful insights to assist political decisions to tackle the epidemic.

Summary: 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).

Summary: Background: Identifying and understanding reasons for being unsure or unwilling regarding intention to be vaccinated against coronavirus disease (COVID-19) may help to inform future public health messages aimed at increasing vaccination coverage. We analyzed a broad array of individual's psychological dispositions with regard to decision-making about COVID-19 vaccination in Japan. Methods: A nationally representative cross-sectional web survey was conducted with 30053 Japanese adults aged 20 years or older at the end of February 2021. In addition to the question on the individual's intention to be vaccinated against COVID-19, respondents were asked about their sociodemographic, health-related, and psychological characteristics as well as information sources about COVID-19 and their levels of trust. Also, those who responded ‘not sure’ or ‘no’ regarding intention to take COVID-19 vaccine were asked why. Multinomial logistic regression with sparse group Lasso (Least Absolute Shrinkage and Selection Operator) penalty was used to compute adjusted odds ratios for factors associated with the intention (not sure/no versus yes). Findings: The percentages of respondents who answered ‘not sure’ or ‘no’ regarding intention to be vaccinated against COVID-19 vaccine were 32.9% and 11.0%, respectively. After adjusting for covariates, the perceived risks of COVID-19, perceived risk of a COVID-19 vaccine, perceived benefits of a COVID-19 vaccine, trust in scientists and public authorities, and the belief that healthcare workers should be vaccinated were significantly associated with vaccination intention. Several sources of information about COVID-19 were also significantly associated with vaccination intention, including physicians, nurses, and television, medical information sites with lower odds of being unsure or unwilling, and internet news sites, YouTube, family members, and scientists and researchers with higher odds. The higher the level of trust in television as a source of COVID-19 information, the higher the odds of responding ‘not sure’ (odds ratio 1.11, 95% confidence interval 1.01–1.21). We also demonstrated that many respondents presented concerns about the side effects and safety of a COVID-19 vaccine as a major reason for being unsure or unwilling. To decide whether or not to get the vaccine, many respondents requested more information about the compatibilities between the vaccine and their personal health conditions, whether other people had been vaccinated, the effectiveness of vaccines against variants, and doctors’ recommendations. Interpretation: Our findings suggest that public health messaging based on the sociodemographic and psychological characteristics of those who are unsure or unwilling regarding intention to be vaccinated against COVID-19 vaccine may help to increase vaccine uptake amongst this population. 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).

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.

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).

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