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1.
SSM Popul Health ; 18: 101105, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1805211

ABSTRACT

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.

2.
Lancet Reg Health West Pac ; 22: 100434, 2022 May.
Article in English | MEDLINE | ID: covidwho-1757639

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has negatively affected access to healthcare systems and treatment timelines. This study was designed to explore the impact of the COVID-19 pandemic on patients who underwent percutaneous coronary intervention (PCI). Methods: From January 2019 to December 2020, 489,001 patients from 1068 institutions were registered in the Japanese nationwide PCI (J-PCI) registry. We constructed generalized linear models to assess the difference in the daily number of patients and in-hospital outcomes between 2019 and 2020. Findings: In total, 207 institutions (19·3%) had closed or restricted access during the first COVID-19 outbreak in May 2020; the number of closed or restricted institutions had plateaued at a median of 121 institutions (11·3%). The daily case volume of PCI significantly decreased in 2020 (by 6·7% compared with that in 2019; 95% confidence interval [CI], 6·2-7·2%; p < 0·001). Marked differences in the presentation of PCI patients were observed; more patients presented with ST-segment elevation myocardial infarction (18·3% vs. 17·5%; p < 0·001), acute heart failure (4·49% vs. 4·30%; p = 0·001), cardiogenic shock (3·79% vs. 3·45%; p < 0·001), and cardiopulmonary arrest (2·12% vs. 2·00%; p = 0·002) in 2020. The excess adjusted in-hospital mortality rate in patients treated in 2020 relative to those treated in 2019 was significant (adjusted odds ratio, 1·054; 95% CI, 1·004-1·107; p = 0·03). Interpretation: While the number of patients who underwent PCI substantially decreased during the COVID-19 pandemic, more patients presented with high-risk characteristics and were associated with significantly higher adjusted in-hospital mortality. Funding: The J-PCI registry is a registry led and supported by the Japanese Association of Cardiovascular Intervention and Therapeutics. The present study was supported by the Grant-in-Aid from the Ministry of Health and Labour (No. 20IA2002 and 21FA1015), the Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (KAKENHI; No. 21K08064), and the Japan Agency for Medical Research and Development (No. 17ek0210097h000).

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-314975

ABSTRACT

The COVID-19 pandemic has highlighted the global need for reliable models of disease spread. We propose an AI-augmented forecast modeling framework that provides daily predictions of the expected number of confirmed COVID-19 deaths, cases and hospitalizations during the following 4 weeks and we present an international, prospective evaluation of our models' performance across all states and counties in the USA and prefectures in Japan. National mean absolute percentage error (MAPE) for predicting COVID-19 associated deaths before and after prospective deployment remained consistently <2% (US) and <10% (Japan). Average statewide (US) and prefecture wide (Japan) MAPE was 6% and 26% respectively (14% when looking at prefectures with more than 10 deaths). We show that our models perform well even during periods of considerable change in population behavior, and that it is robust to demographic differences across different geographic locations. We further demonstrate that our framework provides meaningful explanatory insights with the models accurately adapting to local and national policy interventions. Our framework enables counterfactual simulations, which indicate continuing Non-Pharmaceutical Interventions alongside vaccinations is essential for faster recovery from the pandemic, delaying the application of interventions has a detrimental effect, and allow exploration of the consequences of different vaccination strategies. The COVID-19 pandemic remains a global emergency. In the face of substantial challenges ahead, the approach presented here has the potential to inform critical decisions.

4.
Lancet Reg Health West Pac ; 18: 100330, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1559154

ABSTRACT

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).

5.
Surg Today ; 52(1): 22-35, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1516860

ABSTRACT

BACKGROUND AND PURPOSE: The spread of COVID-19 has restricted the delivery of standard medical care to surgical patients dramatically. Surgical triage is performed by considering the type of disease, its severity, the urgency for surgery, and the condition of the patient, in addition to the scale of infectious outbreaks in the region. The purpose of this study was to evaluate the impact of the COVID-19 pandemic on the number of surgical procedures performed and whether the effects were more prominent during certain periods of widespread infection and in the affected regions. METHODS: We selected 20 of the most common procedures from each surgical field and compared the weekly numbers of each operation performed in 2020 with the respective numbers in 2018 and 2019, as recorded in the National Clinical Database (NCD). The surgical status during the COVID-19 pandemic as well as the relationship between surgical volume and the degree of regional infection were analyzed extensively. RESULTS: The rate of decline in surgery was at most 10-15%. Although the numbers of most oncological and cardiovascular procedures decreased in 2020, there was no significant change in the numbers of pancreaticoduodenectomy and aortic replacement procedures performed in the same period. CONCLUSION: The numbers of most surgical procedures decreased in 2020 as a result of the COVID-19 pandemic; however, the precise impact of surgical triage on decrease in detection of disease warrants further investigation.


Subject(s)
COVID-19 , Surgical Procedures, Operative/statistics & numerical data , Databases, Factual , Humans , Japan/epidemiology , Pandemics
6.
Int J Epidemiol ; 51(1): 75-84, 2022 02 18.
Article in English | MEDLINE | ID: covidwho-1493814

ABSTRACT

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.


Subject(s)
COVID-19 , Disease Outbreaks , Female , Humans , Interrupted Time Series Analysis , Japan/epidemiology , Male , Mortality , SARS-CoV-2
7.
NPJ Digit Med ; 4(1): 146, 2021 Oct 08.
Article in English | MEDLINE | ID: covidwho-1462044

ABSTRACT

The COVID-19 pandemic has highlighted the global need for reliable models of disease spread. We propose an AI-augmented forecast modeling framework that provides daily predictions of the expected number of confirmed COVID-19 deaths, cases, and hospitalizations during the following 4 weeks. We present an international, prospective evaluation of our models' performance across all states and counties in the USA and prefectures in Japan. Nationally, incident mean absolute percentage error (MAPE) for predicting COVID-19 associated deaths during prospective deployment remained consistently <8% (US) and <29% (Japan), while cumulative MAPE remained <2% (US) and <10% (Japan). We show that our models perform well even during periods of considerable change in population behavior, and are robust to demographic differences across different geographic locations. We further demonstrate that our framework provides meaningful explanatory insights with the models accurately adapting to local and national policy interventions. Our framework enables counterfactual simulations, which indicate continuing Non-Pharmaceutical Interventions alongside vaccinations is essential for faster recovery from the pandemic, delaying the application of interventions has a detrimental effect, and allow exploration of the consequences of different vaccination strategies. The COVID-19 pandemic remains a global emergency. In the face of substantial challenges ahead, the approach presented here has the potential to inform critical decisions.

8.
Sci Prog ; 104(3): 368504211029793, 2021.
Article in English | MEDLINE | ID: covidwho-1369465

ABSTRACT

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.


Subject(s)
COVID-19/psychology , Mental Health/statistics & numerical data , Quarantine/psychology , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Japan , Mobile Applications , Social Networking
9.
J Urban Health ; 98(5): 635-641, 2021 10.
Article in English | MEDLINE | ID: covidwho-1351336

ABSTRACT

In the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan-each defined as an area overlaid by several 125-meter grids-from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.


Subject(s)
COVID-19 , Pandemics , Humans , Japan/epidemiology , Longitudinal Studies , SARS-CoV-2
10.
Lancet Reg Health West Pac ; 14: 100223, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1331033

ABSTRACT

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).

11.
PLoS One ; 16(7): e0253434, 2021.
Article in English | MEDLINE | ID: covidwho-1290917

ABSTRACT

BACKGROUND: Descriptive analyses of 2009-2016 were performed using the data of the Universal Coverage Scheme (UCS) which covers nearly 70 percent of the Thai population. The analyses described the time and geographical trends of nationwide admission rates of type 2 diabetes mellitus (T2DM) and its complications, including chronic kidney disease (CKD), myocardial infarction, cerebrovascular diseases, retinopathy, cataract, and diabetic foot amputation. METHODS AND FINDINGS: The database of T2DM patients aged 15-100 years who were admitted between 2009 and 2016 under the UCS and that of the UCS population were retrieved for the analyses. The admitted cases of T2DM were extracted from the database using disease codes of principal and secondary diagnoses defined by the International Classification of Diseases 9th and 10th Revisions. The T2DM admission rates in 2009-2016 were the number of admissions divided by the number of the UCS population. The standardized admission rates (SARs)were further estimated in contrast to the expected number of admissions considering age and sex composition of the UCS population in each region. A linearly increased trend was found in T2DM admission rates from 2009 to 2016. Female admission rates were persistently higher than that of males. In 2016, an increase in the T2DM admission rates was observed among the older ages relative to that in 2009. Although the SARs of T2DM were generally higher in Bangkok and central regions in 2009, except that with CKD and foot amputation which had higher trends in northeastern regions, the geographical inequalities were fairly reduced by 2016. CONCLUSION: Admission rates of T2DM and its major complications increased in Thailand from 2009 to 2016. Although the overall geographical inequalities in the SARs of T2DM were reduced in the country, further efforts are required to improve the health system and policies focusing on risk factors and regions to manage the increasing T2DM.


Subject(s)
Diabetes Complications/therapy , Diabetes Mellitus, Type 2/therapy , Patient Admission/trends , Universal Health Insurance/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Cataract/complications , Cataract/therapy , Diabetes Mellitus, Type 2/etiology , Diabetic Foot/complications , Diabetic Foot/surgery , Diabetic Retinopathy/complications , Diabetic Retinopathy/therapy , Female , Humans , Male , Middle Aged , Myocardial Infarction/complications , Myocardial Infarction/therapy , Patient Admission/statistics & numerical data , Renal Insufficiency, Chronic/complications , Renal Insufficiency, Chronic/therapy , Thailand , Young Adult
12.
Lancet Reg Health West Pac ; 3: 100016, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-1281486

ABSTRACT

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).

13.
J Intensive Care ; 9(1): 42, 2021 Jun 01.
Article in English | MEDLINE | ID: covidwho-1255975

ABSTRACT

Since the start of the coronavirus disease 2019 (COVID-19) pandemic, it has remained unknown whether conventional risk prediction tools used in intensive care units are applicable to patients with COVID-19. Therefore, we assessed the performance of established risk prediction models using the Japanese Intensive Care database. Discrimination and calibration of the models were poor. Revised risk prediction models are needed to assess the clinical severity of COVID-19 patients and monitor healthcare quality in ICUs overwhelmed by patients with COVID-19.

14.
Emerg Infect Dis ; 27(3): 789-795, 2021 03.
Article in English | MEDLINE | ID: covidwho-1100024

ABSTRACT

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.


Subject(s)
COVID-19/mortality , COVID-19/diagnosis , Cause of Death , Humans , Japan/epidemiology , Mortality , SARS-CoV-2
15.
BMJ Open ; 11(2): e042002, 2021 02 15.
Article in English | MEDLINE | ID: covidwho-1085262

ABSTRACT

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.


Subject(s)
COVID-19/epidemiology , Social Networking , Adolescent , Adult , Aged , Aged, 80 and over , Bayes Theorem , Cohort Studies , Epidemiological Monitoring , Female , Humans , Japan/epidemiology , Male , Middle Aged , Young Adult
16.
Sci Rep ; 11(1): 3109, 2021 02 04.
Article in English | MEDLINE | ID: covidwho-1065947

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.


Subject(s)
COVID-19 , Travel/statistics & numerical data , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Japan , Pandemics , Transportation/statistics & numerical data
17.
Lancet Reg Health West Pac ; 1: 100011, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-741396

ABSTRACT

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).

18.
Bull World Health Organ ; 98(8): 518-529, 2020 Aug 01.
Article in English | MEDLINE | ID: covidwho-707108

ABSTRACT

OBJECTIVE: To estimate the effect of airline travel restrictions on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) importation. METHODS: We extracted passenger volume data for the entire global airline network, as well as the dates of the implementation of travel restrictions and the observation of the first case of coronavirus disease (COVID-19) in each country or territory, from publicly available sources. We calculated effective distance between every airport and the city of Wuhan, China. We modelled the risk of SARS-CoV-2 importation by estimating survival probability, expressing median time of importation as a function of effective distance. We calculated the relative change in importation risk under three different hypothetical scenarios that all resulted in different passenger volumes. FINDINGS: We identified 28 countries with imported cases of COVID-19 as at 26 February 2020. The arrival time of the virus at these countries ranged from 39 to 80 days since identification of the first case in Wuhan. Our analysis of relative change in risk indicated that strategies of reducing global passenger volume and imposing travel restrictions at a further 10 hub airports would be equally effective in reducing the risk of importation of SARS-CoV-2; however, this reduction is very limited with a close-to-zero median relative change in risk. CONCLUSION: The hypothetical variations in observed travel restrictions were not sufficient to prevent the global spread of SARS-CoV-2; further research should also consider travel by land and sea. Our study highlights the importance of strengthening local capacities for disease monitoring and control.


Subject(s)
Communicable Disease Control/methods , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Travel/legislation & jurisprudence , Aircraft/legislation & jurisprudence , Airports/standards , Betacoronavirus , COVID-19 , Coronavirus Infections/transmission , Humans , Models, Statistical , Pneumonia, Viral/transmission , Risk Assessment , SARS-CoV-2 , Time Factors
20.
J Epidemiol ; 30(8): 362-370, 2020 08 05.
Article in English | MEDLINE | ID: covidwho-437082

ABSTRACT

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.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Disease Outbreaks/prevention & control , Epidemiological Monitoring , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 , Female , Humans , Japan/epidemiology , Male , Middle Aged , Young Adult
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