COVID-19 Infection risk posed by drinking alcohol at restaurants or bars in Japan

BackgroundOn April 25, 2021, the third state of emergency was declared in Japan. Drinking alcohol at restaurants and bars was banned. ObjectWe used published data to evaluate drinking ban effects. MethodWe bootstrapped the data and evaluated the risk ratio for drinking compared with non-drinking during group dining with similar frequency and numbers of participants. ResultsThe 99% lower bound of the bootstrapped distribution of the risk ratio was less than one. Therefore the null hypothesis, that incidence in the two styles of group dining were the same, cannot be rejected. Discussion and ConclusionResults constitute no clear evidence indicating a risk of drinking alcohol in groups. However, further analyses using collected data are necessary. Moreover, risks posed by the number of group diners or their dining frequency must be evaluated.

Estimating Vaccination Effects on COVID-19 outbreak course in Japan

BackgroundOmicron variant strain dominated since the beginning of 2022. Its infectivity was supposes to be higher than Delta variant strain or strains in past. ObjectWe estimated prevalence of omicron variant strain, particularly bA.2 variant and COVID-19 vaccine effectiveness of the third dose in Japan as well as controlling for waning of second dose of vaccine, other mutated strains, the Olympic Games, and countermeasures. MethodThe effective reproduction number R(t) was regressed on shares of omicron variant strain and bA.2 and vaccine coverage of the third dose, as well as along with data of temperature, humidity, mobility, share of the other mutated strains, and an Olympic Games and countermeasures. The study period was February, 2020 through February 21, 2022, as of March 15, 2022. ResultsEstimation results indicated that waning of the second dose vaccine e with 150 days prior was the most appropriate specification. Moreover, bA.2 of omicron variant strain has higher infectively than other variant strain or traditional strain. DiscussionBecause of data limitation since emerging bA.2, the estimated its infectively will change over time.

Prediction of severe COVID-19 cases requiring intensive care in Osaka, Japan

BackgroundTo avoid exhaustion of medical resources by COVID-19 care, policy-makers must predict care needs, specifically estimating the proportion of severe cases likely to require intensive care. In Osaka prefecture, Japan, the number of these severe cases exceeded the capacity of ICU units prepared for COVID-19 from mid-April, 2021. ObjectiveThis study used a statistical model to elucidate dynamics of severe cases in Osaka and validated the model through prospective testing. MethodsThe study extended from April 3, 2020 through April 26, 2021 in Osaka prefecture, Japan prefecture. We regressed the number of severe cases on the number of severe cases the day prior and the newly onset patients of more than 21 days prior. ResultsWe selected the number of severe cases the day prior and the number of newly onset patients on 21 and 28 days prior as explanatory variables for explaining the number of severe cases based on the adjusted determinant coefficient. The adjusted coefficient of determination was greater than 0.995 and indicated good fit. Prospective out of sample three-week prediction forecast the peak date precisely, but the level was not t. Discussion and ConclusionA reason for the gap in the prospective prediction might be the emergence of variant strains.

Estimating SARS-CoV-2 reproduction number by infection location in Japan

BackgroundCOVID-19 infectiousness might differ by infection location. Nevertheless, no such study of infectiousness has been reported. ObjectThe study objective was estimation of the reproduction number by infection location. MethodPatients who infected no one were ignored because their reliability might be lower than that of patients who infected more than one person. On the assumption that the histogram follows an exponential distribution, we estimated the reproduction number from the histogram of the number of people infected by the same patient. ResultsNight entertainment venues showed the greatest infectiousness, followed by facilities for elderly people and hospitals. Nursery schools and workplaces were followed by homes, with the lowest infectiousness. Discussion and ConclusionCountermeasures under the second declaration of emergency status targeted restaurants. However, infectiousness at restaurants was not high. Comparable to those of universities and karaoke, and not significantly different from homes: the least infectious location studied.

Estimating SARS-CoV-2 variant strain infectiousness in Japan as of March 28, 2021

BackgroundA variant strain of SARS-CoV-2, VOC202012/01, emerged in the UK in September, 2020. Its infectiousness was estimated as higher than that of the original strain. ObjectWe estimated the infectiousness of the variant strain of SARS-CoV-2 in comparison to that of the original strain under conditions prevailing in Japan. MethodsWe estimated infectiousness through a simple susceptible-infected-recovered (SIR) model by strain. The study period was March 1-28, 2020. The information used for the study was available as of April 3, 2020. ResultsThe estimated reproduction number of the SARS-CoV-2 variant strain was 1.799; its 95% CI was [1.642, 1.938]. The onset date of the first case in Japan was estimated as December 4 ([November 16, December 14]), 2020. However, infectiousness of the original strain was estimated as 1.123 ([1.093, 1.166]). Discussion and ConclusionWe demonstrated that infectiousness increased by 0.684 or 60%, increasing from the original to the variant. That finding might be comparable to that of a study conducted in the UK. However, the difference must be monitored continuously and carefully.

Prediction of severe COVID-19 cases requiring a ventilator in Tokyo, Japan

BackgroundTo avoid exhaustion of medical resources by COVID-19, policy-makers must predict care needs, specifically the proportion of severe cases likely to need ventilator care. ObjectiveThis study was designed to use a statistical model to elucidate dynamics of severe cases in Tokyo and to discuss the timing of effective policy activation. MethodsThe study extended from April 27 through October 18, 2020 in Japans Tokyo Metropolitan area. Medical exhaustion was defined as use of more than half of the ventilator capacity available before the COVID-19 outbreak. We regressed the number of severe cases on the newly onset patients of more than 14 days prior. As earlier research indicated, the COVID-19 severity changed at the end of May. Therefore, we added dummy variables to reflect changing severity from June and its product with newly onset patients as the explanatory variable. Then we calculated the threshold using R(t): R(t)=0.99 for the number of patients 14 days prior was used as a threshold at which strong countermeasures should be activated to keep to avoid medical exhaustion. ResultsThe critical number signaling medical exhaustion in Tokyo was defined as 655 cases. We selected 15, 30, 60 and 90 days prior as explanatory variables for explaining the number of severe cases. A coefficient of determination larger than 0.95 was inferred as indicating good fit. The threshold was estimated as more than 4500 cases for R(t)=1.1 and monotonically decreasing by R(t) to be 600 cases for R(t)=2.5. Discussion and ConclusionResults showed that newly onset patients reported more than 14 days prior can explain the number of severe cases very well. We also confirmed the threshold number of patients 14 days prior by R(t) for which strong countermeasures should be activated to avoid medical exhaustion with R(t)=0.99. This method is expected to be useful for countermeasure activation policies for Tokyo.

Optimal mobility restriction minimizing COVID-19 and excess suicide deaths in Japan

BackgroundStrict countermeasures for COVID-19 outbreak such as lockdowns and voluntary restrictions against going out might have reduced mortality because of COVID-19 directly, but might have raised suicide rates. ObjectWe examined best policies for minimizing overall mortality attributable to COVID-19 directly, and excess mortality by suicide because of COVID-19. MethodWe regressed the estimated excess mortality attributable to suicide deaths against mobility-restrictive measures. Mortality attributable to COVID-19 directly was estimated through association between the effective reproduction number and mobility. We sought the best mobility restriction for minimizing overall deaths. ResultsSignificant association was found between mobility and suicide, but the data were very few. Results showed the best mobility level as 65.5, which represents a 34.5% reduction in mobility from the normal level. Discussion and ConclusionAn overly restrictive policy inducing lower than optimal mobility led to higher total mortality.

Excess Mortality in Suicide caused by COVID-19 in Japan

BackgroundCountermeasures against COVID-19 outbreak such as lockdown and voluntary restrictions against going out adversely affect human stress and economic activity. Particularly, this stress might lead to suicide. ObjectWe examined excess mortality attributable to suicide caused by COVID-19. Method: We applied the NIID model to suicide deaths from October 2009 through September, 2021 for the whole of Japan by gender. Effects of the great earthquake that struck in eastern Japan on March 11, 2011 were incorporated into the estimation model. Results: Significant excess mortality in suicide was found between July, 2020 and July, 2021 for both genders. However, in August and September, 2021, excess mortality in suicide was detected only in female. It was greater among females than among males. In total, 2950 excess cases of mortality were identified. Discussion and ConclusionExcess mortality during the four months was more than two times greater than the number of COVID-19 deaths confirmed by PCR testing. Countermeasures against COVID-19 should be chosen carefully in light of suicide effects.

Rule of thumb in human intelligence for assessing the COVID-19 outbreak in Japan

BackgroundThe COVID-19 outbreak in Japan exhibited its third peak at the end of 2020. Mathematical modelling and developed AI cannot explain several peaks in a single year. ObjectThis study was conducted to evaluate a rule of thumb for prediction from past wave experiences. MethodWe rescaled the number of newly infected patients as 100% at the peak and checked similarities among waves. Then we extrapolated the courses of the third and later waves. ResultsResults show some similarity around the second and the third waves. Based on this similarity, we expected the bottom of the third wave will show 2131 newly positive patients including asymptomatic patients at around the end of February, 2021. Discussion and ConclusionWe can infer the course of the third wave from similarity with the second wave. Mathematical modelling has been unable to do it, even when AI was used for prediction. Performance of the rule of thumb used with human intelligence might be superior to that of AI under these circumstances.

Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan

BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan. ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan. MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model. ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November. Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia.

An Estimation of Reproduction Number of SARS-CoV-2 by Age Class for Age Classes in Japan

BackgroundInfectiousness of COVID-19 by age class inferred from the infection source and by infected people might be different. However, studies of such infectiousness have not been reported. ObjectThe object of this study was estimation of reproduction numbers by age class of the source of infection and the infected persons. To do so, after examining a new procedure for reproduction number estimation, we checked infected places by age class of the source of infection and the infected persons. MethodWe ignore patients who infected no one because their reliability might be lower than that of patients who infected more than one person. We estimated the reproduction number from the histogram of the number of the infected people by the same patient, assuming that the histogram follows an exponential distribution. Discussion and ConclusionThe obtained results demonstrated that the effective reproduction numbers for infection from children were very low. They were higher among adult and elderly people than among the same age class. Moreover, although the highest and second-highest infected places were other and at home with some exceptions, the data for infection at hospitals were remarkable among adults and elderly people. Among elderly people, infection at facilities for elderly was also high. Infections at nursing schools, schools, restaurants, and entertainment venues at night were negligible.

Effects of climate conditions, mobility trends, and countermeasures on the COVID-19 outbreak in Japan

BackgroundBefore Olympic and Paralympic Games in Tokyo, whether an audience shall be allowed or not has been a subject of concern in Japan as of early June, 2021. Object: We evaluated effects of professional baseball games with audiences as an example of the large sports events, on COVID-19 infectiousness. MethodWe regressed the effective reproduction number R(t) on a dummy variable for professional baseball games with audiences as along with temperature, humidity, mobility, and countermeasures. We examined two study periods: those including and excluding before initiation of the games in 2020. ResultsEstimation results indicate that the period with audiences exhibited significantly lower infectiousness than when audiences were excluded before initiation of the games with audience attendance. However, audiences were found to have a negative but insignificant effect when compared to the period before initiation of the attended games. Discussion and ConclusionThis study found no clear evidence indicating that big sports events with audiences raise the COVID-19 infectiousness.

Interim evaluation of Google AI forecasting for COVID-19 compared with statistical forecasting by human intelligence in the first week

BackgroundSince June, Google (Alphabet Inc.) has provided forecasting for COVID-19 outbreak by artificial intelligence (AI) in the USA. In Japan, they provided similar services from November, 2020. ObjectWe compared Google AI forecasting with a statistical model by human intelligence. MethodWe regressed the number of patients whose onset date was day t on the number of patients whose past onset date was 14 days prior, with information about traditional surveillance data for common pediatric infectious diseases including influenza, and prescription surveillance 7 days prior. We predicted the number of onset patients for 7 days, prospectively. Finally, we compared the result with Googles AI-produced forecast. We used the discrepancy rate to evaluate the precision of prediction: the sum of absolute differences between data and prediction divided by the aggregate of data. ResultsWe found Google prediction significantly negative correlated with the actual observed data, but our model slightly correlated but not significant. Moreover, discrepancy rate of Google prediction was 27.7% for the first week. The discrepancy rate of our model was only 3.47%. Discussion and ConclusionResults show Googles prediction has negatively correlated and greater difference with the data than our results. Nevertheless, it is noteworthy that this result is tentative: the epidemic curve showing newly onset patients was not fixed.

Effectiveness of COCOA, a COVID-19 contact notification application, in Japan

BackgroundCOCOA, a contact reporting application in Japan, was launched at the end of June 2020. ObjectWe assessed effectiveness of COCOA. MethodAfter developing a simple susceptible-infected-recovery model with COCOA and voluntary restrictions against going out (VRG), we assumed that COCOA can reduce infectiousness by 10-50% points through self-quarantine at home after receiving notification from COCOA. ResultsCOCOA alone is insufficient to halt an outbreak. Even if the entire population were to use COCOA, the reproduction number would be 1.31. However, if VRG were 15%, about half of the maximum VRG effectiveness under the emergency state declaration, then 10% COCOA use by a population can reduce the reproduction number to less than one. ConclusionSignificant effects of COCOA for reducing the reproduction number were found. However, without VRG, COCOA alone is insufficient to control an outbreak.

No Excess Mortality of COVID-19 in Japan until April, 2020

BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.

Asymptomatic infection and herd immunity of COVID-19 in Wuhan and Japan

BackgroundIn Japan, as a measure to inhibit the COVID-19 outbreak, voluntary restrictions against going out (VRG) have been applied. ObjectMobility information provided by Apple Inc. and NTT Docomo were assessed in terms of its usefulness in predicting conditions exacerbating an outbreak. MethodA polynomial function was applied to daily Apple and Docomo data to calculate the observed R(t). ResultsThe correlation coefficient among Apple and Docomo data was 0.91. The adjusted coefficient of determination for R(t) for the whole study period was higher using Docomo data than when Apple data were used. When we regressed R(t) on daily Apple and Docomo data simultaneously, the estimated coefficient of Docomo data was not significant. Discussion and ConclusionWe demonstrated that Apple mobility data might be superior to Docomo data for explaining the entire course of the COVID-19 outbreak in Japan.

First peak of COVID-19 outbreak in Japan might pass as of April 26, 2020

BackgroundIn Japan, as a countermeasure against the COVID-19 outbreak, voluntary restrictions against going out (VRG) have been applied. ObjectWe examined mobility information provided by Apple Inc. to a susceptible-infected-recovery model. MethodWhen applying a polynomial function to daily Apple data with the SIR model, we presumed the function up to a cubic term as in our earlier study. ResultsEstimation results demonstrated R0 as 1.507 and its 95% confidence interval was [1.502, 1.509].. The estimated coefficients of Apple data was 1.748 and its 95% confidence interval was [1.731, 1.788]. Discussion and ConclusionResults show that mobility data from Apple Inc. can explain the entire course of the outbreak in COVID-19 in Japan. Therefore, monitoring Apple data might be sufficient to adjust control measures to maintain an effective reproduction number of less than one.

Interim evaluation of emergency declaration in Japan in the first week of the COVID-19 outbreak

BackgroundJapans Prime Minister Abe declared an emergency to control the COVID-19 outbreak on April 7, 2020. He asked almost half of the population of Japan to reduce their personal contacts by 70-80%. ObjectThis study estimates the effectiveness of that emergency declaration. Method: We applied a simple susceptible-infected-recovery model to data of patients with symptoms in Tokyo, Japan for January 14 - April 21 as of April 22. We estimate the reproduction number in four periods: R0 before voluntary event cancellation and school closure (VECSC) which was introduced since February 27 to March 19, Rv during the VECSC, Ra after VECSC, and Re after the emergency declaration. ResultsResults suggest that the value of R0 was estimated as 1.267; its range was [1.214, 1.341]. However, Rv was estimated as 2.360 [1.844, 2.623]. Ra was estimated as 2.307 [2.035, 2.794] and Re was 0.462 [0.347, 0.514]. Discussion and ConcussionOne must be reminded that these results reflect only those at two weeks after the emergency declaration. The reproduction number probably changed thereafter continuously.

Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19

ObjectThe COVID-19 outbreak emerged in late 2019 in China, expanding rapidly thereafter. Even in Japan, epidemiological linkage of transmission was probably lost already by February 18, 2020. From that time, it has been necessary to detect clusters using syndromic surveillance. MethodWe identified common symptoms of COVID-19 as fever and respiratory symptoms. Therefore, we constructed a model to predict the number of patients with antipyretic analgesics (AP) and multi-ingredient cold medications (MIC) controlling well-known pediatric infectious diseases including influenza or RS virus infection. To do so, we used the National Official Sentinel Surveillance for Infectious Diseases (NOSSID), even though NOSSID data are weekly data with 10 day delays, on average. The probability of a cluster with unknown febrile disease with respiratory symptoms is a product of the probabilities of aberrations in AP and MIC, which is defined as one minus the probability of the number of patients prescribed a certain type of drug in PS compared to the number predicted using a model. This analysis was conducted prospectively in 2020 using data from October 1, 2010 through 2019 by prefecture and by age-class. ResultsThe probability of unknown febrile disease with respiratory symptom cluster was estimated as less than 60% in 2020. DiscussionThe most severe limitation of the present study is that the proposed model cannot be validated. A large outbreak of an unknown febrile disease with respiratory symptoms must be experienced, at which time, practitioners will have to "wing it". We expect that no actual cluster of unknown febrile disease with respiratory symptoms will occur, but if it should occur, we hope to detect it.

Forecast of the COVID-19 outbreak, collapse of medical facilities, and lockdown effects in Tokyo, Japan

BackgroundThe number of patients of COVID-19 in Tokyo has been increasing gradually through the end of March, 2020. ObjectSupport for policymaking requires forecasting of the entire course and outcome of the outbreak if a self-restraint in going out is not initiated. Moreover, the effects of a self-restraint in going out must be considered when choosing to initiate one. Method: Data of Tokyo patients with symptoms during January 14 - March 28, 2020 were used to formulate a susceptible-infected-recovered (SIR) model using three age classes and to estimate the basic reproduction number (R0). Based on the estimated R0, We inferred outbreak outcomes and medical burden if a self-restraint in going out were not enacted. Then we estimate the self-restraint in going out effects. ResultsResults suggest R0 as 2.86, with a 95% confidence interval of [2.73, 2.97]. Exhaustion of medical resources can be expected to occur on April 26 if no self-restraint in going out occurs. If a self-restraint in going out were enacted from April 6, and if more than 60% of trips outside the home were restricted voluntarily, then medical care service could be maintained. Discussion and ConclusionThe estimated R0 was similar to that found from other studies conducted in China and Japan. Results demonstrate that a self-restraint in going out with reasonable cooperation of residents is required to maintain medical care.