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Quantifying the impact on COVID-19 transmission from a single event has been difficult due to the virus transmission dynamics, such as lag from exposure to reported infection, non-linearity arising from the person-to-person transmission, and the modifying effects of non-pharmaceutical interventions over time. To address these issues, we aimed to estimate the COVID-19 transmission risk of social events focusing on the Japanese Coming-of-Age Day and Coming-of-Age ceremony in which "new adults" practice risky behavior on that particular day.Using national surveillance data in Japan in 2021 and 2022, we conducted difference-in-differences regression against COVID-19 incidences by setting "new adults" cases as the treatment group and the cases 1 year younger or older than these "new adults" as the control group. In addition, we employed a triple differences approach to estimate the risk of holding the Coming-Age ceremony by using a binary variable regarding the presence or absence of the ceremony in each municipality.We estimated the relative risks (RRs) of the Coming-of-Age Day as 1.27 (95% confidence interval [CI] 1.02-1.57) in 2021 and 3.22 (95% CI 2.68-3.86) in 2022. The RR of the Coming-of-Age ceremony was also large, estimated as 2.83 (1.81-4.43) in 2022.When planning large social events, it is important to be aware of the unique risks associated with these gatherings, along with effective public health messages to best communicate these risks.

In response to the outbreak of coronavirus disease 2019 (COVID-19) in Japan, a national COVID-19 cluster taskforce (comprising governmental and nongovernmental experts) was established to support the country’s Ministry of Health, Labour and Welfare in conducting daily risk assessment. The assessment was carried out using established infectious disease surveillance systems; however, in the initial stages of the pandemic these were not sufficient for real-time risk assessment owing to limited accessibility, delay in data entry and inadequate case information. Also, local governments were publishing anonymized data on confirmed COVID-19 cases on their official websites as daily press releases. We developed a unique database for nationwide real-time risk assessment that included these case lists from local government websites and integrated all case data into a standardized format. The database was updated daily and checked systematically to ensure comprehensiveness and quality. Between 15 January 2020 and 15 June 2021, 776 459 cases were logged in the database, allowing for analysis of real-time risk from the pandemic. This semi-automated database was used in daily risk assessments, and to evaluate and update control measures to prevent community transmission of COVID-19 in Japan. The data were reported almost every week to the Japanese Government Advisory Panel on COVID-19 for public health responses.

BACKGROUND: Quantifying the impact on COVID-19 transmission from a single event has been difficult due to the virus transmission dynamics, such as lag from exposure to reported infection, non-linearity arising from the person-to-person transmission, and the modifying effects of non-pharmaceutical interventions over time. To address these issues, we aimed to estimate the COVID-19 transmission risk of social events focusing on the Japanese Coming-of-Age Day and Coming-of-Age ceremony in which "new adults" practice risky behavior on that particular day. METHODS: Using national surveillance data in Japan in 2021 and 2022, we conducted difference-in-differences regression against COVID-19 incidences by setting "new adults" cases as the treatment group and the cases 1 year younger or older than these "new adults" as the control group. In addition, we employed a triple differences approach to estimate the risk of holding the Coming-Age ceremony by using a binary variable regarding the presence or absence of the ceremony in each municipality. RESULTS: We estimated the relative risks (RRs) of the Coming-of-Age Day as 1.27 (95% confidence interval [CI] 1.02-1.57) in 2021 and 3.22 (95% CI 2.68-3.86) in 2022. The RR of the Coming-of-Age ceremony was also large, estimated as 2.83 (1.81-4.43) in 2022. CONCLUSIONS: When planning large social events, it is important to be aware of the unique risks associated with these gatherings, along with effective public health messages to best communicate these risks.

Introduction Coronavirus disease 2019 (COVID-19) has caused unprecedented global morbidity and mortality. Japan has faced three epidemic "waves" of COVID-19 from early 2020 through early 2021. Here we narratively review the three waves in Japan, describe the key epidemiologic features of COVID-19, and discuss lessons learned. Methods We assessed publicly available surveillance data, routine surveillance reports, and other relevant sources-multiple indicators were monitored to improve interpretation of surveillance data. Weekly trends for each wave were described based on the number of case notifications; number of tests performed; proportion of those tests that were positive for the novel coronavirus; the prevalent number of COVID-19 hospitalizations (total hospitalizations and those categorized as severe); and number of COVID-19 deaths. For each indicator and wave, we recorded the first calendar week to show an increase over two consecutive previous weeks, along with the peak week. Results The spring wave was characterized by detection of cases imported from China, followed by notifications of sporadic cases without travel history, clusters, and mild/asymptomatic cases. The summer wave saw a large increase in notifications and a younger age distribution, but in the context of increased testing with lower test positivity. The winter wave brought considerable morbidity and mortality, surpassing the cumulative case counts and fatalities from the earlier waves, with high peak values. Overall, relative to the first wave, the burden of severe outcomes was lower in the second and higher in the third wave, but varied by prefecture. In all three waves, severe outcomes peaked after notification counts and test positivity peaked; severe outcomes were also consistently skewed toward the elderly. Conclusions Important lessons were learned from each wave and across waves-some aspects remained constant, while others changed over time. In order to rapidly detect an increase in incidence, continuous, timely, and sensitive surveillance-using multiple information sources with careful interpretations-will be key in COVID-19 control.

BackgroundsThis study analysed secondary attack rates (SARs), comparing alpha variants, delta variants and non-variants of concern (non-VOCs), using clinical and close-contact tracing data.MethodsWe analysed coronavirus disease 2019 (COVID-19) case data from a database and contact tracing data between July and October 2020 (Cohort 1) and April 2021 (Cohort 2) and between July and August 2021 (Cohort 3) in a city in Toyama prefecture, Japan. Real-time polymerase chain reaction (PCR) was used to detect the N501Y (alpha variant) and L452R (delta variant) mutations. We calculated the SARs considering close contact, index case and contact setting characteristics. Relative risks (RRs) of secondary attack were analysed using Poisson regression models.ResultsAmong 123 index cases and 530 close contacts in Cohort 1, 246 index cases and 988 close contacts in Cohort 2, and 304 index cases and 984 close contacts in Cohort 3, the SARs associated with alpha and delta variant index cases were 1.47 times and 1.89 times higher than those associated with non-VOC index cases. Delta variant index cases were associated with the highest SAR (29.2%) in the same household and a 2.40-fold (95% CI: 1.62-3.56) higher risk of transmission than non-VOC index cases. The age and symptoms of index cases were associated with the SAR.ConclusionsWe confirmed that VOC index cases were associated with increased transmissibility. Population longitudinal surveillance data linked with contact-tracing data provide valuable information for elucidation of the characteristics of newly emerging variants.

Objsectives: Super-spreading events caused by overdispersed secondary transmission is crucial in the transmission of coronavirus disease 2019 (COVID-19). However, the exact level of overdispersion, demographics, and other factors associated with secondary transmission remain elusive. In this study, we aimed to elucidate the frequency and patterns of secondary transmission of SARS-CoV-2 in Japan. Methods: We analyzed 16,471 cases between January and August 2020. We generated the number of secondary cases distribution and estimated the dispersion parameter (k) by fitting the negative binomial distribution in each phase. The frequencies of the secondary transmission were compared by demographic and clinical characteristics, calculating the odds ratio by logistic regression models. Results: We observed that 76.7% of the primary cases did not generate secondary cases with an estimated dispersion parameter k of 0.23. The demographic patterns of primary-secondary cases differed between phases, with 20–69 years being the predominant age group. There were higher proportions of secondary cases among elderly, symptomatic cases, and those with two days or more between onset and confirmation. Conclusions: The study demonstrated the estimation of the frequency of secondary transmission of SARS-CoV-2 and the characteristics of people who generated the secondary transmission.

Detection and isolation of infected people are believed to play an important role in the control of the COVID-19 pandemic. Some countries conduct large-scale screenings for testing, whereas others test mainly people with high prior probability of infection such as showing severe symptoms and/or having an epidemiological link with a known or suspected case or cluster of cases. However, what a good testing strategy is and whether the difference in testing strategy shows a meaningful, measurable impact on the COVID-19 epidemic remain unknown. Here, we showed that patterns of association between effective reproduction number (Rt) and test positivity rate can illuminate differences in testing situation among different areas, using global and local data from Japan. This association can also evaluate the adequacy of current testing systems and what information is captured in COVID-19 surveillance. The differences in testing systems alone cannot predict the results of epidemic containment efforts. Furthermore, monitoring test positivity rates and severe case proportions among the nonelderly can predict imminent case count increases. Monitoring test positivity rates in conjunction with the concurrent Rt could be useful to assess and strengthen public health management and testing systems and deepen understanding of COVID-19 epidemic dynamics.

International audience; Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein-protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein\ud requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of\ud investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene\ud prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus\ud performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as\ud complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level.\ud Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length\ud cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also\ud manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene\ud database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following:\ud integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms,\ud non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein\ud three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic\ud microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB\ud analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information\ud build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates\ud (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for nonprotein-coding\ud RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within\ud human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together\ud with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing\ud phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources\ud needed for the exploration of human biology and pathology