Increased SARS-CoV-2 seroprevalence and spread of infection without awareness among healthcare workers through 2020-2022 in a Japanese medical center.

Despite Japan's high vaccination coverage, daily numbers of new COVID-19 cases have been high. However, studies on the seroprevalence among Japanese people and the causative factors for rapid spread have remained limited. In this study, we aimed to examine the seroprevalence and associated factors in healthcare workers (HCWs) of a medical center in Tokyo using blood samples drawn at annual check-ups from 2020 to 2022. We found that of the 3,788 HCWs in 2022 (by mid-June), 669 were seropositive for N-specific antibodies (tested by Roche Elecsys Anti-SARS-CoV-2 assay); the seroprevalence surged from 0.3% in 2020 and 1.6% in 2021 to 17.7% in 2022. Notably, our study found 325 (48.6%; 325/669) cases were infected without awareness. Among those with a previously PCR-confirmed SARS-CoV-2 infection during the past three years, 79.0% (282/357) were found after January 2022, after the Omicron variant was first detected in Tokyo at the end of 2021. This study indicates the fast spread of the SARS-CoV-2 among HCWs during the Omicron surge in Japan. The high percentage of infection without awareness may be a key driving factor causing rapid person-to-person transmission, as shown in this medical center with high vaccination coverage and strict infection control measures.

Mortality Prediction of COVID-19 in Hospitalized Patients Using the 2020 Diagnosis Procedure Combination Administrative Database of Japan.

Objectives Numerous people have died from coronavirus disease 2019 (COVID-19) infection. Identifying crucial predictive biomarkers of disease mortality is critical to support decision-making and logistic planning in healthcare systems. This study investigated the association between mortality and medical factors and prescription records in 2020 in Japan, where COVID-19 prevalence and mortality remain relatively low. Methods This retrospective cohort study analyzed anonymous administrative data from the Diagnosis Procedure Combination (DPC) database in Japan. Results A total of 22,795 patients were treated in DPC hospitals in 2020 in Japan, and of these, 5,980 patients over 50 years old were hospitalized, with 299 (5.0%) dying. There were 2,399 severe patients among 11,440 total hospitalized patients (all ages). The results of a logistic model analysis revealed that an older age, male sex, Parkinson's disease, cerebrovascular diseases, and chronic kidney diseases were risk factors for mortality. A machine learning analysis identified an older age, male sex (mortality), pneumonia, drugs for acid-related disorders, analgesics, anesthesia, upper respiratory tract disease, drugs for functional gastrointestinal disorders, drugs for obstructive airway diseases, topical products for joint and muscular pain, diabetes, lipid-modifying agents, calcium channel blockers, drugs for diabetes, and agents acting on the renin-angiotensin system as risk factors for a severe status. Conclusions This COVID-19 mortality risk tool is a well-calibrated and accurate model for predicting mortality risk among hospitalized patients with COVID-19 in Japan, which is characterized by a relatively low COVID-19 prevalence, aging society, and high population density. This COVID-19 mortality prediction model can assist in resource utilization and patient and caregiver education and be useful as a risk stratification instrument for future research trials.

Changes in social environment due to the state of emergency and Go To campaign during the COVID-19 pandemic in Japan: An ecological study.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic in Japan, the state of emergency, as a public health measure to control the spread of COVID-19, and the Go To campaign, which included the Go To Travel and Go To Eat campaigns and was purposed to stimulate economic activities, were implemented. This study investigated the impact of these government policies on COVID-19 spread. METHODS: This ecological study included all 47 prefectures in Japan as samples between February 3 and December 27, 2020. We used COVID-19 cases and mobility as variables. Additionally, places where social contacts could accrue, defined as restaurants, companies, transportation, and tourist spots; mean temperature and humidity; the number of inhabitants in their twenties to fifties; and the number of COVID-19 cases in the previous period, which were factors or covariates in the graphical modeling analysis, were divided into five periods according to the timing of the implementation of the state of emergency and Go To campaign. RESULTS: Graphical changes occurred throughout all five periods of COVID-19. During the state of emergency (period 2), a correlation between COVID-19 cases and those before the state of emergency (period 1) was observed, although this correlation was not significant in the period after the state of emergency was lifted (period 3). During the implementation of Go To Travel and the Go To Eat campaigns (period 5), the number of places where social contacts could accrue was correlated with COVID-19 cases, with complex associations and mobility. CONCLUSIONS: This study confirms that the state of emergency affected the control of COVID-19 spread and that the Go To campaign led to increased COVID-19 cases due to increased mobility by changing behavior in the social environment where social contacts potentially accrue.