Epidemiology of coronavirus disease 2019 (COVID-19) in Japan during the first and second waves

SARS-CoV-2 IgG Seroprevalence in the Okinawa Main Island and Remote Islands in Okinawa, Japan, 2020-2021

We estimated the seroprevalence of anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) immunoglobulin G (IgG) in different island groups in Okinawa. A cross-sectional serosurvey was conducted over three periods between July 2020 and February 2021. A total of 2,683 serum samples were collected from six referral medical centers, each covering a separate region in Okinawa. In the main island, the seroprevalence was 0.0% (0/392; 95% confidence interval (CI), 0.0- 0.9%), 0.6% (8/1,448, 0.2-1.1%), and 1.4% (8/582, 0.6-2.7%) during the 1st, 2nd, and 3rd serosurvey, respectively. In remote islands, the seroprevalence was 0.0% (0/144; 95% CI, 0.0-2.5%) and 1.6% (2/123, 0.2-5.8%) during the 2nd and 3rd survey, respectively. The case detection ratio was 2.7 (95% CI, 1.3-5.3) in the main island and 2.8 (0.7-11.1) in remote islands during the 3rd survey. The case detection ratio was the highest in individuals aged 20-29 years (8.3; 95% CI, 3.3-21.4) in the main island and in those aged 50-59 years (14.1; 2.1-92.7) in remote islands, suggesting underreporting of clinical cases by the surveillance system in these subgroups. A serosurvey conducted during an emerging infectious disease epidemic can be useful for validating the reliability of the surveillance system by providing case detection ratio.

A comparative study between first three waves of COVID-19 pandemic with respect to risk factors, initial clinic-demographic profile, severity and outcome

Introduction

During the 2 years and 9 months from March 2020 to December 2022, the SARS-CoV-2 virus raged across the country. Cases occurred in three particular time clusters recognised by World Health Organisation as coronavirus disease 2019 (COVID-19) waves. In this study, we compare the clinical parameters of adult non-obstetric COVID-19 patients admitted to our rural tertiary care hospital during the three distinct waves of the pandemic.

Materials and Methods

Retrospective chart analysis of 272, 853 and 97 patients admitted with SARS-CoV-2 infection to the only rural medical tertiary care centre in the Sunderbans of West Bengal in the first, second and third waves, respectively, was done after obtaining ethical and scientific clearance. Clinical [vital parameters, oxygen requirement, mental status, risk factor assessment, duration of hospital stay, modified-emergency warning score (m-EWS), quick Sequential Organ Failure Assessment (qSOFA), confusion, uraemia, respiratory rate, blood pressure, age ≥ 65 years (CURB65)], epidemiological variables (age, gender, and vaccination status), laboratory parameters and in-hospital outcome were recorded and analysed statistically.

Results

Statistically significant (P < 0.05) m-EWS and qSOFA scores were recorded during the second wave of the pandemic. The second wave also recorded the highest mortality (14.89%) compared to the first (12.87%) and third (11.96%) waves, though this was not statistically significant. The highest duration of hospital stay was recorded in the first wave of the pandemic (mean = 9.99 days, P < 0.01). The difference in mortality rates between patients with and without co-morbidity (P < 0.05) was observed during Wave-1, across any pandemic wave, and overall but not in Wave-2 and Wave-3.

Conclusion

The second wave of the COVID-19 pandemic was the most severe in comparison with the other two waves, while the outcome was poorer in those with co-morbidities, especially in the first wave.

Epidemiological impact of travel enhancement on the inter-prefectural importation dynamics of COVID-19 in Japan, 2020

Mobility restrictions were widely practiced to reduce contact with others and prevent the spatial spread of COVID-19 infection. Using inter-prefectural mobility and epidemiological data, a statistical model was devised to predict the number of imported cases in each Japanese prefecture. The number of imported cases crossing prefectural borders in 2020 was predicted using inter-prefectural mobility rates based on mobile phone data and prevalence estimates in the origin prefectures. The simplistic model was quantified using surveillance data of cases with an inter-prefectural travel history. Subsequently, simulations were carried out to understand how imported cases vary with the mobility rate and prevalence at the origin. Overall, the predicted number of imported cases qualitatively captured the observed number of imported cases over time. Although Hokkaido and Okinawa are the northernmost and the southernmost prefectures, respectively, they were sensitive to differing prevalence rate in Tokyo and Osaka and the mobility rate. Additionally, other prefectures were sensitive to mobility change, assuming that an increment in the mobility rate was seen in all prefectures. Our findings indicate the need to account for the weight of an inter-prefectural mobility network when implementing countermeasures to restrict human movement. If the mobility rates were maintained lower than the observed rates, then the number of imported cases could have been maintained at substantially lower levels than the observed, thus potentially preventing the unnecessary spatial spread of COVID-19 in late 2020.

Mortality-associated Risk Factors in Hospitalized COVID-19 Patients in Japan: Findings of the CLOT-COVID Study

BACKGROUND

Reports of mortality-associated risk factors in patients with the novel coronavirus disease 2019 (COVID-19) are limited.

METHODS

We evaluated the clinical features that were associated with mortality among patients who died during hospitalization (n = 158) and those who were alive at discharge (n = 2,736) from the large-scale, multicenter, retrospective, observational cohort CLOT-COVID study, which enrolled consecutively hospitalized COVID-19 patients from 16 centers in Japan from April to September 2021. Data from 2,894 hospitalized COVID-19 participants of the CLOT-COVID study were analyzed in this study.

RESULTS

Patients who died were older (71.1 years vs 51.6 years, P < 0.001), had higher median D-dimer values on admission (1.7 µg/mL vs 0.8 µg/mL, P < 0.001), and had more comorbidities. On admission, the patients who died had more severe COVID-19 than did those who survived (mild: 16% vs 63%, moderate: 47% vs 31%, and severe: 37% vs 6.2%, P < 0.001). In patients who died, the incidence of thrombosis and major bleeding during hospitalization was significantly higher than that in those who survived (thrombosis: 8.2% vs 1.5%, P < 0.001; major bleeding: 12.7% vs 1.4%, P < 0.001). Multivariable logistic regression analysis revealed that age >70 years, high D-dimer values on admission, heart disease, active cancer, higher COVID-19 severity on admission, and development of major bleeding during hospitalization were independently associated with a higher mortality risk.

CONCLUSION

This large-scale observational study in Japan identified several independent risk factors for mortality in hospitalized patients with COVID-19 that could facilitate appropriate risk stratification of patients with COVID-19.

Effect of the COVID-19 pandemic on allogeneic stem cell transplantation in Japan

The coronavirus disease 2019 (COVID-19) pandemic affected healthcare quality and access worldwide and may also have negatively affected the frequency and outcomes of allogeneic hematopoietic stem cell transplantation (HSCT). We evaluated the effect of the pandemic on allogeneic HSCT in Japan. Our subjects were patients who received allogeneic HSCT during January 2018-December 2020 in Japan. We assessed differences in yearly number of allogeneic HSCTs and 1-year outcomes in 2020 versus both 2019 and 2018. The total number of patients who received allogeneic HSCT increased from 3621 patients in 2018 and 3708 patients in 2019 to 3865 patients in 2020. Some following changes in allogeneic HSCT methods were observed: patients were older, fewer patients received bone marrow transplantation, fewer patients received transplants from unrelated donors, fewer patients received transplants from matched donors, more patients received reduced-intensity conditioning, and fewer patients received anti-thymocyte globulin in 2020 compared with previous years. HSCT outcomes were not affected, as 1-year overall survival was not significantly different (65.8% in 2020, vs. 66.5% in 2019 and 66.4% in 2018). Our results suggest that we can maintain transplant care during the pandemic by controlling the spread of COVID-19 and modifying HSCT methods.

Go To Travel campaign and the geographic spread of COVID-19 in Japan

Background

In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020.

Methods

We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign.

Results

Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign.

Conclusions

The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07799-0.

Basic reproduction number of the COVID-19 Delta variant: Estimation from multiple transmission datasets

The basic reproduction number, $ R_0 $, plays a central role in measuring the transmissibility of an infectious disease, and it thus acts as the fundamental index for planning control strategies. In the present study, we apply a branching process model to meticulously observed contact tracing data from Wakayama Prefecture, Japan, obtained in early 2020 and mid-2021. This allows us to efficiently estimate $ R_0 $ and the dispersion parameter $ k $ of the wild-type COVID-19, as well as the relative transmissibility of the Delta variant and relative transmissibility among fully vaccinated individuals, from a very limited data. $ R_0 $ for the wild type of COVID-19 is estimated to be 3.78 (95% confidence interval [CI]: 3.72-3.83), with $ k = 0.236 $ (95% CI: 0.233-0.240). For the Delta variant, the relative transmissibility to the wild type is estimated to be 1.42 (95% CI: 0.94-1.90), which gives $ R_0 = 5.37 $ (95% CI: 3.55-7.21). Vaccine effectiveness, determined by the reduction in the number of secondary transmissions among fully vaccinated individuals, is estimated to be 91% (95% CI: 85%-97%). The present study highlights that basic reproduction numbers can be accurately estimated from the distribution of minor outbreak data, and these data can provide further insightful epidemiological estimates including the dispersion parameter and vaccine effectiveness regarding the prevention of transmission.