Protection against SARS-CoV-2 BA.4 and BA.5 subvariants via vaccination and natural infection: A modeling study.

With continuing emergence of new SARS-CoV-2 variants, understanding the proportion of the population protected against infection is crucial for public health risk assessment and decision-making and so that the general public can take preventive measures. We aimed to estimate the protection against symptomatic illness caused by SARS-CoV-2 Omicron variants BA.4 and BA.5 elicited by vaccination against and natural infection with other SARS-CoV-2 Omicron subvariants. We used a logistic model to define the protection rate against symptomatic infection caused by BA.1 and BA.2 as a function of neutralizing antibody titer values. Applying the quantified relationships to BA.4 and BA.5 using two different methods, the estimated protection rate against BA.4 and BA.5 was 11.3% (95% confidence interval [CI]: 0.01-25.4) (method 1) and 12.9% (95% CI: 8.8-18.0) (method 2) at 6 months after a second dose of BNT162b2 vaccine, 44.3% (95% CI: 20.0-59.3) (method 1) and 47.3% (95% CI: 34.1-60.6) (method 2) at 2 weeks after a third BNT162b2 dose, and 52.3% (95% CI: 25.1-69.2) (method 1) and 54.9% (95% CI: 37.6-71.4) (method 2) during the convalescent phase after infection with BA.1 and BA.2, respectively. Our study indicates that the protection rate against BA.4 and BA.5 are significantly lower compared with those against previous variants and may lead to substantial morbidity, and overall estimates were consistent with empirical reports. Our simple yet practical models enable prompt assessment of public health impacts posed by new SARS-CoV-2 variants using small sample-size neutralization titer data to support public health decisions in urgent situations.

Projecting the COVID-19 immune landscape in Japan in the presence of waning immunity and booster vaccination.

Coronavirus disease 2019 (COVID-19) booster vaccination has been implemented globally in the midst of surges in infection due to the Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of the present study was to present a framework to estimate the proportion of the population that is immune to symptomatic SARS-CoV-2 infection with the Omicron variant (immune proportion) in Japan, considering the waning of immunity resulting from vaccination and naturally acquired infection. We quantified the decay rate of immunity against symptomatic infection with Omicron conferred by the second and third doses of COVID-19 vaccine. We estimated the current and future vaccination coverage for the second and third vaccine doses from February 17, 2021 to August 1, 2022 and used data on the confirmed COVID-19 incidence from February 17, 2021 to April 10, 2022. From this information, we estimated the age-specific immune proportion over the period from February 17, 2021 to August 1, 2022. Vaccine-induced immunity, conferred by the second vaccine dose in particular, was estimated to rapidly wane. There were substantial variations in the estimated immune proportion by age group because each age cohort experienced different vaccination rollout timing and speed as well as a different infection risk. Such variations collectively contributed to heterogeneous immune landscape trajectories over time and age. The resulting prediction of the proportion of the population that is immune to symptomatic SARS-CoV-2 infection could aid decision-making on when and for whom another round of booster vaccination should be considered. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021.

Background: Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods: We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (R t ) before and after these interventions, and then analyzed the relationship between lower R t values and each PHSM. Results: With implementation of pre-emergency measures (PEM) in 16 prefectures, the R t was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated R t < 1, and the average relative reduction was 26%-39%. No single intervention was identified that uniquely resulted in an R t value < 1. Conclusion: An SoE can substantially reduce the R t and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the R t value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

Number of averted COVID-19 cases and deaths attributable to reduced risk in vaccinated individuals in Japan.

Background: In Japan, vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was initiated on 17 February 2021, mainly using messenger RNA vaccines and prioritizing health care professionals. Whereas nationwide vaccination alleviated the coronavirus disease 2019 (COVID-19)-related burden, the population impact has yet to be quantified in Japan. We aimed to estimate the numbers of COVID-19 cases and deaths prevented that were attributable to the reduced risk among vaccinated individuals via a statistical modeling framework. Methods: We analyzed confirmed cases registered in the Health Center Real-time Information-sharing System on COVID-19 (3 March-30 November 2021) and publicly reported COVID-19-related deaths (24 March-30 November 2021). The vaccination coverage over this time course, classified by age and sex, was extracted from vaccine registration systems. The total numbers of prevented cases and deaths were calculated by multiplying the daily risk differences between unvaccinated and vaccinated individuals by the population size of vaccinated individuals. Findings: For both cases and deaths, the averted numbers were estimated to be the highest among individuals aged 65 years and older. In total, we estimated that 564,596 (95% confidence interval: 477,020-657,525) COVID-19 cases and 18,622 (95% confidence interval: 6522-33,762) deaths associated with SARS-CoV-2 infection were prevented owing to vaccination during the analysis period (i.e., fifth epidemic wave, caused mainly by the Delta variant). Female individuals were more likely to be protected from infection following vaccination than male individuals whereas more deaths were prevented in male than in female individuals. Interpretation: The vaccination program in Japan led to substantial reductions in the numbers of COVID-19 cases and deaths (33% and 67%, respectively). The preventive effect will be further amplified during future pandemic waves caused by variants with shared antigenicity. Funding: This project was supported by the Japan Science and Technology Agency; the Japan Agency for Medical Research and Development; the Japan Society for the Promotion of Science; and the Ministry of Health, Labour and Welfare.

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021

Background Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact;these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (Rt) before and after these interventions, and then analyzed the relationship between lower Rt values and each PHSM. Results With implementation of pre-emergency measures (PEM) in 16 prefectures, the Rt was estimated to be < 1 in six prefectures;its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated Rt < 1, and the average relative reduction was 26%–39%. No single intervention was identified that uniquely resulted in an Rt value < 1. Conclusion An SoE can substantially reduce the Rt and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the Rt value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

Response to COVID-19 during the Tokyo Olympic Games: Did we properly assess the risk?

BACKGROUND: The number of coronavirus disease 2019 (COVID-19) cases was expected to increase during the Tokyo Olympic Games because of the increased physical contact within and between the domestic population and international participants of the Games. The rapid rise of the Delta variant (B.1.617) in Japan meant that hosting the Olympic Games without any restrictions was likely to lead to an increase in cases. We aimed to quantitatively assess possible COVID-19 response strategies for the Olympic Games, comparing the prevalence of severe cases and the cumulative number of COVID-19 deaths via scenario analysis. METHODS: We used a discrete-time deterministic compartmental model structured by age group. Parameters were calibrated using the age-stratified COVID-19 incidence data in Osaka. Numerical simulations incorporated the planned Olympics Games and nationwide COVID-19 vaccination into the proposed model, alongside various subjects and types of countermeasures. RESULTS: Our model-informed approach suggested that having spectators at the Tokyo Olympic Games could lead to a surge in both cases and hospitalization. Projections for the scenario that explicitly incorporated the spread of the Delta variant (i.e., time-dependent increase in the relative transmissibility) showed that imposing stringent social distancing measures (Rt=0.7) for more than 8 weeks from the end of the Olympic Games might be required to suppress the prevalence of severe cases of COVID-19 to avoid overwhelming the intensive care unit capacity in Tokyo. CONCLUSIONS: Our modeling analyses guided an optimal choice of COVID-19 response during and after the Tokyo Olympic Games, allowing the epidemic to be brought under control despite such a large mass gathering.

Monitoring the COVID-19 immune landscape in Japan.

OBJECTIVES: COVID-19 vaccination in Japan started on February 17, 2021. Because the timing of vaccination and the risk of severe COVID-19 greatly varied with age, the present study aimed to monitor the age-specific fractions of the population who were immune to SARS-CoV-2 infection after vaccination. METHODS: Natural infection remained extremely rare, accounting for less than 5% of the population by the end of 2021; thus, we ignored natural infection-induced immunity and focused on vaccine-induced immunity. We estimated the fraction of the population immune to infection by age group using vaccination registry data from February 17, 2021, to October 17, 2021. We accounted for two important sources of delay: (i) reporting delay and (ii) time from vaccination until immune protection develops. RESULTS: At the end of the observation period, the proportion of individuals still susceptible to SARS-CoV-2 infection substantially varied by age and was estimated to be ≥90% among people aged 0-14 years, in contrast to approximately 20% among the population aged ≥65 years. We also estimated the effective reproduction number over time using a next-generation matrix while accounting for differences in the proportion immune to infection by age. CONCLUSION: The COVID-19 immune landscape greatly varied by age, and a substantial proportion of young adults remained susceptible. Vaccination contributed to a marked decrease in the reproduction number.

Age-Dependent Risks of COVID-19 Putatively Caused by Variant Alpha in Japan.

Background: Osaka, the third largest prefecture in Japan, experienced a rapid replacement of preexisting strains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by variant alpha during March-April 2021. Assessing the burden of variant alpha on health centers and medical institutions is vital to anticipating the surge of patients. The present study aimed to estimate the age-dependent risks of coronavirus disease (COVID-19) putatively caused by variant alpha in Japan, focusing on epidemiological dynamics in Osaka. Methods: Descriptive analyses were conducted using data on confirmed, severe and fatal cases of COVID-19 from 16 November 2020 to 22 May 2021. All cases were divided into 6-9 age groups to compare the risks of confirmed diagnosis, severe illness and death from COVID-19 with variant alpha to those caused by preexisting strains. Results: Individuals with COVID-19 aged under 30 years were more likely to be infected with variant alpha than those in their 40s. The incidence of severe illness and death among all age groups with COVID-19 due to variant alpha was higher than that due to preexisting strains. Patients older than 40 years experienced an increased risk of severe illness and death if infected with variant alpha. However, the proportion of severe cases was lower in the group aged 80 years and older infected with variant alpha than in those infected with preexisting strains. Conclusion: Our analysis suggests that the incidence of infection among young people aged below 30 years old increased relative to ordinary strains. Risks of severe illness and death in patients with variant alpha COVID-19 was higher than in those with preexisting strains in Osaka, Japan. However, a decrease in the risk of severe illness was observed in people aged ≥80 years, which is probably because medical facilities in Osaka were overwhelmed in April and May 2021. Continuous monitoring of COVID-19 cases with new variants is vital to secure sufficient medical resources for all patients who require medical care.

The number of COVID-19 clusters in healthcare and elderly care facilities averted by vaccination of healthcare workers in Japan, February-June 2021.

In Japan, a prioritized COVID-19 vaccination program using Pfizer/BioNTech messenger RNA (mRNA) vaccine among healthcare workers commenced on February 17, 2021. As vaccination coverage increases, clusters in healthcare and elderly care facilities including hospitals and nursing homes are expected to be reduced. The present study aimed to explicitly estimate the protective effect of vaccination in reducing cluster incidence in those facilities. A mathematical model was formulated using three pieces of information: (1) the incidence of clusters in facilities from October 26, 2020 to June 27, 2021; (2) the incidence of confirmed COVID-19 cases during the same period; and (3) vaccine doses among healthcare workers from February 17 to June 27, 2021, extracted from the national Vaccination System database. We found that the estimated proportion at risk in healthcare and elderly care facilities declined substantially as the vaccination coverage among healthcare workers increased; the greater risk reduction was observed in healthcare facilities, at 0.10 (95% confidence interval (CI): 0.04-0.16) times that in the pre-vaccination period, while that in elderly care facilities was 0.34 (95% CI: 0.24-0.43) times that in the earlier period. The averted numbers of clusters in healthcare facilities and elderly care facilities were estimated to be 247 (95% CI: 210-301) and 279 (95% CI: 218-354), respectively. Prioritized vaccination among healthcare workers had a marked impact on preventing the incidence of clusters in facilities.

Estimating the transmissibility of SARS-CoV-2 VOC 202012/01 in Japan using travel history information.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly spread across the globe. The variant of concern (VOC) 202012/01 (B.1.1.7, also known as the alpha variant) bearing the N501Y mutation emerged in late 2020. VOC 202012/01 was more transmissible than existing SARS-CoV-2 variants and swiftly became dominant in many regions. More than 150 cases of VOC 202012/01 were reported in Japan by 26 February 2021. During the very early stage of introduction, only a subset arose from domestic transmission. If the reproduction number R (i.e., the average number of secondary transmission events caused by a single primary case) is greater than 1, the corresponding proportion should converge to 1 in a short period of time, and thus it is critical to understand the transmissibility of VOC 202012/01 based on travel history information. The present study aimed to estimate R of VOC 202012/01 using overseas travel history information. A mathematical model was developed to capture the relationship between travel history and R. We obtained travel history data for each confirmed case of VOC 202012/01 infection from 26 December 2020 to 26 February 2021. Maximum likelihood estimation was used to estimate R, accounting for right censoring during real-time estimation. In the baseline scenario, R was estimated at 2.11 (95% confidence interval: 1.63, 2.94). By 26 February 2021, an average of nine generations had elapsed since the first imported case. If the generation time of VOC 202012/01 was assumed to be longer, R was increased, consistent with estimates of R from case data. The estimated R of VOC 202012/01 in Japan exceeded 1 on 26 February 2021, suggesting that domestic transmission events caused a major epidemic. Moreover, because our estimate of R was dependent on generation time and ascertainment biases, continuous monitoring of contact tracing data is crucial to decipher the mechanisms of increased VOC 202012/01 transmissibility.

Phenomenological and mechanistic models for predicting early transmission data of COVID-19.

Forecasting future epidemics helps inform policy decisions regarding interventions. During the early coronavirus disease 2019 epidemic period in January-February 2020, limited information was available, and it was too challenging to build detailed mechanistic models reflecting population behavior. This study compared the performance of phenomenological and mechanistic models for forecasting epidemics. For the former, we employed the Richards model and the approximate solution of the susceptible-infected-recovered (SIR) model. For the latter, we examined the exponential growth (with lockdown) model and SIR model with lockdown. The phenomenological models yielded higher root mean square error (RMSE) values than the mechanistic models. When using the numbers from reported data for February 1 and 5, the Richards model had the highest RMSE, whereas when using the February 9 data, the SIR approximation model was the highest. The exponential model with a lockdown effect had the lowest RMSE, except when using the February 9 data. Once interventions or other factors that influence transmission patterns are identified, they should be additionally taken into account to improve forecasting.

Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021.

BACKGROUND: In Japan, a part of confirmed patients' samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. METHODS: The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. RESULTS: The weekly incidence with variant alpha from 18-24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420-1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. CONCLUSIONS: The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

A Comparison of Case Fatality Risk of COVID-19 between Singapore and Japan.

The crude case fatality risk (CFR) for coronavirus disease (COVID-19) in Singapore is remarkably small. We aimed to estimate the unbiased CFR by age for Singapore and Japan and compare these estimates by calculating the standardized mortality ratio (SMR). Age-specific CFRs for COVID-19 were estimated in real time, adjusting for the delay from illness onset to death. The SMR in Japan was estimated by using the age distribution of the Singapore population. Among cases aged 60-69 years and 70-79 years, the age-specific CFRs in Singapore were estimated as 1.84% (95% confidence interval: 0.46-4.72%) and 5.57% (1.41-13.97%), respectively, and those in Japan as 5.52% (4.55-6.62%) and 15.49% (13.81-17.27%), respectively. The SMR of COVID-19 in Japan, when compared with Singapore as the baseline, was estimated to be 1.46 (1.09-2.96). The overall CFR for Singapore is lower than that for Japan. It is possible that the circulating variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Singapore causes a milder clinical course of COVID-19 infection compared with other strains. If infection with a low-virulence SARS-CoV-2 variant provides protection against infection by high-virulence strains, the existence of such a strain is encouraging news for the many countries struggling to suppress this virus.

Hospital Caseload Demand in the Presence of Interventions during the COVID-19 Pandemic: A Modeling Study.

A surge in hospital admissions was observed in Japan in late March 2020, and the incidence of coronavirus disease (COVID-19) temporarily reduced from March to May as a result of the closure of host and hostess clubs, shortening the opening hours of bars and restaurants, and requesting a voluntary reduction of contact outside the household. To prepare for the second wave, it is vital to anticipate caseload demand, and thus, the number of required hospital beds for admitted cases and plan interventions through scenario analysis. In the present study, we analyzed the first wave data by age group so that the age-specific number of hospital admissions could be projected for the second wave. Because the age-specific patterns of the epidemic were different between urban and other areas, we analyzed datasets from two distinct cities: Osaka, where the cases were dominated by young adults, and Hokkaido, where the older adults accounted for the majority of hospitalized cases. By estimating the exponential growth rates of cases by age group and assuming probable reductions in those rates under interventions, we obtained projected epidemic curves of cases in addition to hospital admissions. We demonstrated that the longer our interventions were delayed, the higher the peak of hospital admissions. Although the approach relies on a simplistic model, the proposed framework can guide local government to secure the essential number of hospital beds for COVID-19 cases and formulate action plans.