Serologic Survey of IgG Against SARS-CoV-2 Among Hospital Visitors Without a History of SARS-CoV-2 Infection in Tokyo, 2020-2021

Reconstructing the age-structured case count of COVID-19 from sentinel surveillance data in Japan: A modeling study

OBJECTIVES

To reconstruct age-structured case counts of COVID-19 using sentinel reporting, which replaced universal reporting of COVID-19 from May 2023 in Japan.

METHODS

Using COVID-19 sentinel data stratified by discrete age groups in selected prefectures and referring to universal case count data up to May 8, 2023, we fitted a statistical model to handle weekly growth rates as a function of age and time so as to convert sentinel data to case counts after cessation of universal reporting.

RESULTS

The age distribution of cases in sentinel reporting was significantly biased toward younger age groups compared to universal reporting. When comparing the epidemic size of the 9th wave (May 8 to September 18, 2023) to the 8th wave (October 3, 2022 to April 10, 2023), using the wave-on-wave ratio of total cumulative sentinel cases led to a significant underestimation of the wave-on-wave in Tokyo (0.975, vs 1.461 by universal reporting) and Okinawa (1.299, vs 1.472). The estimates of growth rates, scaling factors between universal and sentinel cases, and expected universal case count showed robustness to changes in the ending week of the data period.

CONCLUSION

Our model quantified COVID-19 dynamics, comparably to universal reporting that ended in May 2023, enabling detailed and up-to-date health burden analysis using sentinel reports. The cumulative incidence was greater than that suggested from sentinel data in Tokyo, Nara, and Okinawa. Per-population burdens among children were particularly high in Osaka and Nara, indicating a strong bias in sentinel reporting toward pediatric cases.

Science-based exit from stringent countermeasures against COVID-19: Mortality prediction using immune landscape between 2021 and 2022 in Japan

Background

Stringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures.

Methods

Immune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained.

Results

Accounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged ≥ 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older.

Conclusions

Our estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.

Vaccine-induced reduction of COVID-19 clusters in school settings in Japan during the epidemic wave caused by B.1.1.529 (Omicron) BA.2, 2022

Clusters of COVID-19 in high-risk settings, such as schools, have been deemed a critical driving force of the major epidemic waves at the societal level. In Japan, the vaccination coverage among students remained low up to early 2022, especially for 5-11-year-olds. The vaccination of the student population only started in February 2022. Given this background and considering that vaccine effectiveness against school transmission has not been intensively studied, this paper proposes a mathematical model that links the occurrence of clustering to the case count among populations aged 0-19, 20-59, and 60+ years of age. We first estimated the protected (immune) fraction of each age group either by infection or vaccination and then linked the case count in each age group to the number of clusters via a time series regression model that accounts for the time-varying hazard of clustering per infector. From January 3 to May 30, 2022, there were 4,722 reported clusters in school settings. Our model suggests that the immunity offered by vaccination averted 226 (95% credible interval: 219-232) school clusters. Counterfactual scenarios assuming elevated vaccination coverage with faster roll-out reveal that additional school clusters could have been averted. Our study indicates that even relatively low vaccination coverage among students could substantially lower the risk of clustering through vaccine-induced immunity. Our results also suggest that antigenically updated vaccines that are more effective against the variant responsible for the ongoing epidemic may greatly help decrease not only the incidence but also the unnecessary loss of learning opportunities among school-age students.

Modeling of anti-spike IgG and neutralizing antibody waning after anti-SARS-CoV-2 mRNA vaccination

At present, mRNA-based vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are being administered on a global scale. While the efficacy of mRNA vaccines has been demonstrated, several unknowns remains. For example, as the number of booster vaccinations increases, there are uncertainties regarding how long effects of a vaccine will last and how much individual variability exists. In this study, to predict the duration of vaccine efficacy, we modeled the kinetics of antibody levels for each SARS-CoV-2 vaccination dose, incorporating predictive intervals to estimate the duration of vaccine efficacy and to account for variability among individuals. A total of 3,059 serum samples from 1,346 participants were assayed to quantify IgG antibodies specific for the S1 subunit of the S protein (anti-S1 IgG) and neutralizing antibody activities against SARS-CoV-2. A power law model was used to simulate the decay of antibody titers following vaccination, and models were constructed to assess antibody level kinetics after the second, third, fourth, and fifth vaccinations. The models assumed that booster vaccinations would significantly reduce the decline in anti-S antibody and neutralizing antibody levels, resulting in levels being maintained for a longer period. No significant differences in the decay rate of antibody levels were observed among age groups, yet the peak titers of antibody levels were significantly higher in the ≤ 39 age group than in the ≥ 60 age group following the second vaccination; these differences were not observed after the third and fourth vaccinations. The modeling of antibody level kinetics after vaccination is considered to be useful for understanding the immune status of mRNA vaccine recipients.

Protective effect of previous infection and vaccination against reinfection with BA.5 Omicron subvariant: a nationwide population-based study in Japan

Background

The Omicron variant of SARS-CoV-2 was reported to evade immunity derived from vaccination and previous infection. A better understanding of hybrid immunity informs effective infection control strategies. Since the reinfection risk was not well-assessed in East Asia, this study aims to evaluate the risk of infection with Omicron subvariant BA.5 among previously infected individuals in Japan.

Methods

All notified cases were extracted from the Japanese national COVID-19 surveillance database including 20,297,335 records up to 25 September 2022. Reinfection with BA.5 was defined as the infection notified during the BA.5 dominated period with any prior SARS-CoV-2 infection. The protective effect of prior infections against reinfections with BA.5 was estimated by applying a case-population design and the protective effect of vaccination was estimated by a multivariable Cox regression adjusting for age, sex, variants of prior infection, and the time since the last vaccination.

Findings

Among 19,830,548 SARS-CoV-2 first infections, 233,424 (1.2%) were reinfected with BA.5. The protective effect against BA.5 reinfection of prior infection with Wuhan strain was 46%, Alpha variant was 35%, Delta variant was 41%, and BA.1/BA.2 subvariant was 74%. The reduced risk of BA.5 reinfection by 7%, 33%, and 66% was associated with two, three, and four doses of vaccination, respectively, compared with one-dose vaccination.

Interpretation

The prior infections with Omicron subvariant BA.1/BA.2 protected BA.5 reinfection more than pre-Omicron variants. Increased frequency of vaccination led to more protection from reinfection with BA.5. Up-to-date vaccination may be encouraged to prevent future reinfection among the previously infected population.

Funding

None.

Assessing the COVID-19 vaccination program during the Omicron variant (B.1.1.529) epidemic in early 2022, Tokyo

BACKGROUND

Many countries, including high-income nations, struggled to control epidemic waves caused by the Omicron variant (B.1.1.529), which had an antigenically distinct evolution. Evaluating the direct and indirect effects of vaccination during the Omicron waves is essential to assess virus control policies. The present study assessed the population impacts of a vaccination program during the sixth wave caused by BA.1 and BA.2 from January to May 2022, in Tokyo.

METHODS

We analyzed the primary series and booster vaccination coverages and the confirmed cases stratified by vaccination history. We estimated the number of COVID-19 cases that were directly and indirectly prevented by vaccination. To estimate the direct impact, we used a statistical model that compared risks between unvaccinated and vaccinated individuals. A transmission model employing the renewal process was devised to quantify the total effect, given as the sum of the direct and indirect effects.

RESULTS

Assuming that the reporting coverage of cases was 25%, mass vaccination programs, including primary and booster immunizations, directly averted 640,000 COVID-19 cases (95% confidence interval: 624-655). Furthermore, these programs directly and indirectly prevented 8.5 million infections (95% confidence interval: 8.4-8.6). Hypothetical scenarios indicated that we could have expected a 19% or 7% relative reduction in the number of infections, respectively, compared with the observed number of infections, if the booster coverage had been equivalent to that of the second dose or if coverage among people aged 10-49 years had been 10% higher. If the third dose coverage was smaller and comparable to that of the fourth dose, the total number of infections would have increased by 52% compared with the observed number of infections.

CONCLUSIONS

The population benefit of vaccination via direct and indirect effects was substantial, with an estimated 65% reduction in the number of SARS-CoV-2 infections compared with counterfactual (without vaccination) in Tokyo during the sixth wave caused by BA.1 and BA.2.

Evaluating the COVID-19 vaccination program in Japan, 2021 using the counterfactual reproduction number

Japan implemented its nationwide vaccination program against COVID-19 in 2021, immunizing more than one million people (approximately 1%) a day. However, the direct and indirect impacts of the program at the population level have yet to be fully evaluated. To assess the vaccine effectiveness during the Delta variant (B.1.617.2) epidemic in 2021, we used a renewal process model. A transmission model was fitted to the confirmed cases from 17 February to 30 November 2021. In the absence of vaccination, the cumulative numbers of infections and deaths during the study period were estimated to be 63.3 million (95% confidence interval [CI] 63.2-63.6) and 364,000 (95% CI 363-366), respectively; the actual numbers of infections and deaths were 4.7 million and 10,000, respectively. Were the vaccination implemented 14 days earlier, there could have been 54% and 48% fewer cases and deaths, respectively, than the actual numbers. We demonstrated the very high effectiveness of COVID-19 vaccination in Japan during 2021, which reduced mortality by more than 97% compared with the counterfactual scenario. The timing of expanding vaccination and vaccine recipients could be key to mitigating the disease burden of COVID-19. Rapid and proper decision making based on firm epidemiological input is vital.

Population-Level Immunity for Transient Suppression of COVID-19 Waves in Japan from April 2021 to September 2022

Multiple COVID-19 waves have been observed worldwide, with varying numbers of positive cases. Population-level immunity can partly explain a transient suppression of epidemic waves, including immunity acquired after vaccination strategies. In this study, we aimed to estimate population-level immunity in 47 Japanese prefectures during the three waves from April 2021 to September 2022. For each wave, characterized by the predominant variants, namely, Delta, Omicron, and BA.5, the estimated rates of population-level immunity in the 10-64-years age group, wherein the most positive cases were observed, were 20%, 35%, and 45%, respectively. The number of infected cases in the BA.5 wave was inversely associated with the vaccination rates for the second and third injections. We employed machine learning to replicate positive cases in three Japanese prefectures to validate the reliability of our model for population-level immunity. Using interpolation based on machine learning, we estimated the impact of behavioral factors and vaccination on the fifth wave of new positive cases that occurred during the Tokyo 2020 Olympic Games. Our computational results highlighted the critical role of population-level immunity, such as vaccination, in infection suppression. These findings underscore the importance of estimating and monitoring population-level immunity to predict the number of infected cases in future waves. Such estimations that combine numerical derivation and machine learning are of utmost significance for effective management of medical resources, including the vaccination strategy.

Estimating infection fatality risk and ascertainment bias of COVID-19 in Osaka, Japan from February 2020 to January 2022

The present study aimed to estimate the infection fatality risk (IFR) and ascertainment bias of SARS-CoV-2 for six epidemic waves in Japan from February 2020 to January 2022. We used two types of datasets: (i) surveillance-based datasets containing the cumulative numbers of confirmed cases and deaths in each epidemic wave and (ii) seroepidemiological datasets conducted in a serial cross-sectional manner. Smoothing spline function was employed to reconstruct the age-specific cumulative incidence of infection. We found that IFR was highest during the first wave, and the second highest during the fourth wave, caused by the Alpha variant. Once vaccination became widespread, IFR decreased considerably among adults aged 40 years plus during the fifth wave caused by the Delta variant, although the epidemic size of fifth wave was the largest before the Omicron variant emerged. We also found that ascertainment bias was relatively high during the first and second waves and, notably, RT-PCR testing capacity during these early periods was limited. Improvements in the ascertainment were seen during the third and fourth waves. Once the Omicron variant began spreading, IFR diminished while ascertainment bias was considerably elevated.

Projection of COVID-19 Positive Cases Considering Hybrid Immunity: Case Study in Tokyo

Since the emergence of COVID-19, the forecasting of new daily positive cases and deaths has been one of the essential elements in policy setting and medical resource management worldwide. An essential factor in forecasting is the modeling of susceptible populations and vaccination effectiveness (VE) at the population level. Owing to the widespread viral transmission and wide vaccination campaign coverage, it becomes challenging to model the VE in an efficient and realistic manner, while also including hybrid immunity which is acquired through full vaccination combined with infection. Here, the VE model of hybrid immunity was developed based on an in vitro study and publicly available data. Computational replication of daily positive cases demonstrates a high consistency between the replicated and observed values when considering the effect of hybrid immunity. The estimated positive cases were relatively larger than the observed value without considering hybrid immunity. Replication of the daily positive cases and its comparison would provide useful information of immunity at the population level and thus serve as useful guidance for nationwide policy setting and vaccination strategies.

Impact of the COVID-19 pandemic on pathological autopsy practices in Japan

During the coronavirus disease 2019 (COVID-19) pandemic, autopsies have provided valuable insights into the pathogenesis of COVID-19. The precise effect of this pandemic on autopsy procedures in Japan, especially in instances unrelated to COVID-19, has not yet been established. Therefore, we conducted a questionnaire survey from December 2020 to January 2021 regarding the status of pathological autopsy practices in Japan during the first year of the COVID-19 pandemic. The questionnaire was sent to 678 medical facilities with pathologists, of which 227 responded. In cases where a confirmed diagnosis of COVID-19 was not made at the time of autopsy, many facilities counted them as suspected COVID-19 cases if pneumonia was suspected clinically. At around half of the sites, autopsies were prohibited for suspected COVID-19 cases. In addition, the number of autopsies of non-COVID-19 cases during the pandemic period was also investigated, and a significant decrease was observed compared with the incidence in the pre-pandemic period. The COVID-19 pandemic has affected not only the autopsies of COVID-19 cases but also the entire practice of pathological autopsies. It is necessary to establish a system that supports the implementation of pathological autopsy practices during the pandemic of an emerging infectious disease.

Antibody response to third and fourth BNT162b2 mRNA booster vaccinations in healthcare workers in Tokyo, Japan

BACKGROUND

Booster vaccinations against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are being promoted worldwide to counter the coronavirus disease 2019 (COVID-19) pandemic. In this study, we analyzed the longitudinal effect of the third BNT162b2 mRNA vaccination on antibody responses in healthcare workers. Additionally, antibody responses induced by the fourth vaccination were analyzed.

METHODS

The levels of anti-spike (S) IgG and neutralizing antibody against SARS-CoV-2 were measured at 7 months after the second vaccination (n = 1138), and at 4 (n = 701) and 7 (n = 417) months after the third vaccination using an iFlash 3000 chemiluminescence immunoassay analyzer. Among the 417 participants surveyed at 7 months after the third vaccination, 40 had received the fourth vaccination. A multiple linear regression analysis was performed to clarify which factors were associated with the anti-S IgG and neutralizing antibody. Variables assessed included sex, age, number of days after the second or third vaccination, diagnostic history of COVID-19, and anti-nucleocapsid (N) IgG level.

RESULTS

At 7 months after the third vaccination, antibody responses were significantly higher than those at the same time after the second vaccination. Unlike the second vaccination, age had no effect on the antibody responses induced by the third vaccination. Furthermore, the fourth vaccination resulted in a further increase in antibody responses. The multiple linear regression analysis identified anti-N IgG level, presumably associated with infection, as a factor associated with antibody responses.

CONCLUSIONS

Our findings showed that BNT162b2 booster vaccinations increased and sustained the antibody responses against SARS-CoV-2.

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".

Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be overdispersed, meaning that only a fraction of infected cases contributes to super-spreading. While cluster interventions are an effective measure for controlling pandemics due to the viruses' overdispersed nature, a quantitative assessment of the risk of clustering has yet to be sufficiently presented. Using systematically collected cluster surveillance data for coronavirus disease 2019 (COVID-19) from June 2020 to June 2021 in Japan, we estimated the activity-dependent risk of clustering in 23 establishment types. The analysis indicated that elderly care facilities, welfare facilities for people with disabilities, and hospitals had the highest risk of clustering, with 4.65 (95% confidence interval [CI]: 4.43-4.87), 2.99 (2.59-3.46), and 2.00 (1.88-2.12) cluster reports per million event users, respectively. Risks in educational settings were higher overall among older age groups, potentially being affected by activities with close and uncontrollable contact during extracurricular hours. In dining settings, drinking and singing increased the risk by 10- to 70-fold compared with regular eating settings. The comprehensive analysis of the COVID-19 cluster records provides an additional scientific basis for the design of customized interventions.

Reduced antibody response to SARS-CoV-2 in COVID-19 patients with newly diagnosed diabetes: a retrospective observational study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has dramatically impacted global health, and patients with type 2 diabetes have been identified as a high-risk group for COVID-19 infection and the development of severe disease. In response, this study aimed to evaluate whether patients with type 2 diabetes infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could develop antibody responses in the same manner as patients without diabetes, and whether there is a difference in antibody response to SARS-CoV-2 between patients with diabetes diagnosed prior to hospitalization, and those with newly diagnosed diabetes.

METHODS

SARS-CoV-2-specific immunoglobulin G (IgG) levels were quantified using two iFlash 3000 Chemiluminescence Immunoassay analyzer kits (Shenzhen YHLO Biotech Co., Ltd.) to detect IgG antibodies specific for nucleocapsid protein (IgG-N), and specific for the S1 subunit of the spike protein (IgG-S1). In 124 hospitalized patients with COVID-19, 40 patients with type 2 diabetes were matched to 40 patients without diabetes using propensity score matching (PSM).

RESULTS

There was no difference in IgG-N and IgG-S1 levels between the patients with diabetes and those without. Of patients with diabetes, 31 patients had known diabetes and nine patients had newly diagnosed diabetes. The median levels of IgG-N at 7-13 days in patients with newly diagnosed diabetes were significantly lower than those in patients with known diabetes (IgG-N; 10.9 vs. 31.0 AU/mL, p = 0.031, IgG-S1; 7.5 vs. 24.4 AU/mL, p = 0.023).

CONCLUSIONS

Even after adjusting for covariates using PSM, COVID-19 patients with type 2 diabetes had comparable antibody responses to patients without diabetes. Patients with newly diagnosed diabetes had lower IgG-N and IgG-S1 production in the second week of the disease compared with those with previously known diabetes.

B cell receptor repertoire analysis from autopsy samples of COVID-19 patients

Neutralizing antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are being developed world over. We investigated the possibility of producing artificial antibodies from the formalin fixation and paraffin-embedding (FFPE) lung lobes of a patient who died by coronavirus disease 2019 (COVID-19). The B-cell receptors repertoire in the lung tissue where SARS-CoV-2 was detected were considered to have highly sensitive virus-neutralizing activity, and artificial antibodies were produced by combining the most frequently detected heavy and light chains. Some neutralizing effects against the SARS-CoV-2 were observed, and mixing two different artificial antibodies had a higher tendency to suppress the virus. The neutralizing effects were similar to the immunoglobulin G obtained from healthy donors who had received a COVID-19 mRNA vaccine. Therefore, the use of FFPE lung tissue, which preserves the condition of direct virus sensitization, to generate artificial antibodies may be useful against future unknown infectious diseases.

Estimation of mRNA COVID-19 Vaccination Effectiveness in Tokyo for Omicron Variants BA.2 and BA.5: Effect of Social Behavior

The variability of the COVID-19 vaccination effectiveness (VE) should be assessed with a resolution of a few days, assuming that the VE is influenced by public behavior and social activity. Here, the VE for the Omicron variants (BA.2 and BA.5) is numerically derived for Japan’s population for the second and third vaccination doses. We then evaluated the daily VE variation due to social behavior from the daily data reports in Tokyo. The VE for the Omicron variants (BA.1, BA.2, and BA.5) are derived from the data of Japan and Tokyo with a computational approach. In addition, the effect of the different parameters regarding human behavior on VE was assessed using daily data in Tokyo. The individual VE for the Omicron BA.2 in Japan was 61% (95% CI: 57–65%) for the second dose of the vaccination from our computation, whereas that for the third dose was 86% (95% CI: 84–88%). The individual BA.5 VE for the second and third doses are 37% (95% CI: 33–40%) and 63% (95% CI: 61–65%). The reduction in the daily VE from the estimated value was closely correlated to the number of tweets related to social gatherings on Twitter. The number of tweets considered here would be one of the new candidates for VE evaluation and surveillance affecting the viral transmission.

Attenuated humoral response against SARS-CoV-2 mRNA vaccination in allogeneic stem cell transplantation recipients

Antibody persistence several months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccination in allogeneic stem cell transplantation recipients remains largely unknown. We sequentially evaluated the humoral response to two doses of mRNA vaccines in 128 adult recipients and identified the risk factors involved in a poor response. The median interval between stem cell transplantation and vaccination was 2.7 years. The SARS-CoV-2 S1 Ab became positive after the second vaccination dose in 87.6% of the recipients, and the median titer was 1235.4 arbitrary units (AU)/ml. In patients on corticosteroid treatment, the corticosteroid dose inversely correlated with Ab titer. Multivariate analysis identified risk factors for poor peak response such as an interval from stem cell transplantation ≤1 year, history of clinically significant CMV infection, and use of >5 mg/day prednisolone at vaccination. Six months after vaccination, the median titer decreased to 185.15 AU/ml, and use of >5 mg/day prednisolone at vaccination was significantly associated with a poor response. These results indicate that early vaccination after stem cell transplantation (<12 months) and CMV infection are risk factors for poor peak response, while steroid use is important for a peak as well as a persistent response. In conclusion, although humoral response is observed in many stem cell transplantation recipients after two doses of vaccination, Ab titers diminish with time, and factors associated with persistence and a peak immunity should be considered separately.

[Grasping COVID-19 immune landscape in Japan]

COVID-19 vaccination commenced globally in December 2020. Japan launched its vaccination rollout on February 17, 2021 and commenced booster vaccination campaign on December 1, 2021. It has been crucial to grasp the immune landscape in the country in order to aid in decision-making and evaluation of vaccination campaigns as well as understating the transmission dynamics of various variants of SARS-CoV-2. The present article shows a framework that enables us to predict the immune landscape, specifically, the proportion of immune population, using a mathematical modeling approach. This involved: prediction of vaccine coverage; estimation of vaccine effectiveness against the dominant SARS-CoV-2 variant in circulation; the quantification of increasing vaccine effectiveness (immune-build up) since receiving the first dose; the estimation of waning rate of vaccine effectiveness since receiving the second and third doses; and the consideration on the infection-induced immunity.