Heterologous vaccination as a strategy to minimize inequity in COVID-19 vaccine access: A modeling study in Thailand (preprint)

Background: Vaccinations are the best hope to control the COVID-19 pandemic and save lives. Due to the high demand and failure to share vaccines equitably, there were not enough vaccine supplies to cover the majority of people in low- and middle-income countries during the early stage of vaccination. To cope with this problem, Thailand, an upper-middle-income country, decided to employ a heterologous vaccination strategy as the primary COVID-19 vaccination regimen in the country. The CoronaVac (CV) vaccine was administered as the first dose, followed by the ChAdOx1 nCoV-19 (AZ) vaccine as the second dose. However, there is no study to assess the effectiveness of the heterologous vaccination employed in Thailand compared to the standard homologous vaccination. Methods: We delineated the course and timeline of COVID-19 vaccination in Thailand. An age-structured compartmental model for COVID-19 transmission and vaccination was constructed and employed to assess the effectiveness of the heterologous vaccination strategy. The impact of the vaccine prioritization strategies on COVID-19 mortality and infections was also investigated. Results: We found that the CV+AZ heterologous vaccination strategy outperforms the CV and AZ homologous vaccinations in reducing cumulative cases and deaths when combined with other non-pharmaceutical interventions. Furthermore, the results suggested that prioritizing vaccines for the elderly could be optimal in reducing COVID-19 mortality for a wide range of vaccination rates and transmission dynamics. Conclusions: Our modeling results suggested that to minimize inequity in COVID-19 vaccine access in low- and middle-income countries, those countries may use early accessible but maybe lower-efficacy vaccines as the first dose of heterologous vaccination in combination with higher-efficacy vaccines as the second dose.

Vaccination strategies impact the probability of outbreak extinction: a case study of COVID-19 transmission (preprint)

Mass vaccination has been one of the effective control measures for mitigating infectious disease transmission. Several vaccination strategies have been introduced throughout history to control infections and terminate the outbreak. Here, we employed the coronavirus disease 2019 (COVID-19) transmission as a case study and constructed a stochastic age-structured compartmental model to investigate the effectiveness of different vaccination strategies. We estimated the outbreak extinction probability under different vaccination scenarios in homogeneous and heterogeneous populations. We found that population heterogeneity could enhance the likelihood of outbreak extinction at various vaccine coverage. In addition, prioritizing vaccines for people with higher infection risk could maximize the outbreak extinction probability and reduce more infections. In contrast, allocating vaccines to individuals with higher mortality risk provides better results in reducing deaths. We also found that as the vaccine effectiveness wane over time, a booster dose of vaccine could significantly enhance the extinction probability and mitigate disease transmission.

Estimation of excess all-cause mortality due to COVID-19 in Thailand (preprint)

Thailand has experienced the most prominent COVID-19 outbreak, resulting in a new record for COVID-19 cases and deaths in 2021. To assess the influence of the COVID-19 outbreak on mortality, we estimated excess all-cause and pneumonia mortality in Thailand during the COVID-19 outbreak from April to October 2021. We used the previous five years’ mortality to estimate the baseline number of deaths using generalized linear mixed models (GLMMs). The models were adjusted for seasonality and demographics. We found that the estimated cumulative excess death was 14.3% (95% CI: 8.6%-18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, excess pneumonia deaths were also found to be 26.2% (95% CI: 4.8%-46.0%) above baseline. There was a significant rise in excess fatalities, especially in the older age groups. Therefore, the age and sex structure of the population are essential to assessing the mortality impact of COVID-19. Our modeling results could potentially provide insights into the COVID-19 outbreaks and provide a guide for outbreak control and intervention.