Immune history influences SARS-CoV-2 booster impacts: the role of efficacy and redundancy (preprint)

Given the continued emergence of SARS-CoV-2 variants of concern as well as unprecedented vaccine development, it is crucial to understand the effect of the updated vaccine formulations at the population level. While bivalent formulations have higher efficacy in vaccine trials, translating these findings to real-world effectiveness is challenging due to the diversity in immune history, especially in settings with a high degree of natural immunity. Known socioeconomic disparities in key metrics such as vaccine coverage, social distancing, and access to healthcare have likely shaped the development and distribution of this immune landscape. Yet little has been done to investigate the impact of booster formulation in the context of host heterogeneity. Using two complementary mathematical models that capture host demographics and immune histories over time, we investigated the potential impacts of bivalent and monovalent boosters in low- and middle-income countries (LMICs). These models allowed us to test the role of natural immunity and cross-protection in determining the optimal booster strategy. Our results show that to avert deaths from a new variant in populations with high immune history, it is more important that a booster is implemented than which booster is implemented (bivalent vs. monovalent). However, in populations with low preexisting immunity, bivalent boosters can become optimal. These findings suggest that for many LMICs - where acquiring a new vaccine stock may be economically prohibitive - monovalent boosters can still be implemented as long as pre-existing immunity is high.

Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control (preprint)

SARS-CoV-2 vaccines were developed and distributed during a global crisis at unprecedented speed. Still, little is known about trends in vaccine uptake over time, their association with socioeconomic inequality, and the impact of these temporal trends on disease control. By analyzing data from dozens of countries, we examined vaccination rates across high and low socioeconomic (SES) groups, showing that socioeconomic disparities in the fraction of the population vaccinated exist at both national and sub-national levels. We also identified two distinct vaccination trends: one characterized by rapid initial roll-out, quickly reaching a plateau; and another trend that is sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences across the two vaccination types in the burden of infections and deaths. The timing of initial roll-out has a more significant effect on transmission and deaths than the eventual level of coverage or the degree of SES disparity. Surprisingly, the speed of the roll-out is not associated with wealth inequality or GDP per capita of countries. While socioeconomic disparity should be addressed, accelerating the initial roll-out for all groups is a broadly accessible intervention and has the potential to minimize the burden of infections and deaths across socioeconomic groups.