When older adults are prioritized in vaccine distribution, this can ward off the virus in all populations.
In a recent study published in PLoS Computational Biology, researchers used mathematical modeling to assess whether prioritizing older adults for COVID-19 booster vaccinations consistently results in the best possible public health outcomes. These measures are often taken to ensure vulnerable populations, including seniors, protection as they lack the same immune efficiency as other groups.
At the beginning of the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) such as quarantining, lockdowns, mask-wearing, and social distancing played a critical role in curbing the spread of the virus. However, the introduction of vaccines like those from Pfizer-BioNTech, Moderna, and Oxford-AstraZeneca marked a significant shift in managing the pandemic, helping reduce severe cases and allowing for the relaxation of many NPIs.
Eventually, it became evident that the initial vaccinations weren’t going to be enough to ward off the virus over time, mainly due to its ability to rapidly evolve and an individual’s own immune response to the vaccine. Its effectiveness was put to the test when new strands emerged and people again became sick, even those who had already gotten sick. Thus, booster shots were rolled out, and the current research aimed to more clearly define booster strategies to ensure the best possible solutions for all populations.
The researchers expanded upon a previously used age-structured compartmental model of SARS-CoV-2 transmission and vaccination driven by differential equations, which segments individuals into different categories based on age, infection status, and immune status before any infection. The model further separated individuals into 16 age groups and classifies them as Susceptible, Exposed, Infectious (either symptomatic or asymptomatic), or Recovered.
To improve the model’s accuracy, the researchers used gamma distributions. These distributions provide a more realistic depiction of epidemiological timeframes. The model also tracks immune status, placing individuals into categories such as Vaccinated, Boosted, Partially Waned, Fully Waned, and Unvaccinated, reflecting their vaccination and infection history.
The study examined six age-based booster vaccination strategies across eight countries. The strategies ranged from prioritizing the oldest individuals to vaccinating those with the most social contacts to indirectly protecting the elderly.
One key factor influencing booster vaccine distribution is the varying age structures across countries. High-income countries typically have larger elderly populations compared to those that are low-income. For instance, in the U.K., where the population is largely older, strategies that prioritize the elderly (Strategies 1-4) result in significant coverage for individuals aged 50-74, but the oldest individuals (75+) may not be fully covered due to supply limitations.
By the same token, strategies focusing on younger individuals, particularly those aged 20-49, aim to provide indirect protection to older populations by reducing overall spread. The effectiveness of these strategies varies significantly between countries.
The study’s projections indicate that Strategy 1, which prioritizes the oldest individuals, consistently results in the fewest deaths across all countries studied, particularly in high-income nations where a larger proportion of the population is elderly. Therefore, as the virus continues to evolve, with new variants continually emerging, moving from indirect protection of the elderly to more direct protection may proof to produce that best possible
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Prioritizing older individuals for COVID-19 boosters yields best public health outcomes, study finds
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