Targeted vaccination and the speed of SARS-CoV-2 adaptation

The limited supply of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) raises the question of targeted vaccination. Many countries have opted to vaccinate older and more sensitive hosts first to minimize the disease burden. However, what are the evolutionary consequences of targeted vaccination? We clarify the consequences of different vaccination strategies through the analysis of the speed of viral adaptation measured as the rate of change of the frequency of a vaccine-adapted variant. We show that such a variant is expected to spread faster if vaccination targets individuals who are likely to be involved in a higher number of contacts. We also discuss the pros and cons of dose-sparing strategies. Because delaying the second dose increases the proportion of the population vaccinated with a single dose, this strategy can both speed up the spread of the vaccine-adapted variant and reduce the cumulative number of deaths. Hence, strategies that are most effective at slowing viral adaptation may not always be epidemiologically optimal. A careful assessment of both the epidemiological and evolutionary consequences of alternative vaccination strategies is required to determine which individuals should be vaccinated first.

The development of effective vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) raises hope regarding the possibility of eventually halting the ongoing pandemic. However, vaccine supply shortages have sparked a debate about the optimal distribution of vaccination among different categories of individuals. Typically, infections with SARS-CoV-2 are far more deadly in older individuals than in younger ones (1). Prioritizing vaccination for older classes may thus provide a direct benefit in terms of mortality (2, 3). Yet, younger individuals are usually more active, and consequently, they may contribute more to the spread of the epidemic. Prioritizing vaccination for younger and more active individuals may thus provide an indirect benefit through a reduction of the epidemic size (4, 5). Earlier studies have compared alternative ways to deploy vaccination in heterogeneous host populations and showed that recommendation varies with the choice of the quantity one is trying to minimize (e.g., the cumulative number of deaths, the remaining life expectancy, or the number of infections) (3, 6, 7). The recommendation also varies with the properties of the pathogen and the efficacy of the vaccine (3, 4, 8). For SARS-CoV-2, the increase in mortality with age is such that the direct benefit associated with vaccinating more vulnerable individuals tends to overwhelm the indirect benefits obtained from vaccinating more active individuals (2, 3, 9, 10). However, some studies challenge this view and identified specific conditions where vaccinating younger and more active classes could be optimal (5, 7, 11, 12). A similar debate emerges over the possibility to delay the second vaccination dose to maximize the number of partially vaccinated individuals. A quantitative exploration of alternative vaccination strategies can help provide useful recommendations: a two-dose strategy is recommended when the level of protection obtained after the first dose is low and/or when vaccine supply is large (13–16).Vaccine-driven evolution, however, could erode the benefit of vaccination and alter the above recommendations which are based solely on the analysis of epidemiological dynamics. Given that hosts differ both in their sensitivity to the disease and in their contribution to transmission, who should we vaccinate first if we want to minimize the spread of vaccine-adapted variants? The effect of alternative vaccination strategies on the speed of pathogen adaptation remains unclear. Previous studies of adaptation to vaccines focused on long-term evolutionary outcomes (17, 18). These analyses are not entirely relevant for the ongoing pandemic because what we want to understand first is the short-term consequence of different vaccination strategies (19). A few studies have discussed the possibility of SARS-CoV-2 adaptation following different targeted vaccination strategies but did not explicitly account for evolutionary dynamics (12, 20). A recent simulation study explored the effect of a combination of vaccination and social distancing strategies on the probability of vaccine-driven adaptation (21). This model, however, did not study the impact of targeted vaccination strategies on the speed of adaptation.Here we develop a theoretical framework based on the analysis of the deterministic dynamics of multiple variants after they successfully managed to reach a density at which they are no longer affected by the action of demographic stochasticity. We study the impact of different vaccination strategies on the rate of change of the frequency of a novel variant, which allows us to quantify the speed of virus adaptation to vaccines. Numerical simulations tailored to the epidemiology of SARS-CoV-2 confirm the validity of our approximation of the strength of selection for vaccine-adapted variants.