Evolution of HIV virulence in response to disease-modifying vaccines: A modeling study

Abstract

Pathogens face a tradeoff with respect to virulence; while more virulent strains often have higher per-contact transmission rates, they are also more likely to kill their hosts earlier. Because virulence is a heritable trait, there is concern that a disease-modifying vaccine, which reduces the disease severity of an infected vaccinee without changing the underlying pathogen genotype, may result in the evolution of higher pathogen virulence. We explored the potential for such virulence evolution with a disease-modifying HIV-1 vaccine in an agent-based stochastic epidemic model of HIV in United States men who have sex with men (MSM). In the model, vaccinated agents received no protection against infection, but experienced lower viral loads and slower disease progression. We compared the genotypic set point viral load (SPVL), a measure of HIV virulence, in populations given vaccines that varied in the degree of SPVL reduction they induce. Sensitivity analyses were conducted under varying vaccine coverage scenarios. With continual vaccination rollout under ideal circumstances of 90 % coverage over thirty years, the genotypic SPVL of vaccinated individuals evolved to become greater than the genotypic SPVL of unvaccinated individuals. This virulence evolution in turn diminished the public health benefit of the vaccine, and in some scenarios resulted in an accelerated epidemic. These findings demonstrate the complexity of viral evolution and have important implications for the design and development of HIV vaccines.

Keywords: HIV; Modeling; Vaccine; Viral evolution; Virulence.

Figure 1.. Optimal virulence as a product of host survival and transmission probability

While transmission probability increases with higher SPVL (blue line), host survival decreases (green line). In this conceptual figure, fitness is optimized when these lines intersect. We hypothesize that a disease modifying vaccine that extends host survival (dotted green line) could select for viruses with higher SPVLs.

Figure 2.. Mean phenotypic SPVL of infected agents over time under four vaccine scenarios

Each line represents the mean phenotypic SPVL of newly infected agents at each time point (every 30 days) in a no vaccine scenario or with 90% coverage of a vaccine that reduces SPVL by 0.5, 1.0, 1.5, or 2.0 log₁₀ copies/ml, over 50 replicates. Shaded area reflects the 95% confidence interval.

Figure 3.. Mean genotypic SPVL of new infections over time under 90% coverage of a disease modifying vaccine with varying effects on phenotypic SPVL

Mean genotypic SPVL of all new infections at each time point (every 30 days) over 50 replicates. Shaded area reflects the 95% confidence interval. Inset: focus on mean genotypic SPVL of new infections during year 30 after vaccine rollout, with bars indicating the 95% confidence interval

Figure 4.. Average genotypic SPVL under a 1log10 vaccine campaign with varying coverage levels

Points represent the mean genotypic SPVL at the time point indicated, showing a no-vaccine scenario and varying coverage levels of a vaccine that reduces phenotypic SPVL by 1.0 log₁₀ copies/ml, over fifty replicates. Bars represent the 95% confidence interval.

Figure 5.. HIV-1 incidence per 100 person-years with a 1.0 log10 vaccine at varying coverage levels

Mean incidence (per 100 person-years) at each time point (every 30 days) over 50 replicates under varying coverage levels of a vaccine that reduces phenotypic SPVL by 1.0 log₁₀ copies/ml. Shaded area reflects the 95% confidence interval.

Figure 6.. HIV-1 prevalence with a 1.0 log10 vaccine at varying coverage levels

Mean HIV-1 prevalence at each time point (every 30 days) over 50 replicates under varying coverage levels of a vaccine that reduces phenotypic SPVL by 1.0 log₁₀ copies/ml. Shaded area reflects the 95% confidence interval.

Figure 7.. Proportion of infections averted due to a 1.0 log10 vaccine at varying coverage levels.

The mean proportion of cumulative infections averted by the vaccine relative to the no-vaccine scenario at varying coverage levels of a vaccine that reduced phenotypic SPVL by 1.0 log₁₀ copies/ml. Bars represent 95% confidence intervals.

Figure 8.. Kaplan-Meier survival curves for agents unvaccinated at infection in the first ten years of the vaccine campaign compared to the final 10 years

First plot: survival among agents who became infected between year 0 and 10, with each line (overlapping and not distinguishable) representing survival under different coverage levels of a 1.0 log₁₀ disease modifying vaccine. Second plot: survival among agents who became infected between year 20 and 30, with each line representing survival under different coverage levels of a 1.0 log₁₀ disease modifying vaccine.