Relational concurrency, stages of infection, and the evolution of HIV set point viral load

Abstract

HIV viral load (VL) predicts both transmission potential and rate of disease progression. For reasons that are still not fully understood, the set point viral load (SPVL) established after acute infection varies across individuals and populations. Previous studies have suggested that population mean SPVL (MSPVL) has evolved near an optimum that reflects a trade-off between transmissibility and host survival. Sexual network structures affect rates of potential exposure during different within-host phases of infection marked by different transmission probabilities, and thus affect the number and timing of transmission events. These structures include relational concurrency, which has been argued to explain key differences in HIV burden across populations. We hypothesize that concurrency will alter the fitness landscape for SPVL in ways that differ from other network features whose impacts accrue at other times during infection. To quantitatively test this hypothesis, we developed a dynamic, stochastic, data-driven network model of HIV transmission, and evolution to assess the impact of key sexual network phenomena on MSPVL evolution. Experiments were repeated in sensitivity runs that made different assumptions about transmissibility during acute infection, SPVL heritability, and the functional form of the relationship between VL and transmissibility. For our main transmission model, scenarios yielded MSPVLs ranging from 4.4 to 4.75 log₁₀ copies/ml, covering much of the observed empirical range. MSPVL evolved to be higher in populations with high concurrency and shorter relational durations, with values varying over a clinically significant range. In linear regression analyses on these and other predictors, main effects were significant (P < 0.05), as were interaction terms, indicating that effects are interdependent. We also noted a strong correlation between two key emergent properties measured at the end of the simulations-MSPVL and HIV prevalence-most clearly for phenomena that affect transmission networks early in infection. Controlling for prevalence, high concurrency yielded higher MSPVL than other network phenomena. Interestingly, we observed lower prevalence in runs in which SPVL heritability was zero, indicating the potential for viral evolution to exacerbate disease burden over time. Future efforts to understand empirical variation in MSPVL should consider local HIV burden and basic sexual behavioral and network structure.

Keywords: HIV-1; relational concurrency; set point viral load; sexual networks; viral evolution.

Figure 1.

Schematic diagram of a potential trade-off function between virulence (as measured by mortality) and transmissibility, for a pathogen like HIV that has no recovery. Under a host of simplifying assumptions, virulence is expected to evolve to the level marked by the dot, located at the point of intersection for the tangent line that contains the origin, and representing the conditions under which R₀ is maximized. Adapted from Bull and Lauring (2014).

Figure 2.

Scenarios with all default parameters but varying coital frequency within extant relationships. (a) Time series of incident MSPVL evolution; (b) time series of HIV prevalence; (c) final HIV prevalence plotted against MSPVL. Blue dots represent outcomes from individual runs; black squares represent the mean of these and bars represent the inner 50% of the data for each scenario. HIV prevalence is measured at the end of the simulation. MSPVL is measured across all incident infections from the last 10 years of the simulation. Selection of prevalence for the x-axis and MSPVL for the y-axis is arbitrary, as the two epidemic outcomes are linked together in a feedback loop and are mutually dependent.

Figure 3.

Incident MSPVL and final HIV prevalence, varying mean relational duration and level of relational concurrency. (a) MSPVL; (b) prevalence plotted against MSPVL.

Figure 4.

Percent of transmissions that occur during the acute HIV infection phase, for the same scenarios as in Figure 3. Measure is taken for all transmissions during the final year of the simulation.

Figure 5.

HIV prevalence by incident MSPVL, for different levels of heightened infectiousness during acute infection (above and beyond heightened VL) and varying concurrency.

Figure 6.

HIV prevalence by incident MSPVL, for scenarios varying timing of coital cessation during AIDS stage, and concurrency.

Figure 7.

HIV prevalence by MSPVL, comparing two functional forms for the relationship between VL and transmission (continually increasing vs. plateauing), for a range of coital frequencies and concurrency levels. Here the filled symbols signify the increasing transmission function, open symbols signify the plateauing transmission function. Because the two models yielded different prevalence levels with default parameters, we vary coital frequency over different ranges for the two forms in order to compare across scenarios with similar prevalence.

Figure 8.

HIV prevalence by MSPVL, varying heritability and concurrency.