title: Effects of contact structure on the transient evolution of HIV virulence.
abstract: Early in an epidemic, high densities of susceptible hosts select for relatively high parasite virulence; later in the epidemic, lower susceptible densities select for lower virulence. Thus over the course of a typical epidemic the average virulence of parasite strains increases initially, peaks partway through the epidemic, then declines again. However, precise quantitative outcomes, such as the peak virulence reached and its timing, may depend sensitively on epidemiological details. Fraser et al. proposed a model for the eco-evolutionary dynamics of HIV that incorporates the tradeoffs between transmission and virulence (mediated by set-point viral load, SPVL) and their heritability between hosts. Their model used implicit equations to capture the effects of partnership dynamics that are at the core of epidemics of sexually transmitted diseases. Our models combine HIV virulence tradeoffs with a range of contact models, explicitly modeling partnership formation and dissolution and allowing for individuals to transmit disease outside of partnerships. We assess summary statistics such as the peak virulence (corresponding to the maximum value of population mean log10 SPVL achieved throughout the epidemic) across models for a range of parameters applicable to the HIV epidemic in sub-Saharan Africa. Although virulence trajectories are broadly similar across models, the timing and magnitude of the virulence peak vary considerably. Previously developed implicit models predicted lower virulence and slower progression at the peak (a maximum of 3.5 log10 SPVL) compared both to more realistic models and to simple random-mixing models with no partnership structure at all (both with a maximum of ≈ 4.7 log10 SPVL). In this range of models, the simplest random-mixing structure best approximates the most realistic model; this surprising outcome occurs because the dominance of extra-pair contact in the realistic model swamps the effects of partnership structure.
authors.affiliation: Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada.
authors.forename: Sang Woo
authors.identifier: 0000-0003-2202-3361
authors.initials: SW
authors.lastname: Park
authors.affiliation: Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada.|Department of Biology, McMaster University, Hamilton, Ontario, Canada.|Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada.
authors.forename: Benjamin M
authors.identifier: 0000-0002-2127-0443
authors.initials: BM
authors.lastname: Bolker
mesh_terms: D005075:Biological Evolution; D019295:Computational Biology; D058872:Epidemics; D019143:Evolution, Molecular; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000635:transmission / Q000821:virology*; D015497:HIV-1 / Q000235:genetics / Q000472:pathogenicity*; D054884:Host-Pathogen Interactions / Q000235:genetics; D006801:Humans; D008297:Male; D008954:Models, Biological; D009154:Mutation; D012725:Sexual Behavior; D013997:Time Factors; D019562:Viral Load; D014774:Virulence