title: Impact of Population Recruitment on the HIV Epidemics and the Effectiveness of HIV Prevention Interventions.
abstract: Mechanistic mathematical models are increasingly used to evaluate the effectiveness of different interventions for HIV prevention and to inform public health decisions. By focusing exclusively on the impact of the interventions, the importance of the demographic processes in these studies is often underestimated. In this paper, we use simple deterministic models to assess the effectiveness of pre-exposure prophylaxis in reducing the HIV transmission and to explore the influence of the recruitment mechanisms on the epidemic and effectiveness projections. We employ three commonly used formulas that correspond to constant, proportional and logistic recruitment and compare the dynamical properties of the resulting models. Our analysis exposes substantial differences in the transient and asymptotic behavior of the models which result in 47 % variation in population size and more than 6 percentage points variation in HIV prevalence over 40 years between models using different recruitment mechanisms. We outline the strong influence of recruitment assumptions on the impact of HIV prevention interventions and conclude that detailed demographic data should be used to inform the integration of recruitment processes in the models before HIV prevention is considered.
authors.affiliation: School of Mathematics, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Yuqin
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Statistical Center for HIV/AIDS Research and Prevention (SCHARP), Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
authors.forename: Daniel T
authors.initials: DT
authors.lastname: Wood
authors.affiliation: Department of Mathematics, The University of Texas at Arlington, Arlington, TX, USA.
authors.forename: Hristo V
authors.initials: HV
authors.lastname: Kojouharov
authors.affiliation: Department of Mathematics and Statistics, Arizona State University, Tempe, AZ, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Kuang
authors.affiliation: Statistical Center for HIV/AIDS Research and Prevention (SCHARP), Fred Hutchinson Cancer Research Center, Seattle, WA, USA. ddimitro@scharp.org.
authors.forename: Dobromir T
authors.initials: DT
authors.lastname: Dimitrov
mesh_terms: D003198:Computer Simulation; D058872:Epidemics / Q000517:prevention & control*; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control* / Q000635:transmission; D006801:Humans; D055641:Mathematical Concepts; D008954:Models, Biological; D011157:Population Dynamics; D065129:Pre-Exposure Prophylaxis; D015995:Prevalence; D011634:Public Health; D013019:South Africa / Q000453:epidemiology
keywords: HIV prevention; Mathematical modeling; Population recruitment; Pre-exposure prophylaxis