Sara Hertog1. 1. Center for Demography and Ecology, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA. shertog@ssc.wisc.edu
Abstract
OBJECTIVES: This study evaluates whether the influence of sexual mixing patterns on the human immunodeficiency virus (HIV) epidemic curve is sensitive to the prevailing rates of sexual partner change in a population. STUDY DESIGN: A biobehavioral macrosimulation model is employed to assess the interacting dynamics of the rates of sexual partner change and patterns of sexual mixing between population subgroups. HIV spread is simulated under 2 rates of partner change scenarios and under various degrees of assortativeness in sexual mixing patterns. RESULTS: With high rates of partner change, disassortativeness in sexual mixing tends to increase the overall size of the HIV epidemic. However, when relatively low rates of partner change are simulated, disassortative mixing yields a smaller epidemic. This pattern is further influenced by the underlying sexual transmission probabilities of HIV. CONCLUSIONS: Each of the various determinants of the sexual spread of HIV must not be considered in isolation. Instead, the interactive nature of those determinants should be accounted for in discussions of HIV epidemic dynamics.
OBJECTIVES: This study evaluates whether the influence of sexual mixing patterns on the human immunodeficiency virus (HIV) epidemic curve is sensitive to the prevailing rates of sexual partner change in a population. STUDY DESIGN: A biobehavioral macrosimulation model is employed to assess the interacting dynamics of the rates of sexual partner change and patterns of sexual mixing between population subgroups. HIV spread is simulated under 2 rates of partner change scenarios and under various degrees of assortativeness in sexual mixing patterns. RESULTS: With high rates of partner change, disassortativeness in sexual mixing tends to increase the overall size of the HIV epidemic. However, when relatively low rates of partner change are simulated, disassortative mixing yields a smaller epidemic. This pattern is further influenced by the underlying sexual transmission probabilities of HIV. CONCLUSIONS: Each of the various determinants of the sexual spread of HIV must not be considered in isolation. Instead, the interactive nature of those determinants should be accounted for in discussions of HIV epidemic dynamics.
Authors: Lin Li; Daying Wei; Wan-Ling Hsu; Tianyi Li; Tao Gui; Charles Wood; Yongjian Liu; Hanping Li; Zuoyi Bao; Siyang Liu; Xiaolin Wang; Jingyun Li Journal: AIDS Res Hum Retroviruses Date: 2015-03-09 Impact factor: 2.205
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