Exploring Effect of Individual Risk Behavior Volatility on Model Inference of HIV Transmission Dynamics and HIV Phylogenetic Tree

HIV/AIDS;infectious disease;mathematical epidemiology;mathematical modeling;Universal Test and Treat;pre-exposure prophylaxis;Public Health;Health Sciences;Science;Epidemiological Science

Zhang, XinyuMeza, Rafael ;

University of Michigan

关键词: HIV/AIDS;    infectious disease;    mathematical epidemiology;    mathematical modeling;    Universal Test and Treat;    pre-exposure prophylaxis;    Public Health;    Health Sciences;    Science;    Epidemiological Science;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/140946/xinyuz_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Men who have sex with men (MSM) are heavily affected by HIV infections. However, controlling HIV transmission among MSM population remains a challenging task due to the complexity of the transmission dynamics of HIV. Mathematical models can facilitate understanding such dynamics. They also provide a basis for estimating important epidemiological parameters that can guide public health decision. This thesis advances methods to achieve both of these objectives and makes a substantive advance in the first area. In this dissertation, we relaxed the constancy of individual risk behavior assumption, by allowing individual risk behavior to fluctuate among different levels over time, namely individual risk behavior volatility (risk volatility).We found that increasing risk volatility considerably increases fraction of transmission from acute HIV infection and prevalence at endemic equilibrium. In addition, we found that increasing risk volatility considerably reduces the minimum required individual effectiveness to eliminate HIV infections of Universal Test and Treat or universally applied pre-exposure prophylaxis (PrEP). Furthermore, our results suggest that increasing risk volatility reduces the extent that a case’s risk level at HIV acquisition determines this case’s capacity to cause onward transmission later during infection. Consequently, assuming no risk volatility may cause one to overestimate the benefit of prioritizing PrEP efforts to susceptible individuals experiencing high risk as a strategy to eliminate HIV infections. Finally, we explored the possibility of using HIV phylogeny to indicate when risk volatility affects HIV transmission dynamics. Our results suggest that risk volatility has unique and strong impact on phylogeny imbalance and clustering pattern. This implies that risk volatility is potentially identifiable from HIV sequence data.Research in this thesis contributions to the field of study that uses mathematical models to estimate epidemiological parameters of HIV transmission from two perspectives. Firstly, research in this thesis reveals the importance of evaluating individual risk behavior volatility to enhance robustness of model inference of epidemiological parameters and quantities. Secondly, research in this thesis suggests HIV sequence data is potentially valuable to improve the identifiability of risk volatility parameter. Therefore, research in this thesis takes significant steps forward to improve mathematical model inference of HIV transmission parameters.