The role of HIV viral load in mathematical models of HIV transmission and treatment: a review

• Main Authors: Landon Myer, Tracy Glass
• Format: Article
• Language: English
• Published: BMJ Publishing Group 2020-01-01
• Series: BMJ Global Health
• Online Access: https://gh.bmj.com/content/5/1/e001800.full

IntroductionHIV viral load (VL) is accepted as a key biomarker in HIV transmission and pathogenesis. This paper presents a review of the role of VL testing in mathematical models for HIV prevention and treatment.MethodsA search for simulation models of HIV was conducted in PubMed, yielding a total of 1210 studies. Publications before the year 2000, studies involving animals and analyses that did not use mathematical simulations were excluded. The full text of eligible articles was sourced and information about the intervention and population being modelled, type of modelling approach and disease monitoring strategy was extracted.Results and discussionA total of 279 studies related to HIV simulation models were included in the review, though only 17 (6%) included consideration of VL or VL testing and were evaluated in detail. Within the studies that included assessment of VL, routine monitoring was the focus, and usually in comparison to alternate monitoring strategies such as clinical or CD4 count-based monitoring. The majority of remaining models focus on the impact or delivery of antiretroviral therapy (n=68; 27%), pre-exposure prophylaxis (n=28; 11%) and/or HIV testing (n=24; 9%) on population estimates of HIV epidemiology and exclude consideration of VL. Few studies investigate or compare alternate VL monitoring frequencies, and only a small number of studies overall (3%) include consideration of vulnerable population groups such as pregnant women or infants.ConclusionsThere are very few simulations of HIV treatment or prevention that include VL measures, despite VL being recognised as the key determinant of both transmission and treatment outcomes. With growing emphasis on VL monitoring as key tool for population-level HIV control, there is a clear need for simulations of HIV epidemiology based on VL.