Abstract
Objective: Build a dynamic model system to assess the effects of HIV intervention and prevention strategies on future annual numbers of new HIV infections, newly diagnosed cases of HIV infection, and deaths among persons infected with HIV.
Design and Setting: Model parameters are defined to quantify the putative effects of HIV prevention strategies that would increase HIV testing, thereby diagnosing infection earlier; increase linkage to care and viral suppression, thereby reducing infectiousness; and increase the use of preexposure prophylaxis, thereby protecting persons at risk of infection. Surveillance data are used to determine the initial values of the model system's variables and parameters, and the impact on the future course of various outcome measures of achieving either specified target values or specified rates of change for the model parameters is examined.
Participants: A hypothetical population of persons with HIV infection and persons at risk of acquiring HIV infection.
Main Outcome Measures: HIV incidence, HIV prevalence, proportion of persons infected with HIV whose infection is diagnosed, and proportion of persons with diagnosed HIV infection who are virally suppressed.
Results: A model system based on the basic year-to-year algebraic relationships among the model variables and relying almost exclusively on HIV surveillance data was developed to project the course of HIV disease over a specified time period. Based on the most recent HIV surveillance data in the United States-which show a relatively high proportion of infections having been diagnosed but a relatively low proportion of diagnosed persons being virally suppressed-increasing the proportion of diagnosed persons who are virally suppressed and increasing preexposure prophylaxis use appear to be the most effective ways of reducing new HIV infections and accomplishing national HIV prevention and care goals.
Conclusions: Both having current and accurate information regarding the epidemiologic dynamics of HIV infection and knowing the potential impact of prevention strategies are critical in order for limited HIV prevention resources to be optimally allocated.