Using Mathematical Modelling to Assess Public Health Strategy for HIV/AIDS

An important measure of the success of public health strategies for containing the HIV/AIDS epidemic is incidence, the rate at which new infections appear in the population. However, a patient infected with HIV may not become symptomatic for as long as 8 years. This means that the number of new positive tests is not necessarily a good indicator of disease incidence. In Canada, it is often accepted that as much as 25% of the HIV-positive population may be undiagnosed. A new pilot project called Seek and Treat for the Optimal Prevention of HIV and AIDS pilot project (STOP HIV/AIDS) is being rolled out by the Government of British Columbia. As one of the approaches to evaluating the success of STOP HIV/AIDS, we have developed a compartmental disease model which relates public health surveillance data to the epidemiologic parameters of the epidemic. Key advantages of combining disease modelling with existing public health surveillance data over traditional methods of estimating incidence, such as back-calculation and cohort studies, are that it is a relatively inexpensive approach and that it provides near real-time feedback on the state of the epidemic. Our model estimates that the fraction of the HIV positive population in British Columbia that has been diagnosed has remained approximately constant at about 80% from 2003 to 2009. In addition to validating the model historically, we have determined signatures in the public health surveillance data that the model establishes as indicators of whether STOP HIV/AIDS is having a significant impact on HIV incidence