Using Cd4 Data to Estimate Hiv Incidence, Prevalence, and Percent of Undiagnosed Infections in the United States

Introduction: The incidence and prevalence of HIV infection are important measures of HIV trends; however, they are difficult to estimate because of the long incubation period between infection and symptom development and the relative infrequency of HIV screening. A new method is introduced to estimate HIV incidence, prevalence, and the number of undiagnosed infections in the United States using data from the HIV case surveillance system and CD4 test results. Methods: Persons with HIV diagnosed during 2006–2013 and their CD4 test results were used to estimate the distribution of diagnosis delay from HIV infection to diagnosis based on a well-characterized CD4 depletion model. This distribution was then used to estimate HIV incidence, prevalence, and the number of undiagnosed infections. Results: Applying this method, we estimated that the annual number of new HIV infections decreased after 2007, from 48,300 (95% confidence interval [CI]: 47,300 to 49,400) to 39,000 (95% CI: 36,600 to 41,400) in 2013. Prevalence increased from 923,200 (95% CI: 914,500 to 931,800) in 2006 to 1,104,600 (95% CI: 1,084,300 to 1,124,900) in 2013, whereas the proportion of undiagnosed infections decreased from 21.0% in 2006 (95% CI: 20.2% to 21.7%) to 16.4% (95% CI: 15.7% to 17.2%) in 2013. Conclusions: HIV incidence, prevalence, and undiagnosed infections can be estimated using HIV case surveillance data and information on first CD4 test result after diagnosis. Similar to earlier findings, the decreases in incidence and undiagnosed infections are encouraging but intensified efforts for HIV testing and treatment are needed to meet the goals of the National HIV/AIDS Strategy.