Identifying Gay Neighborhoods and Estimation of the Size of the Men who have Sex with Men Population in Florida who would benefit from Pre-exposure Prophylaxis

Given the potential benefit of pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) at risk for human immunodeficiency virus (HIV), it would be useful to assess the size of the at-risk population and their geographic distribution to target PrEP and other prevention programs efficiently. In 2017, Florida ranked third for HIV diagnosis rates in the US, and 63% of those who received a new HIV diagnosis in Florida were MSM. The purpose of this dissertation was to 1) summarize population-based methods to estimate the size of the population of MSM, 2) identify gay neighborhoods using latent class analysis (LCA), and 3) estimate the size of the MSM population in Florida. A systematic review of population-based methods to estimate the size of the MSM population was conducted. Twenty-eight studies met inclusion criteria. Sixteen studies were conducted in the US, five in European countries, two in Canada, three in Australia, one in Israel, and one in Kenya. Men who have sex with men made up 0.03–6.4% of men among all studies and ranged from 3.8–6.4% in the US, 7,000–39,100 in Canada, 0.03–6.5% in European countries, and 127,947–182,624 in Australia. Latent class analysis was used to identify gay neighborhoods in Florida. Data at the ZIP code level was drawn from the 2011–2015 ACS, website lists of gay bars and neighborhoods, and the Florida Department of Health’s HIV surveillance system. A two-class model was selected. About 9% of the ZIP code data were in class two (gay neighborhoods). Cohen’s kappa coefficient was used to examine agreement between the classification of ZIP codes from LCA and gay neighborhoods from websites. Fair agreement was found (0.2501). Three methods were used to estimate the MSM population in Florida with high-risk behaviors that would indicate eligibility for PrEP use. The resulting three estimates were averaged, and the number of MSM living with HIV infection in each ZIP code was subtracted. The average MSM estimate in ZIP codes ranged from 1–2,184 men (1.5–22.9%). The presumed HIV-negative MSM estimate in ZIP codes ranged from 1–1,346 men (0.02–12.7%). Indications for PrEP were highest for MSM with more than one sex partner in the past year and lowest when the estimate was multiplied by 24.7% (percent of MSM with PrEP indications from other studies). In conclusion, there is no widely accepted method to estimate the size of the MSM population, and estimates vary substantially based on the method used.

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