Determinants of PrEP Uptake, Intention and Awareness in the Netherlands: A Socio-Spatial Analysis.

PrEP uptake in the Netherlands is growing but remains at suboptimal levels. Hence, the analysis of hurdles is paramount. Given the initial focus of PrEP provision among men-who-have-sex-with-men (MSM) via a demonstration project that was launched in June 2015, AmPrEP in Amsterdam, and pharmacies in the main urban areas (so called "Randstad", entailing Amsterdam, Utrecht, Leiden, The Hague and Rotterdam), investigating regional differences is necessary. This study seeks to unravel regional differences jointly with the psycho-social determinants of PrEP uptake. This cross-sectional study included 3232 HIV-negative MSM recruited via the Dutch subsample of the European-MSM-Internet-Survey in late 2017 (EMIS-2017), which aimed to inform interventions for MSM who are highly affected by infections with HIV and other sexually transmitted infections. Prevalence and the standardised prevalence ratio (SPR) of PrEP awareness, intention and uptake were measured on a regional level (Randstad vs. the rest of the country). Multi-level logistic modelling was conducted to identify the association of PrEP uptake with PrEP awareness and intention, socio-demographic, psycho-social determinants and random effects from regional differences. MSM from the Randstad used more PrEP (SPR = 1.4 vs. 0.7) compared to the rest of the country, but there were minor differences for awareness and intention. The regional distinction was estimated to explain 4.6% of the PrEP use variance. We observed a greater influence from PrEP intention (aOR = 4.5, 95% CI 2.0-10.1), while there was limited influence from the awareness of PrEP (aOR = 0.4, 95% CI 0.04-4.4). Lower education (aOR = 0.4, 95% CI 0.2-0.9) was negatively associated with PrEP uptake; however, no significant difference was found between middle (aOR = 1.2, 95% CI 0.7-2.0) and high education. We showed that regional differences-MSM in non-urban regions-and other psycho-social determinants account for lower PrEP uptake. Based on these findings, more fine-tuned PrEP access with a focus on non-urban regions can be implemented, and tailored campaigns increasing intention/use can be conducted among target populations.

The effects of free condom distribution on HIV and other sexually transmitted infections in men who have sex with men.

BACKGROUND: HIV and other sexually transmitted infections remain a burden on men who have sex with men in the era of effective combination antiretroviral therapy. New prevention efforts are therefore needed. One of these approaches is the current country-wide free condom distribution at gay bars with darkrooms and gay saunas in the Netherlands. This study assessed the effects of free condom distribution on incidence and burden of disease of HIV and other sexually transmitted infections. METHODS: A static model was constructed to calculate the impact of free condom distribution on HIV, hepatitis C, chlamydia, gonorrhoea, and syphilis among men who have sex with men visiting these venues. Outcomes included new infections averted and disability-adjusted life years averted. Scenario studies were performed to predict the effects of a further increase of condom use, condom effectiveness and coverage. Lastly, cost-effectiveness and sensitivity analyses were performed. RESULTS: Our model showed that condom use at public sex venues increased after the intervention. Annual incidence risk decreased, ranging from 5.73% for gonorrhoea to 7.62% for HIV. The annual number of new infections averted was largest for chlamydia and gonorrhoea (261 and 394 infections, respectively), but 42 new HIV infections were averted as well. In scenarios where condom use and condom effectiveness were further increased, the number of infections reduced more extensively. Over 99% of the decrease in burden of disease was due to HIV. The intervention was cost-effective and cost-saving (for every €1 spent on condom distribution, €5.51 was saved) and remained this in all sensitivity analyses. CONCLUSIONS: Free condoms at public sex venues could reduce the transmission of HIV and other sexually transmitted infections. Condom distribution is an affordable and easily implemented intervention that could reduce the burden of disease in men who have sex with men substantially.

Comparing databases: determinants of sexually transmitted infections, HIV diagnoses, and lack of HIV testing among men who have sex with men.

BACKGROUND: Early detection and treatment of STI/HIV are public health priorities. Our objective was to compare characteristics of men who have sex with men (MSM) in Dutch data available in 2010 from EMIS, an international internet survey, Schorer Monitor, a Dutch internet survey, and data from STI- clinic visits, since these might be subject to different and unknown biases. METHODS: Data from Dutch MSM Internet Surveys (EMISNL N = 3,787; Schorer Monitor, SMON N = 3,602), and 3,800 STI clinic visits (SOAP) were combined into one dataset. We included factors that were measured in all three databases. The socio-demographics included were age (at the time of the survey), zip code, and ethnicity. Behavioural variables included were the number of sexual partners, condom use with last sexual partner, drug use, being diagnosed with STI, being diagnosed with HIV, and HIV testing. Outcomes we investigated were being diagnosed with STI, HIV, and never been tested for HIV. RESULTS: Logistic regressions showed that determinants for being diagnosed with STI were having more sexual partners, drug use, and having had an HIV test (aORs 1.3 to 17.1) in EMIS and SMON. Determinants for being diagnosed with HIV in all three databases were older age, living in Amsterdam, and having more partners (aORs 1.8 to 4.4). In EMIS and SMON, drug use, non-condom use, and having STI were additional determinants (aORs 1.6 to 8.9). Finally, determinants associated with never been tested for HIV were being younger (only SOAP), living outside of Amsterdam, having fewer partners, no drug use, and no STI (aORs 0.2 to 0.8). CONCLUSIONS: Risk factors from internet surveys were largely similar, but differed from STI clinics, possibly because it involves self-reports rather than diagnoses or because of differences in timing. The difference between the internet surveys and STI clinic data is much less pronounced for having never been tested, suggesting both are appropriate for this outcome. These findings shed light on conclusions drawn from different data sources, as well as the comparability of recruitment strategies, the robustness of risk factors, consequences of phrasing questions differently, and on (policy) implications based on different data sources.