The Best Predictor of Future Behavior May Be the Past: Exploring Behavior Change in Men Who Have Sex with Men Using Pre-exposure Prophylaxis in the Netherlands.

Pre-exposure prophylaxis (PrEP) use prevents HIV transmission, and may lead to changes in sexual behavior. We aimed to explore sexual behavior over time, and identify predictors of behavior change in men who have sex with men (MSM) using PrEP at sexual health centers (SHC) in the Netherlands. We used longitudinal data from the national STI surveillance database (January 2018-June 2021) of HIV-negative MSM who first initiated PrEP in the national PrEP pilot. We modelled behavior change after PrEP initiation, and identified predictors of behavior change using multi-state Markov models. The probability of stopping group sex, chemsex, use of poppers or erection stimulants, and having ≥ 10 partners in the past 6 months among included MSM (n = 4,349, n SHC visits = 21,820) was higher compared to the probability of starting with these behaviors after PrEP initiation. However, MSM who used condoms consistently during anal sex had a high probability of changing to inconsistent condom use (0.8) at the next visit, and inconsistent condom users mostly remained inconsistent (0.8). First visit, visiting the SHC more often (vs. regular), and STI diagnosis were predictors of starting or continuing with most of the behaviors associated with increased risk. Behavior change was less likely among older participants (> 34 compared to ≤ 34 years), and during COVID-19 lockdown and post-lockdown periods compared to pre-COVID-19. Although condom use decreased over time, transitions towards stopping with other behaviors associated with increased likelihood of acquiring an STI after PrEP initiation were common. This may suggest increased sexual empowerment, especially among younger MSM. Predictors of behavior change may help to identify MSM who are likely to start with or continue to engage in these behaviors in the near future and to provide suitable and timely counselling about behavior and PrEP adherence.

MSM with HIV: Improving prevalence and risk estimates by a Bayesian small area estimation modelling approach for public health service areas in the Netherlands.

Despite close monitoring of HIV infections amongst MSM (MSMHIV), the true prevalence can be masked for areas with small population density or lack of data. This study investigated the feasibility of small area estimation with a Bayesian approach to improve HIV surveillance. Data from EMIS-2017 (Dutch subsample, n = 3,459) and the Dutch survey SMS-2018 (n = 5,653) were utilized. We applied a frequentist calculation to compare the observed relative risk of MSMHIV per Public Health Services (GGD) region in the Netherlands and a Bayesian spatial analysis and ecological regression to quantify how spatial heterogeneity in HIV amongst MSM is related to determinants while accounting for spatial dependence to obtain more robust estimates. Both estimations converged and confirmed that the prevalence is heterogenous across the Netherlands with some GGD regions having a higher-than-average risk. Our Bayesian spatial analysis to assess the risk of MSMHIV was able to close data gaps and provide more robust prevalence and risk estimations.

Availability and accessibility of HIV self-tests and self-sample kits at community pharmacies in the Netherlands.

BACKGROUND: In 2016 the WHO declared HIV self-testing and self-sampling an effective and safe test option that can reduce testing barriers. HIV self-tests and self-sampling kits (HIVST/HIVSS) are available for purchase at Dutch community pharmacies since 2019. We investigated the availability and accessibility of HIVST/HIVSS in community pharmacies, and factors associated with test availability. METHODS: An online survey among all Dutch community pharmacies (n = 1,987) was conducted between April and June 2021. Availability of HIVST/HIVSS and experiences of pharmacists with the test offer were analyzed with descriptive statistics. The association of pharmacy and pharmacists' characteristics with HIVST/HIVSS availability was explored by logistic regression analysis. RESULTS: In total, 465 pharmacists completed the questionnaire. Of the responding pharmacists, 6.2% (n = 29) offered HIVST/HIVSS. The majority (82.8%) sold between 0 and 20 tests per year. In total, pharmacies sold an estimated 370 HIVST/HIVSS per year. Pharmacies having HIVST/HIVSS available were less often located in moderately-urbanized to rural neighborhoods (OR 0.35, 95%CI 0.16-0.77 versus highly-urbanized), and were less often located in moderate-to-low SES neighborhoods (OR 0.40, 95%CI 0.18-0.88 versus high-SES). Reasons for not offering HIVST/HIVSS by pharmacists were no or little demand (69.3%), and not being familiar with these tests (17.4%). 52% of the pharmacists provided information about testing to test buyers. Reported options to improve the test offer were giving advice about (performing) the test to test buyers (72.4%), placing tests visible on the counter (51.7%), and advertisement (37.9%). CONCLUSION: HIVST/HIVSS have a limited practical availability in Dutch community pharmacies since their introduction in 2019, especially in lower-urbanized and lower-SES areas. Further research is needed to explore how to expand access to HIVST/HIVSS through community pharmacies in the Netherlands, and how to tailor it to the needs of pharmacy clients.

Community-based HIV testing in The Netherlands: experiences of lay providers and end users at a rapid HIV test checkpoint.

BACKGROUND: The AIDS Healthcare Foundation (AHF-Checkpoint) in The Netherlands offers rapid HIV testing for key populations by lay providers. We explored the experiences and needs of lay providers and end users of HIV testing at AHF-Checkpoint, taking into account the WHO 5C-(consent, confidentiality, counselling, correct-results, connection-to-care) criteria for HIV test services. METHODS: Qualitative evaluation with 15 semi-structured interviews conducted during 2020 with ten lay providers and five gay or bisexual end users. Recorded interviews were thematically analysed, taking data triangulation into account. RESULTS: Four domains were identified: (1) accessibility of HIV testing, (2) quality of test procedures, (3) bridging (transitional care), and (4) future strategies for service delivery. AHF-Checkpoint fills a gap for key populations including LGBTQ and refugees, who experience HIV testing barriers at sexual health centres or general practices. The level of trust between lay providers and end users was highly valued by end users. They appreciated the low threshold to test at no costs, and the absence of waiting lists or triaging. Needs expressed by lay providers included more preparedness for emotionally charged situations, and extra training to improve STI knowledge. End users expressed a need for a full STI test package. Of the 5Cs, consent, counselling, and correct results were realised but confidentiality was sometimes difficult to achieve at pop-up locations, and referral barriers for confirmation testing (connection-to-care) were occasionally experienced by lay providers during weekends. CONCLUSION: AHF-Checkpoint was described as a convenient and easily accessible service by end users and lay providers. Of the WHO 5Cs, connection-to-care could be optimised to ensure HIV confirmation and STI testing through a liaison approach with professionals from the regular healthcare sector.

Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data.

BACKGROUND: Estimates of the size of the undiagnosed HIV-infected population are important to understand the HIV epidemic and to plan interventions, including "test-and-treat" strategies. METHODS: We developed a multi-state back-calculation model to estimate HIV incidence, time between infection and diagnosis, and the undiagnosed population by CD4 count strata, using surveillance data on new HIV and AIDS diagnoses. The HIV incidence curve was modelled using cubic splines. The model was tested on simulated data and applied to surveillance data on men who have sex with men in The Netherlands. RESULTS: The number of HIV infections could be estimated accurately using simulated data, with most values within the 95% confidence intervals of model predictions. When applying the model to Dutch surveillance data, 15,400 (95% confidence interval [CI] = 15,000, 16,000) men who have sex with men were estimated to have been infected between 1980 and 2011. HIV incidence showed a bimodal distribution, with peaks around 1985 and 2005 and a decline in recent years. Mean time to diagnosis was 6.1 (95% CI = 5.8, 6.4) years between 1984 and 1995 and decreased to 2.6 (2.3, 3.0) years in 2011. By the end of 2011, 11,500 (11,000, 12,000) men who have sex with men in The Netherlands were estimated to be living with HIV, of whom 1,750 (1,450, 2,200) were still undiagnosed. Of the undiagnosed men who have sex with men, 29% (22, 37) were infected for less than 1 year, and 16% (13, 20) for more than 5 years. CONCLUSIONS: This multi-state back-calculation model will be useful to estimate HIV incidence, time to diagnosis, and the undiagnosed HIV epidemic based on routine surveillance data.