A novel Bayesian approach to predicting reductions in HIV incidence following increased testing interventions among gay, bisexual and other men who have sex with men in Vancouver, Canada

Cost-effectiveness of internet-based HIV screening among gay, bisexual and other men who have sex with men (GBMSM) in Metro Vancouver, Canada

BACKGROUND

GetCheckedOnline is an internet-based screening service aiming to increase HIV testing among gay, bisexual and other men who have sex with men (GBMSM). We assessed the cost-effectiveness of GetCheckedOnline in its first implementation phase at different uptake scenarios compared to clinic-based screening services alone in Metro Vancouver, Canada.

METHODS

From a healthcare payer's perspective, our cost-utility analysis used an established dynamic GBMSM HIV compartmental model estimating the probability of acquiring HIV, progressing through diagnosis, disease stages and treatment over a 30-year time horizon. The base case scenario assumed 4.7% uptake of GetCheckedOnline in 2016 (remainder using clinic-based services), with 74% of high-risk and 44% of low-risk infrequent testers becoming regular testers in five years. Scenario analyses tested increased GetCheckedOnline uptake to 10% and 15%.

RESULTS

The cost per test for GetCheckedOnline was $29.40 compared to clinic-based services $56.92. Compared with clinic-based screening services, the projected increase in testing frequency with 4.7% uptake of GetCheckedOnline increased the costs by $329,600 (95% Credible Interval: -$498,200, $571,000) and gained 4.53 (95%CrI: 0, 9.20) quality-adjusted life years (QALYs) in a 30-year time horizon. The probability of GetCheckedOnline being cost-effective was 34% at the threshold of $50,000 per QALY, and increased to 73% at the threshold of $100,000 per QALY. The results were consistent in the other uptake scenarios. The probability of GetCheckedOnline being cost-effective became 80% at the threshold of $50,000 per QALY if assuming 5-year time horizon.

CONCLUSIONS

GetCheckedOnline is almost half the cost of clinic-based services on a per-test basis. However, increased access to testing should be balanced with risk profiles of patients to ensure the implementation can be a cost-effective strategy for increasing HIV screening among GBMSM in Metro Vancouver. Additional analyses are needed to understand the impact of internet-based screening including screening for other STIs and in other populations.

Estimation of HIV prevalence and burden in Nigeria: a Bayesian predictive modelling study

Background

The cost of population-based surveys is high and obtaining funding for a national population-based survey may take several years, with follow-up surveys taking up to five years. Survey-based prevalence estimates are prone to bias owing to survey non-participation, as not all individuals eligible to participate in a survey may be reached, and some of those who are contacted do not consent to HIV testing. This study describes how Bayesian statistical modeling may be used to estimate HIV prevalence at the state level in a reliable and timely manner.

Methods

We analysed national HIV testing services (HTS) data for Nigeria from October 1, 2020, to September 30, 2021, to derive state-level HIV seropositivity rates. We used a Bayesian linear model with normal prior distribution and Markov Chain Monte Carlo approach to estimate HIV state-level prevalence for the 36 states +1 FCT in Nigeria. Our outcome variable was the HIV seropositivity rates and we adjusted for demographic, economic, biological, and societal covariates collected from the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), 2018 Nigeria Demographic and Health Survey (NDHS) and 2016-17 Multiple Indicator Cluster Surveys (MICS). The estimated population of 15-49 years olds in each state was multiplied by estimates from the estimated prevalence to generate state-level HIV burden.

Findings

Our estimated national HIV prevalence was 2.1% (95% CI: 1.5-2.7%) among adults aged 15-49 years in Nigeria, which corresponds to approximately 2 million people living with HIV, compared to previous national HIV prevalence estimates of 1.4% from the 2018 NAIIS and UNAIDS estimation and projection package PLHIV estimation of 1.8 million in 2022. Our modelled HIV prevalence in Nigeria varies by state, with Benue (5.7%, 95% CI: 5.0-6.3) having the highest prevalence, followed by Rivers (5.2%, 95% CI: 4.6-5.8%), Akwa Ibom (3.5%, 95% CI: 2.9-4.1%), Edo (3.4%, 95% CI: 2.9-4.0%) and Taraba (3.0%, 95% CI: 2.6-3.7%) placing fourth and fifth, respectively. Jigawa had the lowest HIV prevalence (0.3%), which was consistent with prior estimates.

Interpretation

This model provides a comprehensive and flexible use of evidence to estimate state-level HIV seroprevalence for Nigeria using program data and adjusting for explanatory variables. Thus, investment in program data for HIV surveillance will provide reliable estimates for HIV sub-national monitoring and improve planning and interventions for epidemiologic control.

Funding

This article was made possible by the support of the American people through the United States Agency for International Development (USAID) under the U.S. President's Emergency Plan for AIDS Relief (PEPFAR).

Impact and cost-effectiveness of non-governmental organizations on the HIV epidemic in Ukraine among MSM

OBJECTIVE

Non-governmental organizations (NGOs) in Ukraine have provided HIV testing, treatment, and condom distribution for MSM. HIV prevalence among MSM in Ukraine is 5.6%. We estimated the impact and cost-effectiveness of MSM-targeted NGO activities in Ukraine.

DESIGN

A mathematical model of HIV transmission among MSM was calibrated to data from Ukraine (2011-2018).

METHODS

The model, designed before the 2022 Russian invasion of Ukraine, evaluated the impact of 2018 status quo coverage levels of 28% of MSM being NGO clients over 2016-2020 and 2021-2030 compared with no NGO activities over these time periods. Impact was measured in HIV incidence and infections averted. We compared the costs and disability adjusted life years (DALYs) for the status quo and a counterfactual scenario (no NGOs 2016-2020, but with NGOs thereafter) until 2030 to estimate the mean incremental cost-effectiveness ratio (cost per DALY averted).

RESULTS

Without NGO activity over 2016-2020, the HIV incidence in 2021 would have been 44% (95% credibility interval: 36-59%) higher than with status quo levels of NGO activity, with 25% (21-30%) more incident infections occurring over 2016-2020. Continuing with status quo NGO coverage levels will decrease HIV incidence by 41% over 2021-2030, whereas it will increase by 79% (60-120%) with no NGOs over this period and 37% (30-51%) more HIV infections will occur. Compared with if NGO activities had ceased over 2016-2020 (but continued thereafter), the status quo scenario averts 14 918 DALYs over 2016-2030 with a mean incremental cost-effectiveness ratio of US$600.15 per DALY averted.

CONCLUSION

MSM-targeted NGOs in Ukraine have prevented considerable HIV infections and are highly cost-effective compared with a willingness-to-pay threshold of 50% of Ukraine's 2018 GDP (US$1548).

Leveraging Resilience-supportive Strategies to Enhance Protective Factors in Young Sexual Minority Men: A Scoping Review of HIV Behavioral Interventions Implemented in High-income Countries

Behavioral HIV interventions focused on strengthening young sexual minority men's (SMM) internal (assets) and external (resources) protective factors are promising, yet their evaluation as resilience-supportive strategies to minimize or negate HIV-related risks remain understudied. The objective of this scoping review was to describe resilience-supportive intervention strategies that have been used to achieve desired HIV behavioral outcomes and to identify how these strategies have been evaluated using a resilience analytic framework. Our scoping review uncovered 271 peer-reviewed articles, of which 38 were eligible for inclusion based on our review criteria. The majority of interventions relied on social support strategies as their primary resilience-supportive strategy. A third of interventions reviewed analyzed their findings from a deficits-focused model, another third used compensatory resilience models, and the remaining interventions employed a hybrid (i.e., deficit and compensatory model) strategy. None of the interventions evaluated their intervention effects using a risk-protective model. From our synthesis regarding the current state of research around resilience-informed interventions, we propose strategies to inform the design of resilience-supportive approaches and make recommendations to move the field forward on how to develop, implement, and measure young SMM's resiliency processes.

A cohort study comparing rate of repeat testing for sexually transmitted and blood-borne infections between clients of an internet-based testing programme and of sexually transmitted infection clinics in Vancouver, Canada

Objectives

Internet-based sexually transmitted and blood-borne infection (STBBI) testing services reduce testing barriers through bypassing face-to-face clinical encounters, potentially enabling clients at ongoing sexual risk to test more frequently. To our knowledge, this hypothesis has not been previously tested. We compared the frequency of repeat testing between Vancouver-based clients of GetCheckedOnline (GCO)—an internet-based STBBI testing service in British Columbia, Canada—and clients of three sexually transmitted infection (STI) clinics in Vancouver for 29 months after GCO launched.

Methods

An administrative data cohort (n=19 497) was assembled using GCO, clinical and laboratory databases. We included all individuals who tested for HIV, gonorrhoea/chlamydia, syphilis or hepatitis C at three STI clinics or using GCO, between September 2014 and February 2017. The rate of repeat testing (>30 days after first episode) was compared between clients who used GCO at least once and those who tested only in STI clinics. Poisson regression was used to generate relative rate (RR) for repeat testing, with adjustment for age, gender/sexual orientation, risk factors (eg, history of STI diagnosis) and rate of testing before GCO launched.

Results

1093 GCO clients were identified, of whom 434 (40%) had repeat test episodes; 8200/18 404 (45%) of clinic clients tested more than once. During the 29-month analysis period, GCO clients repeat tested 1.87 times per person-year, whereas clinic clients repeat tested 1.53 times per person-year, resulting in a crude RR of 1.22 (95% CI: 1.14 to 1.31). Adjustment for covariates increased the RR to 1.26 (95% CI: 1.15 to 1.37).

Conclusions

In this cohort, individuals using internet-based STBBI testing had a rate of repeat testing 22% greater than clinic-based clients. This effect was increased after adjusting for characteristics associated with higher test frequency. The online interface of GCO may facilitate more frequent testing and may therefore contribute to earlier STBBI diagnosis.

Predicting the impact of clustered risk and testing behaviour patterns on the population-level effectiveness of pre-exposure prophylaxis against HIV among gay, bisexual and other men who have sex with men in Greater Vancouver, Canada

Pre-exposure prophylaxis (PrEP) has the potential to greatly reduce transmission of HIV. However, significant questions remain around how behavioural factors may influence its impact within target populations. We used a 2014 sexual behaviour survey to modify and recalibrate a mathematical model of HIV infection dynamics within the population of gay, bisexual and other men who have sex with men (GBMSM) in the Greater Vancouver area of British Columbia, Canada. We performed a clustering analysis on the survey data to divide the population into categories associated with their reported risk of HIV exposure as well as their reported testing habits and attitudes towards PrEP. We found a positive association between reported risk and testing behaviour and level of awareness/interest in PrEP. Using the cluster groups to structure the population, we then estimated the impact of PrEP on HIV transmission in our study population. We found that the association between behaviour and interest in PrEP substantially boosted the population-level effectiveness of PrEP. Within our model, if PrEP adoption was unrelated to risk and testing, an additional 206 (95% credible interval 5-261), new infections representing 15% of total infections are predicted to occur among GBMSM over ten years, compared to where PrEP is adopted by individuals according to their level of interest. Our results underscore the importance of incorporating behavioural data into models when predicting the impact of future public health interventions.