Dataset Information

Modelling the impact of HIV and hepatitis C virus prevention and treatment interventions among people who inject drugs in Kenya.

ABSTRACT:

Objectives

People who inject drugs (PWID) in Kenya have high HIV (range across settings: 14-26%) and hepatitis C virus (HCV; 11-36%) prevalence. We evaluated the impact of existing and scaled-up interventions on HIV and HCV incidence among PWID in Kenya.

Design

HIV and HCV transmission model among PWID, calibrated to Nairobi and Kenya's Coastal region.

Methods

For each setting, we projected the impact (percent of HIV/HCV infections averted in 2020) of existing coverages of antiretroviral therapy (ART; 63-79%), opioid agonist therapy (OAT; 8-13%) and needle and syringe programmes (NSP; 45-61%). We then projected the impact (reduction in HIV/HCV incidence over 2021-2030), of scaling-up harm reduction [Full harm reduction ('Full HR'): 50% OAT, 75% NSP] and/or HIV (UNAIDS 90-90-90) and HCV treatment (1000 PWID over 2021-2025) and reducing sexual risk (by 25/50/75%). We estimated HCV treatment levels needed to reduce HCV incidence by 90% by 2030.

Results

In 2020, OAT and NSP averted 46.0-50.8% (range of medians) of HIV infections and 50.0-66.1% of HCV infections, mostly because of NSP. ART only averted 12.9-39.8% of HIV infections because of suboptimal viral suppression (28-48%). Full HR and ART could reduce HIV incidence by 51.5-64% and HCV incidence by 84.6-86.6% by 2030. Also halving sexual risk could reduce HIV incidence by 68.0-74.1%. Alongside full HR, treating 2244 PWID over 2021-2025 could reduce HCV incidence by 90% by 2030.

Conclusion

Existing interventions are having substantial impact on HIV and HCV transmission in Kenya. However, to eliminate HIV and HCV, further scale-up is needed with reductions in sexual risk and HCV treatment.

SUBMITTER: Stone J

PROVIDER: S-EPMC9671825 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Modelling the impact of HIV and hepatitis C virus prevention and treatment interventions among people who inject drugs in Kenya.

Stone Jack J Fraser Hannah H Walker Josephine G JG Mafirakureva Nyashadzaishe N Mundia Bernard B Cleland Charles C Bartilol Kigen K Musyoki Helgar H Waruiru Wanjiru W Ragi Allan A Bhattacharjee Parinita P Chhun Nok N Lizcano John J Akiyama Matthew J MJ Cherutich Peter P Wisse Ernst E Kurth Ann A Luhmann Niklas N Vickerman Peter P

AIDS (London, England) 20220914 15

<h4>Objectives</h4>People who inject drugs (PWID) in Kenya have high HIV (range across settings: 14-26%) and hepatitis C virus (HCV; 11-36%) prevalence. We evaluated the impact of existing and scaled-up interventions on HIV and HCV incidence among PWID in Kenya.<h4>Design</h4>HIV and HCV transmission model among PWID, calibrated to Nairobi and Kenya's Coastal region.<h4>Methods</h4>For each setting, we projected the impact (percent of HIV/HCV infections averted in 2020) of existing coverages of ...[more]

PMID: 36111533

Similar Datasets

Project description:IntroductionPeople who inject drugs (PWID) in Dar es Salaam, Tanzania, have a high prevalence of HIV and hepatitis C virus (HCV). While needle and syringe programmes (NSP), opioid agonist therapy (OAT) and anti-retroviral therapy (ART) are available in Tanzania, their coverage is sub-optimal. We assess the impact of existing and scaled up harm reduction (HR) interventions on HIV and HCV transmission among PWID in Dar es Salaam.MethodsAn HIV and HCV transmission model among PWID in Tanzania was calibrated to data over 2006-2018 on HIV (∼30% and ∼67% prevalence in males and females in 2011) and HCV prevalence (∼16% in 2017), numbers on HR interventions (5254 ever on OAT in 2018, 766-1479 accessing NSP in 2017) and ART coverage (63.1% in 2015). We evaluated the impact of existing interventions in 2019 and impact by 2030 of scaling-up the coverage of OAT (to 50% of PWID), NSP (75%, both combined termed "full HR") and ART (81% with 90% virally suppressed) from 2019, reducing sexual HIV transmission by 50%, and/or HCV-treating 10% of PWID infected with HCV annually.ResultsThe model projects HIV and HCV prevalence of 19.0% (95% credibility interval: 16.4-21.2%) and 41.0% (24.4-49.0%) in 2019, respectively. For HIV, 24.6% (13.6-32.6%) and 70.3% (59.3-77.1%) of incident infections among male and female PWID are sexually transmitted, respectively. Due to their low coverage (22.8% for OAT, 16.3% for NSP in 2019), OAT and NSP averted 20.4% (12.9-24.7%) of HIV infections and 21.7% (17.0-25.2%) of HCV infections in 2019. Existing ART (68.5% coverage by 2019) averted 48.1% (29.7-64.3%) of HIV infections in 2019. Scaling up to full HR will reduce HIV and HCV incidence by 62.6% (52.5-74.0%) and 81.4% (56.7-81.4%), respectively, over 2019-2030; scaled up ART alongside full HR will decrease HIV incidence by 66.8% (55.6-77.5%), increasing to 81.5% (73.7-87.5%) when sexual risk is also reduced. HCV-treatment alongside full HR will decrease HCV incidence by 92.4% (80.7-95.8%) by 2030.ConclusionsCombination interventions, including sexual risk reduction and HCV treatment, are needed to eliminate HCV and HIV among PWID in Tanzania.

Project description:Background and aimsTo reduce hepatitis C virus (HCV) transmission among people who inject drugs (PWID), Scottish Government-funded national strategies, launched in 2008, promoted scaling-up opioid substitution therapy (OST) and needle and syringe provision (NSP), with some increases in HCV treatment. We test whether observed decreases in HCV incidence post-2008 can be attributed to this intervention scale-up.DesignA dynamic HCV transmission model among PWID incorporating intervention scale-up and observed decreases in behavioural risk, calibrated to Scottish HCV prevalence and incidence data for 2008/09.SettingScotland, UK.ParticipantsPWID.MeasurementsModel projections from 2008 to 2015 were compared with data to test whether they were consistent with observed decreases in HCV incidence among PWID while incorporating the observed intervention scale-up, and to determine the impact of scaling-up interventions on incidence.FindingsWithout fitting to epidemiological data post-2008/09, the model incorporating observed intervention scale-up agreed with observed decreases in HCV incidence among PWID between 2008 and 2015, suggesting that HCV incidence decreased by 61.3% [95% credibility interval (CrI) = 45.1-75.3%] from 14.2/100 person-years (py) (9.0-20.7) to 5.5/100 py (2.9-9.2). On average, each model fit lay within 84% (10.1/12) of the confidence bounds for the 12 incidence data points against which the model was compared. We estimate that scale-up of interventions (OST + NSP + HCV treatment) and decreases in high-risk behaviour from 2008 to 2015 resulted in a 33.9% (23.8-44.6%) decrease in incidence, with the remainder [27.4% (17.6-37.0%)] explained by historical changes in OST + NSP coverage and risk pre-2008. Projections suggest that scaling-up of all interventions post-2008 averted 1492 (657-2646) infections over 7 years, with 1016 (308-1996), 404 (150-836) and 72 (27-137) due to scale-up of OST + NSP, decreases in high-risk behaviour and HCV treatment, respectively.ConclusionsMost of the decline in hepatitis C virus (HCV) incidence in Scotland between 2008 and 2015 appears to be attributable to intervention scale-up (opioid substitution therapy and needle and syringe provision) due to government strategies on HCV and drugs.

Project description:BackgroundChronic infections with hepatitis C virus (HCV) and HIV are highly prevalent in the USA and concentrated in people who inject drugs. Treatment as prevention with highly effective new direct-acting antivirals is a prospective HCV elimination strategy. We used network-based modelling to analyse the effect of this strategy in HCV-infected people who inject drugs in a US city.MethodsFive graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment.FindingsOur model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network.InterpretationSuccessful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded.FundingNational Institute on Drug Abuse.

Dataset Information

Modelling the impact of HIV and hepatitis C virus prevention and treatment interventions among people who inject drugs in Kenya.

Objectives

Design

Methods

Results

Conclusion

Publications

Modelling the impact of HIV and hepatitis C virus prevention and treatment interventions among people who inject drugs in Kenya.

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