grant

Can mental health services break the cycle perpetuating HIV hotspots in sub-Saharan Africa?

Organization NEW YORK UNIVERSITY SCHOOL OF MEDICINELocation NEW YORK, UNITED STATESPosted 19 May 2021Deadline 31 Mar 2027
NIHUS FederalResearch GrantFY2025AIDS VirusAIDS preventionAcquired Immune Deficiency Syndrome VirusAcquired Immunodeficiency Syndrome VirusAdherenceAfrica South of the SaharaAnxietyAreaBehavioralCaringCharacteristicsClassificationCollaborationsCommunitiesCost Effectiveness AnalysisCountryDataDiagnosisEnsureEpidemicEquilibriumFeedbackFractalsGeneral TaxonomyGeneralized GrowthGeographyGoalsGrowthHIVHIV PreventionHIV riskHIV/AIDS preventionHealthHealth BenefitHealth Care ProvidersHealth PersonnelHistoryHuman Immunodeficiency VirusesIncidenceInfectionInvestigatorsInvestmentsKenyaKnowledgeLAV-HTLV-IIILinkLocationLymphadenopathy-Associated VirusMapsMathMath ModelsMathematicsMeasurableMeasuresMental DepressionMental Health ServicesMental Hygiene ServicesMental disordersMental health disordersMethodsModelingNatureNorthern RhodesiaPatternPersonsPhasePoliciesPrEPPrevalencePreventionProliferatingPropertyPsychiatric DiseasePsychiatric DisorderRecording of previous eventsResearch PersonnelResearch ResourcesResearchersResourcesRiskRisk BehaviorsRisky BehaviorRoleRunningSample SizeServicesSpottingsSub-Saharan AfricaSubsaharan AfricaSustainable DevelopmentSystematicsTaxonomyTestingTissue GrowthTranslationsTypologyUnited NationsVariantVariationVirus-HIVVisitWorkZambiaat risk behaviorauthoritybalancebalance functioncommon treatmentcostcost effectivenesscost efficient analysiscost-effective analysisdemographicsdepressionepidemic containmentepidemic controlepidemic mitigationepidemic responsefrontierhealth care personnelhealth care workerhealth providerhealth workforcehigh risk grouphigh risk individualhigh risk peoplehigh risk populationhigh risk sex activityhigh risk sex behaviorhigh risk sexual activityhigh risk sexual behaviorhistoriesin silicoinformation gatheringmathematic modelmathematical modelmathematical modelingmedical personnelmental health caremental illnessontogenypre-exposure prophylaxisprogramspsychiatric illnesspsychological disorderresponserisky sexual behaviorscale upscreeningscreeningssimulationsocial roletransactional sextranslationtreatment provider
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Full Description

ABSTRACT/SUMMARY
HIV incidence is declining in sub-Saharan Africa (SSA), but some areas are not on track to achieve the

“epidemic control” target of <0.1% annual rate of new infections set by the United Nations in the Sustainable

Development Goals. Common mental disorders (CMD) such as depression and anxiety are extremely

prevalent among people living with HIV, interfere with lifelong adherence to treatment, and are associated with

risky sexual behaviors. Accordingly, health authorities in SSA are recognizing the importance of CMD

screening and treatment as a component of HIV prevention, but have not yet determined where to focus these

services. The areas at greatest risk of missing the epidemic control target are known as HIV hotspots. We

hypothesize that there are different types of hotspots: some driven by risky behaviors, some arising by random

chance, and some that emerged in the past and have become trapped in a positive feedback loop between

incidence and prevalence. The optimal role of CMD screening and treatment may differ by hotspot type.

We propose to use mathematical modeling to predict the occurrence of hotspots, determine how to classify

them by type, and estimate the optimal role of CMD screening and treatment for each HIV hotspot type. Next,

we will work with experts in two SSA countries – Kenya and Zambia – to develop an investment case for

incorporating CMD screening and treatment into an optimal HIV response, either nationally or with a focus on

HIV hotspots. Finally, we will use a value-of-information approach to determine whether the costs of finding

and classifying hotspots are justified by the benefits of targeting and customizing the HIV response to each

hotspot. We expect our project to guide Ministries of Health and implementers about scale-up of CMD

treatment in SSA while also expanding basic understanding of HIV epidemics, which were hypothesized to

contain hotspots due to fundamental mathematical properties such as fractals and chaos. These hypotheses

have not been revisited in two decades, while geospatial HIV data and methods have proliferated. We expect

that our project will enable more effective HIV prevention in SSA by expanding hotspot targeting and by

facilitating the integration of CMD care into the HIV response.

Grant Number: 5R01MH124478-05
NIH Institute/Center: NIH

Principal Investigator: Anna Bershteyn

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