Can mental health services break the cycle perpetuating HIV hotspots in sub-Saharan Africa?
Can mental health services break the cycle perpetuating HIV hotspots in sub-Saharan Africa?
批准号:
10327032
负责人:
Anna Bershteyn
金额:
$71.86万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-05-19 至 2026-03-31
关键词:
AIDS preventionAdherenceAfrica South of the SaharaAnxietyAreaBehavioralCaringCharacteristicsCommunitiesCost Effectiveness AnalysisCountryCustomDataDiagnosisEnsureEpidemicEquilibriumFeedbackFractalsGeographyGoalsGrowthHIVHIV riskHealthHealth BenefitHealth PersonnelHealthcareIncidenceInfectionInvestmentsKenyaKnowledgeLeadLinkLocationMapsMathematicsMeasurableMeasuresMental DepressionMental HealthMental Health ServicesMental disordersMethodsModelingNaturePatternPhasePoliciesPrevalencePreventionProliferatingPropertyRecording of previous eventsResearch PersonnelResourcesRiskRisk BehaviorsRoleRunningSample SizeServicesSustainable DevelopmentTaxonomyTestingTranslationsTypologyUnited NationsVariantWorkZambiaauthoritybasecommon treatmentcostcost effectivenessdemographicsfrontierhigh risk populationhigh risk sexual behaviorin silicoinformation gatheringmathematical modelpre-exposure prophylaxisprogramsresponsescale upscreeningsexsimulation
中文摘要
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英文摘要
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.
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