Geospatial Patterns of Progress towards UNAIDS "95-95-95" Targets and Community Vulnerability in Zambia.

dc.contributor.affiliationNational HIV Program, Ministry of Health, Lusaka, Zambia.
dc.contributor.affiliationDigital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.
dc.contributor.affiliationDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
dc.contributor.affiliationCentre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.
dc.contributor.authorCuadros DF
dc.contributor.authorChowdhury T
dc.contributor.authorMilali M
dc.contributor.authorCitron D
dc.contributor.authorNyimbili S
dc.contributor.authorVlahakis N
dc.contributor.authorSavory T
dc.contributor.authorMulenga L
dc.contributor.authorSivile S
dc.contributor.authorZyambo K
dc.contributor.authorBershteyn A
dc.date.accessioned2025-05-23T11:40:35Z
dc.date.issued2023-Apr-26
dc.description.abstractIn sub-Saharan Africa, HIV/AIDS remains a leading cause of death. The UNAIDS established the "95-95-95" targets to improve HIV care continuum outcomes. Using geospatial data from the Zambia Population-based HIV Impact Assessment (ZAMPHIA), this study aims to investigate geospatial patterns in the "95-95-95" indicators and individual-level determinants that impede HIV care continuum in vulnerable communities, providing insights into the factors associated with gaps. This study used data from the 2016 ZAMPHIA to investigate the geospatial distribution and individual-level determinants of engagement across the HIV care continuum in Zambia. Gaussian kernel interpolation and optimized hotspot analysis were used to identify geospatial patterns in the HIV care continuum, while geospatial k-means clustering was used to partition areas into clusters. The study also assessed healthcare availability, access, and social determinants of healthcare utilization. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioral covariates and the three main outcomes of study. Varied progress towards the "95-95-95" targets were observed in different regions of Zambia. Each "95" displayed a unique geographic pattern, independent of HIV prevalence, resulting in four distinct geographic clusters. Factors associated with gaps in the "95s" include younger age, male sex, and low wealth, with younger individuals having higher odds of not being on ART and having detectable viral loads. Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographic patterns and levels of performance in the "95-95-95" targets, highlighting the need for geospatial tailored interventions to address the specific needs of different subnational regions. These findings underscore the importance of addressing differential regional gaps in HIV diagnosis, enhancing community-level factors, and developing innovative strategies to improve local HIV care continuum outcomes.
dc.identifier.doi10.1101/2023.04.24.23289044
dc.identifier.urihttps://pubs.cidrz.org/handle/123456789/10239
dc.sourcemedRxiv : the preprint server for health sciences
dc.titleGeospatial Patterns of Progress towards UNAIDS "95-95-95" Targets and Community Vulnerability in Zambia.

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