Geospatial patterns of progress towards Unaids ‘95-95-95’ targets and community vulnerability in Zambia

Insights from population-based HIV impact assessments

Bibliographic Data

ID21878775
AuthorsDiego F Cuadros (0000-0001-7060-4203, University of Cincinnati, corresponding author), Tuhin Chowdhury (University of Cincinnati), Masabho Milali (New York University), Daniel Citron (0000-0002-1282-4176, New York University), Daniel T Citron (Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA), Sulani Nyimbili (0000-0002-7202-4971, Centre for Infectious Disease Research in Zambia), Natalie Vlahakis (0009-0002-2035-1812, Centre for Infectious Disease Research in Zambia), Theodora Savory (0009-0004-5401-4990, Centre for Infectious Disease Research in Zambia), Lloyd Mulenga (0000-0002-1044-4209, Ministry of Health), Suilanji Sivile (0009-0005-3072-475X, Ministry of Health), Khozya Zyambo (0000-0002-3813-2784, Ministry of Health), Anna Bershteyn (0000-0002-6604-7093, New York University)
Year2023
Volume8
Issue10
Pagese012629
Publication date2023-10-01
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2023-012629
PMID37899088
OpenAlexW4388035565
LanguageEN
Citations received1
References cited23

INTRODUCTION: In 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. METHODS: 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 optimised 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 utilisation. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioural covariates and the three main outcomes of study. RESULTS: Varied progress towards the '95-95-95' targets were observed in different regions of Zambia. Each '95' displayed a unique geographical pattern, independent of HIV prevalence, resulting in four distinct geographical 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 antiretroviral therapy and having detectable viral loads. CONCLUSIONS: Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographical 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

Cartography · Economic growth · Environmental health · Geography · Geospatial analysis · Health care · Health geography · Logistic regression · Odds · Population · Public health · Sociology · Demography · Environmental and Social Impact Assessments · Global Maternal and Child Health · HIV/AIDS Research and Interventions · Medicine · Nursing · Health Policy

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