Geospatial and sociodemographic disparities in HIV prevalence and HIV status unawareness among men in Zimbabwe using ZIMPHIA 2020 data
6 affiliations
- 1Department of Medicine, Washington University School of Medicine
- 2Program in Occupational Therapy, Washington University School of Medicine
- 3Department of Public Health and Health Sciences, Northeastern University
- 4Boston University School of Public Health
- 5Department of Epidemiology and Biostatistics, School of Public Health, Makerere University
- 6School of Public Health, Washington University in St. Louis
Abstract
Introduction Although Zimbabwe is among the countries on track to end the HIV epidemic by 2030, important gaps remain. Recent disruptions in HIV funding risk reversing decades of progress. Understanding geographic and sociodemographic disparities in HIV burden and care is important for optimizing resource allocation. Methods We used cross-sectional data from the ZIMPHIA 2020 survey. Among the 7,664 men included in the study, we estimated survey-weighted descriptive statistics and HIV prevalence across sociodemographic characteristics. The first 95 target was assessed by sociodemographic characteristics, while all 95–95–95 targets were described and mapped. Multivariable logistic regression was performed to identify factors associated with HIV status unawareness. Spatial autocorrelation and hotspot analyses were used to assess geographic clustering of HIV prevalence and HIV unawareness. Results HIV prevalence among men was 10.2% (95% CI: 9.5%–11.0%). Among HIV-positive men (n = 906), 84.3% were aware of their status, 95.9% of those aware were on ART, and 89% of those on ART were virally suppressed. HIV prevalence was highest among men aged 45 + years (21.1%; 95% CI: 19.1%–23.2%). Conversely, unawareness was highest among men aged 15–24. Each additional year reduced the odds of unawareness by 9% (aOR = 0.91; 95% CI: 0.88–0.94). HIV prevalence was highest in the Matabeleland provinces, while unawareness was highest in Mashonaland Central and Masvingo. Cluster-level spatial analyses demonstrated significant spatial clustering of HIV prevalence with localized hotspots, whereas HIV status unawareness showed no significant clustering. Conclusion Our findings demonstrated sociodemographic and geographic heterogeneity in HIV prevalence and unawareness among men. Resource allocation should be targeted accordingly.
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BibTeX
@article{mukwekwerere2026geospatial,
title = {{Geospatial and sociodemographic disparities in HIV prevalence and HIV status unawareness among men in Zimbabwe using ZIMPHIA 2020 data}},
author = {Ellen D. Mukwekwerere and Ellen Wakisa Nyasulu Chiwoni and Elizabeth Nakiyingi and Peter Kalulu and Redvers Kadzungwa and Rubanga David Atube and Bernard F. Banda},
journal = {Discover Public Health},
year = {2026},
month = oct,
doi = {10.1186/s12982-026-02733-0},
url = {https://doi.org/10.1186/s12982-026-02733-0},
note = {CC BY},
}
RIS
TY - JOUR
TI - Geospatial and sociodemographic disparities in HIV prevalence and HIV status unawareness among men in Zimbabwe using ZIMPHIA 2020 data
AU - Ellen D. Mukwekwerere
AU - Ellen Wakisa Nyasulu Chiwoni
AU - Elizabeth Nakiyingi
AU - Peter Kalulu
AU - Redvers Kadzungwa
AU - Rubanga David Atube
AU - Bernard F. Banda
PY - 2026
DA - 2026/10/25
JO - Discover Public Health
DO - 10.1186/s12982-026-02733-0
UR - https://doi.org/10.1186/s12982-026-02733-0
AB - Introduction Although Zimbabwe is among the countries on track to end the HIV epidemic by 2030, important gaps remain. Recent disruptions in HIV funding risk reversing decades of progress. Understanding geographic and sociodemographic disparities in HIV burden and care is important for optimizing resource allocation. Methods We used cross-sectional data from the ZIMPHIA 2020 survey. Among the 7,664 men included in the study, we estimated survey-weighted descriptive statistics and HIV prevalence across sociodemographic characteristics. The first 95 target was assessed by sociodemographic characteristics, while all 95–95–95 targets were described and mapped. Multivariable logistic regression was performed to identify factors associated with HIV status unawareness. Spatial autocorrelation and hotspot analyses were used to assess geographic clustering of HIV prevalence and HIV unawareness. Results HIV prevalence among men was 10.2% (95% CI: 9.5%–11.0%). Among HIV-positive men (n = 906), 84.3% were aware of their status, 95.9% of those aware were on ART, and 89% of those on ART were virally suppressed. HIV prevalence was highest among men aged 45 + years (21.1%; 95% CI: 19.1%–23.2%). Conversely, unawareness was highest among men aged 15–24. Each additional year reduced the odds of unawareness by 9% (aOR = 0.91; 95% CI: 0.88–0.94). HIV prevalence was highest in the Matabeleland provinces, while unawareness was highest in Mashonaland Central and Masvingo. Cluster-level spatial analyses demonstrated significant spatial clustering of HIV prevalence with localized hotspots, whereas HIV status unawareness showed no significant clustering. Conclusion Our findings demonstrated sociodemographic and geographic heterogeneity in HIV prevalence and unawareness among men. Resource allocation should be targeted accordingly.
SN - 3005-0774
ER -