FIXED-EFFECT PANEL COUNTRY-SPECIFIC TRENDS IN HIV PREVALENCE, 1990 -2024 ANALYSIS OF 150 COUNTRIES

Authors

  • Felix Aondongu, IORPENDA ORCID: https://orcid.org/0009-0004-2006-4535 University of Ibadan, Nigeria Author
  • Friday Eyo Uko, PhD ORCID: https://orcid.org/ 0009-0008-2743-5764 National Institute of Social and Economic Research (NISER) Ibadan Author
  • Terna Godfrey Ieren, PhD ORCID: https://orcid.org/0009-0004-2006-4535 Rev. Fr. Moses Orshio Adasu University, Makurdi, Nigeria. Author

DOI:

https://doi.org/10.66811/eijrihs.vol1.no6.107

Keywords:

HIV prevalence, HIV/AIDS, fixed effects, panel data, heterogeneous trends, UNAIDS

Abstract

This study examines changes in HIV prevalence among people aged 15–49 years across 150 countries over 1990–2024. The objective is to estimate country-specific annual changes and identify countries with statistically significant declining trajectories. The World Development Indicators series SH.DYN.AIDS.ZS, sourced from UNAIDS estimates, was reshaped into a country-year panel. A conventional country fixed-effects model with a common time trend was first estimated, followed by a fixed-effects specification allowing country-specific linear trends. Country-specific slopes were estimated with Newey–West heteroskedasticity and autocorrelation-consistent standard errors using three lags; false-discovery-rate adjustment was also examined as a multiple-testing sensitivity check. The common fixed-effects trend was statistically indistinguishable from zero (β = 0.001, cluster-robust SE = 0.008, p = 0.868), while the test for heterogeneous country slopes was highly significant (F(149, 4,944) = 41.86, p < .001). Twenty-four countries out of one hundred and fifty countries recorded statistically significant negative annual trends at the 5% level, and all 24 remained significant after Benjamini–Hochberg adjustment. Zimbabwe had the largest estimated decline (−0.572 percentage points per year), followed by Malawi (−0.225), Kenya (−0.190), Côte d’Ivoire (−0.180), and Uganda (−0.162). The results show that a single pooled trend masks pronounced cross-country heterogeneity. The findings support country-specific surveillance and differentiated HIV-response planning, while cautioning that prevalence is not equivalent to incidence and that a declining prevalence slope cannot by itself establish the causal effect of any intervention.

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Author Biographies

  • Felix Aondongu, IORPENDA ORCID: https://orcid.org/0009-0004-2006-4535, University of Ibadan, Nigeria

    Department of Statistics, University of Ibadan, Nigeria

  • Friday Eyo Uko, PhD ORCID: https://orcid.org/ 0009-0008-2743-5764, National Institute of Social and Economic Research (NISER) Ibadan

    Economics and Business Policy Department, National Institute of Social and Economic Research (NISER), Ibadan

  • Terna Godfrey Ieren, PhD ORCID: https://orcid.org/0009-0004-2006-4535, Rev. Fr. Moses Orshio Adasu University, Makurdi, Nigeria.

    Department of Mathematics and Computer Science, Faculty of Science, Rev. Fr. Moses Orshio Adasu University, Makurdi, Nigeria.

References

Fonner, V. A., Sartorius, B., White, R. G., & Eaton, J. W. (2021). Declining HIV incidence in sub-Saharan Africa: A systematic review and meta-analysis of empiric data. Journal of the International AIDS Society, 24(Suppl. 6), e25730. https://doi.org/10.1002/jia2.25730

Mahy, M., Marsh, K., Sabin, K., Wanyeki, I., Daher, J., & Ghys, P. D. (2024). Methods and assumptions for estimating key HIV indicators in the UNAIDS annual estimates process. Journal of the International AIDS Society, 27(Suppl. 1), e26233. https://doi.org/10.1002/jia2.26233

Rüttenauer, T., & Ludwig, V. (2023). Fixed effects individual slopes: Accounting and testing for heterogeneous effects in panel data or other multilevel models. Sociological Methods & Research, 52(1), 43–84. https://doi.org/10.1177/0049124120926211

Stevens, O., Sabin, K., Anderson, R. L., Arias Garcia, S., Willis, K., Rao, A., McIntyre, A. F., Fearon, E., Grard, E., Stuart-Brown, A., Cowan, F., Degenhardt, L., Stannah, J., Zhao, J., Hakim, A. J., Rucinski, K., Sathane, S., Atuhaire, L., Nyasulu, P. S., Maheu-Giroux, M., Platt, L., Rice, B., Hladik, W., Baral, S., Mahy, M., & Imai-Eaton, J. W. (2024). Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: Collation and synthesis of survey data, 2010–23. The Lancet Global Health, 12(9), e1400–e1412. https://doi.org/10.1016/S2214-109X(24)00236-5

UNAIDS. (2025). AIDS, crisis and the power to transform: 2025 Global AIDS Update. Joint United Nations Programme on HIV/AIDS.

UNAIDS. (n.d.). HIV data and estimates. Retrieved October 12, 2026, from https://www.unaids.org/en/dataanalysis/knowyourresponse/HIVdata_estimates

World Bank. (n.d.). Prevalence of HIV, total (% of population ages 15–49) (SH.DYN.AIDS.ZS). World Development Indicators. Retrieved October 12, 2026, from https://data.worldbank.org/indicator/SH.DYN.AIDS.ZS

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Published

2026-09-29

How to Cite

FIXED-EFFECT PANEL COUNTRY-SPECIFIC TRENDS IN HIV PREVALENCE, 1990 -2024 ANALYSIS OF 150 COUNTRIES. (2026). EIJRIHS, 1(6), 16-39. https://doi.org/10.66811/eijrihs.vol1.no6.107

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