Original Research

HIV epidemic drivers in South Africa: A model-based evaluation of factors accounting for inter-provincial differences in HIV prevalence and incidence trends

Leigh F. Johnson, Rob E. Dorrington, Haroon Moolla
Southern African Journal of HIV Medicine | Vol 18, No 1 | a695 | DOI: https://doi.org/10.4102/sajhivmed.v18i1.695 | © 2017 Leigh F. Johnson, Rob E. Dorrington, Haroon Moolla | This work is licensed under CC Attribution 4.0
Submitted: 21 September 2016 | Published: 28 July 2017

About the author(s)

Leigh F. Johnson, Centre for Infectious Disease Epidemiology and Research, University of Cape Town, South Africa
Rob E. Dorrington, Centre for Actuarial Research, University of Cape Town, South Africa
Haroon Moolla, Centre for Infectious Disease Epidemiology and Research, University of Cape Town, South Africa


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Abstract

Background: HIV prevalence differs substantially between South Africa’s provinces, but the factors accounting for this difference are poorly understood.

Objectives: To estimate HIV prevalence and incidence trends by province, and to identify the epidemiological factors that account for most of the variation between provinces.

Methods: A mathematical model of the South African HIV epidemic was applied to each of the nine provinces, allowing for provincial differences in demography, sexual behaviour, male circumcision, interventions and epidemic timing. The model was calibrated to HIV prevalence data from antenatal and household surveys using a Bayesian approach. Parameters estimated for each province were substituted into the national model to assess sensitivity to provincial variations.

Results: HIV incidence in 15–49-year-olds peaked between 1997 and 2003 and has since declined steadily. By mid-2013, HIV prevalence in 15–49-year-olds varied between 9.4% (95% CI: 8.5%–10.2%) in Western Cape and 26.8% (95% CI: 25.8%–27.6%) in KwaZulu-Natal. When standardising parameters across provinces, this prevalence was sensitive to provincial differences in the prevalence of male circumcision (range 12.3%–21.4%) and the level of non-marital sexual activity (range 9.5%–24.1%), but not to provincial differences in condom use (range 17.7%–21.2%), sexual mixing (range 15.9%–19.2%), marriage (range 18.2%–19.4%) or assumed HIV prevalence in 1985 (range 17.0%–19.1%).

Conclusion: The provinces of South Africa differ in the timing and magnitude of their HIV epidemics. Most of the heterogeneity in HIV prevalence between South Africa’s provinces is attributable to differences in the prevalence of male circumcision and the frequency of non-marital sexual activity.


Keywords

HIV/AIDS; male circumcision; sexual behaviour; South Africa

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