Investigator
University Of North Carolina At Chapel Hill
The impact of HIV on cervical cancer elimination in KwaZulu-Natal: a comparative modeling analysis
Abstract Background Achieving cervical cancer (CC) elimination requires addressing disparities in CC burden for women living with HIV (WLHIV) and how disparities evolve in the context of antiretroviral therapy (ART) scale-up. To inform CC elimination for high HIV prevalence regions, we modeled the impact of HIV, HIV interventions, and CC interventions in KwaZulu-Natal, South Africa. Methods We used 2 independently developed, dynamic compartmental transmission models of HIV and human papillomavirus (DRIVE and Policy1-Cervix-HIV) calibrated to KwaZulu-Natal. We simulated: a counterfactual without HIV but with observed CC screening and vaccination; and scenarios sequentially adding condom use and voluntary medical male circumcision (VMMC); HIV; observed HIV and CC interventions (status quo); achieving United Nations Programme on HIV/AIDS HIV treatment targets; and achieving World Health Organization (WHO) CC elimination targets. The impact of each scenario was measured as the difference in CC incidence from the previous scenario. Results were reported from 2024 to 2124 as a range between the 2 models; CC elimination was WHO-defined as incidence <4/100 000 women-years. Results For the status quo, CC incidence ranged from 61.30 to 78.96/100 000 women-years in 2024, with the highest incidence among WLHIV (126.8-192.0/100 000). HIV contributed an estimated 29.08-48.87 additional cases per 100 000. Neither model predicted elimination under status quo interventions, but achieving HIV treatment and CC elimination targets could reduce incidence to 1.42-6.25/100 000 women-years in 2124. Conclusions HIV is associated with a population-level increase in CC incidence. However, scaling up ART coverage and CC interventions is expected to significantly reduce the burden of CC overall and among WLHIV. These conclusions are consistent between both models and strengthened by the comparative modeling approach.
Enhanced cervical cancer and HIV interventions reduce the disproportionate burden of cervical cancer cases among women living with HIV: A modeling analysis
Introduction Women living with HIV experience heightened risk of cervical cancer, and over 50% of cases in Southern Africa are attributed to HIV co-infection. Cervical cancer interventions tailored by HIV status delivered with HIV antiretroviral therapy (ART) for treatment can decrease cancer incidence, but impact on HIV-related disparities remains understudied. Methods Using a dynamic model calibrated to KwaZulu-Natal, South Africa, we projected HIV prevalence, cervical cancer incidence, and proportion of cancer cases among women living with HIV between 2021–2071. Relative to the status quo of moderate intervention coverage, we modeled three additive scenarios: 1) ART scale-up only; 2) expanded human papillomavirus (HPV) vaccination, screening, and treatment; and 3) catch-up HPV vaccination and enhanced screening for women living with HIV. Results Under the status quo, HIV prevalence among women aged 15+ decreased from a median of 35% [Uncertainty Range (UR): 26–42%] in 2021 to 25% [19–34%] in 2071. The proportion of cervical cancer cases that were women living with HIV declined from 73% [63–86%] to 58% [47–74%], but incidence remained 4.3-fold [3.3–5.7] that of women without HIV. ART scale-up reduced HIV prevalence in 2071, but increased the incidence rate ratio to 5.2 [3.7–7.3]. Disparities remained after expanding cancer interventions for all women (incidence rate ratio: 4.8 [3.6–7.6]), while additional catch-up HPV vaccination and screening for women living with HIV decreased the incidence rate ratio to 2.7 [1.9–3.4] in 2071. Conclusions Tailored cervical cancer interventions for women living with HIV can counteract rising cancer incidence incurred by extended life expectancy on ART and reduce disparate cancer burden.
PhD Student
University of North Carolina at Chapel Hill · Epidemiology
Bachelor of Science
University of Virginia · Biomedical Engineering
Master of Science