Modelling Impact of Prevention Strategies on Cervical Cancer Incidence in SA
Project ended 30 June 2020
Prof Alex Welte
- The DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch
Title of the project
Modelling the impact of prevention strategies on cervical cancer incidence in South Africa.
In recent years, mathematical models are increasingly applied to cervical cancer research. Globally, but particularly important for the South African context, existing models share the limitation that the well-established interaction between HIV and HPV is not dynamically simulated, and therefore the need exists for a sophisticated model that fully incorporates the effect of HIV on HPV incidence and cervical disease progression. This study proposes to 1) extend an individual-based HIV/STI model to include HPV and its progression to cervical cancer, calibrate the model to South African HPV and HIV prevalence data and validate the model with cervical cancer incidence data and 2) evaluate the potential impact of various prevention methods on cervical cancer incidence.
Value of the project in the struggle against cancer
This project was the first to dynamically model infection with both HIV and HPV, explore transmission dynamics (susceptibility/infectiousness) of the one infection in presence of the other, and investigate aspects of viral latency and reactivation of latent HPV, which is crucial in a context with high HIV prevalence. With this model, we can estimate the impact that HIV prevention measures, as well as cervical cancer prevention measures, will have on cervical cancer incidence in the long term.
Future plans for this research project
Future plans include involving health-economists and policymakers to calculate feasibility and cost-effectiveness of specific prevention strategies
- Estimated impact of human papillomavirus vaccines on infection burden: the effect of structural assumptions (2019)
- Are associations between HIV and human papillomavirus transmission due to behavioural confounding or biological effects? (2018)