Objectives Cohort studies have shown significant increased risk of HIV acquisition following human papillomavirus (HPV) detection and increased risk of new HPV detection in individuals with HIV infection, after adjusting for behavioural risk factors. This study uses an individual-based model to assess whether confounding sexual behaviour factors and network level effects can explain these associations between HIV and HPV infection status, without biological interactions.

Methods The model simulates infection with 13 oncogenic HPV types and HIV. It allows for different relationship types, with heterogeneity in probabilities of concurrency and rates of partner change. No effect of prevalent HPV infection on HIV acquisition is assumed and vice versa. The model is calibrated to South African HIV and type-specific HPV prevalence data using a Bayesian approach. The model is used to simulate cohorts with quarterly HIV and HPV testing from 2000 to 2002. These simulated data are analysed using proportional hazard models.

Results The mean of the unadjusted HRs of HIV acquisition following detection of an oncogenic HPV type calculated for each simulated cohort is 2.6 (95% CI 2.2 to 3.1). The mean of the unadjusted HRs for the effect of HIV on newly detected HPV is 2.5 (95% CI 2.2 to 2.8). Simulated associations between HIV and HPV infection status are similar to corresponding empirical estimates. In sensitivity analyses in which HIV and HPV were assumed to increase each other’s transmission risk, simulated associations were stronger but not inconsistent with empirical estimates.

Conclusions Although we cannot rule out the possibility that associations between HIV and HPV transmission may be due in part to biological interactions, these results suggest that observed associations could be explained entirely by residual confounding by behavioural factors and network-level effects that observational studies cannot account for.