Published on September 27, 2018 by

Advancing control of sexually transmitted infections during the era of the Sustainable Development Goals

The far-reaching, highly ambitious Sustainable Development Goals (SDGs) build upon the momentum generated by the Millennium Development Goals (MDGs) and are intended as a guide for health, social and economic initiatives until 2030. Implemented correctly, the STI agenda may well fit better within the SDGs than the MDGs, although that does not become directly clear at first glance. For refocusing attention on the control of STIs in the forthcoming years we propose a framework, most especially within low- and middle-income countries (LMICs).

Short item Published on September 27, 2018

Are associations between HIV and HPV transmission due to behavioural confounding or biological effects?

HIV and human papillomavirus (HPV) are two heavy hitting sexually transmitted infections (STIs). Meta-analyses of the association between HPV prevalence and HIV acquisition and the association between HIV prevalence and new HPV detection have estimated a two-fold increased risk in both directions, after adjusting for individual-level (sexual behavioural) factors. The studies argue that biological mechanisms may be responsible for these increased risks, but they also concur that residual confounding due to behaviour at the sexual network level cannot be ruled out. We used an individual based model to shed some light on the matter.

Published on June 18, 2015 by

Speeding up agent-based modelling of sexually transmitted diseases

Agent-based modelling, also called microsimulation, is a way of modelling epidemics that is growing in popularity. Instead of the traditional way of modelling using differential equations, an agent-based model consists of, perhaps, thousands of agents, each representing a person, and each behaving according to a simple set of rules. Instead of outputs such as infection and mortality rates being derived from equations, they are derived from the interactions of the agents over many iterations. These models are providing rich insights into the HIV epidemic.