There have been numerous papers and books on South Africa’s catastrophic era of AIDS denialism. There is much less known and written about the “when-to-start antiretrovirals (ARVs)” debate. This debate offers a fascinating look at how scientific disagreements between reasonable people, who are experts in the field, work, and how consensus evolves as evidence accumulates.
Individual-based models of sexually transmitted infection epidemics allow us to account for heterogeneity of sexual behaviour in a way that is impractical with traditional differential-equation-based models. But do we increase our knowledge by using more complex models? When we use sexual behaviour data in our models are we generating outputs, such as estimates of prevalence and mortality, that reflect the real-world populations we are studying? In this article we present examples that help us explore this question.
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.