Halting HIV/AIDS with avatars and havatars

Halting HIV/AIDS with avatars and havatars: a virtual world approach to modelling epidemics.

Gordon R, Björklund NK, Smith RJ, Blyden ER. BMC Public Health. 2009;9 Suppl 1:S13.

A major deficit of all approaches to epidemic modelling to date has been the need to approximate or guess at human behaviour in disease-transmission-related contexts. Avatars are generally human-like figures in virtual computer worlds controlled by human individuals. The authors introduce the concept of a "havatar", which is a (human, avatar) pairing. Evidence is mounting that this pairing behaves in virtual contexts much like the human in the pairing might behave in analogous real-world contexts. Gordon et al. propose that studies of havatars, in a virtual world, may give a realistic approximation of human behaviour in real-world contexts. If the virtual world approximates the real world in relevant details (geography, transportation, etc.), virtual epidemics in that world could accurately simulate real-world epidemics. Havatar modelling of epidemics therefore offers a complementary tool for tackling how best to halt epidemics, including perhaps HIV, since sexual behaviour is a significant component of some virtual worlds, such as Second Life. Havatars place the control parameters of an epidemic in the hands of each individual. By providing tools that everyone can understand and use, we could democratise epidemiology.

Reviewing current modelling approaches (continuous or deterministic, discrete or individual, and stochastic process modelling), these authors point out that all epidemic modelling second-guesses human behaviour. Their proposition that epidemiological modellers monitor the social networks of havatars (“h” stands for human) to obtain a better representation of real-world disease transmission raises several questions. Although the 13 million people who joined the virtual world Second Life signed waivers that would allow tracking of all transactions, there may be ethical issues to consider when modellers intervene in people’s virtual worlds with HIV epidemic simulations to study the behaviour of the avatars under a person’s control and make extrapolations to human behaviour. Unleashing invisible, simulated viruses that infect havatars and can be transmitted could cause problems, even if the viruses themselves have no effects such as simulated weight loss or changes in colour. The possibility of virtual world stigma might become real. As well, the people currently part of this virtual world are unlikely to represent populations at higher risk of HIV exposure around the world so the validity of the extrapolations to the HIV epidemic we face today could well be in question.