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This article is part of the supplement: The OptAIDS project: towards global halting of HIV/AIDS

Open Access Research

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

Richard Gordon1*, Natalie K Björklund2, Robert J Smith?3 and Eluemuno R Blyden4

Author Affiliations

1 Department of Radiology, University of Manitoba, GA216, HSC, 820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada

2 Silver Bog Research Inc., 350 Inkster Blvd., Winnipeg MB R2W 0K3, Canada

3 Department of Mathematics & Faculty of Medicine, The University of Ottawa, 585 King Edward Drive, Ottawa, ON K1N 6N5, Canada

4 AfriVax, Inc., 613 19th Ave. E. Suite 101, Seattle WA 98112, USA

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BMC Public Health 2009, 9(Suppl 1):S13  doi:10.1186/1471-2458-9-S1-S13

Published: 18 November 2009

Abstract

Background

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.

Methods

We 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.

Results

We 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/AIDS, since sexual behaviour is a significant component of some virtual worlds, such as Second Life.

Conclusion

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.