Assumptions about a video game – the video game of the HIV epidemic

As a gay man studying public health at University of Cape Town, I am privileged to work on a project relating to and in support of the health of gay, bisexual and other men who have sex with men.

 

During my research thought process and conversations I have had with people, I realized I can situate my epidemiological -mathematical – project within the larger LGBT movement. I wish to draw upon my understandings of qualitative research and social science where inter-disciplinary research is valued, because social scientist subscribe to the notion that knowledge is merely a fabric of different threads, which the scientists themselves weave and my mathematical is but one of those threads. The present blog then is just an opportunity to apply the concepts of participatory research to my project.

 

It may then occur to you to ask me whether you dear reader are then a research subject who will participate in my project. Nothing could be further from the truth. My project is one where there are no actual human subjects. Instead, it is a game, quite similar to a video game, except it is a grim one of an epidemic that proceeds due to the laws of probability – or chance – rather than players who control the movements of virtual characters. The characters in my game are men and women of South Africa in an idealized population. Here people come together, they may form partnerships that are long lasting, or ones that are fleeting, regardless we model that they have sex. And it through this sex that HIV spreads. The likelihood any two people from a sexual partnerships is predefined and then the rules of chance operate in a population to from these relationships at random.

 

In my project, men will now be able to have sex with other men, in addition to women. Until now, this model only assumed there were heterosexuals in the population. As we all know this is not an accurate description of any population, much less of South Africa where the higher prevalence rate of HIV in men who have sex with men compared to men who do not report (or deny) such practises implies man-to-man sex is one way the virus is being spread.

 

One of the questions we are posing is what the impact of PrEP – pre-exposure prophylaxis – for HIV would have on new infections. This is where you may participate. What type of MSM do you believe should be using PrEP? When we start the model simulation, we make assumptions regarding who has access to PrEP. Would it make sense to assume only men who have a low chance of being in long-term monogamous relationships use PrEP in the simulation? All good video games need to be grounded in some degree of reality and in the case of our model, reseanoble assumptions are needed for the model outputs to have any bearing on health policy.

 

Thank you for reading.

P.S. My model is called an agent-based model. It is very cool, the “Conway’s Game of Life” provides a good example of what it actually can do.

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About writinghealth

Wannabe Epidemiologist? Wannabe med anthro person? I guess. Christian, scientist (not Christian scientist), i mean like I studied molecular biology. I am doing a Masters of Public Health, at the University of Cape Town.
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