There are millions of scenarios that HIV researchers would love to test out — what would happen if the typical infected New Yorker found out their HIV status a week sooner? Or what if the average Parisian infected with the virus waited a month longer to begin treatment? What would happen if a thousand people in Johannesburg were all of a sudden stricken with a drug-resistant strain? In each case, we would want to know how each individual patient would fare, how best to intervene and treat them, and how the size of the epidemic would change as a result of different interventions.
But it’s neither possible (nor ethical!) to test every scenario that an enterprising epidemiologist dreams up. That’s where computer models come in — using them, we can simulate cases almost as fast as we dream them up. Positively Aware‘s Rick Guasco writes about how these models may change the face of HIV treatment. And he featured some work that we did at Harvard & JHU on finding regimens to fight drug resistance. Right after I spoke with Rick about our project, I was worried that I had inundated him with a great too many details about mutation rates, dose-response curves, and goodness knows what else came to mind, but he distilled everything beautifully — of course, that is why he is a journalist and I am not! (Note to self: develop clearer style for chatting with journalists…)
See the rest of the issue for a tour of other ways that new technology is changing life with HIV.