Impact studies: mathematical models

A number of studies have attempted to quantify the possible impact of PrEP under a number of different efficacy, usage and behavioural scenarios. A 2007 study presented in PLoS One journal found that PrEP could prevent up to three million new HIV infections over ten years in southern Africa if used consistently, according to mathematical modelling.¹

Epidemiologists set out to model the effects of PrEP under different scenarios in Africa, varying the efficacy of PrEP and the effects of sexual disinhibition within the population after its introduction in order to illustrate the range of effects that might be expected.

The model looked at the effect of introducing PrEP in epidemics where adult HIV prevalence has reached 20%.

There were three scenarios within the model:

• An optimistic scenario in which PrEP was assumed to be effective 90% of the time and used by 75% of the sexually active population. In this case, there was a significant public health benefit with a reduction of new HIV infections by 74%.
• A neutral scenario in which PrEP was effective 60% of the time and used by 50% of the sexually active population. This gave a 25% reduction in infections.
• A pessimistic scenario in which PrEP was effective 30% of the time and used by 25% of the sexually active population.  A 3.3% reduction was found.

The researchers also looked at the cost-benefit of distributing PrEP and found that targeting it to individuals who were the most sexually active produced a significant decline in infections at a much lower cost than if PrEP were distributed to the general population.

To address the issue of sexual disinhibition, the researchers assumed a 100% increase in risky sexual behaviour and observed that there was still a notable reduction of HIV infections in the range of 23.4% to 62.7%.

At the 2010 Microbicides conference, a couple of presentations modelled the impact of either a microbicide or PrEP, and Marie-Claude Boily of Imperial College introduced a meta-review of a number of the mathematical models of these approaches.²

These models show that the effect on HIV incidence and prevalence of microbicides and PrEP could vary enormously, according to local conditions. In some cases their adoption could cause an increase in HIV infections. Boily said that models predict some paradoxical effects.

PrEP might have much more effect in a low-prevalence area than a high-prevalence one, and it might reduce HIV infections in people who don’t often use condoms, while considerably increasing infections in people who were using them consistently before the introduction of PrEP.

If PrEP or microbicide adoption were to result in anything more than a slight drop in condom use, the result could be an increase in HIV cases; and even a small amount of anal sex in a heterosexual population may slash the effectiveness of a vaginal microbicide.

Boily presented several different scenarios that modelled condom substitution, all assuming the introduction of a prevention method of 50% efficacy, used 50% of the time.

Situations of initially high condom use were much more sensitive to condom substitution: if condom use was initially 90%, it would only take a 2% drop in use for infections to start rising, despite the introduction of a microbicide. Audience members commented that this validated the fears of groups representing female sex workers, who have managed to enforce this level of condom use in clients. If microbicide use led men to demand more sex without condoms, then both worker and client would be more at risk.