22 Dec Targeting HIV Hot Zones May Lead To Better Prevention Strategies
Medical Research: What is the background for this study? What are the main findings?
Response: In an attempt to control the spread of HIV, governments in sub-Saharan Africa are considering providing antiretroviral drugs to people who do not have the virus but are at risk for becoming infected. Such drugs are known as pre-exposure prophylaxis, or PrEP. Given the cost of PrEP, an important question is how to maximize the impact of interventions given a fixed level of prevention resources.
A common strategy is to target resources to the individuals that are at the highest risk for infection. This group of people is often referred to as the “core group” and can be thought of as sex workers, clients of sex workers and other individuals that are at very high risk for infection. While targeting this core group is ideal and would result in the most cost-effectiveness interventions, being able to identify these individuals is difficult in practice and they are often unwilling to participate in the intervention; take pre-exposure prophylaxis or change their behavior for example. From a mathematical perspective it is also very difficult to quantify their increased level of risk. For example, is a sex worker at 5 times, 25 times, 100 times or 1000 times the risk for HIV infection? Without this quantification, it is impossible to estimate the cost-effectiveness of a targeted strategy.
In our work, we build an intervention strategy based on geographical targeting. This takes advantage of the fact that HIV incidence is much higher in certain geographical locations than others. Therefore, individuals in these areas are at increased risk for HIV infection. Most importantly, such an intervention is feasible because reliable data exists across much of sub-Saharan Africa for the severity of the HIV epidemic in different regions. To illustrate our ideas we used mathematical modeling to consider resource allocation in South Africa and found that targeting the provinces with highest HIV incidence would prevent 40% more infections than a plan that ignored geographic variation while using the same amount of resources.
Medical Research: What should clinicians and patients take away from your report?
Response: In general, I think the take-home message is that in order to get the most prevention bang for the buck out of any intervention, it is necessary to target resources to people at the highest risk. Unfortunately, this is much easier said than done. In our study, we simply note that geographic variation causes individuals in certain areas to be at higher risk. This provides “low-hanging fruit” in terms of targeting an intervention. This targeting of the “hot-zones” could be the first step that may include multiple levels of targeting. For example, if we isolate a region as particularly high-risk, efforts to identify high-risk individuals in that region could then follow.
Medical Research: What recommendations do you have for future research as a result of this study?
Response: I see two particular avenues for future research:
First, as our study used the South African HIV epidemic to illustrate geographic targeting, it would be natural to consider other sub-Saharan countries that have geographic variation in the severity of their HIV epidemic, such as Lesotho, Botswana, Nigeria and Uganda to see how robust our results are.
Secondly, as many forms of PrEP are becoming available, each of which provide different levels of protection and have different costs, much work is needed to figure out which combinations of interventions will be most cost-effective at preventing HIV infections.
Using geospatial modelling to optimize the rollout of antiretroviral-based pre-exposure HIV interventions in Sub-Saharan Africa
David J. Gerberry, Bradley G. Wagner, J. Gerardo Garcia-Lerma,
Walid Heneine & Sally Blower
Nature Communications 5,Article number: 5454 doi:10.1038/ncomms6454