A report by Chris Pilcher, MD, associate professor in residence, UCSF School of Medicine at San Francisco General Hospital and Trauma Center:

With calls for more implementation research and public investment in HIV prevention, how can we measure whether prevention programs in the real world are working?

For years, prevention and surveillance programs have sought a simple blood test to use in population surveys that would determine how many in the population had been recently infected with HIV. Past incidence tests (like the “BED” test) have failed to deliver because they have over-counted, misclassifying some long term HIV infected people as “recent.”

Two sessions at this [international AIDS] conference gave prevention scientists and surveillance programs who need this tool a shot in the arm:  on Monday, Oliver Laeyendecker from [the National Institutes of Health] presented exciting data that by combining the BED-CEIA test with a second test (Bio-rad Avidity), a CD4 cell count and a viral load, the resulting “multi-assay algorithm” reduced the BED misclassification rate from 12 percent to zero.

This result was discussed Tuesday in a forum on HIV Incidence, where Dr. Thomas Rehle announced that South Africa’s national survey in 2012 will use a multi-assay algorithm, despite its complexity.

Dr. Gary Murphy from the UK then announced an international effort, funded by the Gates Foundation, that will independently evaluate the full range of existing incidence tests against a large specimen repository, and find a simpler, single- or multi-test approach that could be used more easily in developing world settings. They promised a report back within the year.

For the first time in years, there was renewed enthusiasm that we may now be able to measure HIV incidence, with even better tools on the way.