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AVAC Report 2016Big Data Real People
• Download AVAC Report 2016
• Read the Executive Summary
• Hope, Hype and Revolutions: Letter from the Executive Director
• Download all graphics from the Report
This year’s AVAC Report takes on one of the most urgent issues facing biomedical HIV prevention today: gaps in the type and quality of data collected on prevention for HIV-negative people. Globally, the number of new HIV infections is not declining. In the places where gains have been made, continued progress is not guaranteed. Fixing core problems with how prevention data are collected and reported is key to slowing the rate of new cases of HIV.
In 2016, there is no justification for prevention data to be as patchy and mysterious as they are. Let's link rhetoric and reporting through the piloting and widespread adoption of HIV Prevention Data Dashboards—a visual display of the critical information needed to achieve objectives; consolidated and arranged so that the information can be easily monitored. To see what a Prevention Data Dashboard could look like, click below.
Prevention Data Dashboards: A key tool for impact on the epidemic
Data points in HIV prevention correspond to real people with specific needs that change over time. AVAC Report 2016 argues that today's prevention data don't reflect these real people in nearly enough detail. Much of the data on services offered to people who test HIV-negative is inadequate. Countries, funders and implementers report on "people reached" with referrals and condoms, yet data on who is being reached—particularly among key populations—are inadequate. And in the era of strategies such as VMMC (voluntary medical male circumcision) and PrEP (pre-exposure prophylaxis) that have direct impact on HIV risk, reports on referral rates are unacceptable. The new prevention data paradigm should provide detailed information on who is being reached and track linkages to evidence-based tools.
Changing the approach to HIV prevention data means assessing and adapting relevant "Big Data" approaches that analyze enormous data sets to identify new correlations. It also means adapting systems that have existed for decades to reflect new prevention tools and goals.
