Applying these data and tools at-scale can yield instantaneous population-level insights to assess behavioral trends that can inform the design and evaluation of HIV prevention programs and interventions. In turn, these publicly available data can be examined using data science principles to detect “digital biomarkers” such as signals of psychological distress or substance use that are known risk factors related to HIV risk. For instance, social media platforms such as Facebook, Instagram, Reddit, and Twitter enable people to share with the public what they are thinking in real time, often before engaging in specific behaviors. However, the potential of these data resources and tools in HIV prevention and treatment has yet to realized. Analyses of digital footprints can accurately reflect population-level health and provide more timely data than traditional data collection methods. One approach that holds great promise to propel HIV surveillance and prevention forward is to leverage the power of digital data and data science (including internet searches, social media, online media) and data science. Moreover, surveys and in-depth interviews are subject to bias, including non-response, missing data and socially desirable responses, which is problematic given that HIV prevalence is higher among those engaging in highly stigmatized sexual and drug use behaviors.
As a consequence, HIV/AIDS surveillance data is prone to bias and potentially hampers the deployment of timely interventions. Even in the US, where we have achieved near complete data on new HIV diagnoses, these “new” diagnoses often reflect infections that occurred months or years prior to diagnosis. Databases of AIDS diagnoses suffer from under-, mis-, and delayed-reporting, partially due to the lengthy 10–15 year incubation period for HIV to progress to AIDS. Yet almost all existing HIV-related surveillance systems rely on time- and resource-intensive retrospective data that by definition are backward-looking. But can we apply this approach to HIV prevention and treatment to end the epidemic? Herein, we outline how the digital data and data science revolution could impact HIV prevention and treatment efforts.Įffective public health interventions depend on timely, accurate surveillance. This quote is commonly referenced by successful industries pointing towards their model to stay one-step-ahead of the market. Wayne Gretzky allegedly said that he skates to where the puck is going to be, not where it has been.