Challenges and Opportunities in Big Data Science to Address Health Inequities and Focus the HIV Response

Katherine Rucinski, Jesse Knight, Kalai Willis, Linwei Wang, Amrita Rao, Mary Anne Roach, Refilwe Phaswana-Mafuya, Le Bao, Safiatou Thiam, Peter Arimi, Sharmistha Mishra, Stefan Baral

Research output: Contribution to journalReview articlepeer-review

Abstract

Purpose of Review: Big Data Science can be used to pragmatically guide the allocation of resources within the context of national HIV programs and inform priorities for intervention. In this review, we discuss the importance of grounding Big Data Science in the principles of equity and social justice to optimize the efficiency and effectiveness of the global HIV response. Recent Findings: Social, ethical, and legal considerations of Big Data Science have been identified in the context of HIV research. However, efforts to mitigate these challenges have been limited. Consequences include disciplinary silos within the field of HIV, a lack of meaningful engagement and ownership with and by communities, and potential misinterpretation or misappropriation of analyses that could further exacerbate health inequities. Summary: Big Data Science can support the HIV response by helping to identify gaps in previously undiscovered or understudied pathways to HIV acquisition and onward transmission, including the consequences for health outcomes and associated comorbidities. However, in the absence of a guiding framework for equity, alongside meaningful collaboration with communities through balanced partnerships, a reliance on big data could continue to reinforce inequities within and across marginalized populations.

Original languageEnglish (US)
Pages (from-to)208-219
Number of pages12
JournalCurrent HIV/AIDS reports
Volume21
Issue number4
DOIs
StatePublished - Aug 2024

Keywords

  • Big Data Science
  • Community HIV response
  • Explanatory modeling
  • HIV transmission dynamics
  • Health equity
  • Key populations
  • Predictive modeling

ASJC Scopus subject areas

  • Virology
  • Infectious Diseases

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