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

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

Journal

Current HIV/AIDS reports
ISSN: 1548-3576
Titre abrégé: Curr HIV/AIDS Rep
Pays: United States
ID NLM: 101235661

Informations de publication

Date de publication:
25 Jun 2024
Historique:
accepted: 31 05 2024
medline: 25 6 2024
pubmed: 25 6 2024
entrez: 25 6 2024
Statut: aheadofprint

Résumé

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. 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. 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.

Identifiants

pubmed: 38916675
doi: 10.1007/s11904-024-00702-3
pii: 10.1007/s11904-024-00702-3
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIH HHS
ID : K01MH129226
Pays : United States
Organisme : NIH HHS
ID : R01AI170249
Pays : United States
Organisme : NIH HHS
ID : R01AI170249
Pays : United States
Organisme : NIH HHS
ID : R01AI170249
Pays : United States
Organisme : South African Medical Research Council
ID : 57035
Organisme : CIHR
ID : FN-13455
Pays : Canada
Organisme : Canada Research Chairs
ID : 950-232643

Informations de copyright

© 2024. The Author(s).

Auteurs

Katherine Rucinski (K)

Department of International Health, Johns Hopkins School of Public Health, Baltimore, MD, USA. rucinski@jhu.edu.

Jesse Knight (J)

MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada.
Institute of Medical Science, University of Toronto, Toronto, ON, Canada.

Kalai Willis (K)

Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.

Linwei Wang (L)

MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada.

Amrita Rao (A)

Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.

Mary Anne Roach (MA)

Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.

Refilwe Phaswana-Mafuya (R)

South African Medical Research Council/University of Johannesburg Pan African Centre for Epidemics Research (PACER) Extramural Unit, Johannesburg, South Africa.
Department of Environmental Health, Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.

Le Bao (L)

Department of Statistics, Pennsylvania State University, University Park, PA, USA.

Safiatou Thiam (S)

Conseil National de Lutte Contre Le Sida, Dakar, Senegal.

Peter Arimi (P)

Partners for Health and Development in Africa, Nairobi, Kenya.

Sharmistha Mishra (S)

MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada.
Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada.
Institute of Health Policy, Management and Evaluation & Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
ICES, Toronto, ON, Canada.

Stefan Baral (S)

Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.

Classifications MeSH