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

Autor: Rucinski K; Department of International Health, Johns Hopkins School of Public Health, Baltimore, MD, USA. rucinski@jhu.edu., Knight J; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada.; Institute of Medical Science, University of Toronto, Toronto, ON, Canada., Willis K; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA., Wang L; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada., Rao A; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA., Roach MA; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA., 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., Bao L; Department of Statistics, Pennsylvania State University, University Park, PA, USA., Thiam S; Conseil National de Lutte Contre Le Sida, Dakar, Senegal., Arimi P; Partners for Health and Development in Africa, Nairobi, Kenya., 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., Baral S; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
Jazyk: angličtina
Zdroj: Current HIV/AIDS reports [Curr HIV/AIDS Rep] 2024 Aug; Vol. 21 (4), pp. 208-219. Date of Electronic Publication: 2024 Jun 25.
DOI: 10.1007/s11904-024-00702-3
Abstrakt: 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. 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.
(© 2024. The Author(s).)
Databáze: MEDLINE
Externí odkaz: