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Challenges and Opportunities in Big Data Science to Address Health Inequities and Focus the HIV Response.
Rucinski, Katherine; Knight, Jesse; Willis, Kalai; Wang, Linwei; Rao, Amrita; Roach, Mary Anne; Phaswana-Mafuya, Refilwe; Bao, Le; Thiam, Safiatou; Arimi, Peter; Mishra, Sharmistha; Baral, Stefan.
Afiliação
  • 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.
  • Willis K; Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
  • Wang L; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
  • Rao A; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada.
  • Roach MA; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
  • Phaswana-Mafuya R; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
  • Bao L; South African Medical Research Council/University of Johannesburg Pan African Centre for Epidemics Research (PACER) Extramural Unit, Johannesburg, South Africa.
  • Thiam S; Department of Environmental Health, Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.
  • Arimi P; Department of Statistics, Pennsylvania State University, University Park, PA, USA.
  • Mishra S; Conseil National de Lutte Contre Le Sida, Dakar, Senegal.
  • Baral S; Partners for Health and Development in Africa, Nairobi, Kenya.
Curr HIV/AIDS Rep ; 2024 Jun 25.
Article em En | MEDLINE | ID: mdl-38916675
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. 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: AIDS Rep Assunto da revista: SINDROME DA IMUNODEFICIENCIA ADQUIRIDA (AIDS) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: AIDS Rep Assunto da revista: SINDROME DA IMUNODEFICIENCIA ADQUIRIDA (AIDS) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos