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Current data science capacity building initiatives for health researchers in LMICs: global & regional efforts

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Kiosia, Agklinta, Boylan, Sally, Retford, Matthew, Marques, Larissa Pruner, Bueno, Flávia Thedim Costa, Kirima, Christine, Islam, Md Saimul, Naheed, Aliya +1 more·2024·Frontiers in Public Health
DOI 10.3389/fpubh.2024.1418382PMC PMC11631614
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Abstract

Background: Data science approaches have proved crucial for generating major insights to address public health challenges. While such approaches have played significant roles during the COVID-19 pandemic, there has been limited investment in capacity building in data science skills and infrastructure for health researchers in LMICs. Objectives: This review aims to identify current health data science capacity building initiatives and gaps in Africa, Asia, and Latin America and the Caribbean (LAC), to support knowledge sharing and collaborations, and inform future initiatives and associated investment. Methods: We conducted a literature review using PubMed and Scopus, supplemented by a grey literature search on Google to identify relevant initiatives. Articles were screened based on inclusion criteria. Findings: From 212 records, 85 met inclusion criteria, with 20 from PubMed and Scopus, and 65 from grey literature. The majority of programmes are tailored to specific disease areas, varying by region. Despite these efforts, there are limited initiatives with a clear, documented strategy on data science capacity building to accelerate global research insights, with the majority adopting a fragmented approach. Conclusion and future directions: Despite the integration of data science approaches into health research initiatives in LMICs, there is a need for a standardised framework on data science capacity building to facilitate multidisciplinary and global collaboration. Structured approaches, inter-disciplinary, inter-regional connections and robust impact measurement will all be vital for advancing health research insights in these settings.

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  • Digital health sustainability literature emphasizes financing barriers, fragmented markets, and the need for strategic partnerships.

    “Digital health sustainability literature emphasizes financing barriers, fragmented markets, and the need for strategic partnerships [1,5,20,21].”

    From A Workflow for Grant Discovery and Proposal Development Using Large Language Models: Development and Formative Evaluation (2026) · cites this paper as [21]

    The Discussion (page not provided) says that sustaining health data science capacity-building initiatives in LMICs depends on continuous funding and describes partnerships with government, academia, and the private sector. It does not discuss fragmented markets, and its focus is narrower than digital health sustainability literature generally. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Recording these structural blockers helps the business-development and evidence teams coordinate and avoids repeated discovery of the same structurally closed opportunities.

    “Recording these structural blockers helps the business-development and evidence teams coordinate and avoids repeated discovery of the same structurally closed opportunities [4,21].”

    From A Workflow for Grant Discovery and Proposal Development Using Large Language Models: Development and Formative Evaluation (2026) · cites this paper as [21]

    The Discussion (page not provided) recommends coordination among health data science initiatives to avoid duplicating funders’ investments. The Findings also describe identifying obstacles to tools and training, but neither passage addresses recording structurally closed opportunities, coordination between business-development and evidence teams, or repeated discovery of those opportunities. Searches for those terms and for recording barriers to avoid duplication found no supporting passage. (LLM, conf=0.76)

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Authors
Kiosia, A., Boylan, S., Retford, M., Marques, L. P., Bueno, F. T. C., Kirima, C., Islam, M. S., Naheed, A., & Wozencraft, A.
Affiliations
  • Health Data Research UK (GB)
  • Fundação Oswaldo Cruz (BR)
  • University of Oxford (GB)
  • International Centre for Diarrhoeal Disease Research (BD)
Corresponding author
  • Kiosia, Agklinta
  • Wozencraft, Anne
ORCID
Venue
Frontiers in Public Health
Publisher
Frontiers Media SA
Published
2024-11-27
Volume
12
Pages
1418382-1418382
ISSN
2296-2565 (ISSN-L)
DOI
10.3389/fpubh.2024.1418382
PMC
PMC11631614
OpenAlex
W4404780458
Cited by
25
References
1
Citations by year
2026: 17 · 2025: 8
FWCI
1.49
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Public Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • Arca - Repositório Institucional da Fiocruz (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Bill and Melinda Gates Foundation (INV-033335)
  • International Centre for Diarrhoeal Disease Research, Bangladesh
Topics
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Global Health and Surgery
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
Keywords
health research capacity, low- and middle-income countries, health data science, research infrastructure, Africa, Asia, Latin America and the Caribbean
MeSH terms
Data Science, COVID-19, Africa, Developing Countries, Humans, Latin America, Research Personnel, Capacity Building

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