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REVIEW article

Front. Public Health
Sec. Public Health Education and Promotion
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1418382

Current Data Science Capacity Building Initiatives for Health Researchers in LMICs: Global & Regional Efforts

Provisionally accepted
Agklinta Kiosia Agklinta Kiosia 1,2*Sally Boylan Sally Boylan 1Matthew Retford Matthew Retford 1Larissa Pruner Marques Larissa Pruner Marques 3Flávia Thedim Costa Bueno Flávia Thedim Costa Bueno 4Christine Kirima Christine Kirima 5Md. Islam Md. Islam 6Aliya Naheed Aliya Naheed 6Anne Wozencraft Anne Wozencraft 1*
  • 1 Health Data Research UK, London, United Kingdom
  • 2 Imperial College London, London, England, United Kingdom
  • 3 Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Rio de Janeiro, Brazil
  • 4 Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Paraná, Brazil
  • 5 Other, Oxford, United Kingdom
  • 6 International Centre for Diarrhoeal Disease Research (ICDDR), Dhaka, Dhaka, Bangladesh

The final, formatted version of the article will be published soon.

    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.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.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, interdisciplinary, inter-regional connections and robust impact measurement will all be vital for advancing health research insights in these settings.

    Keywords: data science, Capacity Building, Global health research, Low-and middle-income countries, health researchers

    Received: 16 Apr 2024; Accepted: 01 Oct 2024.

    Copyright: © 2024 Kiosia, Boylan, Retford, Marques, Bueno, Kirima, Islam, Naheed and Wozencraft. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Agklinta Kiosia, Health Data Research UK, London, United Kingdom
    Anne Wozencraft, Health Data Research UK, London, United Kingdom

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.