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. 2025 Mar 28:13:1523873.
doi: 10.3389/fpubh.2025.1523873. eCollection 2025.

Exploring the landscape of essential health data science skills and research challenges: a survey of stakeholders in Africa, Asia, and Latin America and the Caribbean

Sally Boylan #  1 , Agklinta Kiosia #  1   2 , Matthew Retford #  1 , Larissa Pruner Marques  3 , Flávia Thedim Costa Bueno  3 , Md Saimul Islam  4 , Anne Wozencraft #  1
Affiliations

Exploring the landscape of essential health data science skills and research challenges: a survey of stakeholders in Africa, Asia, and Latin America and the Caribbean

Sally Boylan et al. Front Public Health. .

Abstract

Background: Data science approaches have been pivotal in addressing public health challenges. However, there has been limited focus on identifying essential data science skills for health researchers, gaps in capacity building provision, barriers to access, and potential solutions.

Objectives: This review aims to identify essential data science skills for health researchers and key stakeholders in Africa, Asia, and Latin America and the Caribbean (LAC), as well as to explore gaps and barriers in data science capacity building and share potential solutions, including any regional variations.

Methods: An online survey was conducted in English, French, Spanish and Portuguese, gathering both quantitative and qualitative responses. Descriptive analysis was performed in R V4.3, and a thematic workshop approach facilitated qualitative analysis.

Findings: From 262 responses from individuals across 54 low- and middle-income countries (LMICs), representing various institutions and roles, we summarised essential data science skills globally and by region. Thematic analysis revealed key gaps and barriers in capacity building, including limited training resources, lack of mentoring, challenges with data quality, infrastructure and privacy issues, and the absence of a conducive research environment.

Conclusion and future directions: Respondents' consensus on essential data science skills suggests the need for a standardised framework for capacity building, adaptable to regional contexts. Greater investment, coupled with expanded collaboration and networking, would help address gaps and barriers, fostering a robust data science ecosystem and advancing insights into global health challenges.

Keywords: capacity building; data science; essential data science skills; global health challenges; global health research; low-and middle-income countries.

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Conflict of interest statement

AW, SB, AK and MR are employed by Health Data Research UK. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Methodology framework for landscaping survey.
Figure 2
Figure 2
Health data research project lifecycle, developed by HDR UK’s Global programme.
Figure 3
Figure 3
Density map depicting the percentage of survey responses received by country (n = 262).
Figure 4
Figure 4
Total % survey responses received, broken down by region.
Figure 5
Figure 5
Top 15 responses in % by country—(n-262).
Figure 6
Figure 6
Total percentage (%) of responses in all regions, by primary occupation.
Figure 7
Figure 7
Total percentage (%) of responses from all three regions, by primary institution.
Figure 8
Figure 8
Essential research planning skills as reported by responders in each region.
Figure 9
Figure 9
Essential data access and management skills as reported by survey respondents in each region.
Figure 10
Figure 10
Essential data analysis skills as reported by survey respondents in each region.
Figure 11
Figure 11
Essential outputs and impact skills identified by respondents in each region.
Figure 12
Figure 12
Essential stakeholder engagement skills identified by respondents in each region.
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