Evidence map›Paper›PMID 40226318›Full record

ArticleFrontiers in public health2025

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, Agklinta Kiosia, Matthew Retford, Larissa Pruner Marques, Flávia Thedim Costa Bueno, Md Saimul Islam, Anne Wozencraft

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sally Boylan *Health Data Research UK (HDR UK), HDR Global Programme, London, United Kingdom.
Agklinta Kiosia *Health Data Research UK (HDR UK), HDR Global Programme, London, United Kingdom.
Matthew Retford *Health Data Research UK (HDR UK), HDR Global Programme, London, United Kingdom.
Larissa Pruner MarquesOswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.
Flávia Thedim Costa BuenoOswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.
Md Saimul IslamNon-Communicable Diseases, Nutrition Research Division, icddr,b, Dhaka, Bangladesh.
Anne Wozencraft *Health Data Research UK (HDR UK), HDR Global Programme, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Data ScienceResearch PersonnelStakeholder ParticipationAfricaAsiaCapacity BuildingCaribbean RegionDeveloping CountriesHumansLatin AmericaSurveys and Questionnairescapacity buildingdata scienceessential data science skillsglobal health challengesglobal health researchlow-and middle-income countries

Identifiers

PMID40226318
PMCPMC11985845

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.