Publications

Journal Article Epublish

PubMed: 40028452 DOI: 10.12688/f1000research.154839.1

Enhancing quantitative capacity for the health sector in post-Ebola Liberia, a tracer study of a locally developed and owned coding and biostatistics program.

F1000Res 13:988

Authors: Snoyonoh T Barcon, Trokon O Yeabah, Mulbah K A Kromah, George B Davis, Laura A Skrip

Affiliations

  • Quantitative-Data for Decision-Making (Q4D) Lab, Monrovia, Liberia.
  • Division of Infectious Disease and Epidemiology, National Public Health Institute of Liberia, Monrovia, Liberia.
  • Liberia Institute of Statistics and Geo-Information Services, Executive Mansion Ground, Monrovia, Liberia.
  • School of Public Health, College of Health Sciences, University of Liberia, Monrovia, Montserrado, Liberia.

Abstract

Background

Despite the demonstrated value of quantitative research in understanding and responding to public health events, analytics capability is not always prioritized or available in settings that would greatly benefit from it. In Liberia, there are no university degree-granting programs in biostatistics or mathematical modeling, promoting dependence on external technical assistance. To address the gap, a local NGO, Quantitative-Data for Decision-Making (Q4D), was founded to enhance capacity and opportunities for analyzing quantitative data among Liberians.

Methods

To understand the relevance, utility, and impact of the skills being taught at Q4D, a tracer study was undertaken with current and former students. Participants completed an online survey that evaluated how often and in what ways they are applying course skills, as well as any personal or professional advancement they have attributed to their learning of coding and/or biostatistics through the program.

Results

Among 43 participants, 81% reported a high level of confidence in independently applying skills learned through Q4D classes in their jobs and/or academic programs. Most participants (81%) responded that they were actively demonstrating the skills they acquired; 74% were teaching the skills to others. Among the 83% of employed participants who reported using the skills currently in their jobs, 56% rated the skills they learned as very or extremely useful in their current positions. Several students attributed salary increments, consultancy opportunities, and scholarships to the skills gained through the program.

Conclusions

Program skills are being applied by students employed in health-related sectors, suggesting that the training content is relevant and useful for addressing some of the workforce's analysis needs. Moreover, skills built through the program have positively impacted students by preparing them with the skills required for additional employment and training opportunities to advance in-country health research capacity and reduce inequities.

MeSH

Biomedical Research, Research, Biostatistics