Conference Abstract | Volume 9 (ConfProc7): Abstract 088 | Published: 06 Oct 2026
Kofi Nti Agyarko1,2,&, David Yobo Quansah2, Shirley Brown-Sarkodee2, Benita Anderson3
1Veterinary Services Department, Koforidua, Fish Health Unit, Eastern Region, Ghana, 2Fisheries Commission, Fish Health Unit, Koforidua, Eastern Region, Ghana, 3Veterinary Services Department, Kpong Tamale, Northern Region, Ghana.
&Corresponding author: Kofi Nti Agyarko, Veterinary Services Department, Koforidua, Eastern Region, Ghana; Fisheries Commission, Fish Health Unit, Koforidua, Eastern Region, Ghana.
Received: 29 Aug 2025, Accepted: 28 Oct 2025, Published: 06 Oct 2026
Domain: Infectious Disease Epidemiology
This is part of the Proceedings of the 8th Ghana FELTP Scientific Conference and FELTP Competency Graduation, Accra, Ghana, 10 – 11 December, 2025
Keywords: Aquaculture, Data Management, SILAB, QGIS, Traceability, Fish Farmer Visibility, Laboratory Efficiency
©Kofi Nti Agyarko et al Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article: Kofi Nti Agyarko et al. Enhancing aquatic laboratory data management and fish farm visibility in Koforidua, Ghana, using SILAB and QGIS Technology, 2025. Journal of Interventional Epidemiology and Public Health. 2026;9(ConfProc7):088. https://doi.org/10.37432/JIEPH-CONFPRO7-0088
Ghana’s aquaculture industry is expanding rapidly but faces inefficiencies in laboratory data management, fish farm visibility, and traceability. Manual data systems contribute to diagnostic delays and poor disease surveillance. This project implemented the System for Integrated Laboratory Data (SILAB), a laboratory information management tool and Geographic Information System (GIS) technologies to strengthen aquatic laboratory performance and enhance the visibility of fish farms in Koforidua, Eastern Region. The study aimed to improve laboratory data accuracy through SILAB, build staff capacity in digital data management, and integrate spatial mapping of aquaculture farms for traceability.
A descriptive cross-sectional design was adopted. SILAB was deployed at the Koforidua Veterinary Laboratory, and three staff members were trained in digital diagnostics and data entry. Pre- and post-training assessments were conducted to evaluate knowledge gain. Twenty-two aquaculture farms were geo-referenced using QGIS, collecting attributes such as farm ID, species cultured, water source, and infrastructure type. Data were analysed using descriptive statistics and integrated into SILAB for linkage between laboratory results and farm locations.
Among 23 samples processed within 42 hours, 95.7% were digitally analysed and validated through SILAB. Over half (52.2%) of test results were completed within twenty-four hours, showing improved turnaround time. Staff pre-test and post-test scores increased from 64% to 96%, demonstrating enhanced digital competence. Twenty-two farms were successfully mapped, 7.3% tanks and 22.7% ponds strengthening disease traceability and operational transparency.
Implementing SILAB and QGIS significantly improved laboratory efficiency, staff capacity, and farm visibility in Koforidua. The integrated digital framework offers a scalable model for sustainable aquaculture data governance across Ghana. Continued infrastructure investment and farmer participation are vital for national rollout.
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