Conference Abstract | Volume 9 (ConfPro8): Abstract 72 | Published: 10 Oct 2026
Modesta Bayor1,&, Samuel Dapaa2, Ambrose Yonye1, Magdalene Akos Odikro2, Genevieve Yiripare1, Samuel Oko Sackey2
1Daffiama Bussie Issa District of Ghana Health Service, Daffiama Bussie Issa, Ghana; 2Ghana Field Epidemiology and Laboratory Training Programme; Accra, Ghana
&Corresponding author: Modesta Bayor, Daffiama Bussie Issa District of Ghana Health Service Email: mbayor05025@gmail.com
Received: 11 Mar 2026, Accepted: 30 Aug 2026, Published: 10 Oct 2026
Domain: Infectious Disease Epidemiology
Keywords: Public health surveillance, data quality assessment, surveillance reporting, SWOT analysis, Daffiama Bussie Issa District, Ghana
©Modesta Bayor 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: Modesta Bayor et al., Strengthening routine surveillance for public health action through quality audit, Daffiama Bussie Issa District, 2026. Journal of Interventional Epidemiology and Public Health. 2026;9(ConfPro8):72. https://doi.org/10.37432/JIEPH-CONFPRO8-0072
High-quality surveillance data are essential for outbreak detection, disease monitoring, resource allocation, and evidence-based public health decision-making. Poor quality data undermines surveillance effectiveness. This audit assessed the quality of surveillance data and reporting systems in selected health facilities to identify gaps and opportunities for improvement.
A facility-based cross-sectional data quality audit was conducted from March to April 2026. The audit was conducted in Fian Health Centre, Wogu CHPS, and Tuori CHPS in the Daffiama-Bussie-Issa District. Source documents were reviewed, and health staff interviewed. Data quality dimensions assessed included accuracy, completeness, timeliness, and consistency. Findings were analysed qualitatively using a SWOT framework to identify internal strengths and weaknesses, as well as external opportunities and threats influencing surveillance data quality.
Of 14 participants in the audit, females constituted 57.1% (8/14) and a mean age of 31.6 years. Nurses represented 50% (7/14) and 68% attaining tertiary education. Strengths identified included availability of surveillance registers, routine reporting practices, and staff familiarity with reporting procedures. Weaknesses included incomplete registers, inadequate documentation, limited data analysis, missing validation records, and discrepancies between source documents and reported figures. Opportunities included supportive supervision, routine validation mechanisms, and digital reporting systems, while threats comprised workload pressures, delayed feedback, and logistical constraints.
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