ASSESSMENT OF FACTORS MILITATING AGAINST EFFECTIVE DISEASE SURVEILLANCE AND NOTIFICATION SYSTEMS IN SELECTED LGA IN TARABA STATE.

Abstract

A disease surveillance system is the foundation of public health action. It facilitates the early detection of potential health threats, supports timely intervention, and enables evidence-based policy formulation. This study assessed the factors militating against effective disease surveillance and notification (DSN) system in Ardo-Kola, Bali, and Takum Local Government Areas (LGAs) of Taraba State, Nigeria. A descriptive cross-sectional design was adopted. Using Yamane's (1967) formula, a sample of 300 respondents was drawn from a target population of 1,200 Surveillance Focal Persons and Community Key Informants across the three LGAs through stratified random sampling. Data were collected via a structured self-administered questionnaire and analysed using SPSS version 27. Frequencies, percentages, and Chi-square tests were employed at a 0.05 significance level. Findings revealed that 80.3% of respondents encountered challenges in completing DSN reporting forms, with workload overload (62.3%) and inadequate training (48.3%) as dominant barriers. Electronic data capture systems were available in only 27.7% of facilities. Data analysis prior to submission occurred in only 34.3% of facilities, while regular trend analysis was conducted in only 29.0% of LGAs. A defined interpretation system was absent in 58.7% of facilities, and 52.3% lacked defined dissemination protocols. Outbreak response was hampered by funding gaps (71.3%), inadequate logistics (74.0%), and poor communication (87.7%). Chi-square analysis confirmed statistically significant relationships between DSN effectiveness and: factors hindering data collection (χ² = 9.660, p = .002), factors limiting data analysis (χ² = 4.090, p = .043), and factors undermining response mechanisms (χ² = 5.599, p = .018). The study concludes that the DSN system in the selected LGAs is significantly constrained across its operational dimensions and recommends targeted investment in digital health infrastructure, capacity building, and sustainable funding for outbreak response.