An Evaluation of Influenza Surveillance System at Nayong Hospital, Trang Province, Thailand, 2025

Abstract

In 2025, Trang Province had the second highest incidence rate of influenza in the lower southern region of Thailand, with Na Yong District ranking fourth in the province for the number of patients, showing a continuously increasing trend. This cross-sectional descriptive study aimed to evaluate the influenza surveillance system of Na Yong Hospital, Trang Province, for the year 2025. The evaluation encompassed the data reporting process, quantitative attributes, and qualitative attributes of the surveillance system. The study examined the influenza reporting process within the Digital Disease Surveillance (DDS) system and reviewed the medical records of both outpatients and inpatients diagnosed with influenza and related conditions based on ICD-10 codes in the HosXP system between January 1 and December 31, 2025. Quantitative attributes—including sensitivity, positive predictive value (PPV), completeness, accuracy, timeliness, and representativeness—were analyzed. Qualitative attributes—including simplicity, flexibility, acceptability, stability, and data usefulness—were assessed through in-depth interviews with 10 relevant personnel. The results showed that out of 192 patients with influenza-related ICD-10 codes, 171 met the case definition for reporting, and 136 were reported in the DDS system. The sensitivity of the system was 79.53%. Of the 150 patients reported in the DDS system, 136 met the case definition, yielding a positive predictive value of 90.67%. Data completeness in the DDS system was 100%. Data accuracy for variables including sex, age, occupation, date of onset, and date of diagnosis was 100%, except for address data at the village level, which was 91.91%. Timeliness of reporting within 0–3 days was 95.58%. Data regarding age and date of onset demonstrated a consistent trend in representativeness. Regarding qualitative attributes, the system demonstrated good levels of simplicity, flexibility, acceptability, and stability, with data being utilized for monitoring and controlling disease outbreaks. Therefore, understanding of the disease reporting definitions should be enhanced among personnel starting from the screening process to increase the system's sensitivity and further improve the quality of influenza surveillance.