Introduction: The protracted conflict in Syria has led to a fragmented health system, resulting in two distinct syndromic surveillance systems: Early Warning and Response Network (EWARN) and Early Warning and Response System (EWARS). Given this unique epidemiological context in Syria, there is a need for continuous evaluation of these Early Warning Systems (EWS) to improve their effectiveness in detecting and responding to public health threats. Methods: A retrospective analysis of EWARN and EWARS surveillance data assessed functional characteristics. WHO alert thresholds for measles, acute bloody diarrhea (ABD), acute jaundice syndrome (AJS), and severe acute respiratory infections (SARI) were tested using three methods. Sensitivity, specificity, and Youden’s index determined threshold suitability for each syndrome. Results: The annual average number of reported cases was 1,140,717 for EWARS and 10,189,415 for EWARN. The study found that the optimal alert thresholds varied among the different diseases. The percentile method showed promising results, demonstrating good sensitivity and specificity. For measles, the 85th percentile (P85) threshold had the best results (Youden’s index = .443), whereas for ABD it was the P75 (Y= .532), and for SARI it was P90 (Y= .653). Conclusion: The study supports the use of adaptable disease-specific alert thresholds, such as the percentile approach. Further research is needed to develop statistical methods that can be applied across various EWS in conflict contexts.
Alhaffar et al. (Sun,) studied this question.