The early warning and response systems in Syria: A functionality and alert threshold assessment

Abstract

Objectives

this study aims to provide an updated evaluation of the functional characteristics of the two Early Warning Systems (EWS) in Syria, EWARS (Early Warning, Alert, and Response System) and EWARN (Early Warning, Alert, and Response Network), and to test different alert threshold methods using World Health Organization guidelines against the data of selected diseases.

Methods

A retrospective analysis of EWARN and EWARS surveillance data assessed functional characteristics. The World Health Organization alert thresholds for measles, acute bloody diarrhea, acute jaundice syndrome, and severe acute respiratory infections were tested using three methods. Sensitivity, specificity, and Youden 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. This study found that the optimal alert thresholds varied among different diseases. The percentile method showed promising results with good sensitivity and specificity. For measles, the 85^th percentile threshold had the best results (Youden index = 0.443), whereas for acute bloody diarrhea, it was 75^th percentile (Y = 0.532) and for severe acute respiratory infections, it was 90^th percentile (Y = 0.653).

Conclusions

This study supports the use of adaptable disease-specific alert thresholds such as the percentile approach. Further research is required to develop statistical methods that can be applied to various early warning systems in conflict contexts.