identification and prioritization of potential data sources for a biothreat syndromic surveillance system in iran

Background: syndromic surveillance is considered an effective tool used to detect early manifestations of biothreats and bioterrorismrelated diseases. nowadays, a wide range of data sources has been used in biothreat syndromic surveillance systems. the current study was conducted to identify potential data sources and prioritize the most feasible ones for use in a syndromic surveillance system; we aimed to detect biothreats in iran.methods: mixed-method research was conducted. potential data sources and health indicators were investigated and selected through an extensive literature review and interviews with experts. a topsis model was used to prioritize the data sources based on timeliness, usefulness, representativeness and simplicity attributes.results: healthcare providers for humans and animals, schools, pharmacies, laboratories, workplaces, and social media were found as data contributors for syndromic surveillance systems globally. among identified data sources, a total of 13 health indicators were selected for prioritization. emergency department (ed) visit chief complaints had priority over other health indicators and were found to be the most useful source for early detection of biothreats. it is followed by over-the-counter (otc) drug sales and frequency of emergency visit records.conclusion: syndromic surveillance based on different data sources is widely used across the world. the same approach is recommended for the iranian healthcare system. hospital-based clinical data platforms, such as eds, have existed in the country for many years, and these data can be quickly incorporated into the biothreat syndromic surveillance system. for other data sources, such as otc drug sales and school and work absenteeism, designing a platform for data registration is required.