Outbreak detector: a web application to boost disease surveillance systems and timely detection of infectious disease epidemics

• Published in: BMC research notes Vol. 17; no. 1; pp. 229 - 10
• Main Authors: Zareie, Bushra, Poorolajal, Jalal, Roshani, Amin, Menbari, Ahmed, Karami, Manoochehr
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 20-08-2024; BioMed Central; BMC
• Subjects: Algorithms; Automatic outbreak detection; Communicable diseases; Communicable Diseases - diagnosis; Communicable Diseases - epidemiology; Control charts; Disease Outbreaks - prevention & control; Early warning systems; Epidemics; Epidemics - prevention & control; Health surveillance; Humans; Infections; Infectious diseases; Internet; Medical research; Medicine, Experimental; Methods; Outbreaks; Population Surveillance - methods; Public health; Research Note; Sensitivity analysis; Sentinel health events; Social aspects; Software; Syndromic surveillance systems; Technology application; Testing; Web application; Web applications; Iran; Automatic outbreak detection; Outbreaks; Syndromic surveillance systems; Early warning systems; Web application
• ISSN: 1756-0500; 1756-0500
• DOI: 10.1186/s13104-024-06892-8

Digital technologies have improved the performance of surveillance systems through early detection of outbreaks and epidemic control. The aim of this study is to introduce an outbreak detection web application called OBDETECTOR (Outbreak Detector), which as a professional web application has the ability to process weekly or daily reported data from disease surveillance systems and facilitates the early detection of disease outbreaks.
OBDETECTOR generates a histogram that exhibits the trend of infection within a time range selected by the user. The output comprises red triangles and plus signs, where the former denotes outbreak days determined by the algorithm applied to the data, and the latter represents days identified as outbreaks by the researcher. The graph also displays threshold values and its symbols enable researchers to compute evaluation criteria for outbreak detection algorithms, including sensitivity and specificity. OBDETECTOR allows users to modify algorithm parameters based on their research objectives immediately after loading data. The implementation of automatic web applications results in immediate reporting, precise analysis, and prompt alert notification. Moreover, Public Health authorities and other stakeholders of surveillance can benefit from the widespread accessibility and user-friendliness of these tools, enhancing their knowledge and skills for better engagement in surveillance programs.