This project will develop and evaluate a collection of public health technology tools to assist inremote data collection and dispersion. Mass prophylaxis clinic needs will be addressed to capture dataelectronically and monitor both individual and collections of clinics. Language translation features will beimplemented to support real-time text-to-text or text-to-speech translation in the field, enabling clinic staff tocommunicate with speakers of other languages. Event reporting tools will allow health data from injured orsick individuals to be collected and uploaded to a surveillance system during large public events.Techniques using lightweight, low-investment, multi-use technologies will be readily adaptable to otherpopulation-based public health situations such as vaccine days and mass treatment and casualtysituations.Using clustering, decision tree induction and other data-mining techniques we will developautomated, data-driven methods of defining syndrome groupings for syndromic surveillance systems. Inaddition we will compare the sensitivity and specificity of these data-generated syndromes with currentlyused expert-opinion based syndromes using the CDC's ICD-9-based syndrome definitions as the goldstandard.We will extend available PHIN ontologies and vocabulary concepts to enable standardizedinterchange of aggregated and raw data, expert-user input text, and results of statistical tests within andbetween syndromic surveillance systems. The techniques developed will support the development of interjurisdictionaldetection algorithms in Project 2, and will provide standards for inter-jurisdictional transfer ofinformation and aggregated data when sharing of raw data is legally or politically is not possible.The ability to collect, summarize and share data between diverse information systems is key to thecreation of local and national public health informatics networks (PHIN). Although work will be centered onsyndromic surveillance the techniques developed will be applicable to other areas of public health.
