Aslam Sadia

The summer of 2010 in Maryland was characterized by unusually high temperatures. This type of increased and prolonged heat can potentially make residents sick, and extreme exposure can even kill people at highest risk. Numerous deaths throughout the state were attributed to this heat wave. The Maryland Department of Health and Mental Hygiene addressed this public health issue by using public messaging and maintaining constant situational awareness through the electronic syndromic surveillance. Thus, the electronic surveillance system for the early notification of community-based epidemics (ESSENCE) was used to monitor heat-related illnesses throughout the state.

Objective

This paper describes the use of ESSENCE, a syndromic surveillance system, to monitor heat-related illnesses throughout the state of Maryland during the summer of 2010.

An increasing amount of global discourse reporting has migrated to the online space, in the form of publicly accessible social media outlets, blogs, wikis, and news feeds. Social media also presents pub- licly available and highly accessible information about individual, real-time activity that can be leveraged to detect, monitor, and more efficiently respond to biological events.

Objective

We propose a cloud-based Open Source Health Intelligence (OS- HINT) system that uses open source media outlets, such as Twitter and RSS feeds, to automatically characterize foodborne illness events in real-time. OSHINT also forecasts response requirements, through predictive models, to allow more efficient use of resources, person- nel, and countermeasures in biological event response.