Emergency Preparedness

Kansas storms can occur without warning and have potential to cause a multitude of health issues. Extreme weather preparedness and event monitoring for public health effects is being developed as a function of syndromic surveillance at the Kansas Department of Health and Environment (KDHE). The Syndromic Surveillance Program at KDHE utilized emergency department (ED) data to detect direct health effects of the weather events in the first 9 months of 2016. Current results show injuries directly related to the storms and also some unexpected health effects that warrant further exploration.

Objective

To evaluate syndrome definitions capturing storm- and extreme weather-related emergency department visits in Kansas hospitals participating in the National Syndromic Surveillance Program (NSSP).

Kansas storms can occur without warning and have potential to cause a multitude of health issues. Extreme weather preparedness and event monitoring for public health effects is being developed as a function of syndromic surveillance at the Kansas Department of Health and Environment (KDHE). The Syndromic Surveillance Program at KDHE utilized emergency department (ED) data to detect direct health effects of the weather events in the first 9 months of 2016. Current results show injuries directly related to the storms and also some unexpected health effects that warrant further exploration.

Objective

To evaluate syndrome definitions capturing storm- and extreme weather-related emergency department visits in Kansas hospitals participating in the National Syndromic Surveillance Program (NSSP).

Mass gatherings can result in morbidity and mortality from communicable and non-communicable diseases, injury, and bioterrorism. Therefore, it is important to identify event-related visits as opposed to community-related visits when conducting public health surveillance. Previous mass gatherings in Virginia have demonstrated the importance of implementing enhanced surveillance to facilitate early detection of public health issues to allow for timelyresponse. Between June 2015 and September 2015, VDH coordinated with two healthcare entities representing six acute care hospitals to conduct enhanced surveillance for the 2015 World Police and Fire Games and 2015 Union Cycliste Internationale (UCI) RoadWorld Championships. VDH established initial communicationwith each healthcare entity between 1 week to 2 months before theevent start date to discuss functional requirements with technical,informatics, and clinical staff.

Objective

To describe the planning strategies and lessons learned by theVirginia Department of Health (VDH) when conducting enhancedsurveillance during mass gathering events and coordinating withhealthcare entities to distinguish event-related emergency department(ED) visits from community-related ED visits

Social media messages are often short, informal, and ungrammatical. They frequently involve text, images, audio, or video, which makes the identification of useful information difficult. This complexity reduces the efficacy of standard information extraction techniques1. However, recent advances in NLP, especially methods tailored to social media2, have shown promise in improving real-time PH surveillance and emergency response3. Surveillance data derived from semantic analysis combined with traditional surveillance processes has potential to improve event detection and characterization. The CDC Office of Public Health Preparedness and Response (OPHPR), Division of Emergency Operations (DEO) and the Georgia Tech Research Institute have collaborated on the advancement of PH SA through development of new approaches in using semantic analysis for social media.

Objective

The objective of this analysis is to leverage recent advances in natural language processing (NLP) to develop new methods and system capabilities for processing social media (Twitter messages) for situational awareness (SA), syndromic surveillance (SS), and event-based surveillance (EBS). Specifically, we evaluated the use of human-in-the-loop semantic analysis to assist public health (PH) SA stakeholders in SS and EBS using massive amounts of publicly available social media data.

Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance applications. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE.

Objective

Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in nonpublic health domains, such as computer sicence and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events), and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).