In general, data from public health surveillance can be used for short- and long-term planning and response through retrospective data analysis of trends over time or specific events. Combining health outcome data (e.g., hospitalizations or deaths) with environmental and socio-demographic information also provides a more complete picture of most vulnerable populations. Using syndromic surveillance systems for climate and health surveillance offers the unique opportunity to help quantify and track in near-real time the burden of disease from climate and weather impacts.
Disaster
Description
Previous research identifies social media as an informal source of near-real time health data that may add value to disease surveillance systems by providing broader access to health data across hard-toreach populations. This indirect health monitoring may improve public health professionals’ ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. The Philippines consists of over 7,000 islands and is prone to meteorological (storms), hydrological (floods), and geophysical disasters (earthquakes and volcanoes). In these situations, evacuation centers are used for safety and medical attention and often house up to 50K people each for 2 or more months, sometimes with unclean water sources and improper sanitation. Consequently, these conditions are a perfect venue for communicable disease transmission and have been proposed to cause disease outbreaks weeks after the original disaster occurred. Coined the social media capital of the world1, the Philippines provides a perfect opportunity to evaluate the potential of social media use in disease surveillance.
Objective
To determine the potential of Twitter data as an early warning of a likely communicable disease outbreak following a natural disaster, and if successful, develop an open-source algorithm for use by interested parties.
Hurricane Sandy hit New York City (NYC) on October 29, 2012. Before and after the storm, 73 temporary evacuation shelters were established. The total census of these shelters peaked at approximately 6,800 individuals. Concern about the spread of communicable diseases in shelters prompted the NYC Department of Health and Mental Hygiene (DOHMH) to rapidly develop a surveillance system to report communicable diseases and emergency department transports from shelters. We describe the implementation of this system.
Disaster epidemiology (i.e., applied epidemiology in disaster settings) presents a source of reliable and actionable information for decision-makers and stakeholders in the disaster management cycle. However, epidemiological methods have yet to be routinely integrated into disaster response and fully communicated to response leaders.
This report is designed to aid state, territorial, tribal, and local public health leaders as they improve their capacity to achieve situational awareness during a public health emergency. We intend this report to serve as a concise reference work public health leaders can use to help design and manage biosurveillance systems to be used during an anticipated public health emergency.
Following Hurricane Superstorm Sandy, the New Jersey Department of Health (NJDOH) developed indicators to enhance syndromic surveillance for extreme weather events in EpiCenter, an online system that collects and analyzes real-time chief complaint emergency department (ED) data and classifies each visit by indicator or syndrome.
Transmission of infectious diseases became an immediate public health concern when approximately 27,000 New Orleans-area residents evacuated to Houston's Astrodome and Reliant Park Complex following Hurricane Katrina. This article presents a surveillance system that was rapidly developed and implemented for daily tracking of various symptoms in the evacuee population in the Astrodome “megashelter.” This system successfully confirmed an outbreak of acute gastroenteritis and became a critical tool in monitoring the course of this outbreak.
Objective
For much of the United States, 2014 began with extreme cold and large snowstorms. As a result, surveillance practitioners around the country have been working to identify, gather, and analyze cold weather-related data. This presentation will focus on data analysis and use for winter weather surveillance in both Indianapolis and Boston.
Description
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).
This seminar will share how states are using existing Electronic Death Registration Systems (ERDS) for active surveillance and EDRS’ role in mass fatality planning. CDC will present an a conceptual framework to leverage EDRS and other available databases to develop an electronic national disaster mortality surveillance system.
Speakers and Topics
Introduction and Overview
Speaker: Ann Madsen, PhD, MPH, Director, Office of Vital Statistics, Bureau of Vital Statistics, NYC Department of Health and Mental Hygiene