Public Health

COMBS is facilitating analyst workflows and collaboration, greatly accelerating the management of a bio-event, effectively implementing new capabilities and technologies, and providing opportunities for a wide variety of organizations to contribute data and tools that support their own goals while supporting and governing the ecosystem collaboratively.

Objective

The goal of DTRA's Biosurveillance Ecosystem (BSVE) program is to significantly reduce the time required to identify threats to human health and respond appropriately. The Draper Team is developing the Collaborative Overarching Multi-feed Biosurveillance System (COMBS) for BSVE to revolutionize biosurveillance (BSV) capabilities. Analysts will benefit from rapid and thorough information access, as will local public health authorities and individual citizens.

Although many syndromic surveillance (SS) systems have been developed and implemented, few have included response protocols to guide local health jurisdictions when alerts occur [1,2]. SS was first implemented in GA during the 2004 G-8 Summit. Six EDs in the Coastal Public Health District (PHD), 1 of 18 GA PHDs (Figure 1), conducted SS during that “national security special event.” Since that time, EDs in other PHDs have been actively recruited to participate in GA’s SS system. In GA, the PHD has the responsibility for monitoring SS data. Likewise, the PHD responds to alerts and initiates public health investigations and interventions; the state Division of Public Health (DPH) assists, if requested. To address these responsibilities, the Coastal PHD informally developed their own response practices.

Objective

To develop a template protocol to guide local response to syndromic surveillance alerts generated through analyses of emergency department (ED) visit data.

Wetter and stormier weather is predicted in the UK as global temperatures rise. It is likely there will be increases in river and coastal flooding. The known short and medium term health effects of flooding are drowning, injury, acute asthma, skin rashes and outbreaks of gastrointestinal and respiratory disease. Longer term health effects of flooding are thought to be psychological stress and increased rates of mental illness. Reacher et al. conducted a retrospective study of illness in a population affected by flooding in Lewes, South-East England during 2000 [1]. They found a significant raised risk of earache (RR=2.2) and gastroenteritis (RR=1.7) for flooded households. More striking was the higher level of psychological distress experienced by these residents (RR=4.1), which may have also explained some of the excess physical illness.

Objective

This paper describes the results of prospective real time syndromic surveillance conducted during a national flooding incident during 2007 in the UK.

Syndromic surveillance has traditionally been used by public health in disease epidemiology. Partnerships between hospital-based and public health systems can improve efforts to monitor for disease clusters. Greenville Hospital System operates a syndromic surveillance system, which uses EARS-X to monitor chief complaint, lab, and radiological data for the four emergency departments within the hospital system. Combined, the emergency departments have approximately 145,000 visits per year. During March 2007 an increase in invasive group A Streptococcus (GAS) disease in the community lead to the use of syndromic surveillance to determine if there was a concomitant increase in Scarlet Fever within the community.

Objective

 Demonstrate the utility of collaboration between hospital-based and public health syndromic surveillance systems in disease investigation. Demonstrate the ability of syndromic surveillance in identification and evaluation of process improvements.

Clinicians can pursue the clinical findings for specific patients until reaching a diagnosis in real time.  When using electronic ED complaints, one relies on symptoms volunteered by patients in the triage setting.  Patients seek emergency care at different stages of disease and there is scant information detailing how they respond when allowed only 2-3 complaints.  Our emergency department (ED) clinical data warehouse includes date, demographics, complaints, diagnosis, laboratory results, and disposition. We used a process similar to reverse engineering to augment our ability to detect chief complaints and test results consistent with MEE.  We started with the diagnosis of MEE and examined the chief complaints and diagnostic findings in patients diagnosed with MEE to develop expanded algorithms.

Objective

Our research questions were:

1.) could we use existing data to empirically improve our syndrome surveillance algorithms?

2.) Is it feasible to combine disparate data sources to detect the same event? We studied these questions using the meningoencephali-tis (MEE) syndrome and the West Nile Virus Chicago outbreak in 2002.

NC DETECT receives data on at least a daily basis from five data sources: emergency departments (ED), the statewide poison center (CPC), the statewide EMS data collection system, a regional wildlife center and laboratories from the NC State College of Veterinary Medicine.  A Web portal is available to users at state, regional and local levels and provides syndromic surveillance reports as well as reports for broader public health surveillance such as injury, occupational health, and post-disaster.  The current portal is built on access controls initially designed in 2002 for hospital-based users only.  The role-based access was modified slightly in 2004 to accommodate public health epidemiologists (PHEs) at the local, regional and state levels who wanted county-based report access.  The design used, however, was shortsighted and limited.  For example, the controls cannot accommodate certain users’ access to non-ED data sources as well as the ability to retrieve protected health information (PHI) via the portal when needed for investigation.  These evolving user needs have led to a full system redesign with a much more robust security model.

Objective

This paper describes the role-based access used in the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) Web portal for early event detection and timely public health surveillance.

By capturing the spatio-temporal organization of the data using a graph, GraphScan avoids the challenges associated with trying to “fit” incoming data into moving windows of predefined shapes and sizes. Whereas the popular space-time permutation scan statistic [1] attempts to find clusters within spacetime volumes of predefined shape, GraphScan employs no such preconceptions about the form of the clusters.  Instead, clusters are allowed to “evolve” freely to better reflect the structural properties of the data.  Moreover, GraphScan is capable of tracking possible causal relationships between spatio-temporal events.

Objective

This paper proposes an efficient and flexible algorithm applicable to spatio-temporal aberration detection in public health data.

 Following the development of an introductory Continuing Education (CME) course in syndromic surveillance, the Education and Training Committee of the International Society for Disease Surveillance recognized the need to educate future non-medical public health workers and reviewed courses offered by the top five public health schools recognized by US News and World Report1.  All public health schools offered courses that included information on public health practice and infectious disease epidemiology and few offered courses on spatial and disaster epidemiology with attention given to syndromic surveillance, but none of the schools offered a comprehensive course that integrated topics of public health practice, infectious disease surveillance, data management and analytic techniques, disaster preparedness, and syndromic surveillance2-6.  The development of the graduate school course builds on our existing CME slide set goals that teaches students about syndromic surveillance and presents the course in a free and easy to use format for all schools of public health.  The ISDS hopes the semester long course will be taught by ISDS members in each state to spread awareness and knowledge on the topic of syndromic surveillance.

Objective

The paper describes the development of a graduate-level course to teach future non-medical public health workers about syndromic surveillance.

As part of public health protection activities conducted in support of the G8 Summit in Sea Island, GA, June 2004, DPH implemented SS in the state’s coastal region using information provided from ED visits, 911 calls, and pharmacy sales. Following this high-profile event, questions arose about whether to maintain the ED system and about whether and where to extend its use in GA.  Despite the emergence of practice-based guidance for conducting SS and the growing experience of public health agencies, little guidance is available regarding strategies for identifying sites where SS should be targeted.

 

Objective

This paper describes the strategy used by the Georgia Division of Public Health (DPH) in implementing syndromic surveillance (SS), including criteria for prioritizing localities and the early results of applying these criteria in initiating new emergency department (ED)-visit based systems.