Surveillance Systems

On July 11, 2012, New Jersey Department of Health (DOH) Communicable Disease Service (CDS) surveillance staff received email notification of a statewide anomaly in EpiCenter for Paralysis. Two additional anomalies followed within three hours. Since Paralysis Anomalies are uncommon, staff initiated an investigation to determine if there was an outbreak or other event of concern taking place. Also at question was whether receipt of multiple anomalies in such a short time span was statistically or epidemiologically significant.

Objective

To describe the investigation of a statewide anomaly detected by a newly established state syndromic surveillance system and usage of that system.

Florida has implemented various surveillance methods to augment existing sources of surveillance data and enhance decision making with timely evidence based assessments to guide response efforts post-hurricanes. Historically, data collected from deployed federal assets have been an integral part of this effort. However, a number of factors have made this type of surveillance challenging: logistical is- sues of field work in a post-disaster environment, the resource inten- sive manual data collection process from DMAT sites, and delayed analysis and interpretation of these data to inform decision makers. The ESSENCE-FL system is an automated and secure web-based ap- plication accessed by FDOH epidemiologists and staff at participat- ing hospitals.

Objective

The Florida Department of Health (FDOH), Bureau of Epidemi- ology, partnered with the U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) to improve surveillance methods in post dis- aster or response events. A new process was implemented for con- ducting surveillance to monitor injury and illness for those presenting for care to ASPR assets such as Disaster Medical Assistance Team (DMAT) sites when they are operational in the state. The purpose of the current work was to field test and document the operational ex- perience of the newly implemented ASPR data module in ESSENCE- FL (syndromic surveillance system) to receive near real-time automated data feeds when ASPR federal assets were deployed in Florida during the 2012 Republican National Convention (RNC).

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.

Lessons learned from the 2009 influenza pandemic have driven many changes in the standards and practices of respiratory disease surveillance worldwide. In response to the needs for timely information sharing of emerging respiratory pathogens (1), the DoD Armed Forces Health Surveillance Center (AFHSC) collaborated with the Johns Hopkins University Applied Physics Laboratory (JHU/APL) to develop an Internet-based data management system known as the Respiratory Disease Dashboard (RDD). The goal of the RDD is to provide the AFHSC global respiratory disease surveillance network a centralized system for the monitoring and tracking of lab-confirmed respiratory pathogens, thereby streamlining the data reporting process and enhancing the timeliness for detection of potential pandemic threats. This system consists of a password-protected internet portal that allows users to directly input respiratory specimen data and visualize data on an interactive, global map. Currently, eight DoD partner laboratories are actively entering respiratory pathogen data into the RDD, encompassing specimens from sentinel sites in eleven countries: Cambodia, Colombia, Kenya, Ecuador, Egypt, Honduras, Nicaragua, Paraguay, Peru, Uganda, and the United States. A user satisfaction survey was conducted to guide further development of the RDD and to support other disease surveillance efforts at the AFHSC.

Objective

Evaluate the user experience of a novel electronic disease reporting and analysis system deployed across the DoD global laboratory surveillance network.

The practice of public health surveillance is evolving as electronic health records (EHRs) and automated laboratory information systems are increasing adopted, as new approaches for health information exchange are employed, and as new health information standards affect the entire cascade of surveillance information flow. These trends have been accelerated by the Federal program to promote the Meaningful Use of electronic health records, which includes explicit population health objectives. The growing use of Internet “cloud” technology provides new opportunities for improving information sharing and for reducing surveillance costs. Potential benefits include not only faster and more complete surveillance but also new opportunities for providing population health information back to clinicians. For public health surveys, new Internet-based sampling and survey methods hold the promise of complementing existing telephonebased surveys, which have been plagued by declining response rates despite the addition of cell-phone sampling. While new technologies hold promise for improving surveillance practice, there are multiple challenges, including constraints on public health budgets and the workforce. This panel will explore how PHSIPO is addressing these opportunities and challenges.

Objective

To provide updates on current activities and future directions for the National Notifiable Diseases Surveillance System (NNDSS), BioSense 2.0, and the Behavioral Risk Factor Surveillance System (BRFSS) and on the role of PHSIPO as the “home” at CDC for addressing cross-cutting issues in surveillance and informatics practice

INDICATOR is a multi-stream open source platform for biosurveillance and outbreak detection, currently focused on Champaign County in Illinois[1]. It has been in production since 2008 and is currently receiving data from emergency departments, patient advisory nurse call center, outpatient convenient care clinic, school absenteeism, animal control, and weather sources. Long term scalability was however compromised during the 2009 H1N1 influenza pandemic as immediate public health needs took priority over our systematic development plan. With the impending addition of veterinary clinic data and recognizing that the health of a community also depends on animal and environmental factors, we decided to revisit the INDICATOR architecture and redesign it to be a more holistic and scalable system. We also decided to revisit the data submission format, keeping in line with the philosophy of making opportunistic secondary use of as much data about the health of a community that we can obtain.

Objective

To redesign INDICATOR for One Health, establish a common data format, and provide for long term scalability.

For radiological incidents, collecting surveillance data can identify radiation-related public health significant incidents quickly and enable public health officials to describe the characteristics of the affected population and the magnitude of the health impact which in turn can inform public health decision-making. A survey administered by the Council of State and Territorial Epidemiologists (CSTE) to state health departments in 2010 assessed the extent of state-level planning for surveillance of radiation-related exposures and incidents: 70%–84% of states reported minimal or no planning completed. One data source for surveillance of radiological exposures and illnesses is regional poison centers (PCs), who receive information requests and reported exposures from healthcare providers and the public. Since 2010, the Centers for Disease Control and Prevention (CDC) and the American Association of Poison Control Centers (AAPCC) have conducted ongoing surveillance for exposures to radiation and radioactive materials reported from all 57 United States (US) PCs to NPDS, a web-based, national PC reporting database and surveillance system.

Objective

To describe radiation-related exposures of potential public health significance reported to the National Poison Data System (NPDS).

The French syndromic surveillance system SurSaUD was set up by the French institute for public health surveillance (InVS) in 2004. The system is based on three main data sources: 1) the attendances in the Emergency departments (ED), 2) the consultations to emergency General Practitioners’ associations SOS Médecins, 3) the mortality data from civil status offices and e-certificates.

In 2012, 400 of the 710 ED and 59 of the 62 GP’s associations are involved in the system. 80% of the national mortality is also collected. Given this large database and the need to analyze data in a short delay to reach the early warning objective of the system, a specific software has been developed.

Objective

The presentation describes the design and the main functionalities of the software developed to support the data management and data analysis of the French syndromic surveillance system.

To meet the long-term needs of public health and social development of China, it is in urgency to establish a comprehensive response system and crisis management mechanism for public health emergencies. Syndromic surveillance system has great advantages in promoting early detection of epidemics and reducing the burden of disease outbreak confirmation. The effective method to set up the syndromic surveillance system is to modify existing case report system, improve the organizational structures and integrate new function with the traditional system.

Objective

To understand the structure and capacity of current infection disease surveillance system, and to provide baseline information for developing syndromic surveillance system in rural China.

As part of the US Department of Defense strategy to counter biological threats, the Defense Threat Reduction Agency’s Cooperative Biological Engagement Program is enhancing the capabilities of countries in the former Soviet Union (FSU) to detect, diagnose, and report endemic and epidemic, man-made or natural cases of especially dangerous pathogens. During these engagements, it was noted that Western-trained and Soviet-trained epidemiologists have difficulty, beyond that of simple translation, in exchanging ideas.

The Soviet public health system and epidemiology developed independently of that of other nations. Whereas epidemiology in the West is thought of in terms of disease determinants in populations and relies on statistics to make inferences, classical Soviet epidemiology is founded on a more ecological view with the main focus on infectious diseases’ spread theory. Consequently many fundamental Soviet terms and concepts lack simple correlates in English and other languages outside the Soviet sphere; the same is true when attempting to translate from English to Russian and other languages of the FSU. Systematic review of the differences in FSU and Western epidemiologic concepts and terminology is therefore needed for strengthening understanding and collaboration in disease surveillance, pandemic preparedness, response to biological terrorism, etc.

Objective

The purpose of this project was to develop an English-Russian Epidemiology Dictionary, which is needed for improved international collaboration in public health surveillance.