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Notifiable Disease Data

Influenza is an important public health problem associated with considerable morbidity and mortality. A disease traditionally monitored via legally mandated reporting, researchers have identified alternative data sources for influenza surveillance. The hospital environment presents a unique opportunity for comparative studies of biosurveillance data with high quality and various level of clinical information ranging from provisional diagnoses to laboratory confirmed cases. This study investigated the alert times achievable from hospital-based sources relative to reporting of influenza cases. The earlier detection of influenza could potentially provide more advanced warning for the medical community and the early implementation of precautionary measures in vulnerable populations.

 

Objective

To determine the relative alert time of influenza surveillance based on hospital data sources compared to notifiable disease reporting.

Referenced File
Submitted by elamb on

On June 7, 2008, federal food protection and public health agencies alerted consumers of a nationwide outbreak of Salmonella Saintpaul infections. As of June 30, 2008, 851 persons infected with Salmonella Saintpaul with the same genetic fingerprint had been identified in 36 states and the District of Columbia since April 20081. On June 13, 2008, Maryland confirmed its first case of Salmonella Saintpaul infection matching the national outbreak strain and as of June 30, 2008, 29 cases of Salmonella related to the outbreak have been identified.

 

Objective 

The purpose of this paper is to describe the use of syndromic surveillance emergency department data as a tool for enhanced case finding of outbreak-related illnesses.

Referenced File
Submitted by elamb on

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

Submitted by uysz on

Most countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health. While most nations likely store incident data in a machine-readable format, governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues1. A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language. The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors. LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.

Objective:

LANL has built software that automatically collects global notifiable disease data, synthesizes the data, and makes it available to humans and computers within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.

Submitted by elamb on

The Epi Evident application was designed for clear and comprehensive visualization for monitoring, comparing, and forecasting notifiable diseases simultaneously across chosen countries. Epi Evident addresses the taxing analytical evaluation of how diseases behave differently across countries. This application provides a user-friendly platform with easily interpretable analytics which allows analysts to conduct biosurveillance with minimal user tasks. Developed at the Pacific Northwest National Laboratory (PNNL), Epi Evident utilizes time-series disease case count data from the Biosurveillance Ecosystem (BSVE) application Epi Archive. This diverse data source is filtered through the flexible Epi Evident workflow for forecast model building designed to integrate any entering combination of country and disease. The application aims to quickly inform analysts of anomalies in disease & location specific behavior and aid in evidence based decision making to help control or prevent disease outbreaks.

Objective:

Epi Evident is a web based application built to empower public health analysts by providing a platform that improves monitoring, comparing, and forecasting case counts and period prevalence of notifiable diseases for any scale jurisdiction at regional, country, or global-level. This proof of concept application development addresses improving visualization, access, situational awareness, and prediction of disease behavior.

Submitted by elamb on
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