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APL novel method accurately predicts disease outbreaks
Date:3/22/2013

ays Lewis. "Ideally, decision-makers want to learn about a disease outbreak before it spreads and PRISM will provide them with highly accurate information to protect our military forces deployed in at-risk areas."

While PRISM's pilot predictive analysis was the study of dengue fever in Peru, APL scientists have extended the method to predicting dengue in the Philippines and are working to fine-tune the model and expand its capabilities to include other infectious diseases. "Dengue was the starting point for our work because the data were readily available, but eventually we want to apply the methodology to other diseases, such as malaria and influenza," says Lewis.

Once fully operational, PRISM will aid in the earliest possible detection of illness within a community by complementing electronic disease surveillance systems such as the APL-developed Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) and the Suite of Automated Global Electronic bioSurveillance (SAGES).

ESSENCE collects, processes and analyzes non-traditional data sources to identify disease activity in a community, allowing data to be queried, analyzed and visualized by the end user. SAGES is a collection of freely available software, including open source versions of ESSENCE, for electronic surveillance in countries with little funding for public health initiatives. SAGES can be used alone or with existing surveillance applications providing governments with the flexibility to develop inexpensive and customized systems to collect and track information about the spread of diseases.


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Contact: Gina Ellrich
Gina.Ellrich@jhuapl.edu
240-228-7796
Johns Hopkins University
Source:Eurekalert

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