Identification

Author

Madoff L, Brownstein J

Title

ProMED and HealthMap: collaboration to improve emerging disease surveillance

Year

2010

Publication type

Article

Journal

International Journal of Infectious Diseases

Modified

2016-07-25 15:51:04.605760+00:00

Details

Volume

14

Number

1

Access

Language

English

URL http://www.sciencedirect.com/science/article/pii/S1201971210019387
DOI

10.1016/j.ijid.2010.02.1898

Accessed

2016-06-06

Extended information

Abstract

Unofficial or informal sources (also called “rumors” or “unstructured data”) of emerging disease outbreaks such as media reports and firsthand accounts have become an important mechanism for detecting these outbreaks. These sources are disseminated by a variety of human-based and automated biosurveillance networks that are now routinely monitored by public health authorities at all levels. The 2005 revisions to the International Health Regulations recognize that these sources often appear in advance of official notification of disease threats and are important in allowing the timely response to emerging diseases. Early media reports of respiratory illness in Mexico were among the first signs of the H1N1 pandemic and unofficial information sources are a critical mechanism for following the pandemic. ProMED-mail (the Program for Monitoring Emerging Diseases of the International Society for Infectious Diseases) has used largely humanbased reporting to detect and report outbreaks of emerging infectious diseases since 1994.

HealthMap, based at Boston Children's Hospital and Harvard Medical School, uses automated mining of open sources in multiple languages to detect emerging disease outbreaks in and place them on a world map. ProMED and HealthMap have begun to collaborate to exploit the strengths of human-based and automated detection and reporting systems. Studies to evaluate the use of informal sources and to improve the detection of emerging disease outbreaks are in progress and have found differences in timeliness of reporting depending on disease type and geographic location. These differences are being used to target the development of new regional and disease specific reporting networks as well as the deployment of new mobile tools for capturing and disseminating news of emerging threats.