Evaluation of local media surveillance for improved disease recognition and monitoring in global hotspot regions

Schwind, Jessica S., Wolking, David J., Brownstein, John S., PREDICT Consortium, , Mazet, Jonna A.K., and Smith, WA (2014) Evaluation of local media surveillance for improved disease recognition and monitoring in global hotspot regions. PLoS ONE, 9 (10). e110236.

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Abstract

Digital disease detection tools are technologically sophisticated, but dependent on digital information, which for many areas suffering from high disease burdens is simply not an option. In areas where news is often reported in local media with no digital counterpart, integration of local news information with digital surveillance systems, such as HealthMap (Boston Children’s Hospital), is critical. Little research has been published in regards to the specific contribution of local health-related articles to digital surveillance systems. In response, the USAID PREDICT project implemented a local media surveillance (LMS) pilot study in partner countries to monitor disease events reported in print media. This research assessed the potential of LMS to enhance digital surveillance reach in five low- and middle-income countries. Over 16 weeks, select surveillance system attributes of LMS, such as simplicity, flexibility, acceptability, timeliness, and stability were evaluated to identify strengths and weaknesses in the surveillance method. Findings revealed that LMS filled gaps in digital surveillance network coverage by contributing valuable localized information on disease events to the global HealthMap database. A total of 87 health events were reported through the LMS pilot in the 16-week monitoring period, including 71 unique reports not found by the HealthMap digital detection tool. Furthermore, HealthMap identified an additional 236 health events outside of LMS. It was also observed that belief in the importance of the project and proper source selection from the participants was crucial to the success of this method. The timely identification of disease outbreaks near points of emergence and the recognition of risk factors associated with disease occurrence continue to be important components of any comprehensive surveillance system for monitoring disease activity across populations. The LMS method, with its minimal resource commitment, could be one tool used to address the information gaps seen in global 'hot spot' regions.

Item ID: 65355
Item Type: Article (Research - C1)
ISSN: 1932-6203
Copyright Information: © 2014 Schwind et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Additional Information:

Paul Horwood is a member of the PREDICT Consortium.

Funders: United States Agency for International Development (USAID)
Projects and Grants: USAID PREDICT project
Date Deposited: 07 Jan 2021 22:48
FoR Codes: 07 AGRICULTURAL AND VETERINARY SCIENCES > 0707 Veterinary Sciences > 070712 Veterinary Virology @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences @ 100%
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