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Elaboration of a new framework for fine-grained epidemiological annotation
Sarah Valentin1,2,3,4, Elena Arsevska2,5, Aline Vilain6
1UMR TETIS (Land, Environment, Remote Sensing and Spatial Information), University of Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France.
Scientific Data
|October 26, 2022
Summary
Event-based surveillance (EBS) uses online news for early disease detection. This study presents a framework to annotate animal disease news, improving epidemic intelligence (EI) systems.
Area of Science:
- Veterinary Epidemiology
- Public Health Surveillance
- Computational Biology
Background:
- Event-based surveillance (EBS) leverages diverse data, including online news, for early disease detection.
- Unstructured data from news articles challenges epidemic intelligence (EI) resource capacity.
- Existing EBS systems like GPHIN and HealthMap can benefit from annotated data.
Purpose of the Study:
- To describe a framework for annotating epidemiological information in animal disease news articles.
- To provide generic annotation guidelines applicable to various infectious diseases and transmission routes.
- To enhance the accuracy and efficiency of EBS systems through structured data annotation.
Main Methods:
- Developed a framework for successive sentence annotation of news articles.
- Created generic annotation guidelines for animal and zoonotic diseases.
- Annotators evaluated sentences within the context of the article's publication date.
Main Results:
- A structured framework for annotating animal disease news articles was established.
- Guidelines were created to be broadly applicable across different pathogens and transmission methods.
- The annotation process supports the improvement of automated EBS systems.
Conclusions:
- The proposed framework and guidelines facilitate the annotation of unstructured news data for EBS.
- This approach can significantly improve the capacity of epidemic intelligence systems.
- Standardized annotation enhances the utility of online news for global animal and zoonotic disease surveillance.
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