Spatio-temporal evaluation of social media as a tool for livestock disease surveillance

Recent outbreaks of Avian Influenza across Europe have highlighted the potential for syndromic surveillance systems that consider other modes of data, namely social media. This study investigates the feasibility of using social media, primarily Twitter, to monitor illness outbreaks such as avian flu...

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Bibliographic Details
Published in:One Health
Main Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O'Hare, George Gunn, Aaron Reeves
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2023
Subjects:
Online Access:https://doi.org/10.1016/j.onehlt.2023.100657
https://doaj.org/article/d7830f5ad0ef41edabc92b92dd88eae3
Description
Summary:Recent outbreaks of Avian Influenza across Europe have highlighted the potential for syndromic surveillance systems that consider other modes of data, namely social media. This study investigates the feasibility of using social media, primarily Twitter, to monitor illness outbreaks such as avian flu. Using temporal, geographical, and correlation analyses, we investigated the association between avian influenza tweets and officially verified cases in the United Kingdom in 2021 and 2022. Pearson correlation coefficient, bivariate Moran's I analysis and time series analysis, were among the methodologies used. The findings show a weak, statistically insignificant relationship between the number of tweets and confirmed cases in a temporal context, implying that relying simply on social media data for surveillance may be insufficient. The spatial analysis provided insights into the overlaps between confirmed cases and tweet locations, shedding light on regionally targeted interventions during outbreaks. Although social media can be useful for understanding public sentiment and concerns during outbreaks, it must be combined with traditional surveillance methods and official data sources for a more accurate and comprehensive approach. Improved data mining techniques and real-time analysis can improve outbreak detection and response even further. This study underscores the need of having a strong surveillance system in place to properly monitor and manage disease outbreaks and protect public health.