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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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
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spelling ftdoajarticles:oai:doaj.org/article:d7830f5ad0ef41edabc92b92dd88eae3 2024-01-14T10:05:33+01:00 Spatio-temporal evaluation of social media as a tool for livestock disease surveillance Samuel Munaf Kevin Swingler Franz Brülisauer Anthony O'Hare George Gunn Aaron Reeves 2023-12-01T00:00:00Z https://doi.org/10.1016/j.onehlt.2023.100657 https://doaj.org/article/d7830f5ad0ef41edabc92b92dd88eae3 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S2352771423001775 https://doaj.org/toc/2352-7714 2352-7714 doi:10.1016/j.onehlt.2023.100657 https://doaj.org/article/d7830f5ad0ef41edabc92b92dd88eae3 One Health, Vol 17, Iss , Pp 100657- (2023) Veterinary epidemiology Disease surveillance Infodemiology Infoveillance Time series Social media Medicine (General) R5-920 article 2023 ftdoajarticles https://doi.org/10.1016/j.onehlt.2023.100657 2023-12-17T01:44:53Z 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. Article in Journal/Newspaper Avian flu Directory of Open Access Journals: DOAJ Articles One Health 17 100657
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Veterinary epidemiology
Disease surveillance
Infodemiology
Infoveillance
Time series
Social media
Medicine (General)
R5-920
spellingShingle Veterinary epidemiology
Disease surveillance
Infodemiology
Infoveillance
Time series
Social media
Medicine (General)
R5-920
Samuel Munaf
Kevin Swingler
Franz Brülisauer
Anthony O'Hare
George Gunn
Aaron Reeves
Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
topic_facet Veterinary epidemiology
Disease surveillance
Infodemiology
Infoveillance
Time series
Social media
Medicine (General)
R5-920
description 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.
format Article in Journal/Newspaper
author Samuel Munaf
Kevin Swingler
Franz Brülisauer
Anthony O'Hare
George Gunn
Aaron Reeves
author_facet Samuel Munaf
Kevin Swingler
Franz Brülisauer
Anthony O'Hare
George Gunn
Aaron Reeves
author_sort Samuel Munaf
title Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
title_short Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
title_full Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
title_fullStr Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
title_full_unstemmed Spatio-temporal evaluation of social media as a tool for livestock disease surveillance
title_sort spatio-temporal evaluation of social media as a tool for livestock disease surveillance
publisher Elsevier
publishDate 2023
url https://doi.org/10.1016/j.onehlt.2023.100657
https://doaj.org/article/d7830f5ad0ef41edabc92b92dd88eae3
genre Avian flu
genre_facet Avian flu
op_source One Health, Vol 17, Iss , Pp 100657- (2023)
op_relation http://www.sciencedirect.com/science/article/pii/S2352771423001775
https://doaj.org/toc/2352-7714
2352-7714
doi:10.1016/j.onehlt.2023.100657
https://doaj.org/article/d7830f5ad0ef41edabc92b92dd88eae3
op_doi https://doi.org/10.1016/j.onehlt.2023.100657
container_title One Health
container_volume 17
container_start_page 100657
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