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Using social media in Kenya to quantify road safety: an analysis of novel data

BACKGROUND: Road traffic injuries are a large and growing cause of morbidity and mortality in low- and middle-income countries, especially in Africa. Systematic data collection for traffic incidents in Kenya is lacking and in many low- and middle-income countries available data sources are disparate...

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Autores principales: Lee, J. Austin, Armes, Lyndsey, Wachira, Benjamin W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238258/
https://www.ncbi.nlm.nih.gov/pubmed/35764949
http://dx.doi.org/10.1186/s12245-022-00432-6
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author Lee, J. Austin
Armes, Lyndsey
Wachira, Benjamin W.
author_facet Lee, J. Austin
Armes, Lyndsey
Wachira, Benjamin W.
author_sort Lee, J. Austin
collection PubMed
description BACKGROUND: Road traffic injuries are a large and growing cause of morbidity and mortality in low- and middle-income countries, especially in Africa. Systematic data collection for traffic incidents in Kenya is lacking and in many low- and middle-income countries available data sources are disparate or missing altogether. Many Kenyans use social media platforms, including Twitter; many road traffic incidents are publicly reported on the microblog platform. This study is a prospective cohort analysis of all tweets related to road traffic incidents in Kenya over a 24-month period (February 2019 to January 2021). RESULTS: A substantial number of unique road incidents (3882) from across Kenya were recorded during the 24-month study period. The details available for each incident are widely variable, as reported and posted on Twitter. Particular times of day and days of the week had a higher incidence of reported road traffic incidents. A total of 2043 injuries and 1503 fatalities were recorded. CONCLUSIONS: Twitter and other digital social media platforms can provide a novel source for road traffic incident and injury data in a low- and middle-income country. The data collected allows for the potential identification of local and national trends and provides opportunities to advocate for improved roadways and health systems for the emergent care from road traffic incidents and associated traumatic injuries.
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spelling pubmed-92382582022-06-29 Using social media in Kenya to quantify road safety: an analysis of novel data Lee, J. Austin Armes, Lyndsey Wachira, Benjamin W. Int J Emerg Med Original Research BACKGROUND: Road traffic injuries are a large and growing cause of morbidity and mortality in low- and middle-income countries, especially in Africa. Systematic data collection for traffic incidents in Kenya is lacking and in many low- and middle-income countries available data sources are disparate or missing altogether. Many Kenyans use social media platforms, including Twitter; many road traffic incidents are publicly reported on the microblog platform. This study is a prospective cohort analysis of all tweets related to road traffic incidents in Kenya over a 24-month period (February 2019 to January 2021). RESULTS: A substantial number of unique road incidents (3882) from across Kenya were recorded during the 24-month study period. The details available for each incident are widely variable, as reported and posted on Twitter. Particular times of day and days of the week had a higher incidence of reported road traffic incidents. A total of 2043 injuries and 1503 fatalities were recorded. CONCLUSIONS: Twitter and other digital social media platforms can provide a novel source for road traffic incident and injury data in a low- and middle-income country. The data collected allows for the potential identification of local and national trends and provides opportunities to advocate for improved roadways and health systems for the emergent care from road traffic incidents and associated traumatic injuries. Springer Berlin Heidelberg 2022-06-28 /pmc/articles/PMC9238258/ /pubmed/35764949 http://dx.doi.org/10.1186/s12245-022-00432-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Original Research
Lee, J. Austin
Armes, Lyndsey
Wachira, Benjamin W.
Using social media in Kenya to quantify road safety: an analysis of novel data
title Using social media in Kenya to quantify road safety: an analysis of novel data
title_full Using social media in Kenya to quantify road safety: an analysis of novel data
title_fullStr Using social media in Kenya to quantify road safety: an analysis of novel data
title_full_unstemmed Using social media in Kenya to quantify road safety: an analysis of novel data
title_short Using social media in Kenya to quantify road safety: an analysis of novel data
title_sort using social media in kenya to quantify road safety: an analysis of novel data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238258/
https://www.ncbi.nlm.nih.gov/pubmed/35764949
http://dx.doi.org/10.1186/s12245-022-00432-6
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