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Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022
Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535521/ https://www.ncbi.nlm.nih.gov/pubmed/37764914 http://dx.doi.org/10.3390/pathogens12091106 |
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author | Thomas, Bryce A. Saylor, Ryan K. Taylor, Zachary P. Rhodes, DeLacy V. L. |
author_facet | Thomas, Bryce A. Saylor, Ryan K. Taylor, Zachary P. Rhodes, DeLacy V. L. |
author_sort | Thomas, Bryce A. |
collection | PubMed |
description | Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environmental conditions. The purpose of this study was to analyze strangles case numbers across the United States of America from 2018 to 2022 to investigate potential temporal or weather patterns associated with outbreaks. Diagnosed case records were obtained from the Equine Disease Communication Center, university databases, government agencies, or veterinary diagnostic labs, and geographic information systems (GISs) were used to map cases and to acquire relevant meteorological data from outbreak areas. These data were analyzed using logistic regression to explore trends that occur between outbreaks and changes in temperature and precipitation. Initial review of weather data suggested monthly changes in strangles case numbers corresponded with changing seasons. Logistic regression indicated that changes in monthly average temperature and minimum temperature were significantly associated with increased or decreased odds of strangles outbreaks, respectively. Future analyses should focus on weather data isolated within a smaller region or state to better resolve trends in strangles outbreaks throughout the continental USA. |
format | Online Article Text |
id | pubmed-10535521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105355212023-09-29 Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 Thomas, Bryce A. Saylor, Ryan K. Taylor, Zachary P. Rhodes, DeLacy V. L. Pathogens Article Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environmental conditions. The purpose of this study was to analyze strangles case numbers across the United States of America from 2018 to 2022 to investigate potential temporal or weather patterns associated with outbreaks. Diagnosed case records were obtained from the Equine Disease Communication Center, university databases, government agencies, or veterinary diagnostic labs, and geographic information systems (GISs) were used to map cases and to acquire relevant meteorological data from outbreak areas. These data were analyzed using logistic regression to explore trends that occur between outbreaks and changes in temperature and precipitation. Initial review of weather data suggested monthly changes in strangles case numbers corresponded with changing seasons. Logistic regression indicated that changes in monthly average temperature and minimum temperature were significantly associated with increased or decreased odds of strangles outbreaks, respectively. Future analyses should focus on weather data isolated within a smaller region or state to better resolve trends in strangles outbreaks throughout the continental USA. MDPI 2023-08-29 /pmc/articles/PMC10535521/ /pubmed/37764914 http://dx.doi.org/10.3390/pathogens12091106 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Thomas, Bryce A. Saylor, Ryan K. Taylor, Zachary P. Rhodes, DeLacy V. L. Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title | Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title_full | Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title_fullStr | Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title_full_unstemmed | Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title_short | Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022 |
title_sort | evaluating trends in strangles outbreaks using temperature and precipitation data in the united states of america for 2018–2022 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535521/ https://www.ncbi.nlm.nih.gov/pubmed/37764914 http://dx.doi.org/10.3390/pathogens12091106 |
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