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Seasonality and the effects of weather on Campylobacter infections
BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter we...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417031/ https://www.ncbi.nlm.nih.gov/pubmed/30866826 http://dx.doi.org/10.1186/s12879-019-3840-7 |
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author | Djennad, Abdelmajid Lo Iacono, Giovanni Sarran, Christophe Lane, Christopher Elson, Richard Höser, Christoph Lake, Iain R. Colón-González, Felipe J. Kovats, Sari Semenza, Jan C. Bailey, Trevor C. Kessel, Anthony Fleming, Lora E. Nichols, Gordon L. |
author_facet | Djennad, Abdelmajid Lo Iacono, Giovanni Sarran, Christophe Lane, Christopher Elson, Richard Höser, Christoph Lake, Iain R. Colón-González, Felipe J. Kovats, Sari Semenza, Jan C. Bailey, Trevor C. Kessel, Anthony Fleming, Lora E. Nichols, Gordon L. |
author_sort | Djennad, Abdelmajid |
collection | PubMed |
description | BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. RESULTS: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. CONCLUSIONS: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3840-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6417031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64170312019-03-25 Seasonality and the effects of weather on Campylobacter infections Djennad, Abdelmajid Lo Iacono, Giovanni Sarran, Christophe Lane, Christopher Elson, Richard Höser, Christoph Lake, Iain R. Colón-González, Felipe J. Kovats, Sari Semenza, Jan C. Bailey, Trevor C. Kessel, Anthony Fleming, Lora E. Nichols, Gordon L. BMC Infect Dis Research Article BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. RESULTS: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. CONCLUSIONS: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3840-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-13 /pmc/articles/PMC6417031/ /pubmed/30866826 http://dx.doi.org/10.1186/s12879-019-3840-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Djennad, Abdelmajid Lo Iacono, Giovanni Sarran, Christophe Lane, Christopher Elson, Richard Höser, Christoph Lake, Iain R. Colón-González, Felipe J. Kovats, Sari Semenza, Jan C. Bailey, Trevor C. Kessel, Anthony Fleming, Lora E. Nichols, Gordon L. Seasonality and the effects of weather on Campylobacter infections |
title | Seasonality and the effects of weather on Campylobacter infections |
title_full | Seasonality and the effects of weather on Campylobacter infections |
title_fullStr | Seasonality and the effects of weather on Campylobacter infections |
title_full_unstemmed | Seasonality and the effects of weather on Campylobacter infections |
title_short | Seasonality and the effects of weather on Campylobacter infections |
title_sort | seasonality and the effects of weather on campylobacter infections |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417031/ https://www.ncbi.nlm.nih.gov/pubmed/30866826 http://dx.doi.org/10.1186/s12879-019-3840-7 |
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