Cargando…
Spatio-temporal models to determine association between Campylobacter cases and environment
BACKGROUND: Campylobacteriosis is a major cause of gastroenteritis in the UK, and although 70% of cases are associated with food sources, the remainder are probably associated with wider environmental exposure. METHODS: In order to investigate wider environmental transmission, we conducted a spatio-...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837245/ https://www.ncbi.nlm.nih.gov/pubmed/29069406 http://dx.doi.org/10.1093/ije/dyx217 |
_version_ | 1783304083867697152 |
---|---|
author | Sanderson, Roy A Maas, James A Blain, Alasdair P Gorton, Russell Ward, Jessica O’Brien, Sarah J Hunter, Paul R Rushton, Stephen P |
author_facet | Sanderson, Roy A Maas, James A Blain, Alasdair P Gorton, Russell Ward, Jessica O’Brien, Sarah J Hunter, Paul R Rushton, Stephen P |
author_sort | Sanderson, Roy A |
collection | PubMed |
description | BACKGROUND: Campylobacteriosis is a major cause of gastroenteritis in the UK, and although 70% of cases are associated with food sources, the remainder are probably associated with wider environmental exposure. METHODS: In order to investigate wider environmental transmission, we conducted a spatio-temporal analysis of the association of human cases of Campylobacter in the Tyne catchment with weather, climate, hydrology and land use. A hydrological model was used to predict surface-water flow in the Tyne catchment over 5 years. We analysed associations between population-adjusted Campylobacter case rate and environmental factors hypothesized to be important in disease using a two-stage modelling framework. First, we investigated associations between temporal variation in case rate in relation to surface-water flow, temperature, evapotranspiration and rainfall, using linear mixed-effects models. Second, we used the random effects for the first model to quantify how spatial variation in static landscape features of soil and land use impacted on the likely differences between subcatchment associations of case rate with the temporal variables. RESULTS: Population-adjusted Campylobacter case rates were associated with periods of high predicted surface-water flow, and during above average temperatures. Subcatchments with cattle on stagnogley soils, and to a lesser extent sheep plus cattle grazing, had higher Campylobacter case rates. CONCLUSIONS: Areas of stagnogley soils with mixed livestock grazing may be more vulnerable to both Campylobacter spread and exposure during periods of high rainfall, with resultant increased risk of human cases of the disease. |
format | Online Article Text |
id | pubmed-5837245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58372452018-03-09 Spatio-temporal models to determine association between Campylobacter cases and environment Sanderson, Roy A Maas, James A Blain, Alasdair P Gorton, Russell Ward, Jessica O’Brien, Sarah J Hunter, Paul R Rushton, Stephen P Int J Epidemiol Infectious Diseases BACKGROUND: Campylobacteriosis is a major cause of gastroenteritis in the UK, and although 70% of cases are associated with food sources, the remainder are probably associated with wider environmental exposure. METHODS: In order to investigate wider environmental transmission, we conducted a spatio-temporal analysis of the association of human cases of Campylobacter in the Tyne catchment with weather, climate, hydrology and land use. A hydrological model was used to predict surface-water flow in the Tyne catchment over 5 years. We analysed associations between population-adjusted Campylobacter case rate and environmental factors hypothesized to be important in disease using a two-stage modelling framework. First, we investigated associations between temporal variation in case rate in relation to surface-water flow, temperature, evapotranspiration and rainfall, using linear mixed-effects models. Second, we used the random effects for the first model to quantify how spatial variation in static landscape features of soil and land use impacted on the likely differences between subcatchment associations of case rate with the temporal variables. RESULTS: Population-adjusted Campylobacter case rates were associated with periods of high predicted surface-water flow, and during above average temperatures. Subcatchments with cattle on stagnogley soils, and to a lesser extent sheep plus cattle grazing, had higher Campylobacter case rates. CONCLUSIONS: Areas of stagnogley soils with mixed livestock grazing may be more vulnerable to both Campylobacter spread and exposure during periods of high rainfall, with resultant increased risk of human cases of the disease. Oxford University Press 2018-02 2017-10-24 /pmc/articles/PMC5837245/ /pubmed/29069406 http://dx.doi.org/10.1093/ije/dyx217 Text en © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Infectious Diseases Sanderson, Roy A Maas, James A Blain, Alasdair P Gorton, Russell Ward, Jessica O’Brien, Sarah J Hunter, Paul R Rushton, Stephen P Spatio-temporal models to determine association between Campylobacter cases and environment |
title | Spatio-temporal models to determine association between Campylobacter cases and environment |
title_full | Spatio-temporal models to determine association between Campylobacter cases and environment |
title_fullStr | Spatio-temporal models to determine association between Campylobacter cases and environment |
title_full_unstemmed | Spatio-temporal models to determine association between Campylobacter cases and environment |
title_short | Spatio-temporal models to determine association between Campylobacter cases and environment |
title_sort | spatio-temporal models to determine association between campylobacter cases and environment |
topic | Infectious Diseases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837245/ https://www.ncbi.nlm.nih.gov/pubmed/29069406 http://dx.doi.org/10.1093/ije/dyx217 |
work_keys_str_mv | AT sandersonroya spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT maasjamesa spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT blainalasdairp spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT gortonrussell spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT wardjessica spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT obriensarahj spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT hunterpaulr spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment AT rushtonstephenp spatiotemporalmodelstodetermineassociationbetweencampylobactercasesandenvironment |