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-...

Descripción completa

Detalles Bibliográficos
Autores principales: Sanderson, Roy A, Maas, James A, Blain, Alasdair P, Gorton, Russell, Ward, Jessica, O’Brien, Sarah J, Hunter, Paul R, Rushton, Stephen P
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