Spatio-temporal models to determine association between Campylobacter cases and environment.

Autor:	Sanderson RA; Biological, Clinical and Environmental Systems Modelling Group, Newcastle University, Newcastle upon Tyne, UK., Maas JA; Norwich Medical School, University of East Anglia, Norwich, UK., Blain AP; Biological, Clinical and Environmental Systems Modelling Group, Newcastle University, Newcastle upon Tyne, UK., Gorton R; Field Epidemiology Services North East, Public Health England, Newcastle upon Tyne, UK., Ward J; Biological, Clinical and Environmental Systems Modelling Group, Newcastle University, Newcastle upon Tyne, UK., O'Brien SJ; Institute of Infection and Global Health, University of Liverpool, Liverpool, UK., Hunter PR; Norwich Medical School, University of East Anglia, Norwich, UK., Rushton SP; Biological, Clinical and Environmental Systems Modelling Group, Newcastle University, Newcastle upon Tyne, UK.
Jazyk:	angličtina
Zdroj:	International journal of epidemiology [Int J Epidemiol] 2018 Feb 01; Vol. 47 (1), pp. 202-216.
DOI:	10.1093/ije/dyx217
Abstrakt:	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. (© The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Databáze:	MEDLINE
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