ArticleEpidemiology and infection2014
Weather and livestock risk factors for Escherichia coli O157 human infection in Alberta, Canada.
Article in Epidemiology and infection, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Epidemiology of Shiga Toxin-ProducingToxins · 2019Article
- A geostatistical investigation of agricultural and infrastructural risk factors associated with primary verotoxigenic E. coli (VTEC) infection in the Republic of Ireland, 2008-2013.Epidemiology and infection · 2017Article
- Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigated the extent to which proximity to cattle and weather events in Alberta predispose human populations to E. coli O157 disease. Cases of human E. coli O157 infection in Alberta between 2004 and 2011 were obtained from the province's Communicable Disease Reporting System and Discharge Abstract Database. Regression models based on spatial area incorporated human infection data with livestock and weather covariates. A variety of regression models were applied (i.e. least squares, spatial lag/error, Poisson, negative binomial) to test the most appropriate approach. Ratios for the total number of calves, bulls and beef cows to human population were highlighted as significant cattle density variables in all final best-fitting models. Weather variables were not significant in final regression models averaged over the full study period. Our results provide evidence of a significant association between measures of cattle density and human E. coli O157 disease in Alberta.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.