Evidence map›Paper›PMID 27488877›Full record

ArticleEpidemiology and infection2016

Factors associated with increasing campylobacteriosis incidence in Michigan, 2004-2013.

W Cha, T Henderson, J Collins, S D Manning

Open access · bronzeAbstract read
In one paragraph

Article in Epidemiology and infection, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.0field-weighted citation impact, top 10% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

W ChaDepartment of Microbiology and Molecular Genetics,Michigan State University,East Lansing,MI,USA.
T HendersonMichigan Department of Health and Human Services,Lansing,MI,USA.
J CollinsMichigan Department of Health and Human Services,Lansing,MI,USA.
S D ManningDepartment of Microbiology and Molecular Genetics,Michigan State University,East Lansing,MI,USA.
Michigan Department of Health and Human Services · USMichigan State University · US

Funding

The Impact of Microbiome Composition, Diversity, and Function on Enteric DiseaseU19AI090872 · NIAID · MICHIGAN STATE UNIVERSITY · PI MANSFIELD, LINDA S. · 2010 to 2014
$7.1M
NIAID NIH HHS U19 AI090872
6 · The paper itself

Abstract

This study was conducted to examine the incidence trend of campylobacteriosis in Michigan over a 10-year period and to investigate risk factors and clinical outcomes associated with infection. Campylobacter case data from 2004 to 2013 was obtained from the Michigan Disease Surveillance System. We conducted statistical and spatial analyses to examine trends and identify factors linked to campylobacteriosis as well as ecological associations using animal density data from the National Agricultural Statistics Service. An increasing trend of Campylobacter incidence and hospitalization was observed, which was linked to specific age groups and rural residence. Cases reporting ruminant contact and well water as the primary drinking source had a higher risk of campylobacteriosis, while higher cattle density was associated with an increased risk at the county level. Additional studies are needed to identify age-specific risk factors and examine prevalence and transmission dynamics in ruminants and the environment to aid in the development of more effective preventive strategies.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsCampylobacterCampylobacter InfectionsChildChild, PreschoolFemaleHumansIncidenceInfantInfant, NewbornMaleMichiganCampylobacterepidemiologyfoodborne infectionssurveillance

Identifiers

PMID27488877
PMCPMC9150283
OpenAlexW2489185419

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.