Evidence map›Paper›PMID 37992129›Full record

ArticlePLoS computational biology2023

Network analysis of patterns and relevance of enteric pathogen co-infections among infants in a diarrhea-endemic setting.

E Ross Colgate, Connor Klopfer, Dorothy M Dickson, Benjamin Lee, Matthew J Wargo, Ashraful Alam, Beth D Kirkpatrick, Laurent Hébert-Dufresne

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. 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
1.1field-weighted citation impact, top 24% 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, 7 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

8 authors at 2 institutions in 2 countries.

E Ross ColgateTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.
Connor KlopferVermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America.
Dorothy M DicksonTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.ORCID 0000-0003-1705-7575
Benjamin LeeTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.
Matthew J WargoTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.
Ashraful AlamInternational Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.ORCID 0000-0003-1389-8510
Beth D KirkpatrickTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.
Laurent Hébert-DufresneTranslational Global Infectious Disease Research Center, University of Vermont, Burlington, Vermont, United States of America.ORCID 0000-0002-0008-3673
University of Vermont · USInternational Centre for Diarrhoeal Disease Research · BD

Funding

Using Dengue Controlled Human Infection Model to Identify Adaptive Immune Correlates of ProtectionP20GM125498 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Kristen Pierce · 2018 to 2026
$24.9M
NIGMS NIH HHS P20 GM125498
6 · The paper itself

Abstract

Despite significant progress in recent decades toward ameliorating the excess burden of diarrheal disease globally, childhood diarrhea remains a leading cause of morbidity and mortality in low-and-middle-income countries (LMICs). Recent large-scale studies of diarrhea etiology in these populations have revealed widespread co-infection with multiple enteric pathogens, in both acute and asymptomatic stool specimens. We applied methods from network science and ecology to better understand the underlying structure of enteric co-infection among infants in two large longitudinal birth cohorts in Bangladesh. We used a configuration model to establish distributions of expected random co-occurrence, based on individual pathogen prevalence alone, for every pathogen pair among 30 enteropathogens detected by qRT-PCR in both diarrheal and asymptomatic stool specimens. We found two pairs, Enterotoxigenic E. coli (ETEC) with Enteropathogenic E. coli (EPEC), and ETEC with Campylobacter spp., co-infected significantly more than expected at random (both pairs co-occurring almost 4 standard deviations above what one could expect due to chance alone). Furthermore, we found a general pattern that bacteria-bacteria pairs appear together more frequently than expected at random, while virus-bacteria pairs tend to appear less frequently than expected based on model predictions. Finally, infants co-infected with leading bacteria-bacteria pairs had more days of diarrhea in the first year of life compared to infants without co-infection (p-value <0.0001). Our methods and results help us understand the structure of enteric co-infection which can guide further work to identify and eliminate common sources of infection or determine biologic mechanisms that promote co-infection.

Indexed as

CoinfectionEscherichia coli InfectionsBacteriaChildDiarrheaEscherichia coliFecesHumansInfant

Identifiers

PMID37992129
PMCPMC10664872
OpenAlexW4388912757

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.