Evidence map›Paper›PMID 35987780›Full record

ArticleAntimicrobial resistance and infection control2022

Estimating the population-level prevalence of antimicrobial-resistant enteric bacteria from latrine samples.

Sylvia Omulo, Maina Mugoh, Joshua Obiya, Moshe Alando, Douglas R Call

Open access · goldAbstract read
In one paragraph

Article in Antimicrobial resistance and infection control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 52% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
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

5 authors at 3 institutions in 3 countries.

Sylvia OmuloPaul G. Allen School for Global Health, Washington State University, Pullman, WA, USA. sylvia.omulo@wsu.edu.ORCID 0000-0002-1214-1092
Maina MugohWashington State University Global Health-Kenya, Nairobi, Kenya.
Joshua ObiyaKenya Medical Research Institute, Kisumu, Kenya.
Moshe AlandoKenya Medical Research Institute, Nairobi, Kenya.
Douglas R CallPaul G. Allen School for Global Health, Washington State University, Pullman, WA, USA.
Kenya Medical Research Institute · KEWashington State Department of Health · USWashington State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLogistical and economic barriers hamper community-level surveillance for antimicrobial-resistant bacteria in low-income countries. Latrines are commonly used in these settings and offer a low-cost source of surveillance samples. It is unclear, however, whether antimicrobial resistance prevalence estimates from latrine samples reflect estimates generated from randomly sampled people.

methodsWe compared the prevalence of antimicrobial-resistant enteric bacteria from stool samples of people residing in randomly selected households within Kibera-an informal urban settlement in Kenya-to estimates from latrine samples within the same community. Fecal samples were collected between November 2015 and Jan 2016. Presumptive Escherichia coli isolates were collected from each household stool sample (n = 24) and each latrine sample (n = 48), resulting in 8935 and 8210 isolates, respectively. Isolates were tested for resistance to nine antibiotics using the replica-plating technique. Correlation- and Kolmogorov-Smirnov (K-S) tests were used to compare results.

resultsOverall, the prevalence values obtained from latrine samples closely reflected those from stool samples, particularly for low-prevalence (< 15%) resistance phenotypes. Similarly, the distribution of resistance phenotypes was similar between latrine and household samples (r > 0.6; K-S p-values > 0.05).

conclusionsAlthough latrine samples did not perfectly estimate household antimicrobial resistance prevalence, they were highly correlated and thus could be employed as low-cost samples to monitor trends in antimicrobial resistance, detect the emergence of new resistance phenotypes and assess the impact of community interventions.

Indexed as

Anti-Infective AgentsGastrointestinal MicrobiomeEscherichia coliHumansPrevalenceToilet FacilitiesAnti-Infective AgentsAntimicrobial resistanceLatrinesPrevalence estimatesSurveillance

Identifiers

PMID35987780
PMCPMC9392229
OpenAlexW4293103300

What OpenQuestion holds

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Registered trials

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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.