Evidence map›Paper›PMID 33482919›Full record

ArticleAntimicrobial resistance and infection control2021

Carriage of antimicrobial-resistant bacteria in a high-density informal settlement in Kenya is associated with environmental risk-factors.

Sylvia Omulo, Eric T Lofgren, Svetlana Lockwood, Samuel M Thumbi, Godfrey Bigogo, Alice Ouma, Jennifer R Verani, Bonventure Juma, M Kariuki Njenga, Samuel Kariuki and 3 more

Open access · goldAbstract read
In one paragraph

Article in Antimicrobial resistance and infection control, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 35 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

13 authors at 4 institutions in 3 countries.

Sylvia OmuloPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA. sylvia.omulo@wsu.edu.ORCID 0000-0002-1214-1092
Eric T LofgrenPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Svetlana LockwoodPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Samuel M ThumbiPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Godfrey BigogoCenter for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya.
Alice OumaCenter for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya.
Jennifer R VeraniCenters for Disease Control and Prevention, Nairobi, Kenya.
Bonventure JumaCenters for Disease Control and Prevention, Nairobi, Kenya.
M Kariuki NjengaPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Samuel KariukiCenters for Disease Control and Prevention, Nairobi, Kenya.
Terry F McElwainPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Guy H PalmerPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Douglas R CallPaul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA.
Washington State Department of Health · USCenters for Disease Control and Prevention · KEWashington State University · USKenya Medical Research Institute · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe relationship between antibiotic use and antimicrobial resistance varies with cultural, socio-economic, and environmental factors. We examined these relationships in Kibera, an informal settlement in Nairobi-Kenya, characterized by high population density, high burden of respiratory disease and diarrhea.

methodsTwo-hundred households were enrolled in a 5-month longitudinal study. One adult (≥ 18 years) and one child (≤ 5 years) participated per household. Biweekly interviews (n = 1516) that included questions on water, sanitation, hygiene, and antibiotic use in the previous two weeks were conducted, and 2341 stool, 2843 hand swabs and 1490 drinking water samples collected. Presumptive E. coli (n = 34,042) were isolated and tested for susceptibility to nine antibiotics.

resultsEighty percent of presumptive E. coli were resistant to ≥ 3 antibiotic classes. Stool isolates were resistant to trimethoprim (mean: 81%), sulfamethoxazole (80%), ampicillin (68%), streptomycin (60%) and tetracycline (55%). Ninety-seven households reported using an antibiotic in at least one visit over the study period for a total of 144 episodes and 190 antibiotic doses. Enrolled children had five times the number of episodes reported by enrolled adults (96 vs. 19). Multivariable linear mixed-effects models indicated that children eating soil from the household yard and the presence of informal hand-washing stations were associated with increased numbers of antimicrobial-resistant bacteria (counts increasing by 0·27-0·80 log

conclusionsAntibiotic use provided little explanatory power for the prevalence of antimicrobial resistance. Transmission of resistant bacteria in this setting through unsanitary living conditions likely overwhelms incremental changes in antibiotic use. Under such circumstances, sanitation, hygiene, and disease transmission are the limiting factors for reducing the prevalence of resistant bacteria.

Indexed as

Drug Resistance, BacterialHygieneResidence CharacteristicsSanitationAdolescentAdultAgedAnti-Bacterial AgentsCarrier StateChild, PreschoolEscherichia coliEscherichia coli InfectionsFamily CharacteristicsFemaleHumansInfantAnti-Bacterial AgentsAntimicrobial resistanceE. coliInformal settlementKenyaSanitation

Identifiers

PMID33482919
PMCPMC7821723
OpenAlexW3120366080

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.