A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective

Namwin Siourimè Somda, Tomiwa Olumide Adesoji, Patience B. Tetteh-Quarcoo, Eric S. Donkor

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

This systematic review aimed to assess the prevalence of Escherichia coli O157:H7 using a One Health approach, integrating data from human, animal, and environmental sources across Africa. Following PRISMA guidelines, studies reporting on E. coli O157:H7 in human, animal, and environment samples from African countries were retrieved from PubMed, Scopus, Web of Science, and Google Scholar. All data were analyzed using a binary random-effects model by the DerSimonian–Laird method at a 95% confidence interval. Out of 1757 publications generated, 56 from 9 countries including Ethiopia (17/56), South Africa (13/56), Nigeria (10/56), Egypt (9/56), Ghana (2/56), Tanzania (2/56), Benin (1/56), Namibia (1/56), and Senegal (1/56) were included. The pooled prevalence of E. coli O157:H7 was 4.7%, with the highest prevalence observed among animal samples (5.4%) followed by the environmental and human samples (3.4 and 2.8%, respectively). The pooled prevalence of antibiotic resistance was observed to be 96.5%, 82.8%, 76.8%, 70.7%, 62.1%, 50.4%, and 40.2% for cefoxitin, ampicillin, cefuroxime, nitrofurantoin, amikacin, amoxiclav, and ciprofloxacin, respectively. This distribution highlights the interconnectedness between animals, the environment, and human populations in the transmission and persistence of this pathogen and the need to implement a suitable and appropriate One Health pathogenic and antimicrobial resistance surveillance system in the African region.

Original languageEnglish
Article number902
JournalMicroorganisms
Volume13
Issue number4
DOIs
Publication statusPublished - Apr 2025

Keywords

  • animal
  • antimicrobial resistance
  • E. coli O157:H7
  • environment
  • human
  • pooled prevalence
  • random-effects model

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