A systematic review and meta-analysis of antimicrobial resistance knowledge, attitudes, and practices: Current evidence to build a strong national antimicrobial drug resistance narrative in Ethiopia

Abstract

Antimicrobial resistance (AMR) is a silent pandemic that has claimed millions of lives, and resulted in long-term disabilities, limited treatment options, and high economic costs associated with the healthcare burden. Given the rising prevalence of AMR, which is expected to pose a challenge to current empirical antibiotic treatment strategies, we sought to summarize the available data on knowledge, attitudes, and practices regarding AMR in Ethiopia. Articles were searched in international electronic databases. Microsoft Excel spreadsheet and STATA software version 16 were used for data extraction and analysis, respectively. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 checklist was followed. The methodological quality of the studies included was assessed by the Joana Briggs Institute critical appraisal checklists. The random-effect meta-analysis model was used to estimate Der Simonian-Laird's pooled effect. Statistical heterogeneity of the meta-analysis was checked through Higgins and Thompson's I2 statistics and Cochran's Q test. Publication bias was investigated by funnel plots, and the regression-based test of Egger for small study effects with a P value < 0.05 was considered to indicate potential reporting bias. In addition, sensitivity and subgroup meta-analyses were performed. Fourteen studies with a total of 4476 participants met the inclusion criteria. Overall, the pooled prevalence of good AMR knowledge was 51.53% [(95% confidence interval (CI): 37.85, 65.21), I2 = 99.0%, P <0.001]. The pooled prevalence of favorable attitudes and good practices were 63.43% [(95% CI: 42.66, 84.20), I2 = 99.6, P <0.001], and 48.85% [(95% CI: 38.68, 59.01), I2 = 93.1, P <0.001] respectively. In conclusion, there is a significant knowledge and practice gap on AMR among the general public, patients, and livestock producers. As a result, we call for greater educational interventions to raise awareness and build a strong national AMR narrative.

Fig 1. PRISMA flow diagram explaining the selection of primary studies.

Fig 2. The forest plot of pooled prevalence.

(Panel A) Good level of AMR knowledge. (Panel B) Favorable attitudes towards AMR. (Panel C) Good AMR practices.

Fig 3. Funnel plots of publication bias.

(Panel A) For a good level of AMR knowledge. (Panel B) Favorable attitudes towards AMR. (Panel C) A good level of AMR practices. The Y-axis shows the standard error of the estimate (prevalence). The 95% confidence interval is represented by the dashed lines. The X-axis represents the estimate (i.e. prevalence) and the dots show the distribution of individual studies.