DTI

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ISSN 1177-3928

Drug Target Insights 2020; 14: 16-25

REVIEW

DOI: 10.33393/dti.2020.2170

Prevalence of multidrug-resistant and extended-spectrum 
beta-lactamase (ESBL)-producing gram-negative bacilli:  
A meta-analysis report in Ethiopia
Mengistu Abayneh and Teshale Worku

School of Medical Laboratory Sciences, Mizan-Tepi University, Mizan-Aman - Ethiopia

ABSTRACT
Multidrug-resistant (MDR) extended-spectrum beta-lactamase (ESBL)-producing bacterial isolates have emerged 
as a global threat to human health. Little is known about the overall prevalence of multidrug resistance profile 
and ESBL-producing gram-negative bacilli (GNB) in Ethiopia. Therefore, this meta-analysis was performed to pro-
duce proportional estimates of multidrug resistance and ESBL-producing GNB in Ethiopia.
 A web-based search was conducted in PubMed, Google Scholar, Research Gate, Scopus and other databases. 
Articles published till 2019 on the prevalence and antimicrobial resistance profiles of ESBL-producing GNB in  
Ethiopia were included in the study. Relevant data were extracted and statistical analysis was performed using com-
prehensive meta-analysis version 3.3.0 software. Publication bias was analyzed and presented with funnel plots.
 In this meta-analysis, the overall proportional estimate of ESBL-producing GNB was 48.9% (95% confidence 
interval [CI]: 0.402, 0.577). The pooled proportional estimates of ESBL-producing Klebsiella pneumoniae, Esch-
erichia coli and other GNB were 61.8%, 41.2% and 42.9%, respectively. Regarding antimicrobial resistance pro-
files against selected drugs, the pooled proportional estimates of resistance against amoxicillin-clavulanic acid, 
trimethoprim-sulfamethoxazole, cefotaxime, ceftazidime, tetracycline, gentamicin and ciprofloxacin was 79.0%, 
78.4%, 78.0%, 72.4%, 72.7%, 58.9% and 43.8%, respectively. The pooled proportional estimates of MDR isolates 
were found to be 82.7% (95% CI: 0.726, 0.896), which are relatively high as compared to other countries. This 
highlights a need for active surveillance systems which can help understand the actual epidemiology of ESBL, aid 
in formulating national guidelines for proper screening of ESBL and support developing standardized approaches 
for managing patients colonized with ESBL.
Keywords: Ethiopia, Extended-spectrum beta-lactamase, Gram negative, Multidrug resistance

Received: June 29, 2020
Accepted: September 14, 2020
Published online: October 5, 2020

Corresponding author:
Mengistu Abayneh
School of Medical Laboratory Sciences
Mizan-Tepi University
Mizan-Aman - Ethiopia
mengeabayneh@mtu.edu.et

use could worsen the condition, increasing infections caused 
by such resistant strains, its emergency and transmission 
(1,2). For instance, in Ethiopia studies show that about 36.8% 
of the population got antibiotics from community drug retail 
outlets without a prescription and 67.9% of people had dis-
continued the use of antibiotics once their symptoms subside 
(3). Low educational status, dissatisfaction with healthcare 
services provided, pharmacy owners’ influence to maximize 
revenue, customer’s pressure, weak regulatory mechanism 
and professional conflicts of interest were found to be strong 
predictors of inappropriate use of antibiotic use among the 
community (3,4).

Enterobacteriaceae that produce ESBL carry plasmid-
encoded enzymes that can efficiently hydrolyze and confer 
resistance to a variety of beta-lactam antibiotics, but not 
to carbapenems or cephamycins. Besides beta-lactam class 
of antibiotic, ESBL producers are commonly resistant to dif-
ferent families of antibiotics including fluoroquinolones, 
aminoglycosides and trimethoprim-sulfamethoxazole (SXT),  
which contribute to the selection and persistence of 

Introduction

The production of extended-spectrum beta-lactamase 
(ESBL) enzymes is the main bacterial mechanism to acquire 
resistance to currently used broad-spectrum beta-lactam an-
tibiotics. The infections caused by such enzyme-producing 
bacteria have significant potential impacts on antibiotic use 
and patient outcomes. Especially in resource-limited coun-
tries, limited availability of drugs coupled with inappropriate 



Abayneh and Worku  17

© 2020 The Authors. Published by AboutScience

multidrug-resistant (MDR) ESBL strains and plasmids in both 
clinical and community settings. These enzymes are predomi-
nantly found in Escherichia coli and Klebsiella pneumoniae, 
although they are also present in other members of the 
gram-negative bacilli (GNB) (5-7). 

ESBL-producing organisms play an important role in 
healthcare infections, increasing hospitalization time and 
morbidity and mortality rates (8). The presence of ESBL com-
plicates antibiotic selection, especially in patients with seri-
ous infections, such as bacteremia. The reason for this is that 
ESBL-producing bacteria are often multiresistant to various 
antibiotics, an interesting feature of CTX-M (CTX stands for 
cefotaxime and M for Munich)-producing isolates is the core-
sistance to various classes of antibiotics such as fluoroquino-
lones, aminoglycosides and co-trimoxazole due to associated 
resistance mechanisms, which may be either chromosomally 
or plasmid-encoded (8-11). 

The spread and the burden of ESBL-producing bacteria 
are greater in developing countries. For instance, the major 
epicenters of ESBL-expressing bacteria are located in Asia, Af-
rica and the Middle East (12-14). Findings of a recent review 
showed that pooled prevalence of healthcare-associated in-
fections in resource-limited settings (15.5%) was twice the 
average prevalence in Europe (7.1%) (15). Some plausible 
reasons for this difference include the following conditions 
that are prevalent in low-income countries: crowded hospi-
tals, more extensive self-treatment and use of nonprescrip-
tion antimicrobials, poorer hygiene in general and particularly 
in hospitals as well as less effective infection control. 

Comprehensive data regarding ESBL-producing bacteria 
are generally lacking in African countries, compared with the 
developed world. In Ethiopia also, it is difficult to evaluate 
the spread and the burden of ESBL-producing organisms, 
because of the limited scope of studies and lack of coordi-
nated epidemiological surveillance systems. By combining 
information from all relevant studies, meta-analyses can pro-
vide more precise estimates of the effects of healthcare than 
those derived from the individual studies included within a 
review. Therefore, to gain a better insight into the propor-
tional estimates of MDR profiles and ESBL-producing GNB in 
Ethiopia, we retrieved available articles and collated the in-
formation in this study article.

Methods

Study design

A descriptive meta-analysis study comprising different 
studies on the prevalence and antimicrobial resistance pro-
file of ESBL-producing GNB in Ethiopia was conducted. 

Data sources and search strategies

A systematic and comprehensive search on available 
records up to December 2019 was carried out in PubMed, 
Google Scholar, Research Gate, Scopus and other databases. 
The following medical subject headings (MESH) in the title 
or abstract, such as “clinical specimen,” “ESBL,” OR “ex-
tended spectrum β-lactamase” “Enterobacteriaceae” OR 

“extended-spectrum-beta-lactamase,” “gram negatives” OR 
“antibacterial resistance,” “gram negatives” OR “antimicro-
bial susceptibility” AND “gram negatives” and “Ethiopia,” 
were searched. In addition, bibliographies of eligible studies 
and other meta-analyses were manually searched carefully 
to identify additional relevant articles. 

Study selection and eligibility criteria 

All articles related to the detection of ESBL-producing 
GNB from clinical specimens and hospital environment 
samples, written in English language, possessing approved 
microbiological methods for pathogen detection and con-
taining sufficient and extractable data were included in the 
meta-analysis. Having assessed all the information from the 
recovered publications, online records that were available up 
to 2019 were considered as appropriate for eligibility assess-
ment. All review articles and original articles conducted out-
side Ethiopia, articles with irretrievable full texts and records 
with unrelated outcomes of interest were excluded during 
screening and eligibility assessment. 

Screening and eligibility criteria 

There were no limits with regard to study type except that 
the study had to be a primary study. However, the analysis 
was made to those studies which reported sufficient infor-
mation to meet outcomes of interests. Some duplicates re-
cords were addressed manually due to variation in reference 
styles across sources. Thereafter, the authors (MA and TW) 
independently inspected all the titles and abstracts of arti-
cles related to the study question and these were included 
in a group of eligible articles with their own code and with 
irrelevant articles being excluded. All articles in the initially 
selected group were further screened in a second step by 
reviewing the full texts and evaluated for eligibility for final 
inclusion (Fig. 1). 

Data extraction

Studies were identified by the main study name/identifier, 
followed by the year of publication. Using a predetermined, 
standardized and piloted data extraction form, the authors 
(MA and TW) independently extracted important data re-
lated to study characteristics from each article. Data extrac-
tion sheets were individually designed and pilot-tested using 
Microsoft Excel 2007. For each study meeting the review in-
clusion criteria, the following data, such as first author, study 
area, year of publication, study design, sample type, sample 
size, target population, isolate sources and outcomes of in-
terests, number and common species isolated, proportion of 
ESBL-positive strains and proportion and/or number of drug 
and MDR isolate and the methods used to test for ESBL pro-
ducers, were recorded. Data were extracted and analyzed at 
least twice to remove any discordance. Whenever there was 
discordance in the data extracted, a third person, a trained 
MSc laboratory professional, played a role in checking the 
data and a consensus was reached by double-checking of the 
articles with the two authors. 



Meta-analysis on MDR and ESBL-producing GNB in Ethiopia18 

© 2020 The Authors. Published by AboutScience

Quality assessment of included studies

The qualities of eligible studies were checked against 
items included in strengthening the reporting of observa-
tional studies in epidemiology (STROBE) Statement check-
list (16). The quality scores (proportion) for each study were 
calculated against items of the STROBE checklist adequately. 
There were no limits with regard to study type except that 
the study had to be a primary study and we did not exclude 
any studies based on quality. 

Outcome measurements

The first outcome measure is the proportion of ESBL-
producing GNB from clinical specimens in Ethiopia. The 
pooled proportion of ESBL-producing GNB was calculated 
per bacterium isolate. The second outcome measure is the 
antimicrobial and MDR profiles of ESBL-producing and non-
ESBL-producing GNB against selected antimicrobials of differ-
ent categories. 

Data processing and analysis

The relevant data were analyzed using comprehensive 
meta-analysis version 3.3.0 software (www.Meta-analysis.
com). Both random and fixed effects models were used to 
calculate the pooled proportional estimates of ESBL-positive 
and MDR isolates. The I2 statistics was used to expresses the 
percentage of total variation across studies and significant 
heterogeneity was considered at p < 0.05 and I2 > 50%. Pub-
lication bias was evaluated by using Begg’s and Egger’s tests 
and presented with funnel plots of standard error of Logit 

event rate, and a statistical significant publication bias was 
considered at p < 0.05.

Results

Search and screening results and distribution  
of included articles

A total of 39 studies were identified from several sources 
including PubMed, Google Scholar, Research Gate, Scopus 
and other databases. After removing eight duplicated arti-
cles, 31 were screened and four records were removed with 
their title and abstract review because of irrelevance. After 
full-text assessment, ten articles excluded: four from other 
countries, three due to animal and only nonhospital environ-
ment source of sample and three outcome of interest was 
missing and/or insufficient. Seventeen articles fulfilling the 
eligibility criteria were included for systematic meta-analysis 
(Fig. 1). The eligible studies were published in the year up 
to 2019. The study design of all included articles was cross-
sectional studies. Most of the studies indicated that various 
specimens had been utilized for screening of GNB; particu-
larly biological fluids like blood, urine, pus, stool and cerebro-
spinal fluid (CSF) were taken for test. Hospital environment 
samples such as wastewater and different swab samples 
from hospital contact surfaces were also taken for test. With 
regard to sources of biological samples, most of the studies 
included inpatients and outpatients as their sources of sam-
ples. With regard to study areas, six (35.3%) were conducted 
in the southwestern parts of Ethiopia, six (35.3%) in central 
Ethiopia, four (23.5%) in northern parts of Ethiopia and one 
(5.9%) in eastern parts of Ethiopia. Based on the available ev-
idence, the maximum number of articles on this subject was 
published in the year 2014, which means only three articles 
were published in 2005, 2011 and 2012 (Tab. I). The median 
score of published studies against STROBE items was 72.2% 
(with a range of [50.7-79.7]). 

Proportional estimates of ESBL-positive GNB

This study indicates that although different bacterial 
pathogens have the probability of producing ESBL as their 
resistance mechanisms, studies on the proportion of ESBL-
producing bacteria have not been carried out properly in all 
parts of Ethiopia. Based on the available data, the pooled 
proportional estimate of ESBL-producing GNB in Ethiopia 
was 0.489 (95% confidence interval [CI]: 0.402, 0.577). Pro-
portional estimates of ESBL-producing K. pneumoniae were 
0.618 (95% CI: 0.487, 0.734), whereas proportional estimates 
of ESBL-producing E. coli were 0.412 (95% CI: 0.326, 0.504). 
The proportional estimate of other ESBL-producing GNB was 
0.429 (95% CI: 0.352, 0.509). Overall heterogeneity was sig-
nificant [I2 = 93.41%; p = 0.000] (Tab. II and Fig. 2). 

Proportional estimates of MDR profiles of bacterial isolates

The bacterial isolates that showed different antimicrobial 
resistance profile against selected agents were extracted. 
Accordingly, the pooled estimate indicated that 0.720 (95% 

A total of 34records were searched and 

identified fromPubMed, Google 

Scholar,ResearchGate, Scopus and 

other databases.

Id
en

ti
fi

ca
ti

on

Numbers of articles screened after 8 
duplicates removed (n= 31)

Sc
re

en
in

g

Four records were removed 
with their title and abstract

review because of irrelevance.

Numbers of full-text assessed articles 
(n= 27)

E
lig

ib
ili

ty Ten articles excluded due to:
• Four from other countries
• Three due to animal and only 

environmental source of sample
• Three outcome of interest was 

missing and/or insufficient

In
cl

ud
ed Numbers of articles included in 

systematic meta-analysis (n=17)

Records identified through other 

sources (bibliographies)

(n= 5)

Fig. 1 - Flow chart showing the selection process of articles.



Abayneh and Worku  19

© 2020 The Authors. Published by AboutScience

TABLE I - Distribution of articles reviewed on ESBL-producing clinical isolates from different regions of Ethiopia

First author, 
publication  
year

Study 
design

Study 
area

Sample types Sample 
sources

Sample 
size

Total 
isolates

Total ESBL 
positives

Common ESBL producers ESBL  
confirmation 
methodE. coli K.  

pneu-
moniae

Other 
gram-

negatives

Desta et al,  
2016 (17)

CS AA Fecal sample/swab IP 267 295 151/295 106/235 44/58 1/2 CDT + Vitek2

Teklu et al,  
2019 (18)

CS AA Urine, blood, sputum, 
CSF, body fluid, pus 
and discharge

IP and 
OP

426 426 246/426 119/228 81/103 46/95 CDT

Moges et al, 
2019 (19)

CS Bahir 
Dar

Urine, blood, stool, 
pus, sputum, CSF, 
body fluid, ear, nasal, 
cervical discharge

IP and 
OP

532 263 127/148 14/23 79/97 34/76 CDT

Legese et al, 
2017 (20)

CS AA Blood and urine IP and 
OP

322 33 22/28 5/6 16/19 1/8 CDT

Engda et al, 
2018 (21)

CS Gondar Swabs of sinks, bed, 
door handles,  
wastewater

Hospital 
env’t

384 57 57/57 20/57 24/57 13/57 Hicrome 
ESBL agar

Gashaw et al, 
2018 (22)

CS Jimma Urine, blood, sputum, 
wound/pus swab

IP 118 126 51/100 19/31 16/30 18/39 DDST

Mulualem  
et al, 2012 (23)

CS Jimma Urine, stool, sputum, 
wound/pus swab

IP and 
OP

359 67 24/67 24/67 NA NA CDT

Zeynudin 
et al, 2018  
(24)

CS Jimma Wound swabs, urine, 
biopsies, sputum

IP and 
OP

224 224 71/112 13/13 30/31 28/68 Check-MDR 
Microarray 
Kits

Eshetie et al, 
2015 (25)

CS Gondar Urine IP and 
OP

442 183 5/160 2/104 3/28 42 (NA) CHROMagar

Beyene et al, 
2011 (26)

CS Jimma Stool, blood IP and 
OP

1,225 113 71/113 NA NA 71/113 E-test

Abera et al, 
2016 (27)

CS Bahir 
Dar

Blood, urine, pus,  
CSF, ear discharges,  
wound swab, water 

IP and 
OP

757 274 127/274 73/170 36/55 17/49 DDST

Seid et al,  
2005 (28)

CS Harrar Sputum, urine  
and pus

IP and 
OP

384 57 19/57 NA 19/57 NA CDT

Abayneh et al., 
2018 (29)

CS Jimma Urine OP 342 74 17/74 13/63 4/11 NA DDST

Siraj et al,  
2014 (30)

CS Jimma Urine, sputum, blood, 
vaginal swabs, wound/
pus swab, eye dis-
charge

IP and 
OP

471 112 43/112 24/85 19/27 NA DDST

Mulisa et al, 
2016 (31)

CS Adama Urine, wound, nasal, 
stool, pleural fluids, 
ear discharge

IP and 
OP

384 133 17/68 10/35 2/8 5/25 DDST

Bitew  
(2019) (32)

CS AA Urine, wound, blood, 
CSF, ear, nasal

IP and 
OP

996 153 66/135 NA NA 66/135 CDT

Beyene  
(2019) (33)

CS AA Urine, sputum, blood, 
vaginal, wound/pus, 
eye discharge

IP 947 238 159/238 91/144 55/72 13/21 CDT

AA = Addis Ababa; CDT = Combination Disc Test; CS = cross-sectional; CSF = cerebrospinal fluid; DDST = Double Disc Synergy Test; ESBL = extended-spectrum 
beta-lactamase; E-Test = Epsilometric Test; IP = inpatient; MDR = multidrug resistance; NA = not analyzed; OP = outpatient.



Meta-analysis on MDR and ESBL-producing GNB in Ethiopia20 

© 2020 The Authors. Published by AboutScience

TABLE II - Proportional estimates of ESBL-producing gram-negative bacteria in different regions of Ethiopia

Studies Total proportions of ESBL Proportions of ESBL- 
producing E. coli

Proportions of ESBL- 
producing K. pneumoniae

Proportions of ESBL- 
producing other GNs

ES [95% CI] Weight ES [95% CI]  Weight ES [95% CI]  Weight ES [95% CI]  Weight

Desta et al 
(2016)

0.51 [0.455, 0.569] 1.80 0.451 [0.389, 0.515] 2.91 0.759 [0.633, 0.852] 1.00 0.500 [0.059, 0.941] 0.45

Teklu et al 
(2019)

0.58 [0.530, 0.624] 1.81 0.522 [0.457, 0.586] 2.91 0.786 [0.697, 0.855] 1.04 0.484 [0.386, 0.584] 3.53

Moges  
et al (2019)

0.858 [0.792, 0.906] 1.67 0.609 [0.402, 0.782] 1.96 0.814 [0.725, 0.880] 1.03 0.447 [0.340, 0.560] 3.40

Legese  
et al (2017)

0.786 [0.598, 0.900] 1.32 0.833 [0.369, 0.977] 0.66 0.842 [0.608, 0.948] 0.77 0.125 [0.017, 0.537] 0.72

Engda et al 
(2018)

0.991 [0.877, 0.999] 0.39 0.351 [0.239, 0.482] 2.48 0.421 [0.301, 0.552] 1.02 0.228 [0.137, 0.354] 2.93

Gashaw  
et al (2018)

0.510 [0.413, 0.606] 1.71 0.613 [0.435, 0.765] 2.16 0.533 [0.358, 0.701] 0.96 0.462 [0.317, 0.617] 2.90

Mulualem 
et al (2012)

0.358 [0.253, 0.479] 1.64 0.358 [0.253, 0.479] 2.55 NA NA NA

Zeynudin 
et al (2018)

0.634 [0.541, 0.718] 1.72 0.964 [0.616, 0.998] 0.42 0.968 [0.804, 0.995] 0.52 0.412 [0.302, 0.532] 3.31

Eshetie  
et al (2015)

0.027 [0.011, 0.064] 1.34 0.018 [0.004, 0.069] 1.20 0.103 [0.034, 0.276] 0.78 42 (NA) NA

Beyene  
et al (2011)

0.628 [0.536, 0.712] 1.72 NA NA NA 0.628 [0.536, 0.712] 3.58

Abera et al 
(2016)

0.464 [0.405, 0.523] 1.79 0.429 [0.357, 0.505] 2.85 0.655 [0.521, 0.768] 1.01 0.415 [0.276, 0.569] 2.93

Seid et al 
(2005)

0.333 [0.224, 0.464] 1.61 NA NA 0.333 [0.224, 0.464] 1.02 NA NA

Abayneh  
et al (2018)

0.230 [0.148, 0.339] 1.61 0.206 [0.124, 0.324] 2.36 0.364 [0.143, 0.661] 0.77 NA NA

Siraj et al 
(2014)

0.384 [0.299, 
0.477]

1.72 0.282 [0.197, 0.387] 2.60 0.704 [0.510, 0.844] 0.92 NA NA

Mulisa et al 
(2016)

0.250 [0.161, 0.366] 1.61 0.286 [0.161, 0.454] 2.14 0.250 [ 0.063, 
0.623]

0.64 0.200 [0.086, 0.400] 2.04

Bitew 
(2019)

0.489 [0.406, 
0.573]

2.00 NA NA NA 0.489 [0.406, 0.573] 4.42

Beyene 
(2019)

0.668 [0.606, 0.725] 20.5 0.632 [0.550, 0.707] 2.57 0.764 [0.653, 0.848] 1.11 0.619 [0.402, 0.797] 2.51

Overall R 
ES [95% CI]
Overall F 
ES [95% CI]

0.489 [0.402, 0.577]
 

0.526 [0.505, 0.548]

0.412 [0.326, 0.504] 
  

0.451 [0.422, 0.481]

0.618 [0.487, 0.734]
 

0.646 [0.604, 0.686]

0.429 [0.352, 0.509]
  

0.461 [0.424, 0.500]

CI = confidence interval; ESBL = extended-spectrum beta-lactamase; F = fixed; GN = gram negatives; NA = not analyzed; R = random; ES = event rate.

CI: 0.586, 0.820) and 0.780 (95% CI: 0.615, 0.891) of the 
ESBL-producing and non-ESBL-producing GNB were found 
resistant to third-generation cephalosporin (ceftazidime and 
cefotaxime), respectively. The pooled estimate indicated 
that 0.589 (95% CI: 0.482, 0.688), 0.438 (95% CI: 0.347, 
0.534) and 0.790 (95% CI: 0.713, 0.850) of ESBL-producing 
and non-ESBL-producing GNB isolates were resistant to 

gentamicin, ciprofloxacin and amoxicillin-clavulanic acid, re-
spectively. Besides, 0.784 (95% CI: 0.726, 0.832) and 0.727 
(95% CI: 0.605, 0.823) of ESBL-producing and non-ESBL- 
producing GNB isolates were resistant to SXT and tetracycline 
(TET), respectively. The pooled proportional estimates of 
MDR isolates were found to be 0.827 (95% CI: 0.726, 0.896)  
(Tab. III).



Abayneh and Worku  21

© 2020 The Authors. Published by AboutScience

TABLE III - Antimicrobial and multidrug resistance profile of bacterial isolates obtained from different samples in Ethiopia

Authors Total 
isolates

Total ESBL-
producer

Antimicrobial resistance profiles

CAZ CTX GNT CIP SXT TET AMC MDR

Desta et al. 
(2016)

295 151/295 137/150 146/150 105/150 94/150 136/150 NA 134/150 150/150

Teklu et al. 
(2019)

426 246/426 257/426 265/426 185/426 240/426 324/426 NA 305/426 237/246 or 
291/426*

Moges  
et al. (2019)

185 127/148 143/148 129/148 116/148 52/148 138/148 127/148 117/148 127/148 or 
148/185*

Legese  
et al. (2017)

33 22/28 NA 29/33 26/33 NA 29/33 25/33 28/33 NA

Engda et al. 
(2018)

57 57/57 57/57 57/57 11/57 25/57 37/57 NA 57/57 32/57

Gashaw  
et al. (2018)

100 51/100 63/100 60/100 68/100 48/100 79/100 90/100 94/100 28/100*

Mulualem 
et al. (2012)

67 24/67 4/67 6/67 2/67 14/67 38/67 49/67 47/67 67/67*

Zeynudin  
et al. (2018)

224 71/112 63/68 66/68 60/68 41/68 62/68 NA NA 67/68* 

Eshetie  
et al. (2015)

183 5/183 90/160 40/160 94/160 4/160 103/160 79/160 81/160 160/183*

Beyene  
et al. (2011)

113 71/113 NA NA 84 1 91 45 NA 78/113*

Abera et al. 
(2016)

274 127/274 NA NA NA 106/274 174/274 NA NA NA

Seid et al. 
(2005)

57 19/57 23/57 22/57 35/57 NA 37/57 NA NA 41/57*

Abayneh  
et al. (2018)

74 17/74 12/17 17/17 11/17 13/17 14/17 14/17 14/17 14/17

Raw weight Relative weight 

Random

Desta K (2016) 151 / 295 2.07 6.73

Teklu DS (2019) 246 / 426 2.09 6.79

Moges F (2019) 127 / 148 1.90 6.19

Legese M (2017) 22 / 28 1.47 4.77

Engda T (2018) 57 / 57 0.40 1.31

Gashaw M (2018) 51 / 100 1.96 6.38

Mulualem Y (2012) 24 / 67 1.87 6.08

Zeynudin A.(2018) 71 / 112 1.97 6.40

Eshetie S. (2015) 5 / 160 1.48 4.81

Beyene G (2011) 71 / 113 1.97 6.41

Abera B (2016) 127 / 274 2.06 6.72

Seid J (2005) 19 / 57 1.82 5.93

Abayneh M (2018) 17 / 74 1.83 5.96

Siraj SM (2014) 1.97 6.41

Mulisa G (2016) 1.82 5.93

Bitew A (2019) 2.00 6.51

Beyene D (2019) 2.05 6.66

-0.50 0.00 0.50 1.00
Overall F ES [95% CI]

0.512 [0.455,0.569]

0.577 [0.530,0.624]

0.858 [0.792, 0.906]

0.991 [0.877, 0.999]

0.510 [0.413, 0.606]

0.358 [0.253, 0.479]

0.634 [0.541, 0.718]

0.031 [0.013, 0.073]

0.628 [0.536, 0.712]

0.464 [0.405, 0.523]

0.786 [0.598, 0.900]

0.333 [0.224, 0.464]

0.230 [0.148, 0.339]

0.384 [0.299, 0.477]

0.250 [0.161, 0.366]

0.489 [0.406, 0.573]

0.668 [0.606, 0.725]

Overall R ES [95% CI] 0.489 [0.402, 0.577]

Heterogeneity I2 = 93.41%; p = 0.000

0.526 [0.505, 0.548]

Statistics for each study

ES [95% CI]Study name ESBL/Total

43 / 112

17 / 68

66/135

159/238

Fig. 2 - Proportional estimates of 
ESBL-producing GNB in different 
clinical samples in Ethiopia. CI = 
confidence interval; ESBL = exten-
ded-spectrum beta-lactamase;  
ES = event rate.

(Continued)



Meta-analysis on MDR and ESBL-producing GNB in Ethiopia22 

© 2020 The Authors. Published by AboutScience

Authors Total 
isolates

Total ESBL-
producer

Antimicrobial resistance profiles

CAZ CTX GNT CIP SXT TET AMC MDR

Siraj et al. 
(2014)

112 43/112 42/43 43/43 36/43 33/43 41/43 39/43 38/43 38/43

Mulisa  
et al. (2016)

68 17/68 NA NA 12/17 14/17 14/17 6/17 NA 17/17

Bitew 
(2019)

135 66/135 45/135 NA 32/135 47/135 86/135 92/135 100/135 110/135*

Beyene 
(2019)

238 159/238 176/238 NA 117/238 137/238 195/238 191/238 148/238 225/238*

Overall R,  
ES [95% CI]

1273/2487 0.72 
[0.586, 
0.820]

0.78  
[0.615, 
0.891]

0.589  
[0.482, 
0.688]

0.438  
[0.347, 
0.534]

0.784  
[0.726, 
0.832]

0.727 
[0.605, 
0.823]

0.790  
[0.713, 
0.850]

0.827  
[0.726, 
0.896]

AMC = ampicillin-clavulanic acid; CAZ = ceftazidime; CI = confidence interval; CIP = ciprofloxacin; CTX = cefotaxime; GNT = gentamicin; ESBL = extended-spectrum 
beta-lactamase; MDR = multi-drug resistance; NA = not analyzed; R = resistance; SXT = trimethoprim-sulfamethoxazole; TET = tetracycline; ES = event rate.
*From overall isolates.

Laboratory methods used to estimate the proportion of  
ESBL-producing strains

According to this review, 8/17 (47.1%) of the articles re-
viewed used combination disk test (CDT) and 5/17 (29.4%) 
articles used double disk synergy test (DDST) methods alone. 
Two (11.8%) articles used CHROMagar and one article used 
E-test to estimate ESBL proportions. Only one article used 
Check-MDR CT103 Microarray Kits for detection and molecu-
lar characterization of the ESBL genes (Tab. I). 

Publication bias

Funnel plots of standard error with Logit event rate con-
firmed that there is no statistically significant evidence of 
publication bias on studies reporting the prevalence of ESBL-
producing bacterial isolates from different clinical samples 
in Ethiopia (Begg’s test, p = 0.217; Egger’s test, p = 0.231) 
(Fig. 3). However, Begg suggested that a nonsignificant 

correlation may be due to low statistical power and cannot 
be taken as evidence that bias is absent. 

Discussion

This is the first meta-analysis study relating the extent of 
the ESBL-producing GNB in Ethiopia. Accordingly, the pooled 
proportional estimates of ESBL-producing GNB were 48.9%, 
which is higher than previous estimates of meta-analysis in 
East Africa (34) and Pakistan (35), in which overall pooled pro-
portion of ESBL-producers was 42% and 40%, respectively. As 
compared to each country in East Africa, this finding is higher 
than the pooled proportion of ESBL-producing Enterobacte-
riaceae in Tanzania (39%) and Kenya (47%) (34). The result is 
also higher than estimates of meta-analysis in African coun-
tries, in which the total proportion of ESBL-producing isolates 
was 15% in 16 out of 26 studies (36).

As compared to resource-rich countries, the pooled pro-
portion of ESBL-producing isolates was thus considerably 
higher in resource-limited countries, including our setting. 
For instance, the pooled global prevalence of ESBL-producing 
Enterobacteriaceae among pregnant women diagnosed with 
urinary tract infections (UTIs) is 25%, with the highest rates in 
Africa (45%) and India (33%), followed by 15% in other Asian 
countries, 5% (2.8%) in Europe and the lowest one of 4% in 
South America and 3% in North America (37). This study find-
ing is also close to data reported for China, where a nation-
wide survey that included 30 hospitals reported over 46% 
resistance due to ESBL (38). However, our estimate is slightly 
lower than for Uganda (62%) (34), Ghana (49%) (39), Camer-
oon (54%) (40) and Morocco (43%) (41). 

With regard to the frequency of isolates, in this study, 
the pooled proportional estimates of ESBL-producing 
K. pneumoniae, E. coli and other GNB were 60.3%, 39.0% 
and 40.9%, respectively. This is much higher than a SMART 
study between 2009 and 2010, in which ESBL prevalence 
among K. pneumoniae and E. coli was 38.9% and 17.6%, 
respectively, in Europe, and 8.8% and 8.5, respectively, in 

-5 -4 -3 -2 -1 0 1 2 3 4 5

0.0

0.5

1.0

1.5

2.0

Logit event rate

St
an

da
rd

 E
rr

or

Fig. 3 - Funnel plot depicting publication bias of studies reporting the 
prevalence of extended-spectrum beta-lactamase (ESBL)-producing 
gram-negative bacilli in different clinical samples in Ethiopia.

TABLE III - Continued 



Abayneh and Worku  23

© 2020 The Authors. Published by AboutScience

North America (42). Moreover, our meta-analysis result is 
also higher than a report of in vitro activity of tigecycline and 
comparators against gram-negative and gram-positive organ-
isms collected from Asia-Pacific during 2004-2010 and 2015, 
in which 24.6% and 15.8% of E. coli and K. pneumoniae were 
ESBL producers in 2015, respectively[A: Please check the clar-
ity of this sentence.] (43). In addition, among GNB collected 
from intra-abdominal infections in the Asia-Pacific region 
during 2007, 42.2% and 35.8% of E. coli and Klebsiella spp., 
respectively, were ESBL positive (44). However, higher pro-
portions of ESBL-producing E. coli and K. pneumoniae were 
reported from India, Vietnam and China (44,45).

In this study, inter-study results showed a wide and statis-
tically significant degree of variation in proportion estimates 
of ESBL proportions (p < 0.05). There are several possible fac-
tors that may account for the variations seen in this review. 
The first factor is the difference in sensitivity and specificity 
between methods used in estimating ESBL proportions. Some 
studies reviewed estimated ESBL proportions using purely 
phenotypic methods, while others used both phenotypic 
and molecular-based methods. For instance, in this study, 
most of the reviewed articles used CDT (17-20,23,28,32,33) 
and DDST (22, 27,29-31) methods alone for the detection of 
ESBL-producing isolates, and only one study used molecu-
lar technique for investigations and characterizations of the 
gene encoding ESBL (24).

The other factor contributing to the variation in proportion 
estimates of ESBL proportions is type of wards or units, type 
of specimen collected and whether patients were attending 
outpatient or inpatient departments. In this meta-analysis, 
many reviewed studies showed that ESBL-producing isolates 
were more among inpatients than outpatients (20,24,30). 
In contrast, two reviewed studies showed the reverse find-
ing (23,27). A meta-analysis study in areas of sub-Saharan 
Africa showed that pooled ESBL-producing Enterobacte-
riaceae colonization was 18%, 32% and 55% in community 
studies, at hospital admission and for inpatient studies, re-
spectively (46). Many reports have documented the differ-
ence in ESBL proportion estimates between hospitals versus 
community-based surveys (23,25,27,30). However, the lack 
of any estimates for community-based ESBL carriage in  
Ethiopia underscores an urgent need for surveillance in the 
region. Infection control in hospitals including hand hygiene 
and rational antibiotic use can be effective measures to stop 
further spread of the ESBL-producing and MDR strains in 
both hospitals and communities.

MDR GNB are now globally widespread and present a 
major challenge to modern medical practice. To date, the 
overall epidemiology and burden of MDR bacteria and their 
mechanisms of resistance have not been fully understood, 
especially in resource-limited countries, including Ethiopia. 
This is the first meta-analysis study conducted to deter-
mine the pooled proportional estimates of ESBL-producing 
GNB and MDR isolates in Ethiopia. Accordingly, the pooled 
proportional estimates of MDR isolates were found to be 
82.7% (Tab. III). This finding is higher than a finding of previ-
ous meta-analysis in Ethiopia, in which the pooled propor-
tional estimates of MDR isolates were 59.7% (47); however, 
it was lower than a single study finding in Ethiopia (33) and 
Chile (48), in which 94.5% and 100% isolates exhibited MDR 

profiles. Lower study finding was also reported in Ethiopia, 
in which the overall prevalence of MDR was 69.9%, of which 
81.5% was in the hospital environment, while 54.2% was in 
non-hospital environment samples (49). The occurrence of 
MDR may be linked with indiscriminate utilization of anti-
microbial agents such as wrong indication, wrong duration, 
improper route of administration, use of leftover antibiot-
ics from a family member and improper discontinuation of 
antibiotics or genetic mutation (47,50,51). A meta-analysis 
finding in Ethiopia indicated that the pooled estimate of in-
appropriate antibiotic use was 49.2% and the pooled propor-
tion of self-antibiotic prescription was 43.3% (47). Thus, the 
frequent and inappropriate use of antibiotics in humans and 
animals may contribute to the recent emergence of ESBL pro-
ducers and MDR strains both in healthcare institutions and  
communities. 

Moreover, medication required to treat ESBL-producing 
isolates is expensive and unaffordable for the majority of the 
population in these settings, making these bacteria difficult 
to treat. A study in Ethiopia concluded that mortality was sig-
nificantly associated with antimicrobial resistance (52). For 
instance, all 11 patients with Enterobacteriaceae resistant 
to third-generation cephalosporins died. Another system-
atic review and meta-analysis estimated that the mortality 
in neonates with bloodstream infections (BSIs) due to ESBL-
producing Enterobacteriaceae was 36%, as compared to 18% 
among all other neonates with BSI (53). It is therefore of the 
utmost importance to make reliable data available to guide 
strategies devoted to limiting the spread of particularly ESBL-
producing pathogens and MDR strains in Ethiopia. 

In this study, significant numbers of bacterial isolates 
showed different resistance profile against selected antimi-
crobial agents. The pooled proportional estimate of resis-
tance against third-generation cephalosporins (cefotaxime 
and ceftazidime), amoxicillin-clavulanic acid, gentamicin, 
ciprofloxacin, SXT and TET ranges from 43.8% to 79.0%. Al-
most similar findings were reported in Ethiopia and Chile, in 
which 45.4% to >88% isolates exhibit resistance against beta-
lactams and non-lactam drugs (33,48). This high resistance 
rate might be associated with an interesting feature of ESBL-
producing isolates as resistance mechanisms, which may be 
either chromosomally or plasmid-encoded, especially CTX-M 
that often showed feature of coresistance to various classes 
of antibiotics such as fluoroquinolones, aminoglycosides, and 
co-trimoxazole. Therefore, interventions including infection 
control measures and restriction of low-quality and inappro-
priate use of antibiotics may aid in controlling the emergency 
and spread of ESBL-producing pathogens and may actually 
prove cost-beneficial. As a limitation, in this study, due to the 
lack of sufficient records on the prevalence of ESBL producers 
from different clinical samples in Ethiopia, all primary studies, 
including those with very small datasets (<10 ESBL-producing 
strains) were included. 

Conclusion

The problems related to antibiotic resistance, including 
MDR due to ESBL, are significant in Ethiopia. The scarcity of 
data on predictors, clinical outcomes, magnitudes and gene 
variants encoding resistance due to ESBL-producing GNB 



Meta-analysis on MDR and ESBL-producing GNB in Ethiopia24 

© 2020 The Authors. Published by AboutScience

calls for active surveillance systems, which can help under-
stand the current epidemiology of ESBL within the country. 
Furthermore, this can aid in developing national guidelines 
for proper screening of ESBL as well as developing standard-
ized approaches for managing patients colonized with ESBL-
producing GNB.

Disclosures
Conflict of interest: The authors declare that they have no compet-
ing interest.
Financial support: No funding was allocated for this study. 
Availability of data and materials: All the data supporting our find-
ings were incorporated within the manuscript, but are available 
from the corresponding author on reasonable request. 
Authors’ contributions: MA and TW participated in the study design, 
study searching and screening and data extractions. MA analyzed 
the data and drafted the manuscript. TW support data analysis, 
read, revised and approved the final version of the manuscript. 

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