Literature DB >> 35294487

Prevalence and drug resistance patterns of Gram-negative enteric bacterial pathogens from diarrheic patients in Ethiopia: A systematic review and meta-analysis.

Achenef Melaku Beyene1, Mucheye Gezachew1, Desalegn Mengesha2, Ahmed Yousef3, Baye Gelaw1.   

Abstract

BACKGROUND: Diarrhoea is the leading cause of morbidity and mortality in the world particularly in developing countries and among vulnerable groups of the population. Gram-negative enteric bacterial pathogens (GNEBPs) are a group of organisms that reside mainly in the intestine and induce diarrhoea. Antimicrobial agents are usually the part of their treatment regimen. The therapeutic effect of antimicrobials is hindered by the emergence and spread of drug-resistant strains. The information regarding the prevalence and antimicrobial resistance patterns of GNEBPs in Ethiopia is limited and found in a scattered form.
OBJECTIVES: This study was designed to determine the pooled prevalence and drug resistance patterns of GNEBPs by meta-analysis of data from diarrhoeic patients in Ethiopia.
METHOD: A comprehensive literature search was conducted through internet searches using Google Scholar, PubMed, Science Direct, HINARI databases, and reference lists of previous studies. Published articles were included in the study based on priorly set inclusion and exclusion criteria. Results were presented in the forest plot, tables, and figures with a 95% confidence interval (CI). The inconsistency index (I2) test statistics was used to assess heterogeneity across studies. The pooled prevalence estimate of GNEBPs and their drug resistance patterns were computed by a random-effects model. Software for Statistics and Data Science (STATA) version 14 statistical software was used for the analysis. RESULT: After removing those articles which did not fulfil the inclusion criteria, 43 studies were included in the analysis. Studies were conducted in 8 regions of the country and most of the published articles were from the Amhara region (30.23%) followed by Oromia (18.60%) and Southern Nations, Nationalities, and Peoples' region (SNNP) (18.60%). The pooled prevalence of GNEBPs was 15.81% (CI = 13.33-18.29). The funnel plot indicated the presence of publication bias. The pooled prevalence of GNEBPs in Addis Ababa, Amhara, SNNP, and Oromia regions were 20.08, 16.67, 12.12, and 11.61%, respectively. The pooled prevalence was 14.91, 18.03, and 13.46% among studies conducted from 2006-2010, 2011-2015, and 2016-2021, respectively and it was the highest (20.35%) in children having age less than or equal to 15 years. The pooled prevalence of Escherichia coli, Campylobacter spp., Shigella spp., and Salmonella enterica were 19.79, 10.76, 6.24, and 5.06%, respectively. Large proportions (60-90%) of the isolates were resistant to ampicillin, amoxicillin, tetracycline, and trimethoprim-sulphamethoxazole. The pooled prevalence of multidrug resistance (MDR) was 70.56% (CI = 64.56-76.77%) and MDR in Campylobacter spp., Shigella spp., E. coli, and S. enterica. were 80.78, 79.08, 78.20, and 59.46%, respectively.
CONCLUSION: The pooled estimate showed a high burden of GNEBPs infections and a high proportion of drug resistance characters to commonly used antimicrobial agents in Ethiopia. Therefore, performing drug susceptibility tests, establishing an antimicrobial surveillance system and confirmation by molecular techniques are needed.

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Year:  2022        PMID： 35294487      PMCID： PMC8926281          DOI： 10.1371/journal.pone.0265271

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

World Health Organization (WHO) defines diarrhoea as the passage of three or more loose or liquid stools per day (24 hours). During diarrhoea, the water content and volume of stool and defecation frequency will usually increase. The syndrome may be accompanied by other illnesses like vomiting, fever, dysentery, nausea, and abdominal cramps. It is the leading cause of morbidity and mortality in the world and contributes about 4% of all deaths and 5% of health loss to disability [1-3]. Diarrhoea is the fifth leading cause of death and it contributes to one in nine deaths among children younger than 5 years [4,5]. The problem is severe among the vulnerable population such as children, people with HIV, the elderly, and other individuals having weak immunity. Many factors contribute to diarrhoea; however, childhood wasting (low weight-for-height score), unsafe water, and unsafe sanitation are the leading risk factors [5]. The incidence of diarrhoea is different among the regions or continents of the world. It is highly prevalent in Sub-Saharan Africa and South Asia. The report from WHO showed that these countries account for about 78% of all diarrheal deaths among children in the developing world [2,4]. Ethiopia is one of the top three countries with very high child mortality due to diarrhoea in Africa [5-7]. Diarrhoea can be induced by a variety of causes. However, infectious agents like viruses and bacteria are among the leading causes. Bacteria, particularly Gram-negative enteric bacterial pathogens (GNEBPs) are the common causes of the syndrome. The group includes bacteria that reside mainly in the intestine. Genera such as Escherichia, Shigella, Campylobacter, Salmonella, Enterobacter, Klebsiella, Yersinia, Serratia, Proteus, and others are included in the group. However, the most common and significant pathogens are S. enterica, E. coli, Campylobacter, and Shigella spp. [8]. Antimicrobial agents are usually part of the treatment regimen, particularly on diarrhoea caused by bacteria. Due to the widespread and indiscriminate use of antimicrobials, several resistant strains are emerging which tend to spread globally [9,10]. Hence, antimicrobial resistance (AMR) is a global health threat and was recognized in the 2016 United Nations (UN) General Assembly [11]. It is one of the top challenges in achieving the 2030 UN sustainable development goals [10]. Infections caused by resistant organisms affect treatment outcomes, treatment costs, disease spread, and duration of illness, posing a challenge to the future of chemotherapy [12]. Some pathogenic strains are also developing resistance not only to one but to several agents, i.e., multidrug resistance [13,14]. Information regarding the prevalence and antimicrobial resistance patterns of GNEBPs in Ethiopia is limited, and available information is found in scattered forms. Hence, there is an interest to conduct a nationwide study. To fill this significant gap, this systemic review and meta-analysis was prepared. The review focused on the prevalence and antimicrobial resistance patterns of GNEBPs isolated from diarrheic patients in Ethiopia. The output of this systematic review and meta-analysis can be used by clinicians, policymakers, and researchers to make evidence-based decisions.

Methods

Literature search and selection

The published articles were searched based on preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline [15]. The search was performed from June to August 2021 using Google Scholar, PubMed, Science Direct, and HINARI databases. The search queries were set based on medical subject headlines (MESH) and Boolean logic. Relevant MeSH terms and keywords were used to retrieve all relevant articles from the databases listed above. The keywords and MeSH terms used were “enteric bacteria AND diarrhoea AND drug resistance AND Ethiopia”, “Salmonella AND diarrhoea, AND Ethiopia AND drug resistance”, “Shigella AND diarrhoea AND Ethiopia AND drug resistance”, “Escherichia coli AND diarrhoea AND Ethiopia AND drug resistance”, “Campylobacter AND diarrhoea AND Ethiopia AND drug resistance” “Yersinia AND diarrhoea AND Ethiopia AND drug resistance”. Each bacterial genus was searched separately, and a search was also conducted on reference lists of previous studies to increase the chance of getting more articles. Only those articles which fulfil the selection criteria were used to analyse the information.

Inclusion and exclusion criteria

Research conducted on GNEBPs from the diarrhoeic patient or their antimicrobial susceptibility in Ethiopia and full-length published articles in the English language were included in the analysis. To get updated information on the issue, articles published from 2010 to August 2021 were considered. Studies that did not focus on GNEBPs from the diarrhoeic patient or their antimicrobial susceptibility, anonymous reports, abstracts (incomplete information), and published articles before 2010 and unpublished information were not included in the study. Studies that were conducted to assess the knowledge, attitude, and practice (KAP) of the community or the professionals were not also included.

Data extraction

The selected articles were coded, and data were collected using a format prepared in Microsoft Excel. The format consists of the author’s name, study period, year of publication, study design, study region, study population, sample size, sample type, age, gender, isolated bacteria species, their prevalence, resistance patterns of the isolates, and prevalence of multidrug resistance. The extracted data were checked at least twice for their accuracy.

Quality control

The quality of eligible studies was checked using a set of criteria based on Joanna Briggs Institute critical appraisal tools including appropriateness of the research design to address the target population, adequate sample size, quality of paper, completeness of the information, and appropriateness of methods for isolation of the bacteria and appropriate statistical analysis [16]. The eligibility of selected articles was also assessed and approved by experts in the discipline.

Data analysis

The data were compiled in Excel 2010 (Microsoft, Redmond, WA, USA) spreadsheet and summarized by descriptive statistics. A random-effect model was used to determine the pooled prevalence and the 95% confidence interval (CI). All statistical analysis was achieved by using Software for Statistics and Data Science (STATA; https://www.stata.com/company/our-sites/) version 14. The data were described using forest plots, figures, and tables. The presence of publication bias was assessed by funnel plot. Sub-group analysis was performed based on the regions in the country, age group; (children, adults, and all age groups), and year of study (2006–2010, 2011–2015, and 2016–2021). Statistical heterogeneity was evaluated by the inconsistency index (I2) test. The I2 provides an estimate of the percentage of the variability in effect estimates that is due to heterogeneity rather than sampling error or chance differences. Hence, the I2 test measures the level of statistical heterogeneity among studies [17,18].

Results

Characteristics of published articles

Of 7,349 identified studies, 6,680 articles were excluded upon reviewing the titles and abstracts because they were irrelevant (were not focusing on GNEBPs, diarrhoea, and drug resistance or were outside Ethiopia or duplicates). The remaining 669 articles were assessed for eligibility; of these, 626 articles were excluded since they were review, KAP, or meta-analysis studies. Finally, 43 studies meeting the inclusion criteria were included in this study. Selected articles were focusing on one or more GNEBPs. Fig 1 shows a flow diagram of the selection of articles for the analysis.
Fig 1

A flow diagram that shows the selection of articles for the analysis.

Table 1 shows the overall characteristics of articles included in the analysis, type and prevalence of Gram-negative isolates recovered from diarrheic patients. Studies were conducted in 8 regions of the country and most of the published articles were from the Amhara region (30.23%) followed by the Oromia region (18.60%) and South Nation and Nationalities Region (SNNP) (18.60%). Published articles were not found in other regions of the country (Afar, Somali, and Benishangul Gumuz regions) (Fig 2).
Table 1

Characteristics, quality, and the number of Gram-negative isolates recovered from diarrheic patients.

ReferencesYear of publicationStudy periodRegionStudy populationAge categoryGenderNumber examinedNo PositivePrevalenceE. coli Salmonella Shigella Klebsiella Proteus Enterobacter Campylobacter Citrobacter
MaleFemale
[19]2018Aug–Dec 2015Addis AbabaDiarrheic patient<15 yrs1151382539437.15612310
[20]2021Mar 2019 to Nov 2019SNNPdiarrheic patientAdult > 15yrs151127278248.63159
[21]2018Nov 2015 and Aug 2016Amharadiarrheic patient<15 yrs99641639155.8347531172
[22]2020Jan to March 2018AmharaDiarrheic patient, HIV +all163191354246.78177
[23]2020Jan to July 2014Oromiadiarrheic children<15 yrs12511423993.7736
[24]2018June to Sept 2017SNNPdiarrheic patient<15 yrs101103204199.31317
[25]2011Aug to Nov 2009Amharadiarrheic patientall125902153214.8832
[26]2014Feb to May, 2014Amharadiarrheic patientall180192372215.65417
[27]2018June to Oct, 2016Amharadiarrheic patient<15 yrs684411243.5713
[28]2014March to Nov 2012Oromiadiarrheic patient<15 yrs114146260228.46166
[29]2015March to May 2011Oromiadiarrheic patient<15 yrs141024729.177
[30]2020March and Aug 2019SNNPHIV infected diarrheicAdult >15 yrs8496180158.33528
[13]2011Jan to Aug 2006Addis Ababadiarrheic patient<15 yrs654571122512610.296561
[31]2019Nov 2016 and May 2017Addis Ababadiarrheic patient<15 yrs1551352904214.4813722
[32]2013Oct 2011 to March 2012Amharadiarrheic patient<15 yrs1441412854415.4444
[33]2015Dec 2011 to Feb 2012Amharadiarrheic patient<15 yrs2391834227317.303340
[34]2014Feb to May 2011Hararidiarrheic patientall1931913845614.5856
[35]2014June to Oct, 2011SNNPdiarrheic patient<15 yrs81771583522.1541120
[36]2014Dec 2011 to Feb 2012Amharadiarrheic patient<15 yrs422337.8233
[37]2019Feb 2017 to March 2017Oromiadiarrheic patientall991332324218.102220
[38]2020Nov 2016 to Jan 2017Amharadiarrheic patientall181203384205.2120
[39]2015Dec 2011 to Feb 2012Amharadiarrheic patient<15 yrs18323942220448.34204
[40]2016Dec 2013 to Mar 2014Addis Ababadiarrheic patient<15 yrs1251312567830.4778733
[41]2019January to March 2018Amharadiarrheic patient<15 yrs1511212722910.6629
[42]2018Oct 2015 to Feb 2016Oromiadiarrheic patientall223199422399.24309
[43]2014July to Oct 2012Oromiadiarrheic patient<15 yrs1061212273816.7438
[44]2018Mar to May, 2017SNNPdiarrheic patient<15 yrs95721672917.37218
[45]2019June to Dec 2017Gambelladiarrheic patient<15 yrs74601345541.04414
[46]2015August to Nov 2014Tigraydiarrheic patientall109107216156.9415
[47]2014Oct 2011 to June 2012SNNPdiarrheic patientall2211613825714.924017
[48]2011Jan to Feb 2007Hararidiarrheic patientall1191252444518.442817
[49]2019April to July 2016Oromiadiarrheic patient<15 yrs1792434224711.142918
[50]2018Nov 2011 to March 2012Tigraydiarrheic patient<15 yrs1451152603714.231918
[51]2011Oct 2006 to March 2007Amharadiarrheic patientAll1802043846617.19606
[52]2021Apr to Aug 2019SNNPRdiarrheic patientAll130133263217.98120
[53]2015May 2013 to Jan 2014Addis AbabaDiarrheic patientAll425532957596.1759
[54]2020January 2017AmharaDiarrheic patient<15 yrs1521923444513.083564
[55]2016-OromiaDiarrheic patientall84921762111.93192
[56]2015Aug.-Dec. 2012Addis Ababadiarrheic patient<15 yrs11513825310441.1161102310
[57]2017Feb to May, 2016SNNPHIV-infected with Gastroenteritisall1031122152712.56211313
[58]2018Dec. 2014 to March 2015Dire DawaDiarrheic patient<15 yrs105911964321.9425711
[59]2021-Addis Ababadiarrheic patientAll176122298144.7014
[60]2014-Hararidiarrheic patientAll2081763845614.5856

yrs = years, SNNP = Southern Nations, Nationalities, and Peoples’ Region.

Fig 2

Percent of published articles in different regions of Ethiopia.

The country has 9 regions and two city administrations. Reports were from 8 of them which are indicated in the figure. Reports were not found from Afar, Somali, and Benishangul Gumuz regions during the period of data collection (SNNP = South Nation and Nationalities Region).

Percent of published articles in different regions of Ethiopia.

The country has 9 regions and two city administrations. Reports were from 8 of them which are indicated in the figure. Reports were not found from Afar, Somali, and Benishangul Gumuz regions during the period of data collection (SNNP = South Nation and Nationalities Region). yrs = years, SNNP = Southern Nations, Nationalities, and Peoples’ Region. All studies were cross-sectional; conducted from 2006 to 2020 and published online from 2010 to August 2021. Almost all studies (97.67%) were institution-based (conducted on patients visiting health facilities). The stool samples were the specimen used to isolate the bacterial species. Isolates were characterized and their identities were confirmed by cultural and conventional biochemical tests, but molecular techniques were not used. Patients suffering from diarrhoea were used as the population of the studies and three studies were conducted on diarrhoeic patients with HIV. More than half of the studies (55.81%) were focusing on children less than equal to fifteen years of age. However, 39.53% of studies were considering all age groups (Fig 3 and Table 3).
Fig 3

Age categories and percentage of published articles.

Table 3

Bacterial isolates reported by published articles from diarrheic patient.

Bacterial isolatesNo of StudiesStudies reporting the agent (%)No of sampleNo positivePositives (%)Prevalence (%)
MinimumMaximumPooled (95% CI)
Shigella spp.3541.6710,0266325.611.0337.506.24 (4.66–7.81)
Salmonella enterica 3538.0911,3606445.670.3862.505.06 (4.04–6.09)
Escherichia coli 97.1239251421.490.9351.6519.79 (10.48–29.09)
Campylobacter spp.56.0107912311.404.1216.7410.76 (5.62–15.91)
Citrobacter spp.11.2253103.95---
Enterobacter spp.11.216321.23---
Klebsiella spp.11.2163116.75---
Proteus spp.11.216374.29---
Total88*

*An article may report one or more bacterial species from diarrheic patients; No = Number; % = Percent; CI = confident interval.

Prevalence of Gram-negative enteric bacterial pathogens

To isolate GNEBPs, in each study, 24 to 1,225 stool samples were collected. Totally, 13,350 stool samples were examined from 3,688 male and 3,822 female diarrheic patients and 1,962 (14.70%) samples were positive for GNEBPs. The minimum and maximum prevalence of GNEBPs in Ethiopia from diarrhoeic patients were 3.57% [27] and 55.83% [21]. The estimated pooled prevalence of GNEBPs in diarrheic patients from 43 studies was 15.81% (95% CI = 13.33–18.29) (Fig 4).
Fig 4

Forest plot of pooled prevalence estimates of Gram-negative enteric bacterial pathogens among diarrheic patients.

The middle solid vertical line represents the minimum possible prevalence value (0). The dashed line represents the mean pooled prevalence estimate. The black diamond at the centre of the grey box represents the point prevalence estimate of each study and the horizontal line indicates the 95% confidence interval of the estimates. The grey box shows the weight of each study contributing to the pooled prevalence estimate. The last row represents the overall pooled prevalence estimate with a 95% confidence interval.

Forest plot of pooled prevalence estimates of Gram-negative enteric bacterial pathogens among diarrheic patients.

The middle solid vertical line represents the minimum possible prevalence value (0). The dashed line represents the mean pooled prevalence estimate. The black diamond at the centre of the grey box represents the point prevalence estimate of each study and the horizontal line indicates the 95% confidence interval of the estimates. The grey box shows the weight of each study contributing to the pooled prevalence estimate. The last row represents the overall pooled prevalence estimate with a 95% confidence interval. The distribution of the studies using a funnel plot (Fig 5) showed the asymmetrical distribution of effect estimates; hence, there was a publication bias. To minimize the effect of the bias, subgroup analysis was used. Regionally, the pooled prevalence of GNEBPs from diarrheic patients in Addis Ababa, Amhara, SNNPs and Oromia were 20.08, 16.67, 12.12, and 11.61%, respectively. The pooled prevalence based on the study period was 14. 91, 18.03 and 13.46% among studies from 2006–2010, 2011–2015 and 2016–2021, respectively. The pooled prevalence was the highest (20.35%) in children having age less or equal to 15 years, followed by all age groups (10.83%) and adults greater than 15 years (8.51%) (Table 2).
Fig 5

Funnel plot for the prevalence of Gram-negative enteric bacterial pathogens among diarrheic patients.

Table 2

The pooled prevalence of Gram-negative enterobacterial pathogens from diarrheic patients based on different subgrouping criteria.

Subgrouping criteriaCategoriesNo of studiesSample examinedNo PositivePooled prevalence ((%), CI)I2% (p-value)
RegionsAddis Ababa7353251720.08 (12.85–27.31)97.9 (0.00)
Amhara13415168616.67 (10.08–22.48)97.5 (0.00)
SNNP8184722712.12 (9.15–15.08)75.7 (0.00)
Oromia8200222511.61 (7.98–15.24)85.6 (0.00)
Tigray24765210.47 (3.33–17.61)85.5 (0.00)
Harari3101215715.39 (13.17–17.67)0.00 (0.38)
Dire Dawa11964321.94 (16.15–27.73)-
Gambella11345541.04 (32.72–49.37)-
Study period2006–20104206826914.91 (10.44–19.39)84.3 (0.00)
2011–2015216548110618.03 (13.70–22.36)96.8 (0.00)
2016–202118473858713.46 (10.11–16.80)93.8 (0.00)
Age of the study subjectsChildren <15 years247017130820.35 (19.92–24.77)96.8 (0.00)
Adult > 15 years2458398.51 (5.96–11.07)0.00 (0.91)
All age groups17588261510.83 (8.69–12.98)88.0 (0.00)

No = number, % = percent, SNNP = Southern Nations, Nationalities, and Peoples’ Region, CI = confident interval, I = Inconsistency Index.

No = number, % = percent, SNNP = Southern Nations, Nationalities, and Peoples’ Region, CI = confident interval, I = Inconsistency Index. Table 3 shows the types of bacterial isolates reported by published articles from diarrheic patients. Shigella spp. were the most frequent isolate (41.67%), followed by S. enterica (38.09%). The pooled estimate of E. coli was the highest (19.79%) among enteric bacterial isolates. The pooled prevalence of Campylobacter spp., Shigella spp. and Salmonella enterica. were 10.76, 6.24 and 5.06%, respectively. *An article may report one or more bacterial species from diarrheic patients; No = Number; % = Percent; CI = confident interval. Escherichia coli was the most common (15.95%) isolate among children less than or equal to fifteen years of age whereas Salmonella enterica and Shigella spp. were common among studies that were focused on all age groups (Tables 1 and 4).
Table 4

Type bacterial isolates among different age groups.

Age category (years)Type of bacterial IsolatesNo of studiesNo of SampleNo PositivePooled prevalence ((95% CI)
< 15Campylobacter spp.3670102
E. coli8217752415.95 (14.52–17.38)
Salmonella enterica 1958932962.95 (2.52–3.37)
Shigella spp.2057673443.95 (3.45–4.44)
Adult >15Campylobacter spp.11808
Salmonella spp.245820
Shigella spp.245811
All age groupsCampylobacter spp.121513
E. coli12152
Salmonella enterica 1450673813.21 (2.74–3.69)
Shigella spp.1338592213.14 (2.59–3.68)

No = Number; % = Percent; CI = confident interval.

No = Number; % = Percent; CI = confident interval.

Drug resistance patterns of Gram-negative enteric bacterial pathogens

Drug resistance in Shigella spp

Twenty-six antimicrobial panels were used to assess the drug resistance pattern of Shigella spp. The highest percentage of resistance was reported among members of the penicillin group such as ampicillin (85.01%) and amoxicillin (82.07%). Resistance against the tetracycline group was also very common (67.01%). A considerable proportion of resistance was also reported among cephalosporin groups, particularly on the first-generation agents and erythromycin. Resistance was not reported against carbapenems (Table 5).
Table 5

Prevalence of Shigella spp. resistance to different antimicrobial agents in Ethiopia.

Antimicrobial AgentsThe Main group of antimicrobial agentsNo of studiesThe total no of isolates testedNo of resistant isolateResistant isolate (%)Pooled prevalence (%) (95% CI)I2% (p-value)
AmpicillinPenicillins3051945287.0985.01 (79.79–90.22)61.4 (0.00)
AmoxicillinPenicillins1417515387.4382.07 (74.05–89.65)0.00 (0.47)
Augmentin (Amoxicillin and clavulanate potassium)Penicillins and β-lactamase inhibitors101969146.4343.87 (22.5–65.24)93.1 (0.00)
TetracyclineTetracyclines2240430976.4967.01 (55.83–78.36)89.9(0.00)
DoxycyclineTetracyclines2201680.00--
Cephalothin1st G cephalosporins4574070.1870.18 (60.56–100.65)100(-)
Cefoxitin2nd G cephalosporins120630.00--
cefuroxime2nd G cephalosporins1201365.00--
Cefaclor2nd G cephalosporins1171164.71--
Ceftriaxone3rd G cephalosporins141511610.6029.53 (7.80–51.25)79.5 (0.001)
ceftazidime3rd G cephalosporins662711.298.24 (0.42–16.05)0.00 (0.46)
cefotaxime3rd G cephalosporins220420.00--
Ceftizoxime3rd G cephalosporins1401127.5--
ChloramphenicolChloramphenicol3050822043.3136.95 (29.65–44.24)66.7 (0.00)
KanamycinAminoglycosides234720.59-
GentamicinAminoglycosides274438819. 8625.38 (17.78–32.99)70.4
AmikacinAminoglycosides32229.0914.29 (-4.04–32.62)100(-)
StreptomycinAminoglycosides1323196.87--
Nalidixic acidFluoroquinolones171913216.7517.14 (11.34–22.94)0.00(0.69)
NorfloxacinFluoroquinolones14229146.118.34 (4.02–12.66)0.00 (0.976)
CiprofloxacinFluoroquinolones28468326.8411.86 (5.31–18.42)65.6 (0.001)
Trimethoprim-sulphamethoxazoleFolic acid metabolism inhibitors2847627056.7253.00 (44.34–61.67)72.90 (0.00)
MeropenemCarbapenems21100--
ErythromycinMacrolides5382668.4269.67(46.56–92.77)59.9 (0.058)
AzithromycinMacrolides2311032.26--
ClindamycinMacrolides18450--

No = Number; % = Percent; CI = confident interval, I = Inconsistency Index.

No = Number; % = Percent; CI = confident interval, I = Inconsistency Index.

Drug resistance of Salmonella enterica

Twenty-five antimicrobial panels were used to assess the drug resistance patterns of S. enterica. The highest percentage of resistance was reported among members of the penicillin group such as ampicillin (64.98%) and amoxicillin (82.89%). Resistance against tetracycline and trimethoprim-sulphamethoxazole were also common. A considerable proportion of resistance was also reported against erythromycin and cephalosporin groups. Resistance was not reported against doxycycline, meropenem and azithromycin (Table 6).
Table 6

The pooled prevalence of Salmonella enterica resistance to different antimicrobial agents in Ethiopia.

Antimicrobial AgentsThe main group of antimicrobial agentsNo of studiesThe Total no of isolates testedNo of resistant isolateResistant isolate (%)Pooled prevalence (%) (95% CI)I2% (p-value)
AmpicillinPenicillins2958844776.0264.98 (45.2–84.76)96.5 (0.00)
AmoxicillinPenicillins1225522387.4582.89 (70.58–95.21)62.0 (0.072)
Augmentin (Amoxicillin and clavulanate potassium)Penicillins and β-lactamase inhibitors81857540.5445.34 (19.11–71.56)95.2 (0.00)
TetracyclineTetracycline2455528751.7154.59 (41.28–67.90)90.03 (0.00)
DoxycyclineTetracycline23400.00--
Cephalothin1st G cephalosporins29111.11--
Cefaclor2nd G cephalosporins144100.00--
Cefoxitin2nd G cephalosporins133927.27--
Ceftizoxime2nd G cephalosporins121523.81--
cefuroxime2nd G cephalosporins2551629.09--
Ceftriaxone3rd G cephalosporins1638410928.3933.1 (7.88–58.33)98.0 (0.00)
ceftazidime3rd G cephalosporins527414.8129.22 (22.42–8086)81.7 (0.02)
cefotaxime3rd G cephalosporins27228.57--
ChloramphenicolChloramphenicol2962926041.3442.39 (27.39–57.38)96.1(0.00)
KanamycinAminoglycosides3732432.8833.7 (22.72–44.69)0.00 (0.67)
GentamicinAminoglycosides2449112124.6417.36 (7.57–27.15)93.4 (0.00)
AmikacinAminoglycosides32613.85--
Nalidixic acidFluoroquinolones194626614.2914.60 (9.23–19.97)64.2 (0.00)
NorfloxacinFluoroquinolones1020094.505.17 (1.79–8.55)0.00(0.98)
CiprofloxacinFluoroquinolones2828285.297.66 (2.67–12.66)74.8 (0.00)
Trimethoprim-sulphamethoxazoleFolic acid metabolism inhibitors2546421846.9846.72 (29.74–61.69)94.4 (0.00)
MeropenemCarbapenems22000.00--
ErythromycinMacrolides5452555.5652.97 (37.96–68.72)5.8 (0.364)
AzithromycinMacrolides1500.00--
ClindamycinMacrolides111310.88--

No = Number; % = Percent; CI = confident interval, I = Inconsistency Index.

No = Number; % = Percent; CI = confident interval, I = Inconsistency Index.

Drug resistance of Escherichia coli

Sixteen antimicrobial panels were used to assess the drug resistance pattern of E. coli. The highest percentage of resistance was reported on agents like ampicillin (77.97%). Resistance against tetracycline (76.87%) and trimethoprim-sulphamethoxazole (66.97%) were also common. A considerable proportion of resistance was also reported among cephalosporin groups. Resistance was not reported against meropenem (Table 7).
Table 7

The pooled prevalence of Escherichia coli resistance to different antimicrobial agents in Ethiopia.

Antimicrobial AgentsThe main group of antimicrobial agentsNo of studiesThe total no of isolates testedNo of resistant isolateResistant isolate (%)Pooled prevalence (%) (95% CI)I2 (p-value)
AmpicillinPenicillins644635980.4977.97 (70.17–85.76)71.4 (0.00)
AmoxicillinPenicillins147510.64--
Augmentin (Amoxicillin and clavulanate potassium)Penicillins and B-lactamase inhibitors533920460.1864.78 (42.00–87.57)95.0 (0.00)
TetracyclineTetracyclines325319476.6876.87 (71.69–82.05)0.00 (0.563)
Ceftriaxone3rd G cephalosporins5284113.872.91 (0.74–5.08)11.5 (0.34)
Cephalothin1st G cephalosporins147817.02--
cefotaxime3rd G cephalosporins12045024.51--
GentamicinAminoglycosides638810226.2919.72 (7.41–32.03)88.03 (0.00)
AmikacinAminoglycosides111321.77--
ChloramphenicolChloramphenicol537512132.2730.39 (20.95–39.84)67.0 (0.016)
Nalidixic acidFluoroquinolones52243816.9616.71 (11.81–21.6)0.00 (0.713)
NorfloxacinFluoroquinolones2206209.71--
CiprofloxacinFluoroquinolones7439276.155.57 (3.42–7.71)0.00 (0.063)
Trimethoprim-sulphamethoxazoleFolic acid metabolism inhibitors742830170.3366.97 (56.21–77.71)80.7 (0.00)
MeropenemCarbapenems113300--
ErythromycinMacrolides12150--

No = Number; % = Percent; CI = confident interval; I = Inconsistency Index.

No = Number; % = Percent; CI = confident interval; I = Inconsistency Index.

Drug resistance of Campylobacter spp

Eighteen antimicrobial panels were used to assess the drug resistance patterns of Campylobacter spp. The highest percentage of resistance was reported for Cephalothin (81.52%). Resistance against ampicillin (65.61%) and trimethoprim-sulphamethoxazole (52.6%) were also common. Resistance was not reported against meropenem and azithromycin (Table 8).
Table 8

Pooled prevalence of Campylobacter spp. resistance to different antimicrobial agents in Ethiopia.

Antimicrobial AgentsThe main group of antimicrobial agentsNo of studiesThe total no of isolates testedNo of resistant isolateResistant isolate (%)Pooled prevalence (%) (95% CI)I2 (p-value)
AmpicillinPenicillins41107265.4565.61(44.90–86.32)83.3 (0.000
AmoxicillinPenicillins1201680.00--
Augmentin (Amoxicillin and clavulanate potassium)Penicillins and B-lactamase inhibitors1441636.36--
TetracyclineTetracyclines51236048.7842.17 (20.30–64.05)85.4 (0.00)
DoxycyclineTetracyclines3901617.7818.94 (10.5–27.38)0.00 (0.379)
Ceftriaxone3rd G cephalosporins4851517.6539.43 (0.96–77.91)79.0 (0.029)
ceftazidime3rd G cephalosporins18225.00--
Cephalothin1st G cephalosporins31029189.2281.52 (63.78–99.27)63.2 (0.09)
GentamycinAminoglycosides51232923.5830.70 (8.04–53.36)88.0 (0.00)
ChloramphenicolChloramphenicol51232621.1428.03 (10.33–45.85)74.4 (0.00)
Nalidixic acidFluoroquinolones41151311.3010.45 (4.89–16.00)0.00 (0.711)
NorfloxacinFluoroquinolones3951010.5312.02 (4.99–19.05)0.00 (0.665)
CiprofloxacinFluoroquinolones51231915.4513.9 (7.87–19.94)0.00 (0.528)
Trimethoprim-sulphamethoxazoleFolic acid metabolism inhibitors51236754.4752.6 (33.76–71.43)78.4 (0.00)
MeropenemCarbapenems1800.00--
ErythromycinMacrolides51233730.0835.72 (18.34–35.10)78.4 (0.001)
AzithromycinMacrolides1800.00--
ClindamycinMacrolides2822834.15--

No = Number; % = Percent; CI = confident interval; I = Inconsistency Index.

No = Number; % = Percent; CI = confident interval; I = Inconsistency Index.

Drug resistance of other enteric bacterial species

The number of published articles on other enteric bacterial species from diarrheic patients was very limited and impossible to summarize. However, one study conducted by Zenebe et al. [21] reported the presence of Klebsiella spp., Proteus spp., Enterobacter spp. in under-five children with diarrhoea. These bacteria were showing antimicrobial resistance character as indicated in Table 9.
Table 9

Pooled prevalence of other enteric bacterial resistance to different antimicrobial agents in Ethiopia.

Referencesbacterial isolateAmpicillinChloramphenicolGentamicinNalidixic acidTetracyclineCiprofloxacinTrimethoprim-sulphamethoxazoleCeftriaxoneAmoxicillinCephalothin
No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%No isolate testedNo resistance%
[21] Klebsiella 11327.2711218.1811436.361119.0911981.821100.0011872.731100.0011436.3611218.18
[21] Proteus 7228.577114.297342.867457.147228.57700.007228.577114.297342.86700.00
[21] Enterobacter 2150.0200.002150.02150.0200.0200.0200.0200.0200.0200.00

Multidrug resistance

Out of 43 published articles on enteric bacterial pathogens, 32 (74.42%) reported multidrug-resistant (MDR) characters among the isolates. Among 1470 bacterial isolates, 1104 (75.52%) with a pooled prevalence of 70.56% (CI = 64.56–76.77%) were resistant to three or more antimicrobial agents (multidrug resistance). The report showed that the pooled prevalence of MDR in Campylobacter spp., Shigella spp., E. coli and S. enterica were 80.78, 79.08, 78.20 and 59.46%, respectively (Table 10).
Table 10

Multidrug resistance pattern of enteric bacteria pathogens from diarrheic patients.

Type bacterial isolateNo of studiesThe total no of isolates testedNo of multidrug-resistant isolatesMultidrug-resistant isolate (%)Pooled prevalence (%) (95% CI)I2 (p-value)
Shigella spp.2444336381.9479.08 (72.19–85.97)68.2 (0.00)
Salmonella enterica 2349631763.9159.46 (46.13–72.79)91.1 (0.00)
Escherichia coli 641033280.9878.20 (67.46–88.93)84.7 (0.00)
Campylobacter spp.41108779.0980.78 (65.04–96.52)94.6 (0.00)
Klebsiella spp.111545.45--
1470110475.52

No = number, % = percent; CI = confidence interval, I = Inconsistency Index.

No = number, % = percent; CI = confidence interval, I = Inconsistency Index.

Discussion

Diarrhoea is a common health problem, causing mortality and morbidity for thousands of people around the globe. Both infectious and non-infectious agents can induce the problem, among the infectious agents, enteric bacterial pathogens like diarrheagenic E. coli, S. enterica, Shigella spp., and Campylobacter spp. play important roles in the induction or severity of diarrhoea [61]. Determining their burden in a given population is very essential to design strategies for the reduction of the incidence and influences of diarrhoea. The minimum and maximum prevalence of GNEBPs in Ethiopia from diarrhoeic patients were 3.57% [27] and 55.83% [21], respectively. The pooled prevalence of EBP isolates from the stool of diarrheic patients in Ethiopia was 15.81% (CI = 13.33–18.29). In line with this finding, Getie et al. [62] reported 13.2% prevalence of GNEBP in other groups of population (food handlers) in Gondar town, Northwest Ethiopia. On the other hand, Shah et al. [63] reported a 33.62% prevalence of GNEBP in Kenya. The difference may be due to the detection methods since they use molecular techniques in addition to the conventional culturing methods. Almost all studies (97.67%) were institutional, and samples were collected from patients visiting health facilities. Focusing only on health facilities may not reflect the overall prevalence of GNEBPs and their drug resistance patterns in the country. Since some GNEBP infection cases may not arrive at health institutions and widespread use or misuse of antimicrobial drugs in the community may accelerate the occurrence of antimicrobial resistance [64,65]. Sub-grouping of the prevalence of GNEBPs based on the studies conducted in different regions of the country showed that the pooled prevalence was high in Addis Ababa (20.08%). In line with this, a spatial variation across the regions of Ethiopia was reported by Bogale et al. [66]. The difference based on the study period was not significant. However, a declining pattern of diarrhoea at the national level was reported by Bogale et al. [66]. Published articles were from 8 regions of Ethiopia, published articles were not found in Afar, Somali and Benishangul Gumuz regions of the country in this study. Hence, the pooled prevalence was calculated from 8 regions ignoring others. However, the scenario may not be equivalent to the region of the country having no reports. Grouping of study participants based on their age showed that the pooled prevalence was the highest (20.35%) in children having age below or equal to 15 years which indicated that children are more exposed to the GNEBPs and express severe syndromes to visit health facilities. In line with this, Kotloff [4] and Havelaar et al. [67] reported that children contribute a huge proportion of diarrheal diseases in the world. Diarrheagenic E. coli, Shigella spp., S. enterica and Campylobacter spp. were the most common isolates among GNEBPs. In line with this, Getie et al. [62] reported that Shigella spp. enterohemorrhagic E. coli (EHEC) and S. enterica were important isolates of GNEBPs among food handlers. In this study, the pooled estimate of E. coli was the highest (19.79%) among enteric bacterial pathogens. The result is very close to the report of Zenebe et al. [68] who reported that the pooled prevalence of E. coli was 25% in Ethiopia. A 33.8% pooled prevalence was reported by Oppong et al. [69] in Sub-Sharan Africa. Oppong et al. [69] also found that E. coli detection was the highest in the East African region and lowest in the middle part of Africa. The difference may be due to the number of studies in the summary and the targeted strain of E. coli. For example, in a single study in Niger, 11.1% of diarrhoeic children were positive for diarrheagenic E. coli [70]. Similarly, the Global enteric multicentre study on infants and children showed that diarrheagenic E. coli was among the four major pathogens responsible for diarrhoea in low-income and middle-income countries [71]. The pooled prevalence of Campylobacter spp. in this analysis was 10.76%. In line with this report, Kassie et al. [72] reported a prevalence of 10.5% among children in Denbia district, Ethiopia and 13.8% prevalence was also reported by Gedlu and Aseffa [73] among children in northwest Ethiopia. Oppong et al. [69] reported a 12.3% pooled prevalence of Campylobacter in East Africa. A high rate of Campylobacter infection among children was also reported in Kenya [63]. In contrary to the report of this study, Fletcher et al. [74] reported a pooled prevalence of 2.7% in Sub-Saharan countries. The difference may be related to the area coverage, disease prevention and control practices. The pooled prevalence of Shigella spp. in this study was 6.24% which is equivalent to the report of Hussen et al. [75]. According to their report, the pooled prevalence of Shigella spp. in Ethiopia was 6.6%. Similarly, Oppong et al. [69] reported a pooled prevalence of 5.6% from children under five and Fletcher et al. [74] 4.3% of children aged less than 12 years in Sub-Saharan countries. The pooled prevalence of S. enterica was 5.06% which is almost comparable with the reported pooled prevalence by Abate and Assefa [76], which was 4.8% among human stools and animal origin foods in Ethiopia. Resistance to antimicrobial agents is a natural evolutionary process for the bacteria, however, the process is accelerated by human activities in terms of antimicrobial usage patterns and infection control or prevention practices. The risks are very high in developing countries like Ethiopia where there is a widespread use or misuse of antimicrobial agents with a high burden of infectious diseases [76-79]. In this meta-analysis, Shigella isolates were more resistant to the penicillin group of antimicrobial agents like ampicillin (85.01%) and amoxicillin (82.07%). A high percentage of resistance against ampicillin (83.1%) and amoxicillin (84.1%) were also reported by Hussen et al. [75]. There were also reports of drug resistance among the first-line drugs like ciprofloxacin (11.86%) and ceftriaxone (29.53%) for the treatment of Shigellosis. Resistance development against such types of antimicrobial agents was also reported by Hussen et al. [75]. They reported 8.9 and 9.3% resistance against ciprofloxacin and ceftriaxone, respectively. In this analysis, high proportions of Salmonella isolates were also resistant against the penicillin group of antimicrobial agents like ampicillin (64.98%) and amoxicillin (82.89%). In line with this Tadesse [80] was also reported a high percentage (86.01%) of resistance of Salmonella against ampicillin and/or amoxicillin. Resistance of Salmonella isolates to fluoroquinolone like ciprofloxacin (2.27%) and third-generation cephalosporin (ceftriaxone 16.68%) were also reported. Similarly, according to Tadesse’s report, the pooled prevalence of ciprofloxacin resistance among Salmonella isolates was 3.61% [80] and a prevalence of 2.9% of resistance against ciprofloxacin was also reported in Iran [81]. Resistance was common among E. coli isolates in this analysis, particularly on antimicrobial agents like ampicillin (77.97%), tetracycline (76.87%) and trimethoprim-sulphamethoxazole (66.97%). Resistance of E. coli against a wide array of antimicrobials was also reported by Pormohammad et al. [82], Zenebe et al. [68] and Tuem et al. [83]. Resistance in non-pathogenic strains of E. coli may not have a direct effect on health, however, non-pathogenic resistant strains may acquire virulence genes and induce disease that may not be treated easily or non-pathogenic strains having resistant character may act as a reserve for the resistant character for other bacteria [82]. Among Campylobacter isolates in this analysis, the highest percentage of resistance was reported on antimicrobial agents like cephalothin (81.52%), ampicillin (65.61%) and trimethoprim-sulphamethoxazole (52.60%). A resistance pattern of 92.3–100% to erythromycin and the β—lactams, 61.5–86.7% to trimethoprim-sulfamethoxazole, 92.3–93.3% to tetracycline, 46.2–80% to chloramphenicol, 0–60% to aminoglycosides and 0% to imipenem were reported among Campylobacter spp. in Ghana [84]. In this study, among 1470 bacterial isolates 1104 (75.52%) with a pooled prevalence of 70.56%, were resistant to three or more antimicrobial agents (multidrug resistance) (MDR). In line with this finding, Alemayehu [85] reported that the pooled prevalence of multidrug resistance was 70.5% among bacterial isolates in Ethiopia. Another, meta-analysis study on multidrug resistance by Abayneh et al. [86] reported the pooled prevalence of 80.5% among Gram-negative bacteria. It was also very close to the reports from India (66.12%) [87] and Egypt (65.5%) [88,89]. In contrast to our finding in Ethiopia, a lower prevalence of MDR has been reported from Germany (60%) [90], Nepal (42.6%) [91], Australia (36%) [92], Indonesia (28.7%) [93], the USA (27%) [94], Spain (34.5%) [95] and France (11.6%) [96]. Several factors may play a role in the difference including the magnitude and style of antimicrobial use and infection prevention practices. The MDR report among Campylobacter isolates in this analysis (80.78%) was higher than the report from Bangladesh (28.8%) [97] and Kenya 50% [98] but lower than the report from Ghana (97%) [84]. This may be due to differences in the use of antimicrobial agents, the area coverage, sample type and technique of detections. The MDR report of E. coli in this analysis (78.20) was not in line with other reports like 50% prevalence in Nigeria [99], 40% in Spain [95], 22% among human isolates in the world [82], 26% in China [100], 39.8% in Egypt isolates from animals [101], 28% in low and middle-income countries [102]. The MDR report of this meta-analysis among Shigella isolates (79.08) was almost similar to the report by Hussen et al. [75] (83.2%) but it was lower than other reports from Iran (89.4%) [103], and Bangladesh (94%) [104]. However, it was higher than other reports such as 53.8% among migrants in Europe [74], 60% in Kenya [98] and 19% in Somalia [105]. Factors like the magnitude and style of antimicrobial use and infection prevention practices may play roles in the differences. The development of MDR character among S. enterica is also an important public health concern around the globe [106]. In this analysis, the prevalence of MDR character among Salmonella isolate was 59.46% which is comparable with the MDR report of Garedew et al. [107] (46.2%) among food handlers in Gondar. However, it was lower than the report from Dagnew et al. [108] (76%) and Admassu et al. [109] (100%). The difference may be due to the target population and study methods (single versus pooled meta-analysis reports).

Limitations of the study

Some of the studies included in the analysis were targeting the most common bacterial pathogens that did not rule out the absence of others. Therefore, for bacteria that are thought to be less frequent, the reported prevalence may not accurate. Publication bias and heterogenicity were observed in the analysis, but attempts were made to reduce their impact on the analysis by following the random effect model and subgrouping. However, these may not totally avoid their impact on the interpretation of the pooled results.

Conclusion

According to this analysis, the burden of Gram-negative enteric bacterial pathogens (GNEBPs) was high and may be considered a major cause of diarrhoea in Ethiopia. A significant proportion of the isolates exhibited resistance to the commonly used antibacterial agents which are expected to affect the treatment response and cost, morbidity and progression of the infection. Shigella spp., S. enterica, E. coli and Campylobacter spp. were the commonly isolated GNEPB from diarrheic patients in the country. The pooled estimate of Campylobacter spp. was the highest followed by E. coli, Shigella spp. and S. enterica. Resistance to antimicrobial agents was most common among the penicillin groups, followed by tetracycline, and trimethoprim-sulphamethoxazole. However, there were also resistant strains against very relevant drugs for the treatment of GNEBP such as fluoroquinolones and thirdgeneration cephalosporins. Almost all isolates were susceptible to meropenem. Since the incidences of these bacterial diseases are related to hygiene, all activities that enhance hygienic practices (clean water and food, handwashing, proper use of latrine) must be advocated and implemented. Performing drug sensitivity tests for suspected diarrheagenic bacteria is extremely advantageous to select the appropriate antimicrobial drugs for the treatment. The antimicrobial resistance surveillance system must be established to understand the trend of resistance among pathogenic bacteria and to plan and implement mitigating strategies like proper control and prevention of infectious diseases and antimicrobial stewardship programs. Almost all studies were using conventional techniques for confirmation of the isolates, thus, adding molecular methods in the future will increase analysis precision.

Forest plot of pooled prevalence estimates of Gram-negative enteric bacterial pathogens in different regions of Ethiopia.

(DOCX) Click here for additional data file.

Forest plot of pooled prevalence estimates of Gram-negative enteric bacterial pathogens subgrouping based on the study period.

(DOCX) Click here for additional data file.

Forest plot of pooled prevalence estimates of Gram-negative enteric bacterial pathogens subgrouping-based age of the study subjects.

(DOCX) Click here for additional data file.

Frost plot of the studies on Shigella species.

(DOCX) Click here for additional data file.

Frost plot of the studies on Salmonella enterica.

(DOCX) Click here for additional data file.

Frost plot of the studies on Escherichia coli strains.

(DOCX) Click here for additional data file.

Frost plot of the studies on Campylobacter species.

(DOCX) Click here for additional data file.

Frost plot of the studies on multidrug resistance.

(DOCX) Click here for additional data file.

Frost plot of the studies on multidrug resistance of Shigella species.

(DOCX) Click here for additional data file.

Frost plot of the studies on multidrug resistance of Salmonella enterica.

(DOCX) Click here for additional data file.

Frost plot of the studies on multidrug resistance of E. coli.

(DOCX) Click here for additional data file.

Frost plot of the studies on multidrug resistance of Campylobacter species.

(DOCX) Click here for additional data file.

Frost plot of the studies on the prevalence of Escherichia coli in children less than or equal to 15 years of age.

(DOCX) Click here for additional data file. (DOCX) Click here for additional data file.

Frost plot of the studies on the prevalence of Shigella spp in children less than or equal to 15 years of age.

(DOCX) Click here for additional data file.

Frost plot of the studies on the prevalence of Salmonella enterica in all age groups.

(DOCX) Click here for additional data file.

Frost plot of the studies on the prevalence of Shigella species in all age groups.

(DOCX) Click here for additional data file. 17 Jan 2022
PONE-D-21-39208
Prevalence and drug resistance patterns of Gram-negative enteric bacterial pathogens from diarrheic patients in Ethiopia: A systematic review and meta-analysis
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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: 1.Published articles were not found in Afar, Somali, and Benishangul Gumuz regions of the country in this study.It is suggested to be analysed in the discussion section. 2. Table 1 lists the detection techniques and methods used in the article should be better. 3. Analysis of Common Pathogens by Adults and Children in table 3 maybe useful. 4. From table 5 to table 7, If there are too few isolates for statistical analysis, it is recommended to delete relevant information to avoid bias in drug resistance 5.Analysis of Multi-drug resistance pattern by Adults and Children in table 9 maybe useful. Reviewer #2: The manuscript attempts to synthesize information on facility based prevalence of GNEBPs in Ethiopia and determine their AMR patterns. It is extremely important to understand the extent of GNEBP infections and the current resistance profiles for not only instituting surveillance and intervention but also for choosing the right antibiotics for emperical treatment whenever required. Therefore the study is appropriate and in context. It has been done by employing standard PRISMA guidelines. I have the following minor comments that I feel should be addressed by the authors at appropriate sections in the manuscript. 1. The study primarily focuses on E.coli, Campylobacter, Shigella, and Salmonella. While all except E.coli are known to be pathogenic, there is no description on how the studies differentiated DEC from commensal E.coli. The authors have touched upon the fact that resistance of commensal E.coli may not be relevant but may affect those of DEC but methods employed by the various reports to identify DEC is completely missing. In particular, it is said that the studies used conventional methods and not molecular methods and therefore it leaves us wondering how they were differentiated. 2. Was there any information available on co-infections? 3. We often see that GNEBPs constitute only a minor portion of childhood diarrhoeas. For eg. Rotavirus is responsible for almost 30-40% of diarrhoeas in developing countries. In one particular study in India, viral infections accounted for almost 80% of all cases of diarrhoea. Therefore the rampant use/misuse of antimicrobials in developing countries in the first place uncalled for, resulting in unnecessary increase in AMR. The authors should try to bring out this fact also in the discussion section / limitation section so as to advocate rational use of antibiotics. 4. In view of the fact that studies with certain antibiotics taken in the panel e.g Meropenem (Carbapenams), 2nd and 3rd generation Cephalosporins etc are extremely low (1 or 2 only) sweeping statements on not finding resistance to these antibiotics may not be appropriate (only a few of the total isolates were actually tested against these antibiotics). 5. It would have been better to provide trends in antimicrobial resistances in various pathogens that would help clinicians for their choice of empirical treatment, when absolutely required. There are other typos and small grammatical errors e.g many words have got joined together (might be due to PDF conversion or ununiform versions of MSO). There is too much use of the word 'causes' in Introduction lines 68-72; Line 164 after Figure 2, Almost all studies (97.67%) ere institutional-based... may be replaced with 'institution-based'; Line 233 'Resistant against...' may be replaced with 'Resistance against...'. [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
18 Feb 2022 The responses are addressed point by point and attached. Submitted filename: Response to Reviewers.docx Click here for additional data file. 28 Feb 2022 Prevalence and drug resistance patterns of Gram-negative enteric bacterial pathogens from diarrheic patients in Ethiopia: A systematic review and meta-analysis PONE-D-21-39208R1 Dear Dr. Beyene, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Simon Clegg, PhD Academic Editor PLOS ONE Additional Editor Comments: Many thanks for resubmitting your manuscript to PLOS One As you have addressed all the comments and the manuscript reads well, I have recommended it for publication You should hear from the Editorial Office shortly. It was a pleasure working with you and I wish you the best of luck for your future research Hope you are keeping safe and well in these difficult times Thanks Simon 8 Mar 2022 PONE-D-21-39208R1 Prevalence and drug resistance patterns of Gram-negative enteric bacterial pathogens from diarrheic patients in Ethiopia: A systematic review and meta-analysis Dear Dr. Beyene: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Simon Clegg Academic Editor PLOS ONE
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Review 1.  Etiology of diarrhea in older children, adolescents and adults: a systematic review.

Authors:  Christa L Fischer Walker; David Sack; Robert E Black
Journal:  PLoS Negl Trop Dis       Date:  2010-08-03

2.  Spatial patterns of childhood diarrhea in Ethiopia: data from Ethiopian demographic and health surveys (2000, 2005, and 2011).

Authors:  Getahun Gebre Bogale; Kassahun Alemu Gelaye; Degefie Tibebe Degefie; Yalemzewod Assefa Gelaw
Journal:  BMC Infect Dis       Date:  2017-06-15       Impact factor: 3.090

3.  Multidrug-Resistant Shigellosis among Children Aged below Five Years with Diarrhea at Banadir Hospital in Mogadishu, Somalia.

Authors:  Bilan Sheikh Ali Nor; Nelson Chengo Menza; Abednego Moki Musyoki
Journal:  Can J Infect Dis Med Microbiol       Date:  2021-06-08       Impact factor: 2.471

4.  Prevalence, associated risk factors and antimicrobial susceptibility pattern of Campylobacter species among under five diarrheic children at Gondar University Hospital, Northwest Ethiopia.

Authors:  Ayalew Lengerh; Feleke Moges; Chandrashekhar Unakal; Belay Anagaw
Journal:  BMC Pediatr       Date:  2013-05-21       Impact factor: 2.125

5.  Undue reliance on I(2) in assessing heterogeneity may mislead.

Authors:  Gerta Rücker; Guido Schwarzer; James R Carpenter; Martin Schumacher
Journal:  BMC Med Res Methodol       Date:  2008-11-27       Impact factor: 4.615

6.  A meta-analysis of the proportion of antimicrobial resistant human Salmonella isolates in Ethiopia.

Authors:  Getachew Tadesse
Journal:  BMC Pharmacol Toxicol       Date:  2014-09-12       Impact factor: 2.483

7.  Prevalence, seasonal variation, and antibiotic resistance pattern of enteric bacterial pathogens among hospitalized diarrheic children in suburban regions of central Kenya.

Authors:  Mohammad Shah; Cyrus Kathiiko; Akihiro Wada; Erick Odoyo; Martin Bundi; Gabriel Miringu; Sora Guyo; Mohamed Karama; Yoshio Ichinose
Journal:  Trop Med Health       Date:  2016-11-29

8.  Antimicrobial susceptibility pattern, and associated factors of Salmonella and Shigella infections among under five children in Arba Minch, South Ethiopia.

Authors:  Gemechu Ameya; Tsegaye Tsalla; Fasil Getu; Eyob Getu
Journal:  Ann Clin Microbiol Antimicrob       Date:  2018-02-01       Impact factor: 3.944

9.  Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhoea in 195 countries: a systematic analysis for the Global Burden of Disease Study 2016.

Authors: 
Journal:  Lancet Infect Dis       Date:  2018-09-19       Impact factor: 25.071

10.  Enteric pathogens associated with gastroenteritis among children under 5 years in sub-Saharan Africa: a systematic review and meta-analysis.

Authors:  T B Oppong; H Yang; C Amponsem-Boateng; E K D Kyere; T Abdulai; G Duan; G Opolot
Journal:  Epidemiol Infect       Date:  2020-03-02       Impact factor: 2.451
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