- Research article
- Open Access
- Open Peer Review
A meta-analysis of the proportion of antimicrobial resistant human Salmonella isolates in Ethiopia
© Tadesse; licensee BioMed Central Ltd. 2014
- Received: 8 April 2014
- Accepted: 9 September 2014
- Published: 12 September 2014
Antimicrobial resistant Salmonella is a global problem and recently, a strain on the verge of pan-resistance was reported. In Ethiopia, the therapeutic management of Salmonellosis is difficult because drug sensitivity tests are not routinely carried out and treatment alternatives are not available in most health care facilities. The objectives of this study were to estimate the temporal changes and proportions of drug resistant isolates in Ethiopia.
Published studies on drug resistant Salmonella isolates were searched in Medline, Google Scholar and the lists of references of articles. Eligible studies were selected by using inclusion and exclusion criteria. Generic, methodological and statistical information were extracted from the eligible studies. The extracted data included the proportions of ampicillin, co-trimoxazole, chloramphenicol, ceftriaxone, ciprofloxacin and multi-drug resistant isolates. Pooled proportions were estimated by a random effects model.
The odds of multi-drug resistant isolates in the 2000s was higher than before the 1990s (OR =18.86, 95% CI = 13.08, 27.19). The pooled proportions of ampicillin, co-trimoxazole, chloramphenicol, ciprofloxacin and multi-drug resistant isolates in the 2000s were 86.01%, 68.01%, 62.08%, 3.61% and 79.56% respectively. S. Concord (>97%) was resistant to ampicillin, co-trimoxazole, chloramphenicol and ceftriaxone.
The proportion of drug resistant isolates has increased since the 1970s. All drugs currently used for the treatment of Salmonellosis but ciprofloxacin are not reliable for an empirical therapy. Alternative drugs should be included in the essential drug list and measures should be taken to re-enforce the drug use policy.
- Antimicrobial resistance
The emergence of drug resistant pathogens is associated with a variety of biological, pharmacological and societal variables with the worst combinations in developing countries. Antimicrobial resistant Salmonella is one of the global problems in present day clinical practices and recently, a strain on the verge of pan-resistance was reported. In sub-Saharan Africa (SSA), the prevalence of MDR Salmonella has increased and outbreaks due to MDR strains were recorded[3–5]. Infections with MDR pathogens are associated with excess morbidity and mortality probably because of the co-selection of traits of drug resistance and virulence. In developing countries like Ethiopia, the therapeutic management of the disease is difficult because drug sensitivity tests are not routinely carried out and treatment alternatives are not available in most health care facilities.
Salmonella is one of the major causes of gastroenteritis and fever in Ethiopia. The bacterium was isolated from a number of patients including pediatrics and mal-nourished children. S. Concord, S. Typhi, S. Typhimurium and S. Paratyphi were the dominant serotypes that accounted for 82.1% of the isolates from patients. S. Concord was isolated from a bone processing plant, an immigrant in Ireland, diarrheal and/or febrile patients[12, 13] and Ethiopian adoptees in Europe and the USA[14–16] but its occurrence in other countries in SSA is reportedly low. Typhoidal Salmonella was the second common isolate and a case fatality rate of 15.7% was recorded in hospital admitted children. In 2006, typhoid fever was diagnosed in 37(6.7%) febrile children aged 3-14 years. S. Typhimurium is prevalent in SSA[17–19], highly invasive[20–22] and causes high mortality in AIDS patients.
Despite the importance of the disease, surveillance and monitoring systems are not in place and the pharmaco-epidemiology of the bacteria is not adequately described. However, integration of previous estimates could provide an insight into the temporal changes and the proportions of drug resistant isolates. The objectives of this study were to quantify the temporal changes and estimate the proportions of drug resistant isolates by using meta-analytical methods.
The study was conducted according to the guideline of the PRISMA group (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The PRISMA check list was used to ensure inclusion of relevant information (Additional file1). The outcomes of interest were the proportions of ampicillin, co-trimoxazole, chloramphenicol, ceftriaxone, ciprofloxacin and multi-drug resistant isolates. MDR was defined as resistance to three or more drugs.
Literature search and eligibility criteria
The literature search strategy is described in a previous report. Briefly, studies were searched in Medline, Google scholar and the lists of references of articles. The last search was done on March 30, 2014. To be eligible, a study had to be (i) published, (ii) written in English and (iii) cross sectional or retrospective. Initially, studies with titles and abstracts that are not relevant to the outcomes of interest were excluded. Of the screened articles, duplicates and studies that reported small number of isolates (1-22) were excluded.
The first author, year of study, location, study design, antimicrobial test methods and interpretative standards, numbers of isolates and numbers of drug resistant isolates were extracted. If the proportion of drug sensitive isolates (q) was reported, the number of resistant isolates was calculated by multiplying the number of isolates (n) by one minus the proportion of drug sensitive isolates (1-q). The study level proportions were derived from the extracted data. The data was abstracted by TG.
A zero reported for the numbers of drug resistant or sensitive isolates was imputed as 0.5. The proportions and standard errors were calculated by the following formulae: p = r/n and s. e. =√ p (1-p)/n, where r = number of resistant isolates and n = number of isolates. To normalize the distribution of the data, the proportions were transformed to logit event estimates[26, 27]: lp = ln [p/(1 - p)], where lp = logit event estimate; ln = natural logarithm; p = study level estimate. The variances were calculated by the following formula: v (lp) = 1/ (np) + 1/[n (1 - p)], where v = variance and n = sample size.
Bias and heterogeneity analyses
The antimicrobial test methods and the interpretative standards (break point levels) were examined to assess the within study biases. Funnel plots were used to get visual impressions of the across study biases (small study effects). The Begg and Mazumdar adjusted rank correlation and the Egger’s regression asymmetry tests were used to test the significance of funnel plots’ asymmetries.
Heterogeneities were assessed by the Galbraith plot and the Cochran’s Q test. The percentage of the variation attributable to heterogeneity was quantified by the inverse variance index (I2). As the power of the Cochran’s Q test is low in small number of studies, studies were considered heterogeneous if the ratio of Q and the degree of freedom was greater than one. I2 values of 25% 50% and 75% were considered as low, moderate and high heterogeneity respectively.
Temporal change and trend analyses
The average temporal changes were estimated by using a meta-regression model: y = a + bx + u + e; where a = constant, b = regression coefficient, x = year of study, u = error term with known standard deviation and e = error term of the additive component of the variance (tau2). If two or more calendar years were reported, the median was considered as year of study. Tau2 was estimated by the methods of moments. The Knapp-Hartung variance modification factor was used to calculate the probability values and confidence intervals of the coefficients. The Mantel extension Chi Square for trend was used to assess the changes in the proportion of MDR isolates across decades (1970s/80s, 1990s and 2000s).
Pooling and sensitivity tests
The DerSimonian and Laird random effects model was used to pool logit event estimates. Pooled logit estimates were back-transformed to proportions by the following formula: p = elp/(elp + 1), where p = proportion and e = the base of the natural logarithm. Single study omitted influence analyses were done to assess the sensitivities of pooled estimates. A study was considered to be influential if the pooled estimate without it was not within the 95% confidence bounds of the overall mean. The statistical significance of a difference between proportions was assessed by the Yates corrected Chi Square test[30, 31]. Alpha was set at 0.05.
Microsoft Office Excel 2007 was used to calculate study level proportions, logit event estimates, standard errors and to back-transform logit event estimates to proportions. Epi info™ (Version 3.5.1, Center for Disease Control, CDC, USA) was used to assess the trend and compare proportions. All other analyses were done by using Stata (Version 11.1, Stata Corp, College Station, Texas).
Literature search and eligible studies
Characteristics of the eligible studies
Characteristics of the eligible studies
Number of resistant isolates (%)
Risks of bias and heterogeneity
The disk diffusion method was reported in 11 studies[12, 13, 32–40]. The micro-broth dilution method[14, 41] and the Episilon test (E-test) were used to determine minimum inhibitory concentrations (MIC). Five studies[12, 32, 33, 35, 36] used the breakpoint levels of Bauer et al. 1966 and nine studies used the standards of NCCLS (National Committee for Clinical and Laboratory Standards) or CLISI (Clinical and Laboratory Standards Institute)[13–15, 34, 37–41]. The DTU (Technical University of Denmark) food defined resistance break point levels were used to assess resistance to ceftiofur, florfenicol and aminoglycosides. In five studies carried out before 2000, the proportions of ampicillin resistant isolates were underestimated because the breakpoint level (11 mm or less) was lower than the level (13 mm or less) in the modified versions. Similarly, differences in the break point levels of drugs such as tetracycline (14 mm or less in Bauer et al. 1966 vs. 11 mm or less in the modified versions) might have affected the proportions of MDR isolates. However, as the occurrence of drug resistant isolates in the earlier years was comparatively lower than in the 2000s, the risks of underestimation or overestimation of the study level proportions are negligible.
Temporal changes of the proportions of drug resistant isolates
Pooled proportions of drug resistant Salmonella isolated between 2000 and 2008
Temporal changes and trend
The increase in the proportion of drug resistant isolates could be due to the irrational use of antimicrobials. Several studies have reported the inappropriateness of the prescription and dispensing methods in both the public and private health set-ups. For instance, in Northern Ethiopia, Gondar, ampicillin and penicillin G were two of the three commonly dispensed antimicrobials and most drugs were prescribed by young interns and dispensed by less qualified personnel. In Southern Ethiopia, Hawassa, amoxicillin, ampicillin, chloramphenicol, penicillin G and ceftriaxone were the most commonly prescribed antibacterials. Moreover, the prescriptions had little justifications and the proportion of patients exposed to antimicrobials (>58%)[45–49] was comparatively higher than the standard (20.0%-26.8%). The pediatric age group was more exposed to antimicrobials than adults and the differences between the prescription behaviors of personnel with shorter and longer pre-service trainings and between public and private health facilities were not significant. Furthermore, prescription-only medications were dispensed without a medical prescription; verbal instructions (87%) were practiced in both pharmacies and rural drug vendors and several patients medicate themselves. Essential drug lists, standard treatment guidelines and drug formulary were available in some but not in all health care settings. In general, the prescription and dispensing practices are not consistent with the rational antimicrobial use guideline and could have favored the selection of antimicrobial resistant microbes.
Table 3 presents the pooled estimates of drug resistant isolates in the 2000s. More than half of the isolates were resistant to ampicillin, co-trimoxazole and chloramphenicol. All single study omitted pooled estimates were within the 95% confidence limits of the respective overall means. The pooled estimates show the magnitude of the problem and the unreliability of ampicillin, co-trimoxazole and chloramphenicol as empirical therapeutic agents. Moreover, the occurrences of isolates resistant to ceftriaxone, 89(78.8%) and norfloxacin, 13(15.5%) were reported.
The higher prevalence of MDR isolates could be associated with the presence of Class I integrons in several isolates. Class I integrons were identified in 52 (53.1%) MDR Salmonella predominantly of animal origin and in S. Concord with extended spectrum β-lactamase genes (bla CTX-M-15). As data on the genetic features of isolates of human origin is limited, further genetic characterization of isolates is important to understand evolving and epidemic prone strains.
Pooled proportions of drug resistant S . Concord
MDR features of S . Concord
Amp Chl Cro Gen Sxt
Amp Chl Cro Gen Sxt Tet
Amp Chl Cro Gen Nal Sxt Tet
Amp Azt Chl (Cep Cfp Cfr Cft Cfz Cpo Cro Ctz ) Str SulTmp
Amp Azt Chl (Cep Cfp Cfr Cft Cfz Cpo Ctz ) Str SulTmp
Amp Chl Cro Gen Str Sul Sxt Tmp
Amp Chl Cro Gen Sul Str Sxt Tet Tmp
Amp Chl Cro Gen Nal Str Sul Sxt Tet Tmp
Amp Chl Cfo Cro Gen Str Sul Tet Tmp
Data on the sensitivities of S. Typhi, S. Paratyphi and S. Typhimurium are limited. However, there are evidences on the occurrence of isolates that are resistant to the older drugs[13, 37] and norfloxacin. In addition, S. Typhimurium isolates of animal origin were shown to be resistant to several drugs including ceftiofur and ciprofloxacin[56–61]. Furthermore, MDR genes located on a virulence-associated plasmid of S. Typhimurium were identified and ST313 appears to have occupied a niche provided by HIV, malaria, and malnutrition in SSA.
Implications and limitations
The results of this study have several implications in clinical practices and in policy and research issues. The comparatively lower proportion of ciprofloxacin resistant isolates suggests the potential use of ciprofloxacin as an empirical therapeutic agent. However, as there are evidences of intermediate resistance to ciprofloxacin, alternative drugs should be included in the essential drug list of the country so as to manage severe and life threatening infections. The fluoroquinolones were used to treat children suffering from MDR Gram negative bacterial infections and azithromycin is an attractive alternative against MDR Salmonella[65, 66]. An association between mass oral azithromycin treatment and a reduction in all-cause and infectious mortalities in rural children was recorded.
Policy and decision makers could make use of the evidences as inputs to re-enforce the drug use policy and to devise strategies and measures that could help reduce the rates of emergence of drug resistant pathogens. Apart from the active involvement of the regulatory bodies and the long-arm of the law on drug smuggling and over- the-counter sells of prescription-only drugs, educational initiatives could be of practical significance to reduce the rates of emergence of drug resistant pathogens in the country. Educational programs were reported to be effective in improving the diagnostic qualities of health workers and reducing unjustified prescriptions. Although information sources offer a framework to base educational intervention measures, a regular training is more effective than guidelines alone.
The reservoirs and host ranges of the NTS isolates are unknown and the factors associated with the emergence of drug resistant strains are not adequately described. Some of the strains (e.g. S. Concord) are becoming international concerns and containment of the problem needs an international approach. To this effect, a large scale investigation into the pharmaco-epidemiology of Salmonella is needed and research efforts should be directed towards hypothesis driven preventive measures.
Apart from the small number of eligible studies, the exact origins of the study subjects were not reported. The pooled estimates were also derived from data collected between 2000 and 2009. Therefore, as most patients could be from the urban areas where access to health care facilities is relatively better than the rural areas, the estimates are more applicable to the urban than the rural population and the current proportions of drug resistant isolates may be higher than the present estimates.
The proportion of drug resistant Salmonella has increased since the 1970s and a considerable proportion of the isolates are multi-drug resistant. Ciprofloxacin could be used as an empirical therapeutic agent. The third generation cephalosporins are not useful against S. Concord infections. Alternative drugs should be included in the essential drug list and intervention measures should be taken to re-enforce the drug use policy. Further large scale studies are required to describe the pharmaco-epidemiology of Salmonella in Ethiopia.
TG conceived the design, searched the literature, extracted and analyzed the data, interpreted the results and drafted the manuscript.
I thank Dr. Byleyegne Molla, Dr. Endrias Zewdu, Dr. Sefinew Alemu and Mr. Bayeh Abera for providing me with their articles and Dr. Tesfaye Sisay for his help in literature search.
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