ABSTRACT
BACKGROUND: The frequent occurrence of bacteria-associated diarrhea together with increased antimicrobial resistance poses a significant public health challenge worldwide. OBJECTIVES: The aim of this study was to assess the prevalence, antimicrobial susceptibility pattern, and associated factors of Salmonella and Shigella among patients with diarrhea at public health facilities in Adama, Ethiopia. METHODS: A cross-sectional study was conducted among 232 patients with diarrhea at public health facilities in Adama, Ethiopia, from February 2017 to March 2017. Data were collected using a structured questionnaire. Stool samples were examined for Salmonella and Shigella species using the culture and serological methods. Descriptive statistics were used to summarize the findings. Logistic regression models were used to assess the association of independent variables with the outcome. A p-value ⩽ 0.05 was considered to be statistically significant. RESULTS: The prevalence of Salmonella and Shigella-associated acute diarrhea was 18.1%. The most common isolates were Shigella dysenteriae (23.8%) and Salmonella typhi (21.4%). S. dysenteriae was 80% resistant to both chloramphenicol and tetracycline. S. typhi was 66.7% resistant to ampicillin, ciprofloxacin, and tetracycline. Those patients aged 11-20 years (adjusted odds ratio: 4.61, 95% confidence interval: 2.48, 7.34), who feed raw vegetables (adjusted odds ratio: 3.67, 95% confidence interval: 1.32, 8.59), and who did not wash hands with soap before a meal (adjusted odds ratio: 2.68, 95% confidence interval: 1.96, 7.48) and after using the toilet (adjusted odds ratio: 3.25, 95% confidence interval: 1.43, 7.36) had higher odds of acute bacterial diarrhea. CONCLUSION: S. dysenteriae and S. typhi were the major causes of acute diarrhea. Most of the isolates showed resistance to ampicillin, ciprofloxacin, and tetracycline. Patients aged 11-20 years, who feed raw vegetables, and who did not wash hands with soap before the meal and after using the toilet had higher odds of acute bacterial diarrhea. Continuous surveillance and the implementation of infection prevention strategies are needed to mitigate acute bacterial diarrhea.
ABSTRACT
BACKGROUND: Respiratory Tract infections continue to be a major cause of morbidity and mortality world wide. There is a failure to treat respiratory infections due to the emergence of antibiotic resistant strains among the most common respiratory pathogens. OBJECTIVES: To evaluate the in vitro antibacterial activities of two traditionally used plants: Albizia gummifera (Ambabesa-Muka, Oromifa, Sessa-Amharic.) and Ferula communis (Doge-Oromifa, Dog-Amharic) against clinical isolates of S. pyogenes and S. pneumoniae. METHODS: The study involving the antibacterial susceptibility test of traditionally used plant species against Gram-positive bacterial pathogens was conducted over a period of 5 months (January - August, 2004) at the Ethiopian Health, and Nutrition Research Institute. The in vitro antibacterial activities of 80% methanol crude extracts prepared from the seeds of Ablizia gummifera and, roots of Ferula communis as well as their respective hydro alcoholic solvent fractionates of both plant species were tested for inhibitory activity against the clinical isolates of six S. pneumonae and twenty two S. pyogenes using agar dilution method. RESULTS: Eighty percent ethanol solubilized fractions of both plants were found to have antibacterial effects to all assayed bacteria while aqueous solubilized fractions did not exhibit any effect. Minimum inhibitory concentration (MIC) of the 80% ethanol solubilized fractions was determined and the MIC of the fractions ranged from 500 mg/ ml to 1000 mg/ml for both plants showing the extracts may contain bioactive compounds of therapeutic interest. CONCLUSION: All extracts showed antibacterial activities against clinical isolates of S. pyogenes and S. pneumoniae. The extracts may contain compounds with potential therapeutic activity. Further purification and identification are needed to be tested using animal models.
