Assessment of Antibiotics Resistance from Isolates Responsible for UTI in Four Regional Referral Hospitals in Tanzania

The global impact of antimicrobial resistance (AMR) includes increased morbidity and mortality rates and healthcare costs, particularly in low- and middle-income countries (LMICs), and it has dire economic and security implications. This study assessed the resistance of clinical isolates responsible for urinary tract infections (UTI) to antibacterial agents for treating UTIs in selected healthcare facilities in Tanzania. A total of 151 clinical isolates of <i>E. coli</i> and <i>S. aureus </i>isolated from urine samples in selected health facilities were analyzed for antimicrobial susceptibility to establish the presence of individual and multi-drug resistance (MDR). The results revealed that <i>E. Coli</i> displayed a significant difference in resistance (χ<sup>2</sup> =12.808, p =0.002) across the selected antibiotics, in which<i> E. coli </i>showed the highest resistance to amoxicillin (AML) and the least resistance to meropenem (p <0.005). In contrast, <i>S. aureus isolates </i>showed a significant difference. (χ<sup>2</sup>=53.627, p-value<0.001) in resistance across the selected antibiotics, in which <i>S. aureus </i>showed the highest resistance to AML, peaking at more than 91%, and least resistant (4%) to nitrofurantoin (NIT) (4%). When p-value<0.005, both <i>E. coli</i> and <i>S. aureus </i>demonstrated MDR against selected antibiotics in all health facilities under study, in which Morogoro Regional Referral Hospital showed the highest (65.4%) for<i> E. coli </i>and Benjamin Mkapa Hospital showed the highest (83.3%) for <i>S. aureus. </i>Similarly, Maweni Regional Referral Hospital demonstrated the lowest MDR for<i> E. coli </i>(23%) and <i>S. aureus </i>(13%). Finding suggest that some antibiotics are still in used in clinical practice despite of the evidence of emerging resistance against them hence it call for effective regular AMR surveillance and antimicrobial stewardship implementation to optimize antibiotics use in clinical practice and exclude less efficacious ones.