Background: Infectious diseases are serious public health issue both in developing countries and industrialized nations. In developing countries, they are the main cause of high mortality rates. In the second group, existing resistance strains to antibiotics is developing and growing at an alarming rate. The purpose of this study was to produce data of national interest to implement sustainable control program against the spread of antimicrobial resistance strains in Benin. Methods: One hundred and ninety (190) urine samples were collected in selected hospitals in Benin from patients with urinary tract infection. After getting the informed consent from the patients, samples collections were performed under aseptic conditions and cultured for further analysis in the laboratory. The resistance profile of the bacterial strains was established. The search for beta-lactamase production by the isolates was performed using the synergy test for amoxicillin/clavulanic acid and cephalosporins. Mathematical modeling for predicting the development of resistance of the strains by the year 2024 was carried out employing the compartmental deterministic models. Results: Two hundred and thirty (230) strains were identified from the urine samples. Male individuals were the most affected by urinary tract infections. Individuals between the ages of 21-30 were predominantly infected. E. coli was the most isolated species (32.43%) in the urine samples, followed by K. pneumoniae (26.85%) and E. cloacae (25.92%). The susceptibility testing of isolates showed a high resistance to amoxicillin (91.82%). Whereas the lowest resistance was to imipenem (2%). The beta-lactamase was produced by 24.03% of the strains. Escherichia coli (32.43%) was the most productive of broad spectrum beta-lactamase, followed by K. pneumoniae (31.03%). The mathematical modeling revealed a rampant rise in resistance development of the strains to the tested antibiotics. Conclusions: These results provide important data for developing new preventive strategies against the evolution of bacterial resistance to antibiotics. It therefore, further deserves a constructive advocacy so that more actions are taken against the rampant spread of antimicrobial resistance strains in our health facilities as well as in the communities.
Background: Infectious diseases are serious public health issue both in developing countries and industrialized countries. In developing countries, they are the main cause of high mortality rates. In the second group, existing resistance to antibiotics is developing growing at an alarming rate. The purpose of this study was to produce data of national interest to implement sustainable control of antimicrobial resistance as well as it spreads. Methods: One hundred ninety (190) urine samples were collected in several hospitals in Benin from patients suspected of having a urinary tract infection. After getting the inform consent from patients, samples collections were performed under aseptic conditions and were further subjected to bacteriological tests in the laboratory. The resistance profile of the bacterial strains identified was then established. The search for betalactamase production was performed by the synergy test between amoxicillin + clavulanic acid and cephalosporins. Mathematical modeling of the resistance of the strains identified by 2024 was finally carried out using compartmental deterministic models. Results: Two hundred thirty (230) strains were identified from urine samples. Male individuals were the most affected by urinary tract infections. Individuals in the 21-30 age groups were predominant. Escherichia coli was the most isolated bacterial species (32.43%) in this study followed by Klebsiella pneumoniae (26.85%) and Enterobacter cloaceae (25.92%). The susceptibility testing of isolates bacteria to antibiotics showed a strong resistance of strains to amoxicillin (91.82%). The lowest resistance obtained was observed with imipenem (2%). The betalactamase was produced by 24.03% of the strains identified. Escherichia coli (32.43%) was indeed the most productive of betalactamase followed by Klebsiella pneumoniae (31.03%). Mathematical modeling revealed a rampant rise in the resistance of bacteria to the antibiotics tested. Conclusions: These results provide important data for public health. They deserve constructive advocacy so that more specific actions are taken in relation to antimicrobial resistance.
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