Environmental monitoring and assessment · 2022
Antibiotic resistance of airborne bacterial populations in a hospital environment.
СтатьяНазвание и аннотация: Перевод в очереди
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Tamsi Nur Sarah Fatihah, Latif Mohd Talib, Othman Murnira, Abu Bakar Farah Diba, Yusof Hanizah Mohd, Noraini Nor Mohd Razif, Zahaba Maryam, Sahani Mazrura
Аннотация
Bacteria in a hospital environment potentially cause hospital-acquired infections (HAIs), particularly in immunocompromised individuals. Treatments of HAIs with antibiotics, however, are ineffective due to the emergence of antibiotic-resistant bacteria (ARB). This study aims to identify airborne bacteria in a tertiary hospital in Malaysia and screen for their resistance to commonly used broad-spectrum antibiotics. Airborne bacteria were sampled using active sampling at the respiratory ward (RW), physician clinic (PC) and emergency department (ED). Physical parameters of the areas were recorded, following the Industry Code of Practice on Indoor Air Quality 2010 (ICOP IAQ 2010). Bacterial identification was based on morphological and biochemical tests. Antibiotic resistance screening was carried out using the Kirby-Bauer disk diffusion method. Results showed that the highest bacterial population was found in the highest density occupancy area, PC (1024 ± 54 CFU/m3), and exceeded the acceptable limit. Micrococcus spp., Staphylococcus aureus, α- and β-Streptococcus spp., Bacillus spp. and Clostridium spp. colonies were identified at the sampling locations. The antibiotic resistance screening showed a vast percentage of resistance amongst the bacterial colonies, with resistance to ampicillin observed as the highest percentage (Micrococcus spp.: 95.2%, S. aureus: 100%, Streptococcus spp.: 75%, Bacillus spp.: 100% and Clostridium spp.: 100%). This study provides awareness to healthcare practitioners and the public on the status of the emergence of ARB in a hospital environment. Early detection of bacterial populations and good management of hospital environments are important prevention measures for HAI.