Bacteriological Assessment of the Indoor Air of Different Hospitals of Kathmandu District

Abstract

Nosocomial infection is the infection that has been caught in a hospital and is potentially caused by organisms that are not susceptible to antibiotics. Nosocomial infections are transmitted directly or indirectly through air and may cause different types of infections. This study was undertaken with an objective to determine the prevalence of nosocomial bacteria present in hospital indoor environment. A total of 16 air samples were taken from general wards and emergency wards of 8 different hospitals using an impactor air sampler in nutrient agar, mannitol salt agar, blood agar, cetrimide agar, and MacConkey agar. The bacteriological agents were isolated and identified by cultural characteristics, Gram staining, and biochemical tests, and their antibiotic susceptibility pattern was determined using CLSI Guideline, 2015. According to the European Union Guidelines to Good Manufacturing Practices, the hospitals were under C- and D-grade air quality. According to the European Commission, most of the hospitals were intermediately polluted. Out of 16 indoor air samples, 47.18% of Staphylococcus aureus and 1.82% Pseudomonas spp. were isolated. CoNS, Streptococcus spp., Micrococcus spp., and Bacillus spp. and Gram-negative bacteria E.coli and Proteus spp. were identified. The bacterial load was found to be high in the emergency ward (55.8%) in comparison to that in the general ward (44.2%). There is statistically no significant difference between bacterial load and 2 wards (general and emergency) of different hospitals and among different hospitals. The most effective antibiotic against S. aureus was gentamicin (81.81%) and ofloxacin (81.81%). Among the antibiotics used for Pseudomonas spp., ceftriaxone (83.3%) and ofloxacin (83.3%) were effective. High prevalence of S. aureus and Gram-negative bacteria was found in this study; it is therefore important to monitor air quality regularly at different hospitals to prevent HAI.