During the third sampling visit the male ward (Room 4), male ward (Room 5), female ward corridor, female ward prep room and female ward (Room 40) had the lowest bacterial counts. This may be attributable to lack of activity in these rooms since patients were discharged at that time of sampling. Counts obtained in this study were lower (≤6.0 × 101 cfu/m-3) when compared with counts (2.54 × 102 cfu/m-3) obtained in another study by Qudiesat and co-workers , and furthermore, counts in the current study were even lower in comparison to the levels of acceptable microbial population
at hospitals. This is the first report on levels of bio-aerosols at this hospital. Even though bacterial counts were low, results indicate biological activity in the air at this hospital
that indicates a need for intervention since https://www.selleckchem.com/products/DMXAA(ASA404).html this is the first report of bioaerosol’ quantification at the hospital under study. Frequent air monitoring is necessary in health-care settings because an increase in microbial counts may place patients as well as staff at high risk of contracting airborne pathogenic microorganisms. Additionally, when the level of microbial activity is known, hospital environmental control procedures can be implemented as an ideal control measure to reduce HAI. Quantification this website of fungal airborne contaminants In general, fungal counts (Figure 2) obtained using the passive and active method in the kitchen area and the, male and female wards ranged between ≥ 4 cfu/m-3, that were isolated during the first sampling round, ≥ 4 cfu/m-3 in the
second sampling round, GABA Receptor ≥ 2 cfu/m-3 in the third sampling round, and ≤ 4.5 × 101 cfu/m-3 in the fourth sampling round. Again counts obtained using passive sampling were higher than counts obtained with active sampling, the Selleckchem GSK1838705A differences observed were statistically significant p = 0.0001 (Figure 2). The current results were contrary to results observed elsewhere  where active sampling was reportedly better at collecting fungal species. The differences are possibly due to the sampling environment which was different in the two studies, Napoli et al.  collected samples from a controlled environment whereas samples in the current study were from an uncontrolled hospital environment. Generally, counts for bacteria and fungi were similar as indicated in the respective figures (Figures 1 and 2). To determine the exact relationships amongst various microbiota, Spearman’s correlation coefficient and F-Test (two-tailed probability) were used to construct a correlation matrix and significant differences. Microbial counts in the kitchen area and the, male and female wards showed a correlation coefficient between bacteria and fungi to be r2 = 0.5 (first sampling rounds), r2 = 0.07 (second sampling rounds), r2 = -0.01 (third sampling rounds) and r2 = -0.3 (fourth sampling rounds) respectively.