What is the relationship between indoor air quality parameters and airborne microorganisms in hospital environments? A systematic review and meta‐analysis. (4th May 2021)

• Record Type: Journal Article
• Authors: Hiwar, Waseem; King, Marco‐Felipe; Shuweihdi, Farag; Fletcher, Louise A.; Dancer, Stephanie J.; Noakes, Catherine J.
• Is Part Of: Indoor air. Volume 31:Number 5(2021)
• Page Start: 1308
• Page End: 1322
• Publication Date: 2021-05-04
• Subjects: airborne microorganisms -- hospital environment -- hospital‐acquired infection -- indoor air quality -- meta‐analysis; Indoor air pollution -- Periodicals; Sick building syndrome -- Periodicals; Ventilation -- Periodicals; 613.5
• DOI: 10.1111/ina.12846
• Languages: English
• ISSNs: 0905-6947

Abstract

Abstract: Airborne microorganisms in hospitals have been associated with several hospital‐acquired infections (HAIs), and various measures of indoor air quality (IAQ) parameters such as temperature, relative humidity, carbon dioxide (CO2 ), particle mass concentration, and particle size have been linked to pathogen survival or mitigation of pathogen spread. To investigate whether there are quantitative relationships between the concentration of airborne microorganisms and the IAQ in the hospital environment. Web of Science, Scopus and PubMed databases were searched for studies reporting airborne microbial levels and any IAQ parameter(s) in hospital environments, from database inception to October 2020. Pooled effect estimates were determined via random‐effects models. Seventeen of 654 studies were eligible for the meta‐analysis. The concentration of airborne microbial measured as aerobic colony count (ACC) was significantly correlated with temperature ( r = 0.25 [95% CI = 0.06–0.42], p = 0.01), CO2 concentration ( r = 0.53 [95% CI = 0.40–0.64], p ˂ 0.001), particle mass concentration (≤5 µg/m 3 ; r = 0.40 [95% CI = 0.04–0.66], p = 0.03), and particle size (≤5 and ˃5 µm), ( r = 0.51 [95% CI = 0.12–0.77], p = 0.01 and r = 0.55 [95% CI = 0.20–0.78], p = 0.003), respectively, while not being significantly correlated with relative humidity or particulate matter of size >5 µm. Conversely, airborne total fungi (TF) were not significantly correlated with temperature, relative humidity, or CO2 level. However, there was a significant weak correlation between ACC and TF ( r = 0.31 [95% CI = 0.07–0.52], p = 0.013). Although significant correlations exist between ACC and IAQ parameters, the relationship is not definitive; the IAQ parameters may affect the microorganisms but are not responsible for the presence of airborne microorganisms. Environmental parameters could be related to the generating source, survival, dispersion, and deposition rate of microorganisms. Future studies should record IAQ parameters and factors such as healthcare worker presence and the activities carried out such as cleaning, sanitizing, and disinfection protocols. Foot traffic would influence both the generation of microorganisms and their deposition rate onto surfaces in the hospital environment. These data would inform models to improve the understanding of the likely concentration of airborne microorganisms and provide an alternative approach for real‐time monitoring of the healthcare environment.