Prevalence of Opportunistic Pathogens and Diversity of Microbial Communities in the Water System of a Pulmonary Hospital

Factors That Affect Legionella Positivity in Healthcare Building Water Systems from a Large, National Environmental Surveillance Initiative

Legionella growth in healthcare building water systems can result in legionellosis, making water management programs (WMPs) important for patient safety. However, knowledge is limited on Legionella prevalence in healthcare buildings. A dataset of quarterly water testing in Veterans Health Administration (VHA) healthcare buildings was used to examine national environmental Legionella prevalence from 2015 to 2018. Bayesian hierarchical logistic regression modeling assessed factors influencing Legionella positivity. The master dataset included 201,146 water samples from 814 buildings at 168 VHA campuses. Overall Legionella positivity over the 4 years decreased from 7.2 to 5.1%, with the odds of a Legionella-positive sample being 0.94 (0.90-0.97) times the odds of a positive sample in the previous quarter for the 16 quarters of the 4 year period. Positivity varied considerably more at the medical center campus level compared to regional levels or to the building level where controls are typically applied. We found higher odds of Legionella detection in older buildings (OR 0.92 [0.86-0.98] for each more recent decade of construction), in taller buildings (OR 1.20 [1.13-1.27] for each additional floor), in hot water samples (O.R. 1.21 [1.16-1.27]), and in samples with lower residual biocide concentrations. This comprehensive healthcare building review showed reduced Legionella detection in the VHA healthcare system over time. Insights into factors associated with Legionella positivity provide information for healthcare systems implementing WMPs and for organizations setting standards and regulations.

Antibiotic resistance of airborne bacterial populations in a hospital environment

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.

The Impact of Extreme Weather Events on Bacterial Communities and Opportunistic Pathogens in a Drinking Water Treatment Plant

Drinking water treatment processes are highly effective at improving water quality, but pathogens can still persist in treated water, especially after extreme weather events. To identify how extreme weather events affected bacterial populations in source and treated water, water samples were collected from the Yangtze River Delta area and a local full-scale drinking water treatment plant. Bacterial community structure and the occurrence of pathogens were investigated in samples using 16S rRNA sequencing and qPCR techniques. In this study, the results show that intense rainfall can significantly increase levels of bacteria and opportunistic pathogens in river and drinking water treatment processes (p < 0.05); in particular, the relative abundance of Cyanobacteria increased after a super typhoon event (p < 0.05). The biological activated carbon (BAC) tank was identified as a potential pathogen reservoir and was responsible for 52 ± 6% of the bacteria released downstream, according to Bayesian-based SourceTracker analysis. Our results provide an insight into the challenges faced by maintaining finished water quality under changing weather conditions.

Legionella and Biofilms-Integrated Surveillance to Bridge Science and Real-Field Demands

Legionella is responsible for the life-threatening pneumonia commonly known as Legionnaires’ disease or legionellosis. Legionellosis is known to be preventable if proper measures are put into practice. Despite the efforts to improve preventive approaches, Legionella control remains one of the most challenging issues in the water treatment industry. Legionellosis incidence is on the rise and is expected to keep increasing as global challenges become a reality. This puts great emphasis on prevention, which must be grounded in strengthened Legionella management practices. Herein, an overview of field-based studies (the system as a test rig) is provided to unravel the common roots of research and the main contributions to Legionella’s understanding. The perpetuation of a water-focused monitoring approach and the importance of protozoa and biofilms will then be discussed as bottom-line questions for reliable Legionella real-field surveillance. Finally, an integrated monitoring model is proposed to study and control Legionella in water systems by combining discrete and continuous information about water and biofilm. Although the successful implementation of such a model requires a broader discussion across the scientific community and practitioners, this might be a starting point to build more consistent Legionella management strategies that can effectively mitigate legionellosis risks by reinforcing a pro-active Legionella prevention philosophy.