A Case Study Evaluating the Risk of Infection from Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV) in a Hospital Setting Through Bioaerosols.

Middle Eastern respiratory syndrome, an emerging viral infection with a global case fatality rate of 35.5%, caused major outbreaks first in 2012 and 2015, though new cases are continuously reported around the world. Transmission is believed to mainly occur in healthcare settings through aerosolized particles. This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. The exposure scenario includes a single index patient emitting virus-containing aerosols into the air by coughing, leading to short- and long-range airborne exposures for other patients in the same room, nurses, healthcare workers, and family visitors. Aerosol transport modeling was coupled with Monte Carlo simulation to evaluate the risk of MERS illness for the exposed population. Results from a typical scenario show the daily mean risk of infection to be the highest for the nurses and healthcare workers (8.49 × 10-4 and 7.91 × 10-4 , respectively), and the lowest for family visitors and patients staying in the same room (3.12 × 10-4 and 1.29 × 10-4 , respectively). Sensitivity analysis indicates that more than 90% of the uncertainty in the risk characterization is due to the viral concentration in saliva. Assessment of risk interventions showed that respiratory masks were found to have a greater effect in reducing the risks for all the groups evaluated (>90% risk reduction), while increasing the air exchange was effective for the other patients in the same room only (up to 58% risk reduction).

Evaluation of the Influenza Risk Reduction from Antimicrobial Spray Application on Porous Surfaces.

Antimicrobial spray products are used by millions of people around the world for cleaning and disinfection of commonly touched surfaces. Influenza A is a pathogen of major concern, leading to up to 49,000 deaths and 114,000 hospitalizations per year in the United States alone. One of the recognized routes of transmission for influenza A is by transfer of viruses from surfaces to hands and subsequently to mucous membranes. Therefore, routine cleaning and disinfection of surfaces is an important part of the environmental management of influenza A. While the emphasis is generally on spraying hard surfaces and laundering cloth and linens with high temperature machine drying, not all surfaces can be treated in this manner. The quantitative microbial risk assessment (QMRA) approach was used to develop a stochastic risk model for estimating the risk of infection from indirect contact with porous fomite with and without surface treatment with an antimicrobial spray. The data collected from laboratory analysis combined with the risk model show that influenza A infection risk can be lowered by four logs after using an antimicrobial spray on a porous surface. Median risk associated with a single touch to a contaminated fabric was estimated to be 1.25 × 10-4 for the untreated surface, and 3.6 × 10-8 for the treated surface as a base case assumption. This single touch scenario was used to develop a generalizable model for estimating risks and comparing scenarios with and without treatment to more realistic multiple touch scenarios over time periods and with contact rates previously reported in the literature. The results of this study and understanding of product efficacy on risk reduction inform and broaden the range of risk management strategies for influenza A by demonstrating effective risk reduction associated with treating nonporous fomites that cannot be laundered at high temperatures.

Multilevel correlations in the biological phosphorus removal process: From bacterial enrichment to conductivity-based metabolic batch tests and polyphosphatase assays.

Enhanced biological phosphorus removal (EBPR) from wastewater relies on the preferential selection of active polyphosphate-accumulating organisms (PAO) in the underlying bacterial community continuum. Efficient management of the bacterial resource requires understanding of population dynamics as well as availability of bioanalytical methods for rapid and regular assessment of relative abundances of active PAOs and their glycogen-accumulating competitors (GAO). A systems approach was adopted here toward the investigation of multilevel correlations from the EBPR bioprocess to the bacterial community, metabolic, and enzymatic levels. Two anaerobic-aerobic sequencing-batch reactors were operated to enrich activated sludge in PAOs and GAOs affiliating with "Candidati Accumulibacter and Competibacter phosphates", respectively. Bacterial selection was optimized by dynamic control of the organic loading rate and the anaerobic contact time. The distinct core bacteriomes mainly comprised populations related to the classes Betaproteobacteria, Cytophagia, and Chloroflexi in the PAO enrichment and of Gammaproteobacteria, Alphaproteobacteria, Acidobacteria, and Sphingobacteria in the GAO enrichment. An anaerobic metabolic batch test based on electrical conductivity evolution and a polyphosphatase enzymatic assay were developed for rapid and low-cost assessment of the active PAO fraction and dephosphatation potential of activated sludge. Linear correlations were obtained between the PAO fraction, biomass specific rate of conductivity increase under anaerobic conditions, and polyphosphate-hydrolyzing activity of PAO/GAO mixtures. The correlations between PAO/GAO ratios, metabolic activities, and conductivity profiles were confirmed by simulations with a mathematical model developed in the aqueous geochemistry software PHREEQC.

Distribution of antimicrobial resistance across the overall environment of dairy farms - A case study.

The environmental implications of antimicrobial resistance arising from food animal farm practice are still a knowledge gap. This study investigates the fate and transport of antimicrobial resistance genes related to the use of antibiotics on a dairy farm in Michigan. Manure, soil, animal feed, animal drinking water, surface and groundwater samples were taken and the abundance of antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) were subsequently measured using high parallel quantitative PCR targeting 136 genes. The total abundance and detected numbers of ARGs were found to be highest in the stagnant lagoon. Up to 44 ARG subtypes with high abundance were found in drinking water in pen which was very close to those in manure compost. The ARGs pattern clustered by soil depth although they were treated by different manure. ARGs and MGEs were detected in surface and groundwater surrounded by dairy farmlands, with the occurrence of carbapenemase-encoding KPC gene in two waters, which may be due to transport of ARGs through runoff or other sources. Overall, the results of the study suggest high prevalence of ARGs both inside and outside the animal raising area and their potential contribution to environmental ARGs.