Development and application of a dose-response model for Elizabethkingia spp.

Elizabethkingia spp. are common environmental pathogens responsible for infections in more vulnerable populations. Although the exposure routes of concern are not well understood, some hospital-associated outbreaks have indicated possible waterborne transmission. In order to facilitate quantitative microbial risk assessment (QMRA) for Elizabethkingia spp., this study fit dose-response models to frog and mice datasets that evaluated intramuscular and intraperitoneal exposure to Elizabethkingia spp. The frog datasets could be pooled, and the exact beta-Poisson model was the best fitting model with optimized parameters α  = 0.52 and ß = 86,351. Using the exact beta-Poisson model, the dose of Elizabethkingia miricola resulting in a 50% morbidity response (LD50 ) was estimated to be approximately 237,000 CFU. The model developed herein was used to estimate the probability of infection for a hospital patient under a modeled exposure scenario involving a contaminated medical device and reported Elizabethkingia spp. concentrations isolated from hospital sinks after an outbreak. The median exposure dose was approximately 3 CFU/insertion event, and the corresponding median risk of infection was 3.4E-05. The median risk estimated in this case study was lower than the 3% attack rate observed in a previous outbreak, however, there are noted gaps pertaining to the possible concentrations of Elizabethkingia spp. in tap water and the most likely exposure routes. This is the first dose-response model developed for Elizabethkingia spp. thus enabling future risk assessments to help determine levels of risk and potential effective risk management strategies.

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).

Occurrence and fate of PPCPs and correlations with water quality parameters in urban riverine waters of the Pearl River Delta, South China.

The occurrence and fate of eight PPCPs was studied in river waters from upstream to downstream of the three rivers in the Pearl River Delta, China. The correlations of PPCP levels and water quality parameters were also investigated. The analytes of the highest concentrations were caffeine, acetaminophen, and ciprofloxacin. Carbamazepine and erythromycin-H2O were detected at the lowest concentrations. The highest concentrations of PPCPs were found in the Shijing River, with 865 ng/L caffeine, 339 ng/L acetaminophen, and 304 ng/L ciprofloxacin. In general, the levels of PPCPs in the Zhujiang River were higher at sites where the metropolitan city Guangzhou is located and decreased from the epicenter along the river. Low levels of PPCPs were generally found in the Beijiang River. Positive correlations were found between PPCP levels, total nitrogen, ammonium nitrogen, and cumulative fluorescence excitation-emission matrix (EEM) volume. Among the four PPCPs evaluated (caffeine, acetaminophen, ciprofloxacin, and sulfamethoxazole), caffeine had the best correlations with the correlation coefficients ranging from 0.62 to 0.98. The prediction of PPCP concentrations at specified locations can be substantially simplified.