Legionellosis is generally attributed to the inhalation of aerosolized Legionella pneumophila from engineered water systems and/or soils. However, aspiration of contaminated water─a known cause of aspiration pneumonia─is seldom modeled in L. pneumophila risk assessment. Here, we develop a quantitative microbial risk assessment model to estimate the risks associated with aspiration exposures. Monte Carlo simulations, incorporating the aspiration water volume, the aspiration frequency, and the alveolar deposition fraction, reveal that low L. pneumophila concentrations in water can yield an appreciable infection risk in populations prone to aspiration. Under equal L. pneumophila concentrations, we find that an aspiration event can pose a higher infection risk than aerosol inhalation from showers or faucets. Sensitivity analyses identify the aspiration volume as a driver of risk. Our findings highlight the need for risk management strategies that address not only aerosol generation but also the aspiration of contaminated water.

Inhalation of aerosols produced during showering exposes people to chemical and microbial contaminants present in the water. To improve quantitative estimates of exposure and to inform the efficacy of potential interventions to reduce exposures, the number and size distributions of aerosols generated during showering events were monitored and a mass balance model of the generated aerosols was developed. The aerosol generation rates were calculated through calibrating the model with the measured aerosol data. Specifically, aerosol count concentrations and size distributions were measured with an aerodynamic particle sizer over the duration of mock showering events under various conditions, including different water temperatures and different showerhead types (conventional and rain showers). The empirical data were then used to fit a mass balance model to obtain aerosol generation rates and decay rates for each aerosol size class through least square fitting. An initial high peak concentration of aerosols was observed under hot water conditions relative to cold water conditions which resulted in a rapid increase in aerosol exposure during the first 1–2 min of showering. This suggests that people showering in hot water conditions will have a potentially increased exposure during the first 1–2 min. The model-fitted values suggest large inter-experiment variation in estimated aerosol generation and decay rates, even among triplicates of the same showering conditions. Current exposure assessment approaches assume constant aerosol concentrations during showers which might lead to miscalculated cumulative risk for microbial hazards because of their uneven distribution in building plumbing systems and biofilm detachment process during flushing. Thus, considering aerosol dynamics is beneficial during shower exposure assessments to inform risk management interventions. The data set and associated modeling results provided can support this, as they can be readily integrated into microbial risk assessments for waterborne pathogens such as Legionella spp., nontuberculous Mycobacteria (NTM) and Pseudomonas aeruginosa.

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose–response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

Risk assessment is critical for identifying target concentrations of antibiotic resistant pathogens necessary for mitigating potential harmful exposures associated with water reuse. However, there is currently limited available data characterizing the concentrations of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in recycled water to support robust efforts at risk assessment. The objective of this systematic review was to identify and synthesize the existing literature documenting the presence and abundance of ARB and ARGs in recycled water. In addition, this review identifies best practices and explores monitoring targets for studying ARB and ARGs in recycled water to guide future work and identifies key research needs aimed at better supporting quantitative microbial risk assessment focused on recycled water and antibiotic resistance. Future efforts to collect data about ARB and ARG prevalence in recycled water should report concentration data per unit volume. Sample metadata should also be provided, including a description of treatment approach, a description of planned water uses (e.g., potable, irrigation), methods for conveyance to the point of use, and available physicochemical water quality data. Additional research is needed aimed at identifying recommended ARB and ARG monitoring targets and for developing approaches to incorporate metagenomic data into risk assessment.

Antibiotic-resistant bacteria and antibiotic resistance genes are abundant in stormwater, yet there is no consensus regarding how to assess their public health risks. We systematically reviewed the literature and identified 15 studies that provided quantitative occurrence and/or abundance information that was linked to stormwater. Sampling and data analysis approaches across studies varied widely, emphasizing that standardized approaches are needed to pool data across studies in a risk analysis. The amounts, timing, and intensity of precipitation within the storm sewershed for fate and transport were rarely considered and/or reported in relation to concentrations of resistance determinants among the reviewed studies. Linking hydrologic and sewershed characteristics to microbial community composition and antibiotic resistance determinants may help improve our understanding of risk and improve sampling protocols. Research needs for ARB and ARG quantification and assessment are discussed, with an emphasis on informing quantitative microbial risk assessments.

The use of aquaculture is increasing to meet the growing global demand for seafood. However, the use of aquaculture for seafood production incurs potential human health risks, especially from enteric bacteria such as Salmonella spp. Salmonella spp. was the most frequently reported cause of outbreaks associated with crustaceans from 1998 to 2004. Among crustacean species, shrimp are the most economically important, internationally traded seafood commodity, and the most commonly aquaculture-raised seafood imported to the United States. To inform safe aquaculture practices, a quantitative microbial risk assessment (QMRA) was performed, incorporating stochastic variability in pathogen growth, industrial shrimp processing, and consumer shrimp preparation. Several scenarios including gamma irradiation and cooking time were considered in order to examine the relative importance of these practices in terms of their impact on risk. Median annual infection risks for all scenarios considered were below 10−4 and median disability adjusted life year (DALY) metrics were below 10−6 DALY per person per year, however, 95th percentile risks were above 10−4 annual probability of infection and 10−6 DALY per person per year for scenarios with improper cooking and lack of gamma irradiation. The greatest difference between microbiological risks for the scenarios tested was observed when comparing proper vs. improper cooking (5–6 orders of magnitude) and gamma irradiation (4–5 orders of magnitude) compared to (up to less than 1 order of magnitude) for peeling and “deveining” (removing the shrimp digestive tract) vs. peeling only. The findings from this research suggest that restriction of Salmonella spp. to low levels (median 5–30 per L aquaculture pond water) may be necessary for scenarios in which proper downstream food handling and processing cannot be guaranteed.