Research gaps and priorities for quantitative microbial risk assessment (QMRA).

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.

Host and Water Microbiota Are Differentially Linked to Potential Human Pathogen Accumulation in Oysters.

Oysters play an important role in coastal ecology and are a globally popular seafood source. However, their filter-feeding lifestyle enables coastal pathogens, toxins, and pollutants to accumulate in their tissues, potentially endangering human health. While pathogen concentrations in coastal waters are often linked to environmental conditions and runoff events, these do not always correlate with pathogen concentrations in oysters. Additional factors related to the microbial ecology of pathogenic bacteria and their relationship with oyster hosts likely play a role in accumulation but are poorly understood. In this study, we investigated whether microbial communities in water and oysters were linked to accumulation of Vibrio parahaemolyticus, Vibrio vulnificus, or fecal indicator bacteria. Site-specific environmental conditions significantly influenced microbial communities and potential pathogen concentrations in water. Oyster microbial communities, however, exhibited less variability in microbial community diversity and accumulation of target bacteria overall and were less impacted by environmental differences between sites. Instead, changes in specific microbial taxa in oyster and water samples, particularly in oyster digestive glands, were linked to elevated levels of potential pathogens. For example, increased levels of V. parahaemolyticus were associated with higher relative abundances of cyanobacteria, which could represent an environmental vector for Vibrio spp. transport, and with decreased relative abundance of Mycoplasma and other key members of the oyster digestive gland microbiota. These findings suggest that host and microbial factors, in addition to environmental variables, may influence pathogen accumulation in oysters. IMPORTANCE Bacteria in the marine environment cause thousands of human illnesses annually. Bivalves are a popular seafood source and are important in coastal ecology, but their ability to concentrate pathogens from the water can cause human illness, threatening seafood safety and security. To predict and prevent disease, it is critical to understand what causes pathogenic bacteria to accumulate in bivalves. In this study, we examined how environmental factors and host and water microbial communities were linked to potential human pathogen accumulation in oysters. Oyster microbial communities were more stable than water communities, and both contained the highest concentrations of Vibrio parahaemolyticus at sites with warmer temperatures and lower salinities. High oyster V. parahaemolyticus concentrations corresponded with abundant cyanobacteria, a potential vector for transmission, and a decrease in potentially beneficial oyster microbes. Our study suggests that poorly understood factors, including host and water microbiota, likely play a role in pathogen distribution and pathogen transmission.

Development of methods to estimate microcystins removal and water treatment resiliency using mechanistic risk modelling.

Drinking water treatment processes are capable of removing microcystins but consistent operation of processes optimized for cyanobacterial harmful algal bloom (cHAB) conditions is not fiscally feasible. Therefore, utilities must ready themselves and start the cHAB processes as a reactionary response. Predictive analytics and modelling are impactful tools to prepare water systems for cHABs, but are still in early stages of development. Until those prospective models are completed, a method to determine best actions in advance of a bloom event thus improving system resiliency is needed. In this study, an adaptation of the quantitative microbial risk analysis (QMRA) methodology was applied to develop this method. This method and resulting models were developed around the Toledo (Ohio, USA) water crisis of 2014, but being mechanistic, they are easily adaptable to other systems' process operations data. Results from this internally validated model demonstrate how rapid action using both powdered activated carbon and measured increases in chlorine dose can mitigate health risks. Our research also demonstrates the importance of modelling the cellular status of the toxins (toxins either in an intact cell or in the water from a lysed cell). Risks were characterized using hazard quotients (HQ) and at the peak of the crisis ranged from a minimum of 0.00244 to a maximum of 2.84 for adults. In simulations where cHAB-specific treatment was used this decreased to 0.00057 and 0.236 respectively. We further outline how this methodology can be used to simulate water system resiliency to likely and aberrant microbial hazard events to plan for the best interventions to protect public health. This method can be used for other hazards expected to be variable in the future, where system prepatory planning is critical to continued public health protection. Considering the water quantity and quality fluctuations occurring and likely to intensify under climate change, this type of computationally supported preparedness is vital to maintaining robust water system resiliency.