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.

Is Personal Protective Equipment Worth the Hassle? Annual Risk of Cryptosporidiosis to Dairy Farmers and How Personal Protective Equipment and Handwashing Can Mitigate It.

Cows are known carriers of Cryptosporidium parvum (C. parvum), a protozoa that can cause the gastrointestinal illness cryptosporidiosis in humans. Despite this potential exposure, dairy farmers tend to wear personal protective equipment (PPE) to protect the milk from contamination, rather than to protect themselves from zoonotic diseases, such as cryptosporidiosis. In this study, cow feces were collected from individual cattle on dairy farms and analyzed for C. parvum using qPCR. Quantitative microbial risk assessment (QMRA) was used to determine the risk of cryptosporidiosis to the dairy farmer with and without the use of handwashing and PPE (gloves and masks). The annualized risk of cryptosporidiosis to dairy farmers was 29.08% but was reduced significantly in each of the three interventions. Among the individual interventions, glove use provided the greatest reduction in risk, bringing the annual risk of cryptosporidiosis to 4.82%. Implementing regular handwashing, the use of gloves and a mask brought the annual risk of cryptosporidiosis to 1.29%. This study provides evidence that handwashing and PPE use can significantly reduce the risk of cryptosporidiosis to farmers and is worth implementing despite potential barriers such as discomfort and cost.

Knowledge to Predict Pathogens: Legionella pneumophila Lifecycle Systematic Review Part II Growth within and Egress from a Host Cell.

Legionella pneumophila (L. pneumophila) is a pathogenic bacterium of increasing concern, due to its ability to cause a severe pneumonia, Legionnaires' Disease (LD), and the challenges in controlling the bacteria within premise plumbing systems. L. pneumophila can thrive within the biofilm of premise plumbing systems, utilizing protozoan hosts for protection from environmental stressors and to increase its growth rate, which increases the bacteria's infectivity to human host cells. Typical disinfectant techniques have proven to be inadequate in controlling L. pneumophila in the premise plumbing system, exposing users to LD risks. As the bacteria have limited infectivity to human macrophages without replicating within a host protozoan cell, the replication within, and egress from, a protozoan host cell is an integral part of the bacteria's lifecycle. While there is a great deal of information regarding how L. pneumophila interacts with protozoa, the ability to use this data in a model to attempt to predict a concentration of L. pneumophila in a water system is not known. This systematic review summarizes the information in the literature regarding L. pneumophila's growth within and egress from the host cell, summarizes the genes which affect these processes, and calculates how oxidative stress can downregulate those genes.

Why pathogens matter for meeting the united nations' sustainable development goal 6 on safely managed water and sanitation.

Water and wastewater utilities, water and sanitation hygiene (WASH) practitioners, and regulating bodies, particularly in developing nations, rely heavily on indicator microorganisms, as opposed to pathogens, for much of their regulatory decisions. This commentary illustrates the importance of considering pathogens and not relying only on indicator organisms when making decisions regarding water and sanitation, especially with respect to meeting the current targets of the Sustainable Development Goal (SDG) 6. We use quantitative microbial risk assessment (QMRA) to present three common scenarios that WASH and public health practitioners encounter to illustrate our point. These include 1) chlorination of surface water for drinking, 2) land application of latrine waste as a fertilizer, and 3) recreation/domestic use of surface waters impacted by wastewater discharge. We show that the calculated probabilities of risk of infection are statistically significantly higher when using treatment/survival information for pathogens versus using indicator species data. Thus, demonstrating that relying solely on indicators for sanitation decision making is inadequate if we truly want to achieve the SDG6 targets of safely managed water and sanitation services.

Legionella pneumophila as a Health Hazard to Miners: A Pilot Study of Water Quality and QMRA.

Legionella pneumophila (L. pneumophila), the causative agent of legionellosis, is an aquatic bacterium that grows in warm water. Humans are only presented with a health risk when aerosolized water containing L. pneumophila is inhaled. In mining operations, aerosolized water is used as dust control and as part of the drilling operations, a currently ignored exposure route. This study characterized L. pneumophila concentrations in the mine's non-potable water and the relationship between L. pneumophila and chlorine concentrations. These concentrations informed a quantitative microbial risk assessment (QMRA) model to estimate the infection risk to miners exposed to aerosolized water containing L. pneumophila. Fourteen water samples were collected from seven locations at a mine and analyzed for temperature, pH, chlorine, and L. pneumophila serogroup. Most samples (93%) tested positive for L. pneumophila cells. The faucet from the sprinkler system on the adit level (entrance to the underground mine levels) showed the highest concentration of L. pneumophila (8.35 × 104 MPN/L). Disability adjusted life years (DALYs) were estimated in the QMRA model and showed that the risk for all miners was significantly lower (p < 0.0001) with the ventilation system on than when the system was off. Our study showed that the use of a ventilation system at the adit level of the mine reduced the risk of infection with aerosolized L. pneumophila.

Dose-Response Models for Eastern US, Western US and Venezuelan Equine Encephalitis Viruses in Mice - Part II: Quantification of the Effects of Host Age on the Dose Response.

Many infectious disease hazards demonstrate higher susceptibility with regards to younger host ages. This trend of increased susceptibility with decreasing host age can also lead to an increased likelihood of mortality, and prolonged/chronic health effects. For quantitative microbial risk assessment (QMRA) modeling, the ability to quantify the effect of host age in the dose response model can allow modelers to account for these effects mechanistically. Additionally, QMRA modelers using age-dependent dose response models can model entire populations within the dose-response itself rather than modeling age ranges using susceptibility factors. This research developed host-age dependent exponential and beta Poisson dose response models for Eastern, Western and Venezuelan encephalitis viruses (EEV, WEV and VEV respectively) for two routes - intracranial and intraperitoneal. Improvement in fit was statistically tested as a means of assessing the benefit of including age dependency into the dose response models. EEV demonstrated improvement in fit using host-age dependency only for the exponential model except for intracranial exposure. EEV demonstrated an improvement in fit when using age dependency in the beta Poisson dose response model for both exposure routes. VEV demonstrated an improvement in fit using age dependency for both exposure routes. WEV demonstrated an improvement in fit for intracranial exposure, but neither of the age dependent dose-response models provided a good fit for WEV intraperitoneal exposure.