Quantitative Microbial Risk Assessment for Spray Irrigation of Dairy Manure Based on an Empirical Fate and Transport Model

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.

Influence of pig farming on human Gut Microbiota: role of airborne microbial communities

It has been hypothesized that both genetics and diet influence the composition of the human cecal microbiota. However, it remains unclear whether and how occupational exposure to microbes impacts the microbial communities in human guts. Using a One Health approach, we visited pig farms (n = 26) and collected stool specimens from pig workers (n = 59), pig barn air samples (n = 19), and rectal swabs from pigs at three different growth stages (n = 144). Stool samples from cattle workers were included as a control group (n = 22). Each sample's microbiota was characterized using 16S rRNA gene sequencing and the DADA2 pipeline.We obtained a significantly different clustering of the microbial compositions of pig and cattle workers by permutational multivariate analysis of variance (PERMANOVA; P < .001). Workers primarily exposed to pigs had higher relative abundances of Prevotellaceae and less Bacteroidaceae than workers exposed to cattle. We also found that the microbial compositions of pig workers' stool samples shared extensive fractions with the samples from their pigs. We also identified amplicon sequencing variants (ASVs) in the airborne microbiota which were likely involved in zoonotic transmission events.We hypothesize that ASVs originating from pig feces are aerosolized and, through breathing, get trapped in the pig farm workers' upper respiratory tract from where they can get swallowed. Consequently, some of the animal associated ASVs are transferred into the gastrointestinal tracts (GITs) which leads to changes in the composition of the human gut microbiota. The importance of this finding for human health must be investigated further.

Risk assessment of Escherichia coli in bioaerosols generated following land application of farmyard slurry

Transfer of Escherichia coli in bioaerosols to humans during and shortly after the land application of farmyard slurry may pose human health hazards, but it has not been extensively explored to date. The present study developed a quantitative risk assessment model for E. coli through the air exposure route. The probabilistic model assessed the predicted number of microorganisms in the air (PN_air) to which humans may be exposed. A Gaussian air dispersion model was used to calculate the concentration of E. coli transmitted through aerosols. Human exposure (HE) to E. coli was estimated using a Monte Carlo simulation approach. This research predicted the mean HE as 26 CFU day^-1 (95th percentile 263 CFU day^-1) and suggests the importance of keeping a distance of at least 100 m for the residential population from land spreading activities. However, the simulated mean daily or annual (once a year application) risk of 2.65 × 10^-7 person^-1 year^-1 due to land application of slurry indicates very low occupational risk for farmworkers not equipped with the personal protective equipment (PPE), who are potentially exposed to E. coli indirectly. The model found that the decay constant of E. coli in air, duration of decay, and bio-aerosolisation efficiency factor (top three) could influence HE to airborne E. coli. Furthermore, this research recommends an average time lag of at least 2.5 h following the application of farmyard slurry to the field before humans access the field again without PPE, allowing the airborne pathogen to decay, thereby ensuring occupational safety. The model suggested that the bio-aerosolisation efficiency factor (E) for other pathogens requires further investigation. The information generated from this model can help to assess likely exposure from bioaerosols triggered by land application of farmyard slurry.

The Environmental Microbiology Minimum Information (EMMI) Guidelines: qPCR and dPCR Quality and Reporting for Environmental Microbiology

Real-time quantitative polymerase chain reaction (qPCR) and digital PCR (dPCR) methods have revolutionized environmental microbiology, yielding quantitative organism-specific data of nucleic acid targets in the environment. Such data are essential for characterizing interactions and processes of microbial communities, assessing microbial contaminants in the environment (water, air, fomites), and developing interventions (water treatment, surface disinfection, air purification) to curb infectious disease transmission. However, our review of recent qPCR and dPCR literature in our field of health-related environmental microbiology showed that many researchers are not reporting necessary and sufficient controls and methods, which would serve to strengthen their study results and conclusions. Here, we describe the application, utility, and interpretation of the suite of controls needed to make high quality qPCR and dPCR measurements of microorganisms in the environment. Our presentation is organized by the discrete steps and operations typical of this measurement process. We propose systematic terminology to minimize ambiguity and aid comparisons among studies. Example schemes for batching and combining controls for efficient work flow are demonstrated. We describe critical reporting elements for enhancing data credibility, and we provide an element checklist in the Supporting Information. Additionally, we present several key principles in metrology as context for laboratories to devise their own quality assurance and quality control reporting framework. Following the EMMI guidelines will improve comparability and reproducibility among qPCR and dPCR studies in environmental microbiology, better inform engineering and public health actions for preventing disease transmission through environmental pathways, and for the most pressing issues in the discipline, focus the weight of evidence in the direction toward solutions.

Quantitative microbial risk assessment of occupational and public risks associated with bioaerosols generated during the application of dairy cattle wastewater as biofertilizer

The reuse or recycling of wastewater provides environmental and economic benefits, representing a sustainable and circular alternative for the management of liquid waste. However, the application of effluents to agricultural crops via spraying creates a potentially dangerous situation for individuals exposed to airborne pathogens. This study used Quantitative Microbial Risk Assessment (QMRA) tools to quantitatively assess the microbial risks of occupational and public exposures to bioaerosols in fertigation scenarios by spraying untreated and treated dairy cattle wastewater. Analyses of Escherichia coli (EC) and spores of Clostridium perfringens (CpSP) in raw and treated effluents as well as pathogen / indicator ratios from the literature were used to estimate the concentrations of Escherichia coli O157:H7 (EC O157:H7) and Cryptospodirium spp. (Crypto) in the air, and the results were applied to an atmospheric microbiological dispersion model. From the concentrations of pathogens in the air, infectious risks for downwind receptors were calculated. The risks of infection by EC O157:H7 to workers at 10 m and 50 m away from the emission source ranged between 3.81 × 10 1 and 2.68 × 10 3 pppy (per person per year), whereas to residents at 100 m and 500 m ranged from 4.59 × 10 1 to 1.51 × 10 4 pppy. Peak values (95th percentile) of occupational and public risks associated with the exposure to Crypto were 3.41 × 10 3 and 6.84 × 10 4 pppy at 10 m and 50 m from the source, respectively, and were lower than 1.48 × 10 6 pppy regarding exposures to CpSP. Anaerobic digestion reduced risks by approximately one order of magnitude. The distance from the source was inversely proportional to the risk of exposure. It is recommended that wastewater is treated prior to its reuse and the adoption of application methods with low aerosolization potential. In addition, the need for workers to use personal protective equipment (PPE) is highlighted.

Roles of Vegetable Surface Properties and Sanitizer Type on Annual Disease Burden of Rotavirus Illness by Consumption of Rotavirus-Contaminated Fresh Vegetables: A Quantitative Microbial Risk Assessment

Enteric viruses are often detected in water used for crop irrigation. One concern is foodborne viral disease via the consumption of fresh produce irrigated with virus-contaminated water. Although the food industry routinely uses chemical sanitizers to disinfect post-harvest fresh produce, it remains unknown how sanitizer and fresh produce properties affect the risk of viral illness through fresh produce consumption. A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)-contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant-based sanitizer. The modeling results showed that the annual disease burden depended on the combination of sanitizer and vegetable type when vegetables were irrigated with RV-contaminated water. Global sensitivity analyses revealed that the most influential factors in the disease burden were RV concentration in irrigation water and postharvest disinfection efficacy. A postharvest disinfection efficacy of higher than 99% (2-log₁₀ ) was needed to decrease the disease burden below the World Health Organization (WHO) threshold, even in scenarios with low RV concentrations in irrigation water (i.e., river water). All scenarios tested here with at least 99.9% (3-log₁₀ ) disinfection efficacy had a disease burden lower than the WHO threshold, except for the endive treated with PAA. The disinfection efficacy for the endive treated with PAA was only about 80%, leading to a disease burden 100 times higher than the WHO threshold. These findings should be considered and incorporated into future models for estimating foodborne viral illness risks.

Quantitative Microbial Risk Assessment and Infectious Disease Transmission Modeling of Waterborne Enteric Pathogens

PURPOSE OF REVIEW

Waterborne enteric pathogens remain a global health threat. Increasingly, quantitative microbial risk assessment (QMRA) and infectious disease transmission modeling (IDTM) are used to assess waterborne pathogen risks and evaluate mitigation. These modeling efforts, however, have largely been conducted independently for different purposes and in different settings. In this review, we examine the settings where each modeling strategy is employed.

RECENT FINDINGS

QMRA research has focused on food contamination and recreational water in high-income countries (HICs) and drinking water and wastewater in low- and middle-income countries (LMICs). IDTM research has focused on large outbreaks (predominately LMICs) and vaccine-preventable diseases (LMICs and HICs). Human ecology determines the niches that pathogens exploit, leading researchers to focus on different risk assessment research strategies in different settings. To enhance risk modeling, QMRA and IDTM approaches should be integrated to include dynamics of pathogens in the environment and pathogen transmission through populations.