Data below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low (10%), medium (35%), high (65%), and severe (90%)) and one real life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a 2.3 genome copies/L limit of detection (LOD). For each data set, 5 methods for handling left-censored data were applied: 1) Substitution with LOD/√2, 2) Lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, 3) Kaplan-Meier estimates (KM), 4) Imputation method using MLE to estimate distribution parameters (MI Method 1), 5) Imputing from a uniform distribution (MI Method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI Method 1 resulted in lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 x 10 from known values under 97% censoring. MI Method 2 was the next overall best method. For medium to severe censoring, MI Method 1 may result in the least error. If unsure of the distribution, MI Method 2 may be a preferred method to avoid distribution misspecification.This study evaluates methods for handling low (10%) to severe (90%) left-censored data within an environmental microbiology context, and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.

The quality of irrigation water drawn from surface water sources varies greatly. This is particularly true for waters that are subject to intermittent contamination events such as runoff from rainfall or direct entry of livestock upstream of use. Such pollution in irrigation systems increases the risk of food crop contamination and require adoption of best monitoring practices. Therefore, this study aimed to define optimal strategies for monitoring irrigation water quality. Following the analysis of 1,357 irrigation water samples for Escherichia coli, total coliforms, and physical and chemical parameters, the following key irrigation water collection approaches are suggested: 1) explore up to 950 m upstream to ensure no major contamination or outfalls exists; 2) collect samples before 12:00 PM local time; 3) collect samples at the surface of the water at any point across the canal where safe access is available; and 4) composite five samples and perform a single E. coli assay. These recommendations comprehensively consider the results as well as sampling costs, personnel effort, and current scientific knowledge of water quality characterization. These strategies will help to better characterize risks from microbial pathogen contamination in irrigation waters in the Southwest United States and aid in risk reduction practices for agricultural water use in regions with similar water quality, climate, and canal construction. HIGHLIGHTS • Microbial testing practices must be based on irrigation water-specific research. • Assaying sample composites is the most cost-effective best representation of microbial content. • Contamination events have 2-log10 reductions 950 m downstream. • Microbial concentrations are highest before noon. • Microbial concentrations are homogenous throughout the canal water column.

Objectives To develop an exposure and risk assessment model to estimate listeriosis infection risks for Peruvian women. Methods A simulation model was developed utilising Listeria monocytogenes concentrations on kitchen and latrine surfaces in Peruvian homes, hand trace data from Peruvian women and behavioural data from literature. Scenarios involving varying proportions of uncontaminated, or ‘clean’, surfaces and non‐porous surfaces were simulated. Infection risks were estimated for 4, 6 and 8 h of behaviours and interactions with surfaces. Results Although infection risks were estimated across scenarios for various time points (e.g. 4, 6, 8 h), overall mean estimated infection risks for all scenarios were ≥ 0.31. Infection risks increased as the proportions of clean surfaces decreased. Hand‐to‐general surface contacts accounted for the most cumulative change in L. monocytogenes concentration on hands. Conclusions In addition to gaining insights on how human behaviours affect exposure and infection risk, this model addressed uncertainties regarding the influence of household surface contamination levels. Understanding the influence of surface contamination in preventing pathogen transmission in households could help to develop intervention strategies to reduce L. monocytogenes infection and associated health risks.

OBJECTIVE To determine whether exposure to UV germicidal irradiation (UVGI) reduces concentrations of viable aerosolized microorganisms (attenuated strains of common veterinary pathogens) in a simulated heating, ventilation, and air conditioning (HVAC) system. SAMPLE 42 air samples seeded with bacteriophage MS2 or attenuated strains of Bordetella bronchiseptica, feline calicivirus, feline herpesvirus-1, canine parvovirus, or canine distemper virus (6/microorganism) or with no microorganisms added (6). PROCEDURES A simulated HVAC unit was built that included a nebulizer to aerosolize microorganisms suspended in phosphate-buffered water, a fan to produce airflow, 2 UVGI bulb systems, and an impinger for air sampling. Ten-minute trials (3 with UVGI, 3 without UVGI, and 1 negative control) were conducted for each microorganism. Impingers collected microorganisms into phosphate-buffered water for subsequent quantification with culture-based assays. Results for samples yielding no target microorganisms were recorded as the assay's lower limit of detection. Statistical analysis was not performed. RESULTS The UVGI treatment resulted in subjectively lower concentrations of viable MS2, B bronchiseptica, and canine distemper virus (arithmetic mean ± SD log10 microorganism reduction, 2.57 ± 0.47, ≥ 3.45 ± 0.24, and ≥ 1.50 ± 0.25, respectively) collected from air. Feline herpesvirus-1 was detected in only 1 sample without and no samples with UVGI treatment. Feline calicivirus and canine parvovirus were not detectable in any collected samples. CONCLUSIONS AND CLINICAL RELEVANCE Results for some surrogates of veterinary pathogens suggested a potential benefit to supplementing manual disinfection practices with UVGI-based air cleaning systems in animal care environments. Further research is needed to investigate the utility of UVGI in operating HVAC systems.

This study suggests a new method for determining the viability of Ascaris spp. ova, based on in-vitro early-to-late stage development of ova. This method includes stages prior to larval development, providing an estimation of potential viability. After application of biosolids onto soil and exposure to 7°C, 22°C, or 37°C for 45 days, ova were microscopically distinguished as viable or non-viable according to progression through development categories. Results were compared to viability estimates from current methods that distinguish viable ova as motile larva. Results suggest conventional techniques underestimate viability, whereas the new method provides a more conservative approach.