Modeling of spatially referenced environmental and meteorological factors influencing the probability of Listeria species isolation from natural environments

Complete genome sequence of Listeria seeligeri strain 43-1 isolated from a Danish forest freshwater swamp

Here, we report the genome sequence of Listeria seeligeri 43-1 isolated from a Danish freshwater swamp using Oxford Nanopore sequencing. The isolate shared a high genomic similarity to two other L. seeligeri isolates from soil and water.

Antimicrobial Resistance Profiles of Listeria Species Recovered from Retail Outlets in Gauteng Province, South Africa

The study determined the antimicrobial resistance (AMR) profiles of Listeria spp. (L. monocytogenes, L. innocua, and L. welshimeri) recovered from beef and beef products sold at retail outlets in Gauteng Province, South Africa. A total of 112 isolates of Listeria spp., including L. monocytogenes (37), L. innocua (65), and L. welshimeri (10), were recovered from beef and beef products collected from 48 retail outlets. Listeria spp. was recovered by direct selective plating following selective enrichment, and PCR was used to confirm and characterize recovered isolates. The disc diffusion method determined the resistance to 16 antimicrobial agents. All 112 isolates of Listeria spp. exhibited resistance to one or more antibiotics (P < 0.05). The prevalence of AMR in Listeria isolates was high for nalidixic acid (99.1%) and cefotaxime (80.4%) but low for gentamycin (2.7%), sulfamethoxazole-trimethoprim (3.6%), azithromycin (5.4%), and doxycycline (6.3%). Overall, for the three species of Listeria, the prevalence of resistance varied significantly only for streptomycin (P = 0.016) and tetracycline (P = 0.034). Multidrug-resistant isolates were detected in 75.7% (28/37), 61.5% (40/65), and 80% (8/10) isolates of L. monocytogenes, L. innocua, and L. welshimeri, respectively. The prevalence of AMR was significantly affected by the location and size of retail outlets, type of beef and beef products, and serogroups of L. monocytogenes. The high prevalence of AMR, particularly among the L. monocytogenes isolates, poses potential therapeutic implications for human consumers of contaminated beef products. There is, therefore, a need to regulate and enforce the use of antimicrobial agents in humans and animals in South Africa.

Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

Relationship of the Poultry Microbiome to Pathogen Colonization, Farm Management, Poultry Production, and Foodborne Illness Risk Assessment

Despite the continuous progress in food science and technology, the global burden of foodborne illnesses remains substantial, with pathogens in food causing millions of infections each year. Traditional microbiological culture methods are inadequate in detecting the full spectrum of these microorganisms, highlighting the need for more comprehensive detection strategies. This review paper aims to elucidate the relationship between foodborne pathogen colonization and the composition of the poultry microbiome, and how this knowledge can be used for improved food safety. Our review highlights that the relationship between pathogen colonization varies across different sections of the poultry microbiome. Further, our review suggests that the microbiome profile of poultry litter, farm soil, and farm dust may serve as potential indicators of the farm environment's food safety issues. We also agree that the microbiome of processed chicken samples may reveal potential pathogen contamination and food quality issues. In addition, utilizing predictive modeling techniques on the collected microbiome data, we suggest establishing correlations between particular taxonomic groups and the colonization of pathogens, thus providing insights into food safety, and offering a comprehensive overview of the microbial community. In conclusion, this review underscores the potential of microbiome analysis as a powerful tool in food safety, pathogen detection, and risk assessment.

Salmonella Prevalence Is Strongly Associated with Spatial Factors while Listeria monocytogenes Prevalence Is Strongly Associated with Temporal Factors on Virginia Produce Farms

The heterogeneity of produce production environments complicates the development of universal strategies for managing preharvest produce safety risks. Understanding pathogen ecology in different produce-growing regions is important for developing targeted mitigation strategies. This study aimed to identify environmental and spatiotemporal factors associated with isolating Salmonella and Listeria from environmental samples collected from 10 Virginia produce farms. Soil (n = 400), drag swab (n = 400), and irrigation water (n = 120) samples were tested for Salmonella and Listeria, and results were confirmed by PCR. Salmonella serovar and Listeria species were identified by the Kauffmann-White-Le Minor scheme and partial sigB sequencing, respectively. Conditional forest analysis and Bayesian mixed models were used to characterize associations between environmental factors and the likelihood of isolating Salmonella, Listeria monocytogenes (LM), and other targets (e.g., Listeria spp. and Salmonella enterica serovar Newport). Surrogate trees were used to visualize hierarchical associations identified by the forest analyses. Salmonella and LM prevalence was 5.3% (49/920) and 2.3% (21/920), respectively. The likelihood of isolating Salmonella was highest in water samples collected from the Eastern Shore of Virginia with a dew point of >9.4°C. The likelihood of isolating LM was highest in water samples collected in winter from sites where <36% of the land use within 122 m was forest wetland cover. Conditional forest results were consistent with the mixed models, which also found that the likelihood of detecting Salmonella and LM differed between sample type, region, and season. These findings identified factors that increased the likelihood of isolating Salmonella- and LM-positive samples in produce production environments and support preharvest mitigation strategies on a regional scale. IMPORTANCE This study sought to examine different growing regions across the state of Virginia and to determine how factors associated with pathogen prevalence may differ between regions. Spatial and temporal data were modeled to identify factors associated with an increased pathogen likelihood in various on-farm sources. The findings of the study show that prevalence of Salmonella and L. monocytogenes is low overall in the produce preharvest environment but does vary by space (e.g., region in Virginia) and time (e.g., season), and the likelihood of pathogen-positive samples is influenced by different spatial and temporal factors. Therefore, the results support regional or scale-dependent food safety standards and guidance documents for controlling hazards to minimize risk. This study also suggests that water source assessments are important tools for developing monitoring programs and mitigation measures, as spatiotemporal factors differ on a regional scale.

Soil Collected from a Single Great Smoky Mountains Trail Contains a Diversity of Listeria monocytogenes and Listeria spp

Listeria monocytogenes, a foodborne pathogen, and other Listeria spp. are present in natural environments. Isolating and characterizing strains from natural reservoirs can provide insight into the prevalence and diversity of Listeria spp. in these environments, elucidate their contribution to contamination of agricultural and food processing environments and food products, and lead to the discovery of novel species. In this study, we evaluated the diversity of Listeria spp. isolated from soil in a small region of the Great Smoky Mountains National Park, the most biodiverse national park in the U.S. National Park system. Of the 17 Listeria isolates recovered, whole-genome sequencing revealed that 14 were distinct strains. The strains represented a diversity of Listeria species (L. monocytogenes [n = 9], L. cossartiae subsp. cossartiae [n = 1], L. marthii [n = 1], L. booriae [n = 1], and a potentially novel Listeria sp. [n = 2]), as well as a diversity of sequence types based on multilocus sequence typing (MLST) and core genome MLST, including many novel designations. The isolates were not closely related (≥99.99% average nucleotide identity) to any isolates in public databases (NCBI, PATRIC), which also indicated novelty. The Listeria samples isolated in this study were collected from high-elevation sites near a creek that ultimately leads to the Mississippi River; thus, Listeria present in this natural environment could potentially travel downstream to a large region that includes portions of nine southeastern and midwestern U.S. states. This study provides insight into the diversity of Listeria spp. in the Great Smoky Mountains and indicates that this environment is a reservoir of novel Listeria spp. IMPORTANCE Listeria monocytogenes is a foodborne pathogen that can cause serious systemic illness that, although rare, usually results in hospitalization and has a relatively high mortality rate compared to other foodborne pathogens. Identification of novel and diverse Listeria spp. can provide insights into the genomic evolution, ecology, and evolution and variance of pathogenicity of this genus, especially in natural environments. Comparing L. monocytogenes and Listeria spp. isolates from natural environments, such as those recovered in this study, to contamination and/or outbreak strains may provide more information about the original natural sources of these strains and the pathways and mechanisms that lead to contamination of food products and agricultural or food processing environments.

What on earth? The impact of digestates and composts from farm effluent management on fluxes of foodborne pathogens in agricultural lands

The recycling of biomass is the cornerstone of sustainable development in the bioeconomy. In this context, digestates and composts from processed agricultural residues and biomasses are returned to the soil. Whether or not the presence of pathogenic microorganisms in these processed biomasses is a threat to the sustainability of the current on-farm practices is still the subject of debate. In this review, we describe the microbial pathogens that may be present in digestates and composts. We then provide an overview of the current European regulation designed to mitigate health hazards linked to the use of organic fertilisers and soil improvers produced from farm biomasses and residues. Finally, we discuss the many factors that underlie the fate of microbial pathogens in the field. We argue that incorporating land characteristics in the management of safety issues connected with the spreading of organic fertilisers and soil improvers can improve the sustainability of biomass recycling.

Monitoring the effect of environmental conditions on safety of fresh produce sold in Qatar's wholesale market

Fresh produce imported by Qatar are mostly sold at the wholesale produce market (WPM) located in open-air and near major animal markets and slaughterhouses. This study was the first in Qatar to monitor the effect of environmental conditions on the microbial quality and safety of fresh produce sold at the WPM over 1 year. The monitoring involved the collection of 540 produce samples along with samples of air, soil, and surface swabs. Samples were analyzed for total aerobic bacteria (TAB); generic Listeria spp., Staphylococcus spp., Salmonella spp.; total coliforms and total fungi. Bacterial and fungal isolates were identified using 16S rRNA/ITS rRNA markers. Environmental/sanitary factors significantly impacted the prevalence of microorganisms in all samples tested. Produce quality was rated 'poor' during the months of November-February or May-August, with TAB and coliform counts exceeding 6 and 4 log₁₀ CFU/g, respectively. Bacillus subtilus, Enterobacter cloacae, E. faecium, P. expansium, P. aurantiocandidum, and A. niger were the most abundant species with prevalence rate of 11-30%. The high microbial load of environmental samples indicates that the location of the WPM near livestock markets is likely impacting the microbial quality of fresh produce. Therefore, effective control measures need to be implemented at WPM to improve produce safety yearlong.

Listeria monocytogenes in Irrigation Water: An Assessment of Outbreaks, Sources, Prevalence, and Persistence

As more fresh fruits and vegetables are needed to meet the demands of a growing population, growers may need to start depending on more varied sources of water, including environmental, recycled, and reclaimed waters. Some of these sources might be susceptible to contamination with microbial pathogens, such as Listeria monocytogenes. Surveys have found this pathogen in water, soil, vegetation, and farm animal feces around the world. The frequency at which this pathogen is present in water sources is dependent on multiple factors, including the season, surrounding land use, presence of animals, and physicochemical water parameters. Understanding the survival duration of L. monocytogenes in specific water sources is important, but studies are limited concerning this environment and the impact of these highly variable factors. Understanding the pathogen’s ability to remain infectious is key to understanding how L. monocytogenes impacts produce outbreaks and, ultimately, consumers’ health.

WGS analysis of Listeria monocytogenes from rural, urban, and farm environments in Norway: Genetic diversity, persistence, and relation to clinical and food isolates

Listeria monocytogenes is a ubiquitous environmental bacterium associated with a wide variety of natural and human-made environments, such as soil, vegetation, livestock, food processing environments, and urban areas. It is also among the deadliest foodborne pathogens, and knowledge about its presence and diversity in potential sources is crucial to effectively track and control it in the food chain. Isolation of L. monocytogenes from various rural and urban environments showed higher prevalence in agricultural and urban developments than in forest or mountain areas, and that detection was positively associated with rainfall. Whole-genome sequencing (WGS) was performed for the collected isolates and for L. monocytogenes from Norwegian dairy farms and slugs (218 isolates in total). The data were compared to available data sets from clinical and food-associated sources in Norway collected within the last decade. Multiple examples of clusters of isolates with 0 to 8 whole-genome multilocus sequence typing (wgMLST) allelic differences were collected over time in the same location, demonstrating persistence of L. monocytogenes in natural, urban, and farm environments. Furthermore, several clusters with 6 to 20 wgMLST allelic differences containing isolates collected across different locations, times, and habitats were identified, including nine clusters harboring clinical isolates. The most ubiquitous clones found in soil and other natural and animal ecosystems (CC91, CC11, and CC37) were distinct from clones predominating among both clinical (CC7, CC121, and CC1) and food (CC9, CC121, CC7, and CC8) isolates. The analyses indicated that ST91 was more prevalent in Norway than other countries and revealed a high proportion of the hypovirulent ST121 among Norwegian clinical cases.

IMPORTANCEListeria monocytogenes is a deadly foodborne pathogen that is widespread in the environment. For effective management, both public health authorities and food producers need reliable tools for source tracking, surveillance, and risk assessment. For this, whole-genome sequencing (WGS) is regarded as the present and future gold standard. In the current study, we use WGS to show that L. monocytogenes can persist for months and years in natural, urban, and dairy farm environments. Notably, clusters of almost identical isolates, with genetic distances within the thresholds often suggested for defining an outbreak cluster, can be collected from geographically and temporally unrelated sources. The work highlights the need for a greater knowledge of the genetic relationships between clinical isolates and isolates of L. monocytogenes from a wide range of environments, including natural, urban, agricultural, livestock, food production, and food processing environments, to correctly interpret and use results from WGS analyses.

Listeria monocytogenes at the interface between ruminants and humans: A comparative pathology and pathogenesis review

The bacterium Listeria monocytogenes (Lm) is widely distributed in the environment as a saprophyte, but may turn into a lethal intracellular pathogen upon ingestion. Invasive infections occur in numerous species worldwide, but most commonly in humans and farmed ruminants, and manifest as distinct forms. Of those, neuroinfection is remarkably threatening due to its high mortality. Lm is widely studied not only as a pathogen but also as an essential model for intracellular infections and host-pathogen interactions. Many aspects of its ecology and pathogenesis, however, remain unclear and are rarely addressed in its natural hosts. This review highlights the heterogeneity and adaptability of Lm by summarizing its association with the environment, farm animals, and disease. It also provides current knowledge on key features of the pathology and (molecular) pathogenesis of various listeriosis forms in naturally susceptible species with a special focus on ruminants and on the neuroinvasive form of the disease. Moreover, knowledge gaps on pathomechanisms of listerial infections and relevant unexplored topics in Lm pathogenesis research are highlighted.

Survival and Persistence of Foodborne Pathogens in Manure-Amended Soils and Prevalence on Fresh Produce in Certified Organic Farms: A Multi-Regional Baseline Analysis

Biological soil amendments of animal origin (BSAAOs), including untreated (e.g., raw or aged manure, or incompletely composted manure) and treated animal products (e.g., compost), are used for crop production and as part of soil health management. Application of BSAAO's must be done cautiously, as raw manure commonly contains enteric foodborne pathogens that can potentially contaminate edible produce that may be consumed without cooking. USDA National Organic Program (NOP) certified production systems follow the 90-or 120-day interval standards between applications of untreated BSAAOs and crop harvest, depending on whether the edible portions of the crops are in indirect or direct contact with the soil, respectively. This study was conducted to evaluate the survival of four foodborne pathogens in soils amended with BSAAOs and to examine the potential for bacterial transfer to fresh produce harvested from USDA NOP certified organic farms (19) from four states. Only 0.4% (2/527) of produce samples were positive for L. monocytogenes. Among the untreated manure and compost samples, 18.0% (42/233) were positive for at least one of the tested and culturable bacterial foodborne pathogens. The prevalence of non-O157 STEC and Salmonella in untreated manure was substantially &gt; that of E. coli O157:H7 and L. monocytogenes. Of the 2,461 soil samples analyzed in this study, 12.9% (318) were positive for at least one pathogen. In soil amended with untreated manure, the prevalence of non-O157 STEC [7.7% (190) and L. monocytogenes (5.0% (122), was &gt; that of Salmonella (1.1% (26)] or E. coli O157 [0.04% (1)]. Foodborne pathogen prevalence in the soil peaked after manure application and decreased significantly 30 days post-application (dpa). However, non-O157 STEC and L. monocytogenes were recovered from soil samples after 90 and 120 dpa. Results indicate that produce contamination by tested foodborne pathogens was infrequent, but these data should not be generalized outside of the specific wait-time regulations for organic crop production and the farms studied. Moreover, other sources of contamination, e.g., irrigation, wildlife, environmental conditions, cropping and management practices, should be considered. This study also provides multi-regional baseline data relating to current NOP application intervals and development of potential risk mitigation strategies to reduce pathogen persistence in soils amended with BSAAOs. These findings contribute to filling critical data gaps concerning occurrence of fecal pathogens in NOP-certified farming systems used for production of fresh produce in different US regions.

Investigation of the roles of AgrA and σB regulators in Listeria monocytogenes adaptation to roots and soil

Little is known about the regulatory mechanisms that ensure the survival of the food-borne bacterial pathogen Listeria monocytogenes in the telluric environment and on roots. Earlier studies have suggested a regulatory overlap between the Agr cell-cell communication system and the general stress response regulator σB. Here, we investigated the contribution of these two systems to root colonisation and survival in sterilised and biotic soil. The ability to colonise the roots of the grass Festuca arundinacea was significantly compromised in the double mutant (∆agrA∆sigB). In sterile soil at 25°C, a significant defect was observed in the double mutant, suggesting some synergy between these systems. However, growth was observed and similar population dynamics were shown in the parental strain, ΔagrA and ΔsigB mutants. In biotic soil at 25°C, viability of the parental strain declined steadily over a two-week period highlighting the challenging nature of live soil environments. Inactivation of the two systems further decreased survival. The synergistic effect of Agr and σB was stronger in biotic soil. Transcriptional analysis confirmed the expected effects of the mutations on known Agr- and σB-dependent genes. Data highlight the important role that these global regulatory systems play in the natural ecology of this pathogen.

Effect of Weather on the Die-Off of Escherichia coli and Attenuated Salmonella enterica Serovar Typhimurium on Preharvest Leafy Greens following Irrigation with Contaminated Water

The Food Safety Modernization Act (FSMA) includes a time-to-harvest interval following the application of noncompliant water to preharvest produce to allow for microbial die-off. However, additional scientific evidence is needed to support this rule. This study aimed to determine the impact of weather on the die-off rate of Escherichia coli and Salmonella on spinach and lettuce under field conditions. Standardized, replicated field trials were conducted in California, New York, and Spain over 2 years. Baby spinach and lettuce were grown and inoculated with an ∼104-CFU/ml cocktail of E. coli and attenuated Salmonella Leaf samples were collected at 7 time points (0 to 96 h) following inoculation; E. coli and Salmonella were enumerated. The associations of die-off with study design factors (location, produce type, and bacteria) and weather were assessed using log-linear and biphasic segmented log-linear regression. A segmented log-linear model best fit die-off on inoculated leaves in most cases, with a greater variation in the segment 1 die-off rate across trials (-0.46 [95% confidence interval {95% CI}, -0.52, -0.41] to -6.99 [95% CI, -7.38, -6.59] log10 die-off/day) than in the segment 2 die-off rate (0.28 [95% CI, -0.20, 0.77] to -1.00 [95% CI, -1.16, -0.85] log10 die-off/day). A lower relative humidity was associated with a faster segment 1 die-off and an earlier breakpoint (the time when segment 1 die-off rate switches to the segment 2 rate). Relative humidity was also found to be associated with whether die-off would comply with FSMA's specified die-off rate of -0.5 log10 die-off/day.IMPORTANCE The log-linear die-off rate proposed by FSMA is not always appropriate, as the die-off rates of foodborne bacterial pathogens and specified agricultural water quality indicator organisms appear to commonly follow a biphasic pattern with an initial rapid decline followed by a period of tailing. While we observed substantial variation in the net culturable population levels of Salmonella and E. coli at each time point, die-off rate and FSMA compliance (i.e., at least a 2 log10 die-off over 4 days) appear to be impacted by produce type, bacteria, and weather; die-off on lettuce tended to be faster than that on spinach, die-off of E. coli tended to be faster than that of attenuated Salmonella, and die-off tended to become faster as relative humidity decreased. Thus, the use of a single die-off rate for estimating time-to-harvest intervals across different weather conditions, produce types, and bacteria should be revised.

An Assessment of Listeriosis Risk Associated with a Contaminated Production Lot of Frozen Vegetables Consumed under Alternative Consumer Handling Scenarios

Frozen foods do not support the growth of Listeria monocytogenes (LM) and should be handled appropriately for safety. However, consumer trends regarding preparation of some frozen foods may contribute to the risk of foodborne listeriosis, specifically when cooking instructions are not followed and frozen products are instead added directly to smoothies or salads. A quantitative microbial risk assessment model FFLLoRA (Frozen Food Listeria Lot Risk Assessment) was developed to assess the lot-level listeriosis risk due to LM contamination in frozen vegetables consumed as a ready-to-eat food. The model was designed to estimate listeriosis risk per serving and the number of illnesses per production lot of frozen vegetables contaminated with LM, considering individual facility factors such as lot size, prevalence of LM contamination, and consumer handling prior to consumption. A production lot of 1 million packages with 10 servings each was assumed. When at least half of the servings were cooked prior to consumption, the median risk of invasive listeriosis per serving in both the general and susceptible population was <1.0 × 10^-16 with the median (5th, 95th percentiles) predicted number of illnesses per lot as 0 (0, 0) and 0 (0, 1) under the exponential and Weibull-gamma dose-response functions, respectively. In scenarios in which all servings are consumed as ready-to-eat, the median predicted risk per serving was 1.8 × 10^-13 and 7.8 × 10^-12 in the general and susceptible populations, respectively. The median (5th, 95th percentile) number of illnesses was 0 (0, 0) and 0 (0, 6) for the exponential and Weibull-Gamma models, respectively. Classification tree analysis highlighted initial concentration of LM in the lot, temperature at which the product is thawed, and whether a serving is cooked as main predictors for illness from a lot. Overall, the FFLLoRA provides frozen food manufacturers with a tool to assess LM contamination and consumer behavior when managing rare and/or minimal contamination events in frozen foods.

Amplicon sequencing and imputed metagenomic analysis of waste soil and sediment microbiome reveals unique bacterial communities and their functional attributes

The discharge of solid and liquid waste from domestic, municipal, and hospital premises pollutes the soil and river ecosystems. However, the diversity and functions of the microbial communities present in these polluted environments are not well understood and may contain harmful microbial communities with specialized metabolic potential. In this present study, we adapted the Illumina sequencing technology to analyze microbial communities and their metabolic capabilities in polluted environments. A total of 1113884 sequences of v3-v4 hypervariable region of the 16S rRNA were obtained using Illumina sequencing and assigned to the corresponding taxonomical ranks using Greengenes databases. Proteobacteria and Bacteroidetes were dominantly present in all the four studied sites (solid waste dumping site (SWD); Chite river site (CHR), Turial river site (TUR), and Tuikual river site (TUKR)). It was found that the SWD was dominated by Firmicutes, Actinobacteria; CHR by Acidobacteria, Verrucomicrobia, Planctomycetes; TUR by Verrucomicrobia, Acidobacteria; and TUKR by Verrucomicrobia and Firmicutes, respectively. The dominant bacterial genus present in all samples was Acinetobacter, Flavobacterium, Prevotella, Corynebacterium, Comamonas, Bacteroides, Wautersiella, Cloacibacterium, Stenotrophomonas, Sphingobacterium, and Pseudomonas. Twenty-seven putative bacterial pathogens were identified from the contaminated sites belonging to Salmonella enterica, Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus. Functional analysis showed a high representation of genes in the KEGG pathway involved in the metabolism of amino acids and carbohydrates and identified several genes associated with antibiotic resistance and xenobiotic degradation in these environments, which can be a serious problem for human health and environment. The results from this research will provide a new understanding of the possible management practices to minimize the spread of pathogenic microorganisms in the environment.

Salmonella and the changing environment: systematic review using New York State as a model

Salmonella is a public health concern, for which a complex interplay between host, agent, and environment exists. An improved understanding of causal processes can be used to better gauge the causes and trajectory of Salmonella in a changing environment. This would be useful in determining the impact of climate change on the New York State (NYS) environment, the effect of climate change on Salmonella in NYS, factors contributing to Salmonella vulnerability in humans, and aspects of climate change and Salmonella which necessitate further research. A systematic review was conducted to study associations between Salmonella and the environment. Using the search criteria, a total of 91 relevant articles were identified from four electronic databases. Key information was abstracted, organized, and synthesized to identify causal processes and linkages between climate change, the environment of NYS, and Salmonella-related outcomes, as well as risk factors to characterize Salmonella vulnerabilities. Three inter-related domains were identified for consideration and application to epidemiological research to confirm and extrapolate disease patterns using climate change scenarios: improved quantification of causal relationships, inclusion of factors linked to sectors not immediately associated with the exposure and outcome, and increased capacity to validate models in diverse settings.

Comparison between random forest and gradient boosting machine methods for predicting Listeria spp. prevalence in the environment of pastured poultry farms

Foodborne pathogens such as Listeria spp. contain the ability to survive and multiply in poultry farming environments, which provides a route of contamination for poultry processing environments and final poultry products. An understanding of the effect of meteorological variables on the prevalence of Listeria spp. in the farming environment is lacking. Soil and feces samples were collected from 11 pastured poultry farms from 2014 to 2017. Random forest (RF) and gradient boosting machine (GBM) predictive models were generated to describe and predict Listeria spp. prevalence in feces and soil samples based on meteorological factors at the farming location. This study attempted to demonstrate the use of GBM models in a food safety context and compare their use to RF models. Both feces models performed very well, with area under the curve (AUC) values of 0.905 and 0.855 for the RF and GBM models, respectively. The soil GBM model outperformed the RF model with AUCs of 0.873 and 0.700, respectively. The developed models can be used to predict the prevalence of Listeria spp. in pastured poultry farm environments and should be of great use to poultry farmers, producers, and risk managers.

Identifying and modeling meteorological risk factors associated with pre-harvest contamination of Listeria species in a mixed produce and dairy farm

This study sought to investigate the prevalence of Listeria species (including L. monocytogenes) in a mixed produce and dairy farm and to identify specific meteorological factors affecting Listeria spp. presence. Environmental samples were collected monthly from locations within the mixed farm over 14months and were analyzed for Listeria spp. Meteorological factors were evaluated for their association with the presence of Listeria spp. by using logistic regression (LR) and random forest (RF). The developed LR model identified wind speed and precipitation as significant risk factors (P<0.05), indicating higher wind speed at day 2 prior to sampling and higher average precipitation over the previous 25days before sampling increased the probability of isolation of Listeria spp. from the mixed farm. Results from RF revealed that average wind speed at day 2 prior to sampling and average precipitation in the previous 25days before sampling were the most important factors influencing the presence of Listeria spp., which supported the findings from LR. These findings indicate that the occurrence of Listeria spp. was influenced by wind speed and precipitation, suggesting run-off and wind-driven dust might be possible routes of pathogen transmission in mixed farms. The developed LR and RF models, with robust predictive performances as measured by the area under the receiver operating characteristic curves, can be used to predict Listeria spp. contamination risk in a mixed farm under different weather conditions and can help with the evaluation of farm management practices and the development of control strategies aimed at reducing pre-harvest microbial contamination in a mixed farming system.

The Role of Stress and Stress Adaptations in Determining the Fate of the Bacterial Pathogen Listeria monocytogenes in the Food Chain

The foodborne pathogen Listeria monocytogenes is a highly adaptable organism that can persist in a wide range of environmental and food-related niches. The consumption of contaminated ready-to-eat foods can cause infections, termed listeriosis, in vulnerable humans, particularly those with weakened immune systems. Although these infections are comparatively rare they are associated with high mortality rates and therefore this pathogen has a significant impact on food safety. L. monocytogenes can adapt to and survive a wide range of stress conditions including low pH, low water activity, and low temperature, which makes it problematic for food producers who rely on these stresses for preservation. Stress tolerance in L. monocytogenes can be explained partially by the presence of the general stress response (GSR), a transcriptional response under the control of the alternative sigma factor sigma B (σB) that reconfigures gene transcription to provide homeostatic and protective functions to cope with the stress. Within the host σB also plays a key role in surviving the harsh conditions found in the gastrointestinal tract. As the infection progresses beyond the GI tract L. monocytogenes uses an intracellular infectious cycle to propagate, spread and remain protected from the host's humoral immunity. Many of the virulence genes that facilitate this infectious cycle are under the control of a master transcriptional regulator called PrfA. In this review we consider the environmental reservoirs that enable L. monocytogenes to gain access to the food chain and discuss the stresses that the pathogen must overcome to survive and grow in these environments. The overlap that exists between stress tolerance and virulence is described. We review the principal measures that are used to control the pathogen and point to exciting new approaches that might provide improved means of control in the future.

Permanent colonization of creek sediments, creek water and limnic water plants by four Listeria species in low population densities

During a 1-year longitudinal study, water, sediment and water plants from two creeks and one pond were sampled monthly and analyzed for the presence of Listeria species. A total of 90 % of 30 sediment samples, 84 % of 31 water plant samples and 67 % of 36 water samples were tested positive. Generally, most probable number counts ranged between 1 and 40 g-1, only occasionally >110 cfu g-1 were detected. Species differentiation based on FT-IR spectroscopy and multiplex PCR of a total of 1220 isolates revealed L. innocua (46 %), L. seeligeri (27 %), L. monocytogenes (25 %) and L. ivanovii (2 %). Titers and species compositions were similar during all seasons. While the species distributions in sediments and associated Ranunculus fluitans plants appeared to be similar in both creeks, RAPD typing did not provide conclusive evidence that the populations of these environments were connected. It is concluded that (i) the fresh-water sediments and water plants are year-round populated by Listeria, (ii) no clear preference for growth in habitats as different as sediments and water plants was found and (iii) the RAPD-based intraspecific biodiversity is high compared to the low population density.

Interacting Effects of Newcastle Disease Transmission and Illegal Trade on a Wild Population of White-Winged Parakeets in Peru: A Modeling Approach

Illegal wildlife-pet trade can threaten wildlife populations directly from overharvest, but also indirectly as a pathway for introduction of infectious diseases. This study evaluated consequences of a hypothetical introduction of Newcastle disease (ND) into a wild population of Peru's most trafficked psittacine, the white-winged parakeet (Brotogeris versicolurus), through release of infected confiscated individuals. We developed two mathematical models that describe ND transmission and the influence of illegal harvest in a homogeneous (model 1) and age-structured population of parakeets (model 2). Infection transmission dynamics and harvest were consistent for all individuals in model 1, which rendered it mathematically more tractable compared to the more complex, age-structured model 2 that separated the host population into juveniles and adults. We evaluated the interaction of ND transmission and harvest through changes in the basic reproduction number (R0) and short-term host population dynamics. Our findings demonstrated that ND introduction would likely provoke considerable disease-related mortality, up to 24% population decline in two years, but high harvest rates would dampen the magnitude of the outbreak. Model 2 produced moderate differences in disease dynamics compared to model 1 (R0 = 3.63 and 2.66, respectively), but highlighted the importance of adult disease dynamics in diminishing the epidemic potential. Therefore, we suggest that future studies should use a more realistic, age-structured model. Finally, for the presumptive risk that illegal trade of white-winged parakeets could introduce ND into wild populations, our results suggest that while high harvest rates may have a protective effect on the population by reducing virus transmission, the combined effects of high harvest and disease-induced mortality may threaten population survival. These results capture the complexity and consequences of the interaction between ND transmission and harvest in a wild parrot population and highlight the importance of preventing illegal trade.

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce.

Spatial and Temporal Factors Associated with an Increased Prevalence of Listeria monocytogenes in Spinach Fields in New York State

While rain and irrigation events have been associated with an increased prevalence of foodborne pathogens in produce production environments, quantitative data are needed to determine the effects of various spatial and temporal factors on the risk of produce contamination following these events. This study was performed to quantify these effects and to determine the impact of rain and irrigation events on the detection frequency and diversity of Listeria species (including L. monocytogenes) and L. monocytogenes in produce fields. Two spinach fields, with high and low predicted risks of L. monocytogenes isolation, were sampled 24, 48, 72, and 144 to 192 h following irrigation and rain events. Predicted risk was a function of the field's proximity to water and roads. Factors were evaluated for their association with Listeria species and L. monocytogenes isolation by using generalized linear mixed models (GLMMs). In total, 1,492 (1,092 soil, 334 leaf, 14 fecal, and 52 water) samples were collected. According to the GLMM, the likelihood of Listeria species and L. monocytogenes isolation from soil samples was highest during the 24 h immediately following an event (odds ratios [ORs] of 7.7 and 25, respectively). Additionally, Listeria species and L. monocytogenes isolates associated with irrigation events showed significantly lower sigB allele type diversity than did isolates associated with precipitation events (P = <0.001), suggesting that irrigation water may be a point source of L. monocytogenes contamination. Small changes in management practices (e.g., not irrigating fields before harvest) may therefore reduce the risk of L. monocytogenes contamination of fresh produce.

Irrigation Is Significantly Associated with an Increased Prevalence of Listeria monocytogenes in Produce Production Environments in New York State

Environmental (i.e., meteorological and landscape) factors and management practices can affect the prevalence of foodborne pathogens in produce production environments. This study was conducted to determine the prevalence of Listeria monocytogenes, Listeria species (including L. monocytogenes), Salmonella, and Shiga toxin-producing Escherichia coli (STEC) in produce production environments and to identify environmental factors and management practices associated with their isolation. Ten produce farms in New York State were sampled during a 6-week period in 2010, and 124 georeferenced samples (80 terrestrial, 33 water, and 11 fecal) were collected. L. monocytogenes, Listeria spp., Salmonella, and STEC were detected in 16, 44, 4, and 5% of terrestrial samples, 30, 58, 12, and 3% of water samples, and 45, 45, 27, and 9% of fecal samples, respectively. Environmental factors and management practices were evaluated for their association with terrestrial samples positive for L. monocytogenes or other Listeria species by univariate logistic regression; analysis was not conducted for Salmonella or STEC because the number of samples positive for these pathogens was low. Although univariate analysis identified associations between isolation of L. monocytogenes or Listeria spp. from terrestrial samples and various water-related factors (e.g., proximity to wetlands and precipitation), multivariate analysis revealed that only irrigation within 3 days of sample collection was significantly associated with isolation of L. monocytogenes (odds ratio = 39) and Listeria spp. (odds ratio = 5) from terrestrial samples. These findings suggest that intervention at the irrigation level may reduce the risk of produce contamination.

Multifactorial effects of ambient temperature, precipitation, farm management, and environmental factors determine the level of generic Escherichia coli contamination on preharvested spinach

A repeated cross-sectional study was conducted to identify farm management, environment, weather, and landscape factors that predict the count of generic Escherichia coli on spinach at the preharvest level. E. coli was enumerated for 955 spinach samples collected on 12 farms in Texas and Colorado between 2010 and 2012. Farm management and environmental characteristics were surveyed using a questionnaire. Weather and landscape data were obtained from National Resources Information databases. A two-part mixed-effect negative binomial hurdle model, consisting of a logistic and zero-truncated negative binomial part with farm and date as random effects, was used to identify factors affecting E. coli counts on spinach. Results indicated that the odds of a contamination event (non-zero versus zero counts) vary by state (odds ratio [OR] = 108.1). Odds of contamination decreased with implementation of hygiene practices (OR = 0.06) and increased with an increasing average precipitation amount (mm) in the past 29 days (OR = 3.5) and the application of manure (OR = 52.2). On contaminated spinach, E. coli counts increased with the average precipitation amount over the past 29 days. The relationship between E. coli count and the average maximum daily temperature over the 9 days prior to sampling followed a quadratic function with the highest bacterial count at around 24°C. These findings indicate that the odds of a contamination event in spinach are determined by farm management, environment, and weather factors. However, once the contamination event has occurred, the count of E. coli on spinach is determined by weather only.

Effects of climate change on the persistence and dispersal of foodborne bacterial pathogens in the outdoor environment: A review

According to the Intergovernmental Panel on Climate Change (IPCC), warming of the climate system is unequivocal. Over the coming century, warming trends such as increased duration and frequency of heat waves and hot extremes are expected in some areas, as well as increased intensity of some storm systems. Climate-induced trends will impact the persistence and dispersal of foodborne pathogens in myriad ways, especially for environmentally ubiquitous and/or zoonotic microorganisms. Animal hosts of foodborne pathogens are also expected to be impacted by climate change through the introduction of increased physiological stress and, in some cases, altered geographic ranges and seasonality. This review article examines the effects of climatic factors, such as temperature, rainfall, drought and wind, on the environmental dispersal and persistence of bacterial foodborne pathogens, namely, Bacillus cereus, Brucella, Campylobacter, Clostridium, Escherichia coli, Listeria monocytogenes, Salmonella, Staphylococcus aureus, Vibrio and Yersinia enterocolitica. These relationships are then used to predict how future climatic changes will impact the activity of these microorganisms in the outdoor environment and associated food safety issues. The development of predictive models that quantify these complex relationships will also be discussed, as well as the potential impacts of climate change on transmission of foodborne disease from animal hosts.

Geographical and meteorological factors associated with isolation of Listeria species in New York State produce production and natural environments

Listeria species have been isolated from diverse environments, often at considerable prevalence, and are known to persist in food processing facilities. The presence of Listeria spp. has been suggested to be a marker for Listeria monocytogenes contamination. Therefore, a study was conducted to (i) determine the prevalence and diversity of Listeria spp. in produce production and natural environments and (ii) identify geographical and/or meteorological factors that affect the isolation of Listeria spp. in these environments. These data were also used to evaluate Listeria spp. as index organisms for L. monocytogenes in produce production environments. Environmental samples collected from produce production (n = 588) and natural (n = 734) environments in New York State were microbiologically analyzed to detect and isolate Listeria spp. The prevalence of Listeria spp. was approximately 33 and 34% for samples obtained from natural environments and produce production, respectively. Co-isolation of L. monocytogenes and at least one other species of Listeria in a given sample was recorded for 3 and 9% of samples from natural environments and produce production, respectively. Soil moisture and proximity to water and pastures were highly associated with isolation of Listeria spp. in produce production environments, while elevation, study site, and proximity to pastures were highly associated with isolation of Listeria spp. in natural environments, as determined by randomForest models. These data show that Listeria spp. were prevalent in both agricultural and nonagricultural environments and that geographical and meteorological factors associated with isolation of Listeria spp. were considerably different between the two environments.

Reservoirs of listeria species in three environmental ecosystems

Soil and water are suggested to represent pivotal niches for the transmission of Listeria monocytogenes to plant material, animals, and the food chain. In the present study, 467 soil and 68 water samples were collected in 12 distinct geological and ecological sites in Austria from 2007 to 2009. Listeria was present in 30% and 26% of the investigated soil and water samples, respectively. Generally, the most dominant species in soil and water samples were Listeria seeligeri, L. innocua, and L. ivanovii. The human- and animal-pathogenic L. monocytogenes was isolated exclusively from 6% soil samples in regions A (mountainous region) and B (meadow). Distinct ecological preferences were observed for L. seeligeri and L. ivanovii, which were more often isolated from wildlife reserve region C (Lake Neusiedl) and from sites in proximity to wild and domestic ruminants (region A). The higher L. monocytogenes detection and antibiotic resistance rates in regions A and B could be explained by the proximity to agricultural land and urban environment. L. monocytogenes multilocus sequence typing corroborated this evidence since sequence type 37 (ST37), ST91, ST101, and ST517 were repeatedly isolated from regions A and B over several months. A higher L. monocytogenes detection and strain variability was observed during flooding of the river Schwarza (region A) and Danube (region B) in September 2007, indicating dispersion via watercourses.

Farm management, environment, and weather factors jointly affect the probability of spinach contamination by generic Escherichia coli at the preharvest stage

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination.

Listeria monocytogenes, a down-to-earth pathogen

Listeria monocytogenes is the causative agent of the food-borne life threatening disease listeriosis. This pathogenic bacterium received much attention in the endeavor of deciphering the cellular mechanisms that underlie the onset of infection and its ability to adapt to the food processing environment. Although information is available on the presence of L. monocytogenes in many environmental niches including soil, water, plants, foodstuff and animals, understanding the ecology of L. monocytogenes in outdoor environments has received less attention. Soil is an environmental niche of pivotal importance in the transmission of this bacterium to plants and animals. Soil composition, microbial communities and macrofauna are extrinsic edaphic factors that direct the fate of L. monocytogenes in the soil environment. Moreover, farming practices may further affect its incidence. The genome of L. monocytogenes presents an extensive repertoire of genes encoding transport proteins and regulators, a characteristic of the genome of ubiquitous bacteria. Postgenomic analyses bring new insights in the process of soil adaptation. In the present paper focussing on soil, we review these extrinsic and intrinsic factors that drive environmental adaptation of L. monocytogenes.

Potential human pathogenic bacteria in a mixed urban watershed as revealed by pyrosequencing

Current microbial source tracking (MST) methods for water depend on testing for fecal indicator bacterial counts or specific marker gene sequences to identify fecal contamination where potential human pathogenic bacteria could be present. In this study, we applied 454 high-throughput pyrosequencing to identify bacterial pathogen DNA sequences, including those not traditionally monitored by MST and correlated their abundances to specific sources of contamination such as urban runoff and agricultural runoff from concentrated animal feeding operations (CAFOs), recreation park area, waste-water treatment plants, and natural sites with little or no human activities. Samples for pyrosequencing were surface water, and sediment collected from 19 sites. A total of 12,959 16S rRNA gene sequences with average length of ≤400 bp were obtained, and were assigned to corresponding taxonomic ranks using ribosomal database project (RDP), Classifier and Greengenes databases. The percent of total potential pathogens were highest in urban runoff water (7.94%), agricultural runoff sediment (6.52%), and Prado Park sediment (6.00%), respectively. Although the numbers of DNA sequence tags from pyrosequencing were very high for the natural site, corresponding percent potential pathogens were very low (3.78–4.08%). Most of the potential pathogenic bacterial sequences identified were from three major phyla, namely, Proteobacteria, Bacteroidetes, and Firmicutes. The use of deep sequencing may provide improved and faster methods for the identification of pathogen sources in most watersheds so that better risk assessment methods may be developed to enhance public health.

Landscape and meteorological factors affecting prevalence of three food-borne pathogens in fruit and vegetable farms

Produce-related outbreaks have been traced back to the preharvest environment. A longitudinal study was conducted on five farms in New York State to characterize the prevalence, persistence, and diversity of food-borne pathogens in fresh produce fields and to determine landscape and meteorological factors that predict their presence. Produce fields were sampled four times per year for 2 years. A total of 588 samples were analyzed for Listeria monocytogenes, Salmonella, and Shiga toxin-producing Escherichia coli (STEC). The prevalence measures of L. monocytogenes, Salmonella, and STEC were 15.0, 4.6, and 2.7%, respectively. L. monocytogenes and Salmonella were detected more frequently in water samples, while STEC was detected with equal frequency across all sample types (soil, water, feces, and drag swabs). L. monocytogenes sigB gene allelic types 57, 58, and 61 and Salmonella enterica serovar Cerro were repeatedly isolated from water samples. Soil available water storage (AWS), temperature, and proximity to three land cover classes (water, roads and urban development, and pasture/hay grass) influenced the likelihood of detecting L. monocytogenes. Drainage class, AWS, and precipitation were identified as important factors in Salmonella detection. This information was used in a geographic information system framework to hypothesize locations of environmental reservoirs where the prevalence of food-borne pathogens may be elevated. The map indicated that not all croplands are equally likely to contain environmental reservoirs of L. monocytogenes. These findings advance recommendations to minimize the risk of preharvest contamination by enhancing models of the environmental constraints on the survival and persistence of food-borne pathogens in fields.

Diversity of Listeria species in urban and natural environments

A total of 442 Listeria isolates, including 234 Listeria seeligeri, 80 L. monocytogenes, 74 L. welshimeri, 50 L. innocua, and 4 L. marthii isolates, were obtained from 1,805 soil, water, and other environmental samples collected over 2 years from four urban areas and four areas representing natural environments. Listeria spp. showed similar prevalences in samples from natural (23.4%) and urban (22.3%) environments. While L. seeligeri and L. welshimeri were significantly associated with natural environments (P ≤ 0.0001), L. innocua and L. monocytogenes were significantly associated with urban environments (P ≤ 0.0001). Sequencing of sigB for all isolates revealed 67 allelic types with a higher level of allelic diversity among isolates from urban environments. Some Listeria spp. and sigB allelic types showed significant associations with specific urban and natural areas. Nearest-neighbor analyses also showed that certain Listeria spp. and sigB allelic types were spatially clustered within both natural and urban environments, and there was evidence that these species and allelic types persisted over time in specific areas. Our data show that members of the genus Listeria not only are common in urban and natural environments but also show species- and subtype-specific associations with different environments and areas. This indicates that Listeria species and subtypes within these species may show distinct ecological preferences, which suggests (i) that molecular source-tracking approaches can be developed for Listeria and (ii) that detection of some Listeria species may not be a good indicator for L. monocytogenes.

Associations among pathogenic bacteria, parasites, and environmental and land use factors in multiple mixed-use watersheds

Over a five year period (2004-08), 1171 surface water samples were collected from up to 24 sampling locations representing a wide range of stream orders, in a river basin in eastern Ontario, Canada. Water was analyzed for Cryptosporidium oocysts and Giardia cyst densities, the presence of Salmonella enterica subspecies enterica, Campylobacter spp., Listeria monocytogenes, and Escherichia coli O157:H7. The study objective was to explore associations among pathogen densities/occurrence and objectively defined land use, weather, hydrologic, and water quality variables using CART (Classification and Regression Tree) and binary logistical regression techniques. E. coli O157:H7 detections were infrequent, but detections were related to upstream livestock pasture density; 20% of the detections were located where cattle have access to the watercourses. The ratio of detections:non-detections for Campylobacter spp. was relatively higher (>1) when mean air temperatures were 6% below mean study period temperature values (relatively cooler periods). Cooler water temperatures, which can promote bacteria survival and represent times when land applications of manure typically occur (spring and fall), may have promoted increased frequency of Campylobacter spp. Fifty-nine percent of all Salmonella spp. detections occurred when river discharge on a branch of the river system of Shreve stream order = 9550 was >83 percentile. Hydrological events that promote off farm/off field/in stream transport must manifest themselves in order for detection of Salmonella spp. to occur in surface water in this region. Fifty seven percent of L. monocytogenes detections occurred in spring, relative to other seasons. It was speculated that a combination of winter livestock housing, silage feeding during winter, and spring application of manure that accrued during winter, contributed to elevated occurrences of this pathogen in spring. Cryptosporidium and Giardia oocyst and cyst densities were, overall, positively associated with surface water discharge, and negatively associated with air/water temperature during spring-summer-fall. Yet, some of the highest Cryptosporidium oocyst densities were associated with low discharge conditions on smaller order streams, suggesting wildlife as a contributing fecal source. Fifty six percent of all detections of ≥ 2 bacteria pathogens (including Campylobacter spp., Salmonella spp., and E. coli O157:H7) in water was associated with lower water temperatures (<∼ 14 °C; primarily spring and fall) and when total rainfall the week prior to sampling was >∼ 27 mm (62 percentile). During higher water temperatures (>∼ 14 °C), a higher amount of weekly rainfall was necessary to promote detection of ≥ 2 pathogens (primarily summer; weekly rainfall ∼>42 mm (>77 percentile); 15% of all ≥ 2 detections). Less rainfall may have been necessary to mobilize pathogens from adjacent land, and/or in stream sediments, during cooler water conditions; as these are times when manures are applied to fields in the area, and soil water contents and water table depths are relatively higher. Season, stream order, turbidity, mean daily temperature, surface water discharge, cropland coverage, and nearest upstream distance to a barn and pasture were variables that were relatively strong and recurrent with regard to discriminating pathogen presence and absence, and parasite densities in surface water in the region.

Spatial modelling of disease using data- and knowledge-driven approaches

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution.