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Institute of Medicine (US). Improving Food Safety Through a One Health Approach: Workshop Summary. Washington (DC): National Academies Press (US); 2012.
During the past decade, fruits and vegetables have become leading vehicles of food-borne illnesses. Furthermore, many plant-based foods and ingredients, not previously considered a risk, have been associated with food-borne disease outbreaks. Most of the pathogens that have been identified as causative agents in these illnesses or outbreaks are enteric zoonotic pathogens that are typically associated with animal hosts. Transmission of zoonotic pathogens from animals to plant systems occurs by a variety of routes, but the initial contributing factor is the discharge of animal manure into the environment. Using a “One Health” approach that focuses on animal, human, and environmental health concurrently can provide practical and effective interventions for reducing the incidence of such outbreaks. This paper addresses this concept by providing recent food-borne disease outbreak data related to fruits and vegetables, delineating findings regarding the prevalence of pathogens in animal manures and describing the vehicles that transmit pathogens from manure to produce fields, and discussing the merits of reducing pathogen transmission through interventions that would not adversely affect the health of the environment or animals.
Outbreaks and Illnesses Associated with Fresh Fruits and Vegetables
Food-borne illnesses have been a persistent challenge to public health and are now being detected with greater frequency largely because of enhanced surveillance systems that have been implemented in many countries. These enhanced surveillance systems have during the past decade revealed that the proportion of total outbreaks attributed to produce is significant (Lynch et al., 2009) but varies with the country. For example, only 4 percent of all food-borne outbreaks reported in Australia from 2001 to 2005 were attributed to fresh produce (Kirk et al., 2008); similarly, in Canada, between 1976 and 2005, 3.7 percent of 5,745 outbreaks with a known vehicle of transmission were attributed to produce (Ravel et al., 2009). However, in contrast, data from the Centers for Disease Control and Prevention (CDC) identified produce as either the first or second leading vehicle in food-borne disease outbreaks attributed to a single commodity within the United States for the period 2006-2008 (Table A3-1). Furthermore, outbreak surveillance data of produce items compiled by the CDC during the period 2000-2009 revealed that leafy greens were the most common item associated with food-borne disease, followed by tomatoes and cantaloupes (Table A3-2). Moreover, attribution risk rankings of fresh produce–associated outbreaks in the United States identified enterohemorrhagic Escherichia coli in leafy greens as the leading pathogen-produce vehicle combination, followed by Salmonella spp. in tomatoes, and Salmonella spp. in leafy greens (Anderson et al., 2011). Further differentiation of vehicles of produce-associated outbreaks that occurred in the United States during the period of 1998-2008 revealed that fresh-cut produce accounted for 56 percent, 36 percent, and 17 percent of the outbreaks attributed to leafy greens, tomatoes, and melons, respectively (Sneed, 2010).
An evaluation of selected produce-associated outbreaks that occurred during the past 5 years revealed several common features (Table A3-3). These outbreaks often were multistate or multinational in nature and reflect the large areas to which the foods are distributed. With imports accounting for nearly 39 percent of fresh fruits and 14 percent of fresh vegetables in 2005 (Johnson, 2012), improved sampling and pathogen testing of produce at the borders of the United States offers one barrier for reducing the likelihood of contaminated produce from entering the retail sector. However, better implementation both domestically and abroad of best food safety practices for producing and processing fruits and vegetables would have even more impact on reducing pathogen contamination and the likelihood of produce-borne illnesses. This approach would address a significant contributing factor associated with several recent produce outbreaks, which is that contamination occurs on the farm where production and processing can occur. For example, in a multistate outbreak of listeriosis in 2011 that resulted in 34 deaths and was the most deadly food-borne outbreak in the United States since 1924, four outbreak-associated strains of Listeria monocytogenes were traced back to whole cantaloupes and packing equipment on Jensen Farms in Colorado (CDC, 2011c). In another 2011 outbreak, fenugreek seeds that were likely contaminated with fecal matter led to the largest outbreak in the number of cases of hemolytic uremic syndrome (22.3 percent of 4,075 total cases) ever reported in the world (WHO, 2011).
Surveillance of Pathogens in Retail Produce
A number of studies have been conducted to determine the prevalence of enteric pathogens on fruits and vegetables, and the results varied with respect to the country of origin and the target pathogen. For Salmonella, there was for most developed countries a very low prevalence in cabbage, lettuce, and mixed salads, whereas higher prevalences were observed for developing countries where agricultural production and hygienic practices were of a lower level of sanitation (Table A3-4). The presence of helminth and protozoan parasites in leafy greens (Table A3-5), however, likely reflects the ability of these pathogens to resist standard chlorine-based wastewater treatments (Erickson and Ortega, 2006; Graczyk et al., 2007). The relatively low occurrence of pathogen contamination on produce makes it inherently difficult to rank the degree of risk associated with the various sources of contamination by which enteric pathogens are transmitted from animals to plant production environments.
Pathogens in Manures from Domesticated Animal
A large number of zoonotic pathogens reside and grow in the gastrointestinal tract of domesticated animals (poultry, cattle, swine, sheep, and goats) and are shed in their feces asymptomatically, often in very large numbers. Those enteric pathogens associated with the largest number of food-borne disease outbreaks and illnesses include Campylobacter jejuni, Salmonella spp., Shiga toxin–producing enterohemorrhagic Escherichia coli (STEC), and Cryptosporidium parvum. Many studies have been conducted to determine the prevalence of these pathogens in the feces of domesticated animals. A selection of results of recent studies are shown in Tables A3-6 to A3-9 to illustrate the range of pathogen prevalences and cell numbers that may occur within animal wastes and between and within different groups of animals. For Cryptosporidium, not all species are pathogenic for humans. For example, currently there are at least 16 recognized species of Cryptosporidium, of which two most affect humans, C. hominis and C. parvum (Jagai et al., 2010). Therefore, when results do not differentiate species of Cryptosporidium, the potential risk of those manures to human health may be overestimated.
Management of Wastes from Domesticated Animals
Globally, food animal production has increased more than fivefold in the past 50 years due in large part to the adoption of the industrialized concentrated animal production model. With multinational companies expanding their operations overseas, estimates indicate that concentrated animal feeding operations (CAFOs) provide 74 percent of poultry, 50 percent of pork, and 43 percent of beef produced worldwide (Halweil and Nierenberg, 2004). Accompanying this expansion in production has been the challenge of managing the massive quantities of animal wastes that are generated in one location. For example, in China, animal waste was estimated to be 3.2 billion tons, which was three times the amount of industrial solid waste produced in that same year (Wang et al., 2005). Within the United States, it has also been reported that confined food animals produce approximately 335 million dry tons of waste per year, which is more than 40 times the amount of human biosolids waste generated from wastewater treatment plants (Graham and Nachman, 2010). The vast majority of this animal waste is applied to land without any required treatment for reduction of pathogens as is required for human biosolids (EPA, 2004).
There are two primary forms of animal wastes generated at CAFOs. In the case of broiler units, solid waste is generated either as single-use, partial reuse, or multiuse litter (Bolan et al., 2010). In confined swine and cattle operations, water is used to flush waste from the floors where the animals are housed, and the liquid slurry is channeled into large ponds for storage (Graham and Nachman, 2010). The application of animal wastes to land is largely based on agronomic requirements, geography, and commodity choices. For example, corn receives more than half of the land-applied manure, of which most of the manure is from dairy and hog stock because of the use of corn as a major feed crop for dairy and hog operations and the high growth nutrient requirement of corn for nitrogen-rich manure. Hay and grasses are the second largest of the crops fertilized by manure, which is mostly from hog, broiler, and dairy producers (MacDonald et al., 2009). Poultry litter, on the other hand, is frequently used as a fertilizer for cotton, peanuts, and fresh produce (Boyhan and Hill, 2008).
Direct Transmission of Enteric Pathogens from Animal Wastes to Produce Fields
Animal manures applied to fields to be used for fruit and vegetable production have the potential to be a direct source of enteric pathogens if there has not been sufficient holding time between planting and harvest. The U.S. Department of Agriculture (USDA) National Organic Program permits the incorporation of raw manure into soil 120 days before harvest if the food crop has direct contact with the soil; however, only 90 days prior to harvest is required if crops have no contact with the soil (7 Code of Federal Regulations [CFR] 205.203). In contrast, more stringent requirements have been set by the Leafy Greens Marketing Agreement in which 1 year between application of raw manure and harvest of the crop is advocated (LGMA, 2012). As part of the Food Safety Modernization Act, it is anticipated that the Food and Drug Administration will include in its produce rule a required time interval between manure application to fields and either the planting or harvest of crops that would be consumed raw.
Transmission via Runoff of Enteric Pathogens from Animal Waste–Applied Lands to Produce Fields
One of the routes by which enteric pathogens may be indirectly transferred to produce fields from domesticated animal waste deposited or stored on land adjacent to produce fields is via storm runoff. Many studies have revealed that enteric pathogens can move both horizontally and vertically to contaminate land, surface waters, and ground waters adjacent to produce fields (Cooley et al., 2007; Forslund et al., 2011). In these situations, the risk of pathogen contamination of produce will be dependent on a number of factors, including the attachment strength of the pathogen to soil particles, the interval between the manure application and the precipitation events, the kinetic energy of the rainfall, the topographical slope that affects the direction and velocity of water flow, and the density of vegetation between the waste source and the destination site (Ferguson et al., 2007; Hodgon et al., 2009; Jamieson et al., 2002; Lewis et al., 2010; Mishra et al., 2008; Saini et al., 2003; Tyrrel and Quinton, 2003). In addition, the physical state of the waste will also affect the direction of movement of the pathogens with greater percolation occurring by a liquid slurry source and greater overland transport for a solid manure source (Forslund et al., 2011; Semenov et al., 2009).
Transmission of Enteric Pathogens from Waste-Contaminated Water Sources to Produce Fields
Storm runoff carrying pathogens from animal wastes does not necessarily have to pass through agricultural produce fields to be a source of contamination. Collection in surface waters and subsequent use of that water to irrigate produce crops is another means to disseminate the pathogens. Surveys of environmental water sources for pathogen contamination have revealed significant contamination with Salmonella spp., STEC, and protozoan parasites (Table A3-10); however, contamination appears to be sporadic and is often associated with recent rain events and seasonality (Gaertner et al., 2009; Haley et al., 2009). Enhanced survival of pathogens in the sediment (Chandran et al., 2011; Garzio-Hadzick et al., 2010) and resuspension of the organisms into the water column may also perpetuate the risk. Contamination of surface waters, moreover, has been associated with the concentration of food animals raised in the area (Cooley et al., 2007; Johnson et al., 2003; Tserendorj et al., 2011; Wilkes et al., 2011). Salmonella and Cryptosporidium contamination of watersheds not impacted by human or domesticated animal production has been observed (Edge et al., 2012; Patchanee et al., 2010), which suggests that there is a level of natural occurrence of these pathogens from wildlife sources.
Several epidemiological studies lend support to the role that contaminated irrigation water serves as a transmission vehicle of enteric pathogens to fresh produce. In 2002 and 2005, two outbreaks of S. Newport infection in the United States were associated with eating tomatoes and the outbreak strain was isolated from the pond water used to irrigate the tomato fields (Greene et al., 2008). Irrigation of fields with contaminated irrigation waters was also indicated as a possible source of contamination of imported cantaloupe associated with an outbreak of S. Poona infection in the United States in consecutive years during 2000-2002 (CDC, 2002). Given the often sporadic nature of contamination of irrigation water, these documented cases linking irrigation water to an outbreak may represent only a small fraction of the contamination events that actually occur. Worldwide, it is estimated that 17 percent of the world's cropland (1.4 billion hectares) is irrigated and, of that, 20 million hectares are irrigated with untreated wastewater (Jimenez et al., 2010). In the United States and the United Kingdom, extensive irrigation of fresh produce crops occurs and, of the acreage irrigated, 48 percent and 78 percent, respectively, are derived from non-groundwater sources (Knox et al., 2011; USDA NASS, 2009), which are subject to intermittent inputs of pathogens from animal husbandry operations.
Contribution of Bioaerosols to Dissemination of Enteric Pathogens from Animal Production Operations to Produce Fields
Aerosolization of microbial pathogens is an inevitable consequence associated with animal production operations as well as the handling and disposition of animal manure. However, estimating the impact of bioaerosol dispersal on pathogen dissemination has been hampered by the notable absence of standardized and validated methods for enumeration of various types of microorganisms in outdoor bioaerosols. Hence, there has been a wide range of prevalence and cell number values reported across very diverse types of animal operations and landscapes (Millner, 2009).
Studies addressing bioaerosol levels in outdoor air generally address fecal indicator organisms because they are more abundant and easily identified in the aerosols, although it is acknowledged that they may behave differently than the pathogens. The general trend that has been observed is decreasing airborne microorganism concentrations as the distance from the source increases with relative humidity, temperature, and solar irradiance being major factors affecting viability (Dungan, 2010). Other pertinent observations made in studies addressing the levels of the indicator organism, E. coli, in aerosols of poultry houses are that the levels of airborne bacteria are intricately linked to the levels of those bacteria in the litter (Chinivasagam et al., 2009; Smith et al., 2012) and the type of ventilation system affects the distance that E. coli is disseminated, with E. coli traversing 11.1 and 7.5 m downwind from houses using tunnel and conventional fans, respectively (Smith et al., 2012).
Limited studies have been conducted addressing bioaerosol transport following land application of animal manures in contrast to those addressing the application of municipal wastes (Pillai and Ricke, 2002). Although there may be some similar behavior between these two sources, there could be differences given that they vary in their organic matter content that can provide differences in the degree of protection against ultraviolet radiation and drying (Dungan, 2010). In one of the few studies addressing land application of cattle and swine slurry and the method used to disperse the wastes, total bacterial counts in the air were greater at greater distances from spray guns that discharged the slurry upward into the air compared to tank spreading that sprayed the slurries closer to the ground (Boutin et al., 1988). In another study in which swine manure was applied through a center pivot irrigation system, coliform concentrations decreased to near background concentrations at 23 m downwind (Kim et al., 2008). Wind speed and topography, however, are likely to also factor into the distances traversed by pathogens and, hence, safe distances between produce fields and animal production activities will likely be site specific.
Wildlife as a Vehicle to Transmit Pathogens from Domesticated Animal Waste to Produce Fields
The recent focus on wildlife as a potential source of pathogen contamination of produce fields was driven by the isolation of E. coli O157:H7 from feral swine that occupied areas near spinach fields and cattle farms in California following the 2006 spinach outbreak (Jay et al., 2007). More recently, Campylobacter jejuni was isolated both from Sandhill crane feces and raw peas and several of the isolates had pulsed-field gel electrophoresis (PFGE) patterns indistinguishable from clinical samples obtained during a C. jejuni gastroenteritis outbreak that occurred in Alaska in 2008 (Gardner et al., 2011). Attention was again focused on wildlife as a potential source of contamination when E. coli O157:H7 isolated from deer feces was determined to have an identical PFGE pattern as the isolates responsible for 15 people who were ill from eating contaminated fresh strawberries in Oregon in 2011 (IEH Laboratories & Consulting Group, 2011). Given that the same strain was also isolated from soil raises the question as to whether the deer were actually the source of the outbreak or were infected when they ate the contaminated strawberries. Most evidence indicating that wildlife is a potential source of food-borne contamination is from the isolation of clinically relevant pathogens from the animal's feces. In one example, Renter et al. (2006) isolated from deer fecal samples four Salmonella serovars (Litchfield, Dessau, Infantis, and Enteritidis) known to be pathogenic to humans and animals. In another example, subtyping of STEC isolates from wildlife meat in Germany identified virulence genes associated with severe clinical outcome (stx2, stx2d, and eae) in 46 of the 140 STEC samples (Miko et al., 2009). More definitive proof that specific types of wildlife could be transmission vectors of pathogens from domesticated animal facilities was obtained with a study of European starlings (Williams et al., 2011). In that study, distinct molecular types of E. coli O157:H7 were similar in starlings and cattle on different farms, and these birds were capable of shedding the pathogen in their feces for more than 3 days (Kauffman and LeJeune, 2011). Hence, it is reasonable to assume that European starlings could serve as a vector of pathogens from cattle and dairy farms to produce fields.
In response to the limited studies linking wildlife to produce contamination, processors and buyers have become overreactive in many cases in requiring the absence of many types of wildlife from farms. To illustrate this trend, the percentage of growers that reported being told by their processors or buyers that feral pigs, deer, birds, rodents, and amphibians were a significant risk was 19, 28, 44, 47, and 28 percent, respectively (Lowell et al., 2010). Several studies, however, have revealed that some groups of animals have a very low prevalence of contamination with relevant human enteric pathogens (Table A3-11). It is likely that all animal groups have the potential to be contaminated with a food-borne pathogen, but whether they are significant harbingers of human enteric pathogens is likely dependent on their access to animal husbandry sites as well as on their social behavior (i.e., existence of a social group and its size). This would also be the case with insects. For example, filth flies collected in leafy green fields were believed to have originated from nearby rangelands that contained fresh cattle manure (Talley et al., 2009).
Persistence of Pathogens on Produce in Fields Requires a Systems Approach to Prevent and Monitor Pathogen Introduction
Many field studies have revealed the persistence of human enteric pathogens, albeit typically at low levels, in a number of different vegetables contaminated at various points during their cultivation (Erickson et al., 2010; Gutiérrez-Rodriguez et al., 2011; Islam et al., 2004a, 2004b, 2004c, 2005; Moyne et al., 2011). This is noteworthy because chemical disinfectants typically used during minimal processing of fresh produce are not fully effective in eliminating pathogen contamination (Doyle and Erickson, 2008). Hence, it is paramount to prevent the introduction of these pathogens into produce fields. The primary approach currently used to reduce the risk of pathogen contamination in fields is the application of good agricultural practices (GAPs). To prevent the introduction of pathogens through nontraditional vehicles (storm runoff, intrusions by pathogen-carrying wildlife) will require the development of novel approaches in addition to GAPs. Given that the environment surrounding the produce field would likely be impacted by these pathogen control practices, it is important to implement a systems approach and consider all ramifications to the adoption of any intervention practices. It is also important to be cognizant that storm runoff and fecal deposits from wildlife may only contaminate the plants at discrete locations within a field. The ability to detect this contamination by current sampling plans that rely on uniform contamination is therefore limited and efforts are needed to develop new monitoring systems that can detect contamination when such pathogen introductions occur.
Concluding Comments
Vegetables, fruits, and a variety of plant foods and ingredients are now recognized as major vehicles of food-borne disease outbreaks, and a primary source of pathogen contamination of this commodity group is animal manure. There are several routes by which pathogens can be transmitted from animal production sites to produce fields. The vehicles likely presenting the greatest risk are manure-contaminated soil amendments and irrigation water. Wildlife, insects, and vermin, however, may also serve as intermediate vectors of pathogens from animal wastes to plants in the field. The multifaceted routes by which pathogens may be transmitted to produce crops illuminates the value of a One Health approach to minimize pathogen contamination in the production environment while ensuring that adverse effects to the environment be minimized.
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- 4
Center for Food Safety, University of Georgia, 1109 Experiment Street, Griffin, GA 30223, USA.
Tables
TABLE A3-1Food-Borne Disease Outbreaks Attributed to a Single Commodity by Leading Food Vehicles, 2006-2008
Year | Rank | Food vehicle | Outbreaks (%) |
---|---|---|---|
2006 | 1 | Produce | 23.5 |
2 | Meat | 19.3 | |
2 | Fish | 19.3 | |
4 | Poultry | 14.4 | |
2007 | 1 | Meat | 23.0 |
2 | Produce | 22.6 | |
3 | Fish | 17.4 | |
4 | Poultry | 17.0 | |
2008 | 1 | Produce | 27.5 |
2 | Meat | 23.4 | |
3 | Poultry | 14.7 | |
4 | Fish | 13.8 |
SOURCE: CDC (2009a, 2010c, 2011e).
TABLE A3-2Number of Outbreaks (illnesses) Reported Between 2000 and 2009 in the United States That Were Associated with Selected Fresh Produce Items as a Function of their Etiologya,b
Produce item | Bacterial agents | Viral agents | Other agents | Total | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Salmonella spp. | Escherichia coli O157:H7c | Shigella spp. | Campylobacter jejuni | Otherd | Norovirus | Hepatitis A | Protozoan parasites | Unknown | ||
Cabbage | 1 (8) | 1 (41) | 2 (68) | 3 (78) | 1(16) | 3 (16) | 11 (227) | |||
Lettuce | 10 (456) | 14 (364) | 1 (4) | 2 (16) | 3 (114) | 39 (999) | 1 (22) | 10 (60) | 80 (2,035) | |
Spinach | 2 (223) | 1 (6) | 3 (9) | 6 (238) | ||||||
Sprouts | 12 (441) | 4 (46) | 1 (20) | 1 (2) | 18 (509) | |||||
Herbs | 3 (70) | 1 (592) | 1 (20) | 5 (682) | ||||||
Leafy green salads | 23 (997) | 15 (280) | 7 (190) | 7 (42) | 10 (145) | 257 (8,520) | 3 (47) | 114 (1,419) | 436 (11,640) | |
Coleslaw | 1 (26) | 4 (22) | 20 (676) | 1 (8) | 1 (11) | 27 (743) | ||||
Peppers | 4 (1,643) | 1 (5) | 2 (17) | 1 (2) | 8 (1,667) | |||||
Tomatoes | 25 (1,867) | 1 (886) | 1 (13) | 2 (10) | 15 (399) | 1 (23) | 45 (3,198) | |||
Cantaloupe/melons | 19 (1,180) | 1 (5) | 1 (56) | 1 (55) | 12 (502) | 6 (79) | 40 (1,877) |
- a
Data compiled from the CDC website on outbreak surveillance (http://www
.cdc.gov/outbreaknet /surveillance_data.html). - b
Outbreaks/illnesses attributed to each pathogen group includes both confirmed and suspected.
- c
Includes other Shiga toxin–producing Escherichia coli.
- d
Includes where multiple bacterial pathogens have been found and cases involving the agents of Bacillus cereus, Clostridium botulinum, C. perfringens, Listeria monocytogenes, and Staphylococcus aureus.
SOURCE: CDC.
TABLE A3-3Selected Food-Borne Disease Outbreaks Attributed to Produce During the Period of 2006-2011
Year | Pathogen | Number of cases | Country of origin | Affected regions | Implicated food | Reference |
---|---|---|---|---|---|---|
2007 | Salmonella Weltevreden | 45 | Italy, seed origin | Norway, Denmark, Finland | Alfalfa sprouts | Emberland et al., 2007 |
2009 | Salmonella Saintpaul | 228 | Domestic, seed company | U.S., multistate | Alfalfa sprouts | CDC, 2009b |
2010 | S. Newport | 44 | Domestic, processor | U.S., multistate | Alfalfa sprouts | CDC, 2010a |
2010 | Salmonella I 4,[5],12:i:- | 112 | Domestic | U.S., multistate | Alfalfa sprouts | CDC, 2011a |
2011 | E. coli O104:H4 | 3,911 | Egypt | Multinational | Fenugreek sprouts | EFSA, 2011 |
2007 | S. Senftenberg | 51 | Israel | U.K., U.S., Denmark, Netherlands | Basil | Elviss et al., 2009 |
2007 | S. Senftenberg | 74 | Israel | U.K., Denmark, Netherlands, U.S. | Basil, fresh | Pezzoli et al., 2008 |
2006 | S. Saintpaul | 36 | Domestic | Australia, multijurisdiction | Cantaloupe | Munnoch et al., 2009 |
2008 | S. Litchfield | 51 | Honduras | U.S., multistate | Cantaloupe | CDC, 2008a |
2011 | S. Panama | 20 | Guatemala | U.S., multistate | Cantaloupe | CDC, 2011b |
2011 | Listeria monocytogenes | 146 | Domestic | U.S., multistate | Cantaloupe | CDC, 2011c |
2006 | Clostridium botulinum | 4 | Domestic | U.S., Georgia | Carrot juice | CDC, 2006a |
2006 | Yersinia pseudotuberculosis | 427 | Domestic, traced to vegetable distributor | Finland | Carrots, grated | Rimhanen-Finne et al., 2009 |
2006 | Norovirus | 43 | China | Sweden | Frozen raspberries | Hjertqvist et al., 2006 |
2006 | E. coli O157:H7 | 71 | Not known | U.S., multistate | Lettuce | FDA, 2006 |
2006 | E. coli O157:H7 | 81 | Domestic | U.S., multistate | Lettuce | FDA, 2007 |
2011 | E. coli O157:H7 | 60 | Domestic | U.S., multistate | Lettuce, romaine | CDC, 2011c |
2008 | Salmonella Newport and Reading | 77 (Newport) 30 (Reading) | Domestic | Finland | Lettuce | Lienemann et al., 2011 |
2010 | Norovirus and E. coli ETEC | 264 | France | Denmark, Norway | Lettuce, lollo biondo type | Ethelberg et al., 2010 |
2010 | E. coli O145 | 33 | Domestic, processor | U.S., multistate | Lettuce, shredded romaine | CDC, 2010b |
2007 | E. coli O157:H-, PT8 | 50 | Netherlands, processing plant | Netherlands, Iceland | Lettuce, shredded, prepacked | Friesema et al., 2007 |
2008 | Cryptosporidium parvum | 21 | Italy | Sweden | Parsley | Insulander et al., 2008 |
2008 | S. Saintpaul | 1,442 | Mexico | U.S., Canada | Peppers (jalapeño and Serrano), tomatoes | CDC, 2008b |
2007 | Shigella sonnei | 227 | Thailand | Denmark, Australia | Raw baby corn | Lewis et al., 2009 |
2006 | E. coli O157:H7 | 204 | U.S. | U.S., Canada | Spinach | Calvin, 2007 |
2006 | S. Typhimurium | 183 | Not known | U.S, multistate | Tomatoes | CDC, 2006b |
SOURCE: CDC.
TABLE A3-4Prevalence of Salmonella in Lettuce, Cabbage, and Mixed Salads Throughout the World (2001-2011)
Produce item | Country | Sampling site | Number positive/number sampled | Prevalence (%) | Reference |
---|---|---|---|---|---|
Cabbage | India | Fields | 4/33 | 12.1 | Rai and Tripathi, 2007 |
India | Street vendors | 2/8 | 25.0 | Viswanathan and Kaur, 2001 | |
Ireland | Supermarkets | 0/4 | 0 | McMahon and Wilson, 2001 | |
Mexico | Supply station | 1/100 | 1.0 | Quiroz-Santiago et al., 2009 | |
U.S. | Packing sheds, southern U.S. | 0/109 | 0 | Johnston et al., 2006 | |
U.S. | Farms, organic, conventional, semiorganic | 0/291 | 0 | Mukherjee et al., 2004, 2006 | |
Lettuce | Canada | Retail distribution centers/farmer's markets | 1/530 | 0.2 | Arthur et al., 2007 |
Ireland | Supermarkets | 0/8 | 0 | McMahon and Wilson, 2001 | |
Italy | Producers | 2/62 | 3.2 | De Giusti et al., 2010 | |
Korea | Department store, supermarket, restaurant | 1/30 | 3.3 | Seo et al., 2010 | |
Mexico | Markets, supermarkets | 10/75 | 13 | Castañeda-Ramírez et al., 2011 | |
Nigeria | Fields | 0/55 | 0 | Okago et al., 2003 | |
Norway | Producers, organic | 0/179 | 0 | Loncarevic et al., 2005 | |
Spain | Farms, organic, conventional | 0/72 | 0 | Oliveira et al., 2010 | |
Spain | Retail establishments | 1/29 | 3.4 | Abadias et al., 2008 | |
U.S. | Farms, organic, conventional, semiorganic | 0/261 | 0 | Mukherjee et al., 2004, 2006 | |
U.S. | Supermarkets, farmer's markets | 0/10 | 0 | Thunberg et al., 2002 | |
U.S. | Markets and wholesale distribution centers | 2/5,453 | 0.04 | USDA, 2007, 2008, 2009 | |
Mixed salads/vegetables | Brazil | Retailers | 1/21 | 4.8 | Fröder et al., 2007 |
Cyprus | Production sites, retail outlets | 6/294 | 2.0 | Eleftheriadou et al., 2002 | |
Korea | Department store, supermarket, restaurant | 1/129 | 0.8 | Seo et al., 2010 | |
Malaysia | Wet markets | 40/112 | 35.7 | Salleh et al., 2003 | |
U.K. | Catering, retail outlets | 5/10,002 | 0.05 | Sagoo et al., 2001, 2003a, 2003b |
SOURCE: CDC.
TABLE A3-5Prevalence of Helminth and Protozoan Parasites in Leafy Greens from 2005-2010
Produce item | Country | Sampling target | Ascaris spp. | Cryptosporidium spp. | Giardia spp. | Taenia spp. | Toxocara spp. | Reference | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Number positive/number of samples | % | Number positive/number of samples | % | Number positive/number of samples | % | Number positive/number of samples | % | Number positive/number of samples | % | ||||
Cabbage | Ghana | Retail fruit, vegetable markets | 33/60 | 55.0 | Amoah et al., 2006 | ||||||||
Spain | Fields | 2/6 | 33.3 | 2/6 | 33.3 | Amorós et al., 2010 | |||||||
Turkey | Wholesale markets | 0/14 | 0 | Kozan et al., 2005 | |||||||||
Lettuce | Ghana | Retail fruit, vegetable markets | 36/60 | 60.0 | Amoah et al., 2006 | ||||||||
Libya | Wholesale, retail markets | 26/27 | 96.3 | 1/27 | 3.7 | 9/27 | 33.3 | 23/27 | 85.2 | Abougrain et al., 2010 | |||
Spain | Fields | 10/13 | 76.9 | 8/13 | 61.5 | Amorós et al., 2010 | |||||||
Turkey | Field | 6/15 | 40.0 | 3/15 | 20.0 | Erdoğrul and Şener, 2005 | |||||||
Turkey | Wholesale markets | 2/35 | 5.7 | 2/35 | 5.7 | Kozan et al., 2005 |
SOURCE: CDC.
TABLE A3-6Prevalence and Cell Numbers of Salmonella spp. in Manures from Domesticated Animals
Pathogen | Source | Location | Prevalence (% of total samples positive) (average cell numbers in positive samples) | Reference |
---|---|---|---|---|
Salmonella | Cattle feces | U.K., England and Wales | 7.7% of 810 samples were positive (4.6 log CFU/g for positive samples) | Hutchison et al., 2004 |
Salmonella spp. | Cattle feces | Britain | 7.7-10.0% samples were positive; 3.3-3.4 log CFU/g in positive samples | Hutchison et al., 2005 |
Salmonella | Cattle, beef and dairy farms, rectal fecal | U.S., TN, NC, AL, WA, CA | 0.2% of 480 beef cattle samples were positive; 0.4% of 480 dairy cattle samples were positive; 8.5% of 18 beef farms had at least one positive sample; 17.9% of 18 dairy farms had at least one positive sample | Rodriguez et al., 2006 |
Salmonella spp. | Cattle, beef, abattoir, feces | Ireland, northern | 3% of 200 samples were positive | Madden et al., 2007 |
Salmonella | Cattle, dairy feces | New Zealand | 0% of 155 samples positive | Moriarty et al., 2008 |
S. enterica | Cattle, feedlot feces | Australia | 6% of 32 samples were positive | Klein et al., 2010 |
S. enterica | Cattle feces | California | 0.13% of 795 samples were positive | Gorski et al., 2011 |
Salmonella | Chicken feces | U.K., England and Wales | 17.9% of 67 samples were positive (3.7 log CFU/g for positive samples) | Hutchison et al., 2004 |
Salmonella spp. | Poultry feces | Britain | 11.5-17.9% samples were positive (2.3-3.6 log CFU/g in positive samples) | Hutchison et al., 2005 |
Salmonella | Turkey feces and litter | U.S., NC | 70% of 48 composite fecal samples were positive; 79% of 48 composite litter samples positive (<1 – 5.3 log MPN/g in positive samples) | Santos et al., 2005 |
Salmonella | Chicken litter | Lebanon | 0% of 24 samples were positive | Omeira et al., 2006 |
Salmonella | Chicken/turkey farms, rectal feces | U.S., TN, NC, AL, WA, CA | 0.2% of 480 samples were positive; 16.2% of 18 farms had at least one positive sample | Rodriguez et al., 2006 |
Salmonella | Chickens, laying hens feces | Belgium | 0% of fecal samples collected on farm were positive | Van Hoorebeke et al., 2009 |
Salmonella | Chicken feces | France | 8.6% of 370 flocks had at least one positive sample; most prevalent serovar was S. hadar followed by S. anatum and S. mgandaka | Le Bouquin et al., 2010 |
Salmonella | Pig feces | U.K., England and Wales | 7.9% of 126 samples were positive (4.0 log CFU/g for positive samples) | Hutchison et al., 2004 |
Salmonella spp. | Pig feces | Britain | 5.2-7.9% samples were positive (2.8 log CFU/g in positive samples) | Hutchison et al., 2005 |
Salmonella | Swine farms, rectal feces | U.S., TN, NC, AL, WA, CA | 6.0% of 480 samples were positive; 57.3% of 18 farms had at least one positive sample | Rodriguez et al., 2006 |
Salmonella | Swine, finishing pigs, feces | Italy, Piedmont | 9% of 75 fecal samples were positive | Lomonaco et al., 2009 |
S. enterica | Swine feces | Japan | 3.1% of 169 samples were positive 22.0% of farms had positive samples | Kishima et al., 2008 |
Salmonella | Sheep feces | U.K., England and Wales | 8.3% of 24 samples were positive (3.0 log CFU/g in positive samples) | Hutchison et al., 2004 |
Salmonella spp. | Sheep feces | Britain | 8.3-11.1% samples were positive (2.8-3.8 log CFU/g in positive samples) | Hutchison et al., 2005 |
NOTE: CFU, colony forming unit; MPN, most probable number.
TABLE A3-7Prevalence and Cell Numbers of Campylobacter spp. in Manures from Domesticated Animals
Pathogen | Source | Location | Prevalence (% of total samples positive) (average cell numbers in positive samples) | Reference |
---|---|---|---|---|
Campylobacter | Cattle feces | U.K., England and Wales | 12.8% of 810 samples were positive (3.9 log CFU/g in positive samples) | Hutchison et al., 2004 |
Campylobacter spp. | Cattle feces | Britain | 9.8-12.8% samples were positive (2.5-2.7 log CFU/g in positive samples) | Hutchison et al., 2005 |
Campylobacter | Cattle, dairy feces | New Zealand | 64% of 155 samples were positive (5.6 log CFU/g in positive samples) | Moriarty et al., 2008 |
Campylobacter spp. | Cattle, beef, abattoir, feces | Ireland, northern | 24.8% of 220 samples were positive | Madden et al., 2007 |
C. jejuni | Cattle, feedlot feces | Australia | 94% of 32 samples were positive | Klein et al., 2010 |
Campylobacter | Chicken feces | U.K., England and Wales | 19.4% of 67 samples were positive (3.6 log CFU/g for positive samples) | Hutchison et al., 2004 |
Campylobacter spp. | Poultry feces | Britain | 7.7-19.4% samples were positive; (2.4-2.8 log CFU/g in positive samples) | Hutchison et al., 2005 |
Campylobacter | Broilers ceca | Sweden | 47% of 540 ceca samples were positive; proportion of positive samples ranged from 10 to 100% within a flock. (1.7 to 8.6 log CFU/g in positive samples) | Hansson et al., 2010 |
Campylobacter | Duck, Mallard, feces | U.K. | 93.3-100.0% of two groups of 60 farmed ducks tested at 28-56 days of age were positive | Colles et al., 2011 |
Campylobacter | Pig feces | U.K., England and Wales | 13.5% of 126 samples were positive (3.3 log CFU/g for positive samples) | Hutchison et al., 2004 |
Campylobacter spp. | Pig feces | Britain | 10.3-13.5% samples were positive (2.5-3.2 log CFU/g in positive samples) | Hutchison et al., 2005 |
Campylobacter | Sheep feces | U.K., England and Wales | 20.8% of 24 samples positive (2.9 log CFU/g for positive samples) | Hutchison et al., 2004 |
Campylobacter spp. | Sheep feces | Britain | 11.1-20.8% samples were positive (2.0-2.6 log CFU/g in positive samples) | Hutchison et al., 2005 |
NOTE: CFU, colony forming unit.
TABLE A3-8Prevalence and Cell Numbers of Shiga Toxin–Producing E. coli in Manures from Domesticated Animals
Pathogen | Source | Location | Prevalence (% of total samples positive) (average cell numbers in positive samples) | Reference |
---|---|---|---|---|
E. coli O157:H7 | Cattle, beef feedlot, feces | Canada, Alberta | 1.9% of 8,682 samples were positive | Berg et al., 2004 |
E. coli O157 | Cattle, dairy beef, farms, rectal feces | Mexico, central | 1.2% of 240 samples were positive | Callaway et al., 2004 |
E. coli O157:H7 | Cattle, beef and dairy, rectal feces | U.S., TN, NC, AL, WA, CA | 3.9% of 408 dairy cattle samples were positive 4.7% of 408 beef cattle samples positive | Doane et al., 2007 |
E. coli O157:H7 | Cattle, cow and calf farms, rectal feces | U.S. | 2.5% of 408 samples were positive; 17.2% of 29 cow-calf farms positive | Dunn et al., 2004 |
E. coli O157 | Cattle feces | U.K., England and Wales | 13.2% of 810 samples were positive (6.5 log CFU/g for positive samples) | Hutchison et al., 2004 |
E. coli O157 | Cattle, beef and dairy farms, feces | Korea | 1.7% of 864 beef cattle samples were positive; 6.7% of 990 dairy cattle samples were positive | Jo et al., 2004 |
E. coli O157:H7 | Cattle, feedlot | U.S., midwest | 10.2% of 10,622 cattle were positive; 52.0% of 711 pens had a positive animal; 95.9% of 73 feedlots sampled had a positive animal | Sargeant et al., 2004 |
E. coli O157 | Cattle feces | Britain | 9.1-13.2% samples positive (2.4-3.1 log CFU/g in positive samples) | Hutchison et al., 2005 |
E. coli STEC | Cattle, beef feces | Japan | 23% of 272 samples positive | Kijima-Tanaka et al., 2005 |
E. coli O157:H7 | Cattle, dairy | Switzerland | 4.2% of 966 samples were positive | Kuhnert et al., 2005 |
E. coli O157:H7 | Cattle feces | Norway | 7.0% of 156 samples were positive | Wasteson et al., 2005 |
E. coli O157:H7 | Cattle, feedlot feces | U.S., KS | 9.2% of 891 samples were positive | Alam and Zurek, 2006 |
E. coli STEC | Cattle, organic and conventional dairy feces | U.S., MN | 32.% of 2208 samples were positive; 71.4% of dairy farms had at least one positive sample | Cho et al., 2006 |
E. coli O26 and O111 | Cattle, beef and dairy farms, feces | Korea | 6.7%, 4.6%, and 2.0% of 809 samples tested positive for O26, O111, and both O26 and O111, respectively. | Jeon et al., 2006 |
E. coli O157 | Cattle, dairy, mature, rectal feces | U.S., OH and Norway | 0.7% of 750 samples were positive in Ohio; 8% of 50 herds had at least one positive sample; 0% of 680 samples positive in Norway | LeJeune et al., 2006 |
E. coli STEC | Cattle, dairy, mature, rectal fecal samples | U.S., OH and Norway | 14% of 750 samples were positive in Ohio; 70% of 50 herds had at least one positive sample; 61% of 680 samples were positive in Norway; 100% of herds had at least one positive sample | LeJeune et al., 2006 |
E. coli O157 | Cattle, feedlot and abattoir, fecal pats and rectal feces | U.S., CO, NE | 24.7% of 450 fecal pats were positive; 27.6% of 145 rectal fecal samples were positive | Woerner et al, 2006 |
E. coli O157:H7 | Cattle, rectal, feces | U.S., TX | 64.3% of 8 cattle were positive | Edrington et al., 2007 |
E. coli O157 | Cattle, 12-30-month-old beef, feces | Scotland | 7.9% of 14,856 samples were positive; 22.8% of 952 farms had at least one positive sample | Gunn et al., 2007 |
E. coli O157:H7 | Cattle feces | U.S., Central California | 33.8% of 77 samples tested were positive | Jay et al., 2007 |
E. coli non-O157 | Cattle, feedlot, feces | Canada, Alberta | 0.7% of 2099 samples were positive; 57% of 21 feedlots sampled had positive samples | Renter et al., 2007 |
E. coli, non-O157 STEC | Cattle, beef, rectal fecal | Spain, northern | 46.0% of 124 samples were positive | Oporto et al., 2008 |
E. coli, non-O157 STEC | Cattle, dairy, rectal fecal | Spain, northern | 20.7% of 82 samples were positive | Oporto et al., 2008 |
E. coli O157:H7 | Cattle, beef, abattoir, feces | Ireland, northern | 0.9% of 220 samples were positive | Madden et al., 2007 |
E. coli, STEC | Cattle, dairy feces | New Zealand | 1.3% of 155 samples were positive | Moriarty et al., 2008 |
E. coli O157:H7 | Cattle, beef, rectal fecal | Spain, northern | 1.6% of 124 samples were positive; 6.7% of herds had positive samples | Oporto et al., 2008 |
E. coli O157:H7 | Cattle, dairy, rectal fecal | Spain, northern | 7.0% of 82 samples were positive | Oporto et al., 2008 |
E. coli O157:H7 | Cattle feces (perineal swab) | Canada | 7.2% of 2,125 cattle were identified as supershedders of E. coli O157:H7 (> 4 log CFU/g) in the spring/summer; 0.5% of 2,000 cattle were identified as supershedders of E. coli O157:H7 (> 4 log CFU/g) in the fall/winter | Stephens et al., 2009 |
E. coli O157:H7 | Cattle, beef GI tract | U.S., KS | 20.3% of 815 samples were positive | Walker et al., 2010 |
E. coli O157 | Chickens feces | Korea | 0% of 418 samples were positive | Jo et al., 2004 |
E. coli STEC | Chicken broiler feces | Japan | 0% of 158 samples were positive | Kijima-Tanaka et al., 2005 |
E. coli O157:H7 | Chicken feces | Norway | 13.6% of 22 samples were positive | Wasteson et al., 2005 |
E. coli O157:H7 | Chicken and turkey, rectal fecal samples | U.S., TN, NC, AL, WA, CA | 2.7% of 444 samples were positive | Doane et al., 2007 |
E. coli O157 | Swine, rectal feces | Mexico, central | 2.1% of 240 samples were positive | Callaway et al., 2004 |
E. coli O157 | Pig feces | UK, England and Wales | 11.9% of 126 samples positive (4.8 log CFU/g for positive samples) | Hutchison et al., 2004 |
E. coli O157 | Swine feces | Korea | 0.3% of 345 samples were positive | Jo et al., 2004 |
E. coli O157 | Pig feces | Britain | 11.9-15.5% samples were positive (3.1-3.6 log CFU/g in positive samples) | Hutchison et al., 2005 |
E. coli STEC | Swine feces | Japan | 14% of 179 samples were positive | Kijima-Tanaka et al., 2005 |
E. coli O157:H7 | Swine, rectal fecal samples | U.S., TN, NC, AL, WA, CA | 8.8% of 426 samples were positive | Doane et al., 2007 |
E. coli O157:H7 | Swine | Spain, northern | 0% of 17 samples were positive | Oporto et al., 2008 |
E. coli, non-O157 STEC | Swine | Spain, Northern | 0% of 17 samples were positive | Oporto et al., 2008 |
E. coli O157 | Sheep feces | UK, England and Wales | 20.8% of 24 samples positive (4.0 log CFU/g for positive samples) | Hutchison et al., 2004 |
E. coli O157 | Sheep feces | Britain | 20.8-22.2% samples were positive (2.4-2.9 log CFU/g in positive samples) | Hutchison et al., 2005 |
E. coli O157:H7 | Sheep feces | Norway | 17.1% of 117 samples positive | Wasteson et al., 2005 |
E. coli O157 | Sheep feces | Turkey | 9.1% of 175 samples positive; 47% of 15 flocks had at least one positive sample | Turutoglu et al., 2007 |
E. coli, non-O157 STEC | Sheep, dairy, rectal feces | Spain, northern | 50.7% of 122 samples were positive | Oporto et al., 2008 |
E. coli O157:H7 | Sheep, dairy, rectal feces | Spain, northern | 8.7% of 122 samples were positive; 7.3% of herds had positive samples | Oporto et al., 2008 |
NOTE: CFU, colony forming unit; STEC, Shiga toxin–producing Escherichia coli.
TABLE A3-9Prevalence and Cell Numbers of Cryptosporidium spp. in Manures from Domesticated Animals
Pathogen | Source | Location | Prevalence (% of total samples positive) (average cell numbers in positive samples) | Reference |
---|---|---|---|---|
C. parvum | Cattle feces | U.K., England and Wales | 5.4% of 810 samples were positive (2.4 log CFU/g for positive samples) | Hutchison et al., 2004 |
Cryptosporidium | Calf feces | Australia, Sydney watersheds | 57.1% of 7 samples were positive | Cox et al., 2005 |
Cryptosporidium | Cattle, adult, feces | Australia, Sydney watersheds | 22.2% of 9 samples were positive | Cox et al., 2005. |
C. parvum | Cattle feces | Britain | 2.8-5.4% samples were positive (1.0-1.3 log CFU/g in positive samples) | Hutchison et al., 2005 |
Cryptosporidium | Cattle, dairy feces | New Zealand | 5.2% of 155 samples were positive | Moriarty et al., 2008 |
Cryptosporidium spp. | Cattle, feedlot feces | Australia | 13% of 32 samples were positive | Klein et al., 2010 |
Cryptosporidium | Chicken feces | Australia, Sydney watersheds | 0% of 7 samples were positive | Cox et al., 2005 |
C. parvum | Pig feces | U.K., England and Wales | 13.5% of 126 samples were positive (2.5 log CFU/g for positive samples) | Hutchison et al., 2004 |
Cryptosporidium | Pig feces | Australia, Sydney watersheds | 77.8% of 9 samples were positive | Cox et al., 2005 |
C. parvum | Pig feces | Britain | 5.2-13.5% samples were positive (1.5-1.8 log CFU/g in positive samples) | Hutchison et al., 2005 |
Cryptosporidium | Pig slurry | Spain | 40% of 5 pig farms were positive | Bornay-Llinares et al., 2006 |
C. parvum | Swine waste lagoons | U.S., Southeast | 1.2% of 407 samples were positive | Jenkins et al., 2010 |
Cryptosporidium | Swine feces | China, Shanghai | 34.4% of 2,323 samples were positive; 82.6% of positive samples were C. suis and 8.7% of positive samples were Cryptosporidium pig genotype II; 100% of 12 pig farms were infected with prevalence ranging from 14.1 to 90.6% | Chen et al., 2011 |
Cryptosporidium | Swine manure | Canada | 55.7% of 122 pooled samples from 10 farms were positive; 55.4% of positive samples were C. parvum and 37.5% of positive samples were Cryptosporidium sp. pig genotype II | Farzan et al., 2011 |
C. parvum | Sheep feces | U.K., England and Wales | 29.2% of 24 samples were positive (1.7 log CFU/g for positive samples) | Hutchison et al., 2004 |
Cryptosporidium | Sheep feces | Australia, Sydney watersheds | 66.6% of 9 samples were positive | Cox et al., 2005 |
C. parvum | Sheep feces | Britain | 29.2% samples were positive (1.0 log CFU/g in positive samples) | Hutchison et al., 2005 |
NOTE: CFU, colony forming unit.
TABLE A3-10Prevalence of Salmonella spp., STEC, and Protozoan Parasites in Environmental Waters
Pathogen | Water source | Location | Prevalence (% positive of number of samples analyzed) | Reference |
---|---|---|---|---|
Salmonella spp. | Water, pond/creeks | Australia, Brisbane | 3% of 32 | Ahmed et al., 2009 |
Water, river | Canada, Ontario | 62% of 32 | Droppo et al., 2009 | |
Water, river | U.S., GA | 79.2% of 72 | Haley et al., 2009 | |
Water, surface | Netherlands | 14.3% of 49 | Heuvelink et al., 2008 | |
Watersheds, swine | U.S., NC | 41.7% of 12 | Patchanee et al., 2010 | |
Watersheds, agriculture crops | U.S., NC | 50% of 12 | Patchanee et al., 2010 | |
Watersheds, forestry | U.S., NC | 57.1% of 28 | Patchanee et al., 2010 | |
Water, surface | Canada, Alberta | 6.2% of 1429 | Johnson et al., 2003 | |
Water, irrigation | Nigeria | 8.2% of 196 | Okago et al., 2003 | |
E. coli O157 | Water, surface | Netherlands | 2.0% of 49 | Heuvelink et al., 2008 |
E. coli O157:H7 | Water, surface | U.S., Central CA | 3.8% of 79 | Jay et al., 2007 |
Water, well | U.S., Central CA | 0% of 19 | Jay et al., 2007 | |
Water, surface | Canada, Alberta | 0.9% of 1483 | Johnson et al., 2003 | |
STEC | Water, pond and creeks | Australia, Brisbane | 9-15% of 32 | Ahmed et al., 2009 |
Cryptosporium | Water, reclaimed | U.S. | 70% of 30 | Harwood et al., 2005 |
Water, irrigation | Mexico | 18% of 11 | Thurston-Enriquez et al., 2002 | |
Water, irrigation | U.S. | <1 of 3 | Thurston-Enriquez et al., 2002 | |
Giardia | Water, reclaimed | U.S. | 80% of 30 | Harwood et al., 2005 |
Water, irrigation | Mexico | 64% of 11 | Thurston-Enriquez et al., 2002 | |
Water, irrigation | U.S. | 67% of 3 | Thurston-Enriquez et al., 2002 | |
Microsporidia | Water, irrigation | U.S. | 67% of 3 | Thurston-Enriquez et al., 2002 |
TABLE A3-11Prevalence of Enteric Food-Borne Pathogens in Wildlife and Insects
Animal | Pathogen | Country | Prevalence (% positive of number of samples analyzed) | Reference |
---|---|---|---|---|
Wild boars/pigs | E. coli O157:H7 | U.S. | 14.9% of 87 | Jay et al., 2007 |
E. coli O157:H7 | Spain | 3.3% of 212 | Sánchez et al., 2010 | |
Non-O157 STEC | Spain | 5.2% of 212 | Sánchez et al., 2010 | |
C. parvum | Australia | 0% of 5 | Cox et al., 2005 | |
Giardia | Australia | 0% of 5 | Cox et al., 2005 | |
Coyotes | Salmonella | U.S. | 5% of 40 | Gorski et al., 2011 |
Rabbits | E. coli (VTEC) | U.K. | 15.5% of 129 | Scaife et al., 2006 |
Cryptosporidium | Australia | 50% of 2 | Cox et al., 2005 | |
Giardia | Australia | 0% of 2 | Cox et al., 2005 | |
Raccoons | Salmonella | U.S. | 0% of 2 | Gorski et al., 2011 |
Skunks | Salmonella | U.S. | 30.7% of 13 | Gorski et al., 2011 |
Deer | E. coli O157:H7 | U.S. | 0% of 4 | Jay et al., 2007 |
Cryptosporidium | Australia | 100% of 1 | Cox et al., 2005 | |
Giardia | Australia | 0% of 1 | Cox et al., 2005 | |
Salmonella | U.S. | 1% of 500 | Renter et al., 2006 | |
Pigeons/sparrows | E. coli O157 | Czech Rep. | 0% of 70 | Čižek et al., 1999 |
Birds (cattle farm) | E. coli O157:H7 | U.S. | 0.5% of 200 pooled | Hancock et al., 1998 |
Geese, Canadian | E. coli (EHEC) | U.S. | 6.0% of 151 | Kullas et al., 2002 |
Multiple birds (domestic animal farms) | Salmonella | Denmark | 1.5% of 1285 | Skov et al., 2008 |
Multiple birds | Salmonella | U.S. | 6.6% of 105 | Gorski et al., 2011 |
Reptiles | Salmonella | Spain | 41.5% of 94 | Briones et al., 2004 |
Amphibians | Salmonella | Spain | 0% of 72 | Briones et al., 2004 |
Rats | E. coli O157 | Czech Rep. | 40% of 10 | Čižek et al., 1999 |
Mice, wood | E. coli O157 | Czech Rep. | 0% of 7 | Čižek et al., 1999 |
Rodents | E. coli O157:H7 | U.S. | 0% of 300 pooled | Hancock et al., 1998 |
Rodents | Toxoplasma gondii | Netherlands | 9.1% of 77 | Kijlstra et al., 2008 |
Rodents | Salmonella | Denmark | 2% of 135 | Skov et al., 2008 |
Mice/rats | S. Enteritidis | U.S. | 16.2% of 715 | Henzler and Opitz, 1992 |
Squirrels | S. enterica | U.S. | 0% of 28 | Gorski et al., 2011 |
Mice/rats | C. parvum | U.S. | 27.8% of 241 | Li et al., 2011 |
Flies | E. coli O157:H7 | U.S. | 3.3% of 60 | Hancock et al., 1998 |
Houseflies | E. coli O157:H7 | U.S. | 2.2% of 3,440 | Alam and Zurek, 2004 |
Flies | Salmonella | Denmark | 22.6% of 31 | Skov et al., 2008 |
Houseflies/dump flies | Salmonella | U.S. | 18% of 22 | Olsen and Hammack, 2000 |
Houseflies | S. Enteritidis | U.S. | ∼50% of 120 | Holt et al., 2007 |
Cockroaches | Salmonella | U.S. | 14.4% of 90 | Kopanic et al., 1994 |
Slugs | E. coli O157:H7 | U.K. | 0.2% of 33 | Sproston et al., 2006 |