Emerging Infectious Diseases [Volume 5 No.5 / September - October 1999] Perspectives *Rabies Surveillance Using GIS and a Spatial Filter, A. Curtis Synopses *Burden of Foodborne Illness in the U.S., P.S. Mead *Infections Associated with Eating Seed Sprouts, P.J. Taormina *Human Ehrlichiosis in the United States, J.H. McQuiston *West Nile Fever Reemerging in Europe, J. Hubálek *Characterization of New Cyclospora Species from Ethiopian Monkeys, M.L. Eberhard Research *Economics of Pandemic Influenza in the U.S.: Intervention Priorities, M. Meltzer *Host Genetics and the Severity of Coccidioidomycosis, L. Louie *Post-Injection Abscesses from M. abscessus After Unapproved Alternative Medication, K. Galil *Drug-Resistant S. pneumoniae in Oregon: Alterative Surveillance Method, A.E. Chin Dispatches *Diphtheria Antitoxin Levels in the Netherlands, H.E. de Melker *Acute Non-HPS Sin Nombre Hantavirus Infection in the U.S., P.T. Kitsutani *C. parvum in Commercially-Harvested Oysters, R. Fayer *B. vinsonii subsp. berkhoffii in California Coyotes, C. Chang *Epidemic Typhus Imported from Algeria, M. Niang *Yersinia enterocolitica O:9 in France, 1989–1997, F. Gourdon Letters *A new confirmed case of C. pseudodiphtheriticum pneumonia, M. Drancourt *Family Outbreak of Rickettsia conorii, G. Shazberg *Iron and the Role of C. pneumoniae in Heart Disease: Hypothesis, J.L. Sullivan *Filth Flies Transport Hosts of C. parvum, T.K. Graczyk *The Cost Effectiveness of Vaccinating Against Lyme Disease, D. Prybylski Book Review *The Elusive Magic Bullet: The Search for the Perfect Drug, A. Zuger News and Notes *European Study Group on Enterohemorrhagic E. coli Meeting Summary *Rabies in the Americas Conference *InternationalSymposium on Viral Hepatitis and Liver Disease *International Conference on Emerging Infectious Diseases *Erratum ------------------------------------------------------------ Perspective Using a Spatial Filter and a Geographic Information System to Improve Rabies Surveillance Data Andrew Curtis Louisiana State University, Baton Rouge, Louisiana, USA ------------------------------------------------------- The design and coordination of antirabies measures (e.g., oral vaccine and disease awareness campaigns) often depend on surveillance data. In Kentucky, health officials are concerned that the raccoon rabies epizootic that has spread throughout the east coast since the late 1970s could enter the state. The quality of surveillance data from Kentucky's 120 counties, however, may not be consistent. This article presents a geographic model that can be used with a geographic information system (GIS) to assess whether a county has a lower number of animals submitted for rabies testing than surrounding counties. This technique can be used as a first step in identifying areas needing improvement in their surveillance scheme. This model is a variant of a spatial filter that uses points within an area of analysis (usually a circle) to estimate the value of a central point. The spatial filter is an easy-to-use method of identifying point patterns, such as clusters or holes, at various geographic scales (county, intraurban), by using the traditional circle as an area of analysis or a GIS to incorporate a political shape (county boundary). Two raccoon rabies epizootics have been spreading from separate sites in the eastern United States. The original site was in Florida in the 1950s (1), the second in West Virginia/Virginia in 1977 as a result of the importation of rabid raccoons from Florida by hunters (2). In 1994, the two rabies waves met in North Carolina (3). Kentucky has so far not been affected by the epizootic because of geographic barriers the Appalachian Mountains in the east and the Ohio River to the north of the state. Raccoon rabies could enter Tennessee and from there move relatively unhindered into the Bluegrass area of central Kentucky (4). Raccoons are the wild animal most frequently submitted for rabies testing in Kentucky (150, 145, and 169 animals in 1995-97, respectively), even though the annual number of positive cases remains low (1 to 2 cases per year). These positive cases appear to occur as a result of spillover infection with skunk rabies, a variant of the virus that differs from the current raccoon rabies epizootic on the eastern seaboard. The high number of raccoons submitted for testing, however, indicates potential for an increase in raccoon rabies similar to that in eastern seaboard states (5-7). In New York State, for example, the number of rabid raccoons increased from 0 in 1985 to >2,000 in 1993. Surveillance data are useful in coordinating the placement of oral vaccination containment lines to limit the spread of the disease or quickly identify clusters of rabies beyond the containment zone. These data usually are provided by county officials or by the public after animal-human interaction (bite, scratch) or after an encounter with an animal exhibiting rabies symptoms. These data underrepresent the actual extent of the disease, because not all animals with rabies interact with people and not all interactions are reported (5,8,9). The quality of surveillance data varies among counties for several reasons (10, unpub. data). According to multivariate analysis, the number of animals submitted for testing was positively correlated with the number of people living in the county and negatively correlated with distance to the state testing facility in Frankfort (unpub. data). We describe a method that can improve the quality of surveillance data by identifying counties that submit lower numbers of animals for testing than their surrounding counties. This method is a variation of a spatial filter that is calculated within a geographic information system (GIS). Using a Spatial Filter in a GIS When counties that submit few animals for rabies testing are surrounded by counties with high numbers of submissions, underreporting is suspected. Different methods of data analysis can produce different visual (mapped) results. Conclusions, and resulting policy actions, therefore may vary according to the method chosen. Figure 1 shows three maps that can be generated from the rabies surveillance data: actual numbers of submissions; standardized submissions (submissions per 10,000 human population); and the mapped residuals of a regression of submissions compared with the human population. Results can also vary according to the classification scheme chosen, that is, the quantity and range of data assigned to each color category on the map. The size and shape of the area investigated (county units, zip codes, census tracts) may also produce different results, depending on the chosen political unitan effect known in geographic research as the Modifiable Area Unit Problem (11). Spatial filter models are methods of exploratory spatial analysis that smooth point data, allowing values for central data points to be calculated. The traditional spatial filter technique, as applied to medical research, involves placing a grid over the investigated area, with the intersections of the grid lines providing the centers of a series of overlapping circles. Rates are then calculated for these circles to give a continuous surface. This approach has the potential to better replicate distribution of a disease, because diseases do not usually follow political boundaries. An important aspect of the spatial filter is the size of the circle, i.e., the area over which the analysis is performed, which can affect the analysis result (12). Applying the Spatial Filter to the Number of Animals Submitted for Rabies Testing in Kentucky In this Kentucky example, the spatial filter is the county to be investigated and a sphere of influence around it. GIS modifies the shape of the filter to include a buffer that follows the exact shape of the county. The size of the filter is the extension of the buffer beyond the county boundary. The total number of points (numbers of animals submitted for rabies testing) that fall within the filter is then randomly distributed across the area, and this randomization is repeated 100 times. If the number of randomly generated points in the investigated county is lower than the actual number of surveillance points in fewer than 5 of the 100 random runs, there is a 95% chance that a significantly low frequency (number of animals submitted for testing) was reported from that county. Figure 1 [Fig] Figure 1. Comparison of data analysis for identifying counties with low submission rates. Applying the Spatial Filter to Surveillance Data in Kentucky The different maps of animals submitted for rabies testing in Kentucky for 1997 (Figure 1) confirm that several counties appear to submit low numbers of animals. For example, one county we investigated, Edmonson, although appearing to be a `hole' in both the map of raw animal submission numbers and the map of residuals generated by the regression of submissions compared with the human population, does not appear to have underreported when the data are standardized by the human population. A benefit of the spatial filter is that it can be applied to any variable with a spatial location. This analysis depends on an initial visual interpretation because the data are aggregated at the county level. In 1997, two animals were submitted for testing from Edmonson County. The surrounding five counties submitted 98 animals for testing, for a total of 100 submissions from the six-county area (Figure 2a). The first step is to randomly distribute all submissions across the county of origin (Figure 2b). Using the actual origin of the animal would improve the analysis, as the more traditional spatial filter method could be used; however, this information is not available from the submissions record. The second step is to layer a grid of coordinates across the six-county area (Figure 2c). This grid consists of closely packed coordinates onto which the submissions for each county can be randomly assigned. The spatial filter is then centered on Edmonson County and a buffer of 5 km is drawn. The buffer size of 5 km provides a standard buffer that could be used for any county, and which would, on average, match the area of an investigated county. The randomly distributed animal submissions for each of the surrounding five counties are then displayed to see how many animals were submitted for testing from the buffered area (Figure 2d). The simulation can be repeated several times, and a histogram can be used to identify the most frequent number of animal submissions from the buffer being chosen for the filter analysis. For this example, 12 animals were allocated to the area of Edmonson County and its surrounding 5-km buffer (two from Edmonson County and 10 from the buffer area). Within a GIS these 12 points are randomly redistributed across the area of Edmonson County plus buffer. This simulation procedure is repeated 100 times (Figure 2e displays 5, 6, and 8 submissions falling on the central county). The number of points falling just within Edmonson County for each of the random runs was recorded. In 100 runs, the fewest number of points (animal submissions) allocated to Edmonson County was three. Thus, the number of submissions is significantly low compared with those from the surrounding counties. Our analysis did not replicate the number of submissions from Edmonson County in 1997 in any of the 100 simulations generated from a data distribution that matched the surveillance data of 1997. The lower count from Edmonson County may result from a smaller human population, more limited animal habitat, or fewer human-animal interactions. The landscape of the buffer may also differ from that of the surrounding counties, making it poor habitat for raccoons. This technique identifies `holes' in data, prompting further investigation for causes. Improvements to the Filter The most important improvement in using the spatial filter technique is that current submission records should start to contain precise spatial locations. Surveillance data from other states contain a spatial location, such as the distance from a road intersection (6), obtained in postrabies confirmation interview. A Global Positioning System, or even a systematic method to locate submissions according to a paper map reference system, would allow the spatial filter to be calculated as a series of overlapping circles that do not depend on political boundaries. The technique presented in this article provides an investigator, such as a state health official, with a quick and accurate method of identifying statistically significant data holes in a surface of animals submitted for rabies testing. A decision can then be made as to whether the `hole' is expected or needs further investigation. This technique can also be applied to any point data surface where the identification of a `hole' is important, e.g., if one part of a suburb has fewer Lyme disease cases than its surrounding areas. Acknowledgments The author thanks M.B. Auslander for his continued support and R. Mitchelson for his critical review of this manuscript. This work was funded by a research grant from Morehead State University. Dr. Curtis is an instructor at the Department of Geography and Anthropology at Louisiana State University. His research interests include developing spatial analysis within a GIS environment, with a particular emphasis on medical data. References 1. Bigler WJ, McLean RG, Trevino HA. Epizootiologic aspects of raccoon rabies in Florida. Am J Epidemiol 1973;98:326-35. 2. Jenkins SR, Winkler WG. Descriptive epidemiology from an epizootic of raccoon rabies in the middle Atlantic states, 1982-1983. Am J Epidemiol 1987;126:429-37. 3. Krebs JW, Strine TW, Smith JS, Rupprecht CE, Childs JE. Rabies surveillance in the United States during 1994. J Am Vet Med Assoc 1995;207:1562-75. 4. Taylor L. Raccoons expected to spread risk in Ky. Lexington Herald-Leader May 25, 1998; Business Monday p. 11. 5. Wilson ML, Bretsky PM, Cooper GH Jr, Egbertson SH, Van Kruiningen HJ, Cartter ML. Emergence of raccoon rabies in Connecticut, 1991-1994: spatial and temporal characteristics of animal infection and human contact. Am J Trop Med Hyg 1997;57:457-63. 6. Hubbard DR. A descriptive epidemiological study of raccoon rabies in a rural environment. J Wildl Dis 1985;21:105-10. 7. Beck A, Felser S, Glickman L. An epizootic of rabies in Maryland, 1982-84. Am J Public Health 1987;77:42-44. 8. Krebs JW, Wilson ML, Childs JE. Rabies-epidemiology, prevention, and future research. Journal of Mammalogy 1985;76:681-94. 9. Smith JS. New aspects of rabies with emphasis on epidemiology, diagnosis, and prevention of the disease in the United States. Clin Microbiol Rev 1996;Apr:166-176. 10. Heidt G, Ferguson D, Lammers J. A profile of reported skunk rabies in Arkansas: 1977-1979. J Wildl Dis 1982;18:269-77. 11. Curtis A, MacPherson AD. The zone definition problem in survey research: an empirical example from New York State. The Professional Geographer 1996;48:310-20. 12. Scott DW. Multivariate density estimation: theory, practice and visualization. New York: J. Wiley; 1992. Address for correspondence: Andrew Curtis, E110 Howe/Russell Geoscience Complex, Louisiana State University, Baton Rouge, LA 70803-4105, USA; fax: 225-388-4420; e-mail: acurti1@lsu.edu. Figure 2 [Fig] Figure 2. Application of spatial filter with a geographic information system. ------------------------------------------------------------ Synopses Food-Related Illness and Death in the United States Paul S. Mead, Laurence Slutsker, Vance Dietz, Linda F. McCaig, Joseph S. Bresee, Craig Shapiro, Patricia M. Griffin, and Robert V. Tauxe Centers for Disease Control and Prevention, Atlanta, Georgia, USA ------------------------------------------------------- To better quantify the impact of foodborne diseases on health in the United States, we compiled and analyzed information from multiple surveillance systems and other sources. We estimate that foodborne diseases cause approximately 76 million illnesses, 325,000 hospitalizations, and 5,000 deaths in the United States each year. Known pathogens account for an estimated 14 million illnesses, 60,000 hospitalizations, and 1,800 deaths. Three pathogens, Salmonella, Listeria, and Toxoplasma, are responsible for 1,500 deaths each year, more than 75% of those caused by known pathogens, while unknown agents account for the remaining 62 million illnesses, 265,000 hospitalizations, and 3,200 deaths. Overall, foodborne diseases appear to cause more illnesses but fewer deaths than previously estimated. More than 200 known diseases are transmitted through food (1). The causes of foodborne illness include viruses, bacteria, parasites, toxins, metals, and prions, and the symptoms of foodborne illness range from mild gastroenteritis to life-threatening neurologic, hepatic, and renal syndromes. In the United States, foodborne diseases have been estimated to cause 6 million to 81 million illnesses and up to 9,000 deaths each year (2-5). However, ongoing changes in the food supply, the identification of new foodborne diseases, and the availability of new surveillance data have made these figures obsolete. New, more accurate estimates are needed to guide prevention efforts and assess the effectiveness of food safety regulations. Surveillance of foodborne illness is complicated by several factors. The first is underreporting. Although foodborne illnesses can be severe or even fatal, milder cases are often not detected through routine surveillance. Second, many pathogens transmitted through food are also spread through water or from person to person, thus obscuring the role of foodborne transmission. Finally, some proportion of foodborne illness is caused by pathogens or agents that have not yet been identified and thus cannot be diagnosed. The importance of this final factor cannot be overstated. Many of the pathogens of greatest concern today (e.g., Campylobacter jejuni, Escherichia coli O157:H7, Listeria monocytogenes, Cyclospora cayetanensis) were not recognized as causes of foodborne illness just 20 years ago. In this article, we report new estimates of illnesses, hospitalizations, and deaths due to foodborne diseases in the United States. To ensure their validity, these estimates have been derived by using data from multiple sources, including the newly established Foodborne Diseases Active Surveillance Network (FoodNet). The figures presented include estimates for specific known pathogens, as well as overall estimates for all causes of foodborne illness, known, unknown, infectious, and noninfectious. Data Sources Data sources for this analysis include the Foodborne Diseases Active Surveillance Network (FoodNet) (6), the National Notifiable Disease Surveillance System (7), the Public Health Laboratory Information System (8), the Gulf Coast States Vibrio Surveillance System (9), the Foodborne Disease Outbreak Surveillance System (10), the National Ambulatory Medical Care Survey (11), the National Hospital Ambulatory Medical Care Survey (12-14), the National Hospital Discharge Survey (15), the National Vital Statistics System (16), and selected published studies. Established in 1996, FoodNet is a collaborative effort by the Centers for Disease Control and Prevention, the U.S. Department of Agriculture, the U.S. Food and Drug Administration, and selected state health departments. FoodNet conducts active surveillance for seven bacterial and two parasitic foodborne diseases within a defined population of 20.5 million Americans (6). Additional surveys conducted within the FoodNet catchment area provide information on the frequency of diarrhea in the general population, the proportion of ill persons seeking care, and the frequency of stool culturing by physicians and laboratories for selected foodborne pathogens. The National Notifiable Disease Surveillance System (7) and the Public Health Laboratory Information System (8) collect passive national surveillance data for a wide range of diseases reported by physicians and laboratories. The Gulf Coast States Vibrio Surveillance System collects reports of Vibrio infections from selected states (9), and the Foodborne Disease Outbreak Surveillance System receives data from all states on recognized foodborne illness outbreaks (defined as two or more cases of a similar illness resulting from ingestion of a common food) (10). As components of the National Health Care Survey, the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey measure health care use in various clinical settings, including physician offices and hospital emergency and outpatient departments (11-14). These surveys collect information on patient characteristics, patient symptoms or reasons for visit, provider diagnosis, and whether the patient was hospitalized. Up to three symptoms are recorded using a standard classification (17), and up to three provider diagnoses are recorded according to the International Classification of Diseases, 9th Revision, Clinical Modifications (ICD-9-CM) [18] (Table 1). The National Hospital Discharge Survey, another component of the National Health Care Survey, is a representative annual sample of discharge records from approximately 475 nonfederal short-stay hospitals (15). The information collected includes up to seven principal discharge diagnoses classified by ICD-9-CM codes (18). Because these data include information on condition at discharge, they can be used as a source of information on in-hospital deaths. Additional information on food-related deaths was obtained from the National Vital Statistics System, which collects death certificate data on causes of death classified by 3- or 4-digit ICD-9 codes 16). In addition to information from these formal surveillance systems, we used data from two published population-based studies. The Tecumseh study was conducted from 1965 through 1971 in 850 households in Tecumseh, Michigan, with an emphasis on households with young children (19). Households were telephoned weekly to identify incident cases of self-defined diarrhea, vomiting, nausea, or stomach upset. The Cleveland study was conducted among a selected group of 86 families followed from 1948 through 1957 (20). A family member recorded occurrences of gastrointestinal illnesses and associated symptoms on a monthly tally sheet. Both studies also collected information on extraintestinal illnesses (e.g., respiratory illness). Other studies with similar designs were not included in our analysis, either because they were relatively small or because they did not provide information on the desired endpoints. The Study Food-Related Illness and Death from Known Pathogens Total Cases To estimate the total number of foodborne illnesses caused by known pathogens, we determined the number of reported cases for each pathogen, adjusted the figures to account for underreporting, and estimated the proportion of illnesses specifically attributable to foodborne transmission. Although data from various periods were used, adjustments for changes in population size had minimal effect on the final estimates and were therefore omitted. Cases may be reported in association with documented foodborne outbreaks, through passive surveillance systems (e.g., the National Notifiable Disease Surveillance System, the Public Health Laboratory Information System), or through active surveillance systems (e.g., FoodNet). Sporadic illness caused by some pathogens (e.g., Bacillus cereus, Clostridium perfringens, Staphylococcus aureus) is not reportable through passive or active systems; hence, the only cases reported are those related to outbreaks. For these pathogens, we have assumed that if diagnosed sporadic cases were reported, the total number would be 10 times the number of outbreak-related cases. This multiplier is based on experience with pathogens for which data are available on both sporadic and outbreak-associated cases (e.g., reported cases of Salmonella or Shigella, Table 2). For all pathogens, the number of outbreak-related cases was calculated as the average annual number of such cases reported to CDC from 1983 to 1992, the most recent years for which published outbreak data are available. For pathogens also under passive surveillance, we used the average number of cases reported to CDC from 1992 through 1997, and for pathogens under active surveillance through FoodNet, we used the average rate observed for the surveillance population from 1996 to 1997 and applied this to the total 1997 U.S. population (with some modification for E. coli O157:H7; Appendix). Table 1. ICD-9-CM codes and associated conditions ------------------------------- Code Condition ------------------------------- 001 Cholera 002 Typhoid fever 003 Salmonella 004 Shigellosis 005.0 Staphyloccocal food poisoning 005.1 Botulism 005.2-005.3 Other Clostridia 005.4 Vibrio parahaemolyticus 005.8-005.9 Other and unspecified bacterial food poisoning 006 Amebiasis 007.1 Giardiasis 007.0, Other protozoal intestinal 007.2-007.9 infections 008.00, Misc. Escherichia coli 008.09 008.01 Enteropathogenic E. coli 008.02 Enterotoxigenic E. coli 008.03 Enteroinvasive E. coli 008.04 Enterohemorrhagic E. coli 008.43 Campylobacter 008.44 Yersinia 008.41-2, Misc. bacterial 008.46-9, 008.5 008.61 Rotavirus 008.62 Adenovirus 008.63 Norwalk virus 008.64 Other small round structured viruses 008.65 Calicivirus 008.66 Astrovirus 008.67 Enterovirus 008.69, Other virus 008.8 009. Ill-defined intestinal infections 558.9 Other noninfectious gastroenteritis ------------------------------- Table 2. Reported and estimateda illnesses, frequency of foodborne transmission, and hospitalization and case-fatality rates for known foodborne pathogens, United States [Table too large to be viewed in ascii format. Please view in html or pdf formats] Irrespective of the surveillance system, many cases of foodborne illness are not reported because the ill person does not seek medical care, the health-care provider does not obtain a specimen for diagnosis, the laboratory does not perform the necessary diagnostic test, or the illness or laboratory findings are not communicated to public health officials. Therefore, to calculate the total number of illnesses caused by each pathogen, it is necessary to account for underreporting, i.e., the difference between the number of reported cases and the number of cases that actually occur in the community. For Salmonella, a pathogen that typically causes nonbloody diarrhea, the degree of underreporting has been estimated at ~38 fold (Voetsch, manuscript in preparation) (21). For E. coli O157:H7, a pathogen that typically causes bloody diarrhea, the degree of underreporting has been estimated at ~20 fold (22). Because similar information is not available for most other pathogens, we used a factor of 38 for pathogens that cause primarily nonbloody diarrhea (e.g., Salmonella, Campylobacter) and 20 for pathogens that cause bloody diarrhea (e.g., E. coli O157:H7, Shigella). For pathogens that typically cause severe illness (i.e., Clostridium botulinum, Listeria monocytogenes), we arbitrarily used a far lower multiplier of 2, on the assumption that most cases come to medical attention. Details of the calculations for each specific pathogen and rationale are provided in the Appendix. Where information from both active and passive reporting was available, we used the figure from active surveillance when estimating the total number of cases. Having estimated the number of cases caused by each pathogen, the final step was to estimate for each the percentage of illness attributable to foodborne transmission. The total number of cases was then multiplied by this percentage to derive the total number of illnesses attributable to foodborne transmission. The rationale for each estimate is presented in the Appendix; although precise percentages are generally difficult to justify, in most instances there is ample support for the approximate value used. Results are presented in Tables 2 and 3. Known pathogens account for an estimated 38.6 million illnesses each year, including 5.2 million (13%) due to bacteria, 2.5 million (7%) due to parasites, and 30.9 million (80%) due to viruses (Table 2). Overall, foodborne transmission accounts for 13.8 million of the 38.6 million illnesses (Table 3). Excluding illness caused by Listeria, Toxoplasma, and hepatitis A virus (three pathogens that typically cause gastrointestinal illness), 38.3 million cases of acute gastroenteritis are caused by known pathogens, and 13.6 million (36%) of these are attributable to foodborne transmission. Among all illnesses attributable to foodborne transmission, 30% are caused by bacteria, 3% by parasites, and 67% by viruses. Hospitalizations To estimate the number of hospitalizations due to foodborne transmission, we calculated for each pathogen the expected number of hospitalizations among reported cases by multiplying the number of reported cases by pathogen-specific hospitalization rates from FoodNet data (23, 24), reported outbreaks (10, 25), or other published studies (Appendix). Not all illnesses resulting in hospitalization are diagnosed or reported. Health-care providers may not order the necessary diagnostic tests, patients may have already taken antibiotics that interfere with diagnostic testing, or the condition leading to hospitalization may be a sequela that develops well after resolution of the actual infection (e.g., Campylobacter-associated Guillain-Barré syndrome). Therefore, to account for underreporting, we doubled the number of hospitalizations among reported cases to derive for each pathogen an estimate of the total number of hospitalizations. Finally, we multiplied this figure by the proportion of infections attributable to foodborne transmission. Because of gaps in the available data, this approach could not be used for some parasitic and viral diseases (Appendix). Overall, the pathogens listed in Table 2 cause an estimated 181,177 hospitalizations each year, of which 60,854 are attributable to foodborne transmission (Table 3). Excluding hospitalizations for infection with Listeria, Toxoplasma, and hepatitis A virus, 163,015 hospitalizations for acute gastroenteritis are caused by known pathogens, of which 55,512 (34%) are attributable to foodborne transmission. Overall, bacterial pathogens account for 60% of hospitalizations attributable to foodborne transmission, parasites for 5%, and viruses for 34%. Deaths Like illnesses and hospitalizations, deaths are also underreported. Precise information on food-related deaths is especially difficult to obtain because pathogen-specific surveillance systems rarely collect information on illness outcome, and outcome-specific surveillance systems (e.g., death certificates) grossly underreport many pathogen-specific conditions. To estimate the number of deaths due to bacterial pathogens, we used the same approach described for hospitalizations: first calculating the number of deaths among reported cases, then doubling this figure to account for unreported deaths, and finally multiplying by the percentage of infections attributable to foodborne transmission. As with hospitalization, this approach could not be used for some parasitic and viral diseases. Overall, the specified pathogens cause an estimated 2,718 deaths each year, of which 1,809 are attributable to foodborne transmission (Table 3). Excluding death due to Listeria, Toxoplasma, and hepatitis A virus, the number of deaths due to pathogens that cause acute gastroenteritis is 1,381, of which 931 (67%) are attributable to foodborne transmission. Bacteria account for 72% of deaths associated with foodborne transmission, parasites for 21%, and viruses for 7%. Five pathogens account for over 90% of estimated food-related deaths: Salmonella (31%), Listeria (28%), Toxoplasma (21%), Norwalk-like viruses (7%), Campylobacter (5%), and E. coli O157:H7 (3%). Table 3. Estimated illnesses, hospitalizations, and deaths caused by known foodborne pathogens, United States [Table too large to be viewed in ascii format. Please view in html or pdf formats] Food-Related Illness and Death from Unknown Pathogens Some proportion of gastrointestinal illness is caused by foodborne agents not yet identified. This conclusion is supported by well-documented foodborne outbreaks of distinctive illness for which the causative agent remains unknown (e.g., Brainerd diarrhea) (26), by the large percentage of foodborne outbreaks reported to CDC for which no pathogen is identified (25), and by the large number of new foodborne pathogens identified in recent years. To estimate food-related illness and death from unknown pathogens, we used symptom-based data to estimate the total number of acute gastrointestinal illnesses and then subtracted from this total the number of cases accounted for by known pathogens; this difference represents the illness due to acute gastroenteritis of unknown etiology. To determine how much of this illness was due to foodborne transmission, we used the percentages of foodborne transmission as determined above for acute gastroenteritis caused by known pathogens. Total Cases To determine the rate of acute gastroenteritis in the general population, we used data on the frequency of diarrhea from the 1996 to 1997 FoodNet population survey. This survey did not collect data on the rate of vomiting among persons without diarrhea, however, so we relied on the Tecumseh and Cleveland studies for information on the frequency of this symptom. Because young children were overrepresented in the Tecumseh and Cleveland studies relative to the current U.S. population, rates of illness for these studies were age-adjusted. For the Tecumseh data, we used the reported age- and symptom-specific rates. For the Cleveland study, we used the method described by Garthright (27) to derive an overall age-adjusted rate of gastrointestinal illness; we then multiplied this rate by the relative frequency of symptoms to derive age-adjusted rates for specific symptoms. In the 1996-97 FoodNet population survey, the overall rate of diarrhea was 1.4 episodes per person per year, and the rate of diarrheal illness, defined as diarrhea ( 3 loose stools per 24-hour period) lasting >1 day or interfering with normal activities, was 0.75 episodes per person per year (H. Herikstad, manuscript in preparation). We used the lower 0.75 rate for our analysis. To this we added the average age-adjusted rate of vomiting without diarrhea from the Tecumseh and Cleveland studies (0.30, Table 4) to derive an overall estimate of 1.05 episodes per person per year of acute gastrointestinal illness characterized by diarrhea, vomiting, or both. Table 4. Frequency of gastrointestinal illness in the general population, in episodes per person per year, as determined by three studies --------------------------------------------------------- FoodNet Population Tecumseh Cleveland Survey Study Study ---------------------------------------------------------- Symptom Age Crude Age Crude Age adj. adj. adj. ----------------------------------------------------------- Diarrhea or vomiting -- 0.98 0.81 1.28 0.87 Diarrhea, any 0.75 0.63 0.52 0.83 0.56 Without vomiting 0.61 0.40 0.33 0.48 0.33 With vomiting 0.14 0.23 0.19 0.35 0.23 Vomiting without -- 0.35 0.29 0.45 0.31 diarrhea ----------------------------------------------------------- Previous studies have shown that some cases of acute gastrointestinal illness are accompanied by respiratory symptoms; although the causes of these illnesses are generally unknown, such cases have traditionally been attributed to respiratory pathogens (20,27). Data on the frequency of concomitant respiratory symptoms were not collected in the 1996-97 FoodNet survey but were 20% to 27% among patients with acute gastroenteritis in the Tecumseh and Cleveland studies. Therefore, we adjusted downward our estimate of acute gastroenteritis by 25%, yielding a final estimate of 0.79 (1.05 X 0.75) episodes of acute gastroenteritis per person per year. Extrapolated to a population of 267.7 million persons, the U.S. resident population in 1997 (28), this rate is equivalent to 211 million episodes each year in the United States. As determined previously, 38.3 million of these 211 million episodes of acute gastroenteritis are attributable to known pathogens. A small proportion of the remaining 173 million episodes can be accounted for by known, noninfectious agents (e.g., mycotoxins, marine biotoxins); however, most are attributable to unknown agents. Because we cannot directly ascertain how many of these illnesses of unknown etiology are due to foodborne transmission, we used the relative frequency of foodborne transmission for known pathogens as a guide. For illnesses of known etiology, foodborne transmission accounts for 36% of total cases. Applying this percentage yields an estimate of 62 million cases of acute gastroenteritis of unknown etiology (36% of 173 million) due to foodborne transmission each year. Hospitalizations The National Ambulatory Medical Care Survey/the National Hospital Ambulatory Medical Care Survey data were searched for visits due to symptoms of diarrhea, vomiting, or gastrointestinal infection (reason for visit classification (RVC) codes 1595, 1530, 1540)(17) and for visits resulting in a diagnosis of infectious enteritis (ICD-9-CM codes 001-009.3; Table 1). Visits associated with respiratory symptoms (RVC codes 1400-1499) or a diagnosis of influenza (ICD-9-CM code 487) were excluded. Data for the years 1992 to 1996 were combined before analysis. Overall, these criteria yielded an average of 15,810,905 visits annually from 1992 through 1996, of which an average of 1,246,763, or 7.9%, resulted in hospitalization. This figure is equivalent to a rate of 4.7 hospitalizations per 1,000 person-years. The National Hospital Discharge Survey data were searched by using diagnostic codes for infectious gastroenteritis of known cause (ICD-9-CM codes 001-008; Table 1), with the exception of the code for Clostridium difficile colitis (ICD9 008.45), a common form of nosocomially acquired diarrhea. In addition, we included the nonspecific ICD-9-CM diagnosis codes 009 (infectious gastroenteritis) and 558.9 (other and unspecified noninfectious gastroenteritis and colitis). Despite the description, many of the illnesses attributed to ICD-9-CM code 558.9 are likely to be either infectious or due to agents possibly transmitted by food. For example, in the absence of laboratory testing, sporadic cases of viral gastroenteritis may be coded as 558.9. Under the previous ICD-8 classification, these same cases would have been assumed to be infectious and coded as 009 (29, 30). Data for the years 1992 to 1996 were weighted according to National Center for Health Statistics criteria and averaged to derive national estimates of annual hospitalizations. Records with a diagnosis of respiratory illness were not excluded because of the high incidence of respiratory infections among hospitalized patients. Considering all listed diagnoses, the National Hospital Discharge Survey data for the years 1992 to 1996 yielded an annual average of 616,337 hospital discharges with a diagnosis of gastrointestinal illness. Included in this figure are 193,084 cases of gastroenteritis with an identified pathogen and an additional 423,293 cases of gastroenteritis of unknown etiology (Table 5). Converted to a rate, the total number is equivalent to 2.3 hospitalizations per 1,000 person-years. Because these data depend on the recording of a diagnosis and not just a symptom, it is likely that they underestimate the rate of hospitalization for acute gastroenteritis. This view is supported by FoodNet population survey data indicating a rate of approximately 7.2 hospitalizations per 1,000 person-years for diarrheal illness (H. Herikstad, manuscript in preparation). These data were not included here because they omit hospitalizations for vomiting alone and are not easily adjusted for concomitant respiratory symptoms. Averaging the rates from the National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey and National Hospital Discharge Survey yields a final estimate of 3.5 hospitalizations per 1,000 person-years, equivalent to 936,726 hospitalizations annually for acute gastroenteritis. As noted previously, 163,153 of these hospitalizations can be attributed to known causes of acute gastroenteritis, yielding an estimated 773,573 hospitalizations for acute gastroenteritis caused by unknown agents. Applying the relative frequency of foodborne transmission as determined for known pathogens yields an estimated 263,015 hospitalizations (34% of 773,573) for acute gastroenteritis due to foodborne transmission of unknown agents. Table 5. Average annual hospitalizations and deaths for gastrointestinal illness by diagnostic category, National Hospital Discharge Survey, 1992–1996 ------------------------------------------------------------ 1st diagnosis All diagnoses -------------------- ------------------- Cause of Hosp. Deaths Hosp. Deaths enteritis(sup a) ----------------------------------------------------------- Bacterial 27,987 148(sup b) 54,953 1,139 (001-005, 008-008.5) Viral 82,149 0(sup b) 132,332 194(sup b) (008.6-008.8) Parasitic 2,806 82(sup b) 5,799 127(sup b) (006-007) Unknown 186,537 868(sup b) 423,293 5,148 etiology (009, 558.9) Total 299,479 1,898 616,377 6,608 ------------------------------------------------------------ (sup a)ICD-9-CM code. (sup b)Estimate unreliable due to small sample size. Deaths Multiple-cause-of-death data (16) and information on in-hospital-death data (National Hospital Discharge Survey) were used. ICD-9-CM codes 001-008 were employed to identify deaths due to diagnosed infectious gastroenteritis and ICD-9-CM codes 009 and 558 to identify deaths due to gastroenteritis of unknown etiology. Death certificate data for the years 1992 to 1996 yielded an annual average of 6,195 total deaths, of which 1,432 (23%) were due to specific causes of gastroenteritis and 4,763 (77%) to undiagnosed causes of gastroenteritis. For the same years and ICD-9-CM codes, the average annual in-hospital deaths for all-listed diagnoses totaled 6,608, of which 1,460 were due to specific and 5,148 (77%) undiagnosed causes of gastroenteritis (Table 5). Averaging the totals for all causes from death certificate and National Hospital Discharge Survey data and adjusting to the 1997 U.S. census estimates, we estimated that gastroenteritis contributed to the death of 6,402 persons in the United States in 1997. A total of 1,386 of these deaths can be explained by known causes of acute gastroenteritis (see above). Thus an estimated 5,016 deaths from acute gastroenteritis are caused by unknown agents. Applying the relative frequency of foodborne transmission as determined for known pathogens yields an estimated 3,360 deaths (67% of 5,016) due to acute gastroenteritis caused by foodborne transmission of unknown agents. Overall Food-Related Illness and Death We summed illness attributable to foodborne gastroenteritis caused by known and unknown pathogens, yielding an estimate of 76 million illnesses, 318,574 hospitalizations, and 4,316 deaths. Adding to these figures the nongastrointestinal illness caused by Listeria, Toxoplasma, and hepatitis A virus, we arrived at a final national estimate of 76 million illnesses, 323,914 hospitalizations, and 5,194 deaths each year (Figure 1). Conclusions The nature of food and foodborne illness has changed dramatically in the United States over the last century. While technological advances such as pasteurization and proper canning have all but eliminated some disease, new causes of foodborne illness have been identified. Researchers have used various methods to estimate the illnesses and deaths due to foodborne diseases in the United States. In 1985, Archer and Kvenberg coupled information on underreporting of salmonellosis with data on other foodborne pathogens to derive estimates of 8.9 million illnesses due to known pathogens and 24 million to 81 million illnesses due to all foodborne agents (2). In 1987, Bennett et al. computed incidence figures for all known infectious diseases and determined the proportion of each due to various modes of transmission. Summing these figures, they concluded that foodborne transmission of known pathogens caused 6.5 million illnesses and up to 9,000 deaths each year (3). In 1989, Todd used a combination of methods, including extrapolation from Canadian surveillance data, to derive an estimate of 12.5 million foodborne illnesses and 522 related deaths each year (4). Finally, in 1994, a task force convened by the Council for Agricultural Science and Technology (CAST) reviewed available studies and estimated the overall number of food-related illnesses at 33 million cases per year (5). These various estimates often refer to different entities. The estimates of 6.5 million and 8.9 million refer to illness caused by known pathogens, whereas the estimate of 33 million refers to all causes of foodborne illnesses, known and unknown, infectious and noninfectious. Our estimates are based on data from a wide variety of sources and differ from previous estimates in several respects. For known pathogens, our estimate of 13.8 million illnesses per year is substantially higher than the previous estimates of 6.5 million and 8.9 million (2, 3), an increase attributable largely to our inclusion of foodborne illness caused by Norwalk-like viruses. For foodborne illness of all etiologies, our estimate of 76 million illnesses is within the range proposed by Archer and Kvenberg (2) but considerably higher than the point estimate of 33 million presented in the CAST report (5). Both our estimate and the CAST estimate assume that foodborne transmission accounts for ~35% of acute gastroenteritis cases caused by unknown agents. The disparity between the two stems from differences in the estimated annual frequency of acute gastroenteritis overall: 211 million cases for our estimate, 99 million for the CAST estimate. Whereas our estimates of illness are generally higher than those of previous studies, our estimates of death are generally lower. We estimate that foodborne illness causes 5,020 deaths annually (1,810 deaths due to known pathogens and 3,210 deaths due to unknown agents), a total that is slightly more than half the 9,000 deaths estimated by Bennett et al. (3). The Bennett estimate includes 2,100 deaths due to campylobacteriosis, 1,200 deaths due to staphylococcal food poisoning, and 1,000 deaths due to trichinosis: our total for all three of these diseases is 101 deaths. Our estimated case-fatality rates for several other diseases are also lower than those used in the Bennett report, either because better data are available or perhaps because treatment has improved. Our analysis suggests that unknown agents account for approximately 81% of foodborne illnesses and hospitalizations and 64% of deaths. Among cases of foodborne illness due to known agents, Norwalk-like viruses account for over 67% of all cases, 33% of hospitalizations, and 7% of deaths. The assumptions underlying the Norwalk-like viruses figures are among the most difficult to verify, and these percentages should be interpreted with caution (Appendix). Other important causes of severe illness are Salmonella and Campylobacter, accounting for 26% and 17% of hospitalizations, respectively. The leading causes of death are Salmonella, Listeria, and Toxoplasma, which together account for 1,427, or more than 75% of foodborne deaths caused by known pathogens. Many of the deaths due to toxoplasmosis occur in HIV-infected patients; recent advances in HIV treatment may greatly reduce deaths due to toxoplasmosis. Of necessity, our analysis entails a number of assumptions. The first major assumption concerns the degree of underreporting. Well-documented estimates of underreporting are not available for most pathogens; therefore, we relied on multipliers derived for salmonellosis and other diseases. For salmonellosis, the multiplier of 38 has been independently derived by investigators in the United States using different data sources. The U.S. figure is five to tenfold higher than multipliers for Salmonella and Campylobacter recently derived in Great Britain (31). However, this difference is nearly or wholly offset by far higher per capita rates of reported infections in Great Britain. Nevertheless, when extrapolated to other pathogens, these multipliers may result in under- or overestimates, and clearly studies such as those conducted for Salmonella are needed to develop better multipliers for these other diseases. However, in our analysis, changing the multipliers for individual diseases has a minimal effect on the overall estimate of foodborne illness. Our second set of assumptions concerns the frequency of foodborne transmission for individual pathogens. We have used published studies when available, but these are rare. As with underreporting multipliers, errors affect estimates for individual pathogens but have minimal effect on the estimate of overall illness and death from foodborne diseases. The one notable exception is the estimate for Norwalk-like viruses. Because these viruses account for an especially large number of illnesses, changes in the percentage attributed to foodborne transmission have a major effect on our overall estimates. For example, if the actual number of infections due to foodborne transmission were 30% rather than 40%, the overall estimate would decrease from 76 million to 63 million illnesses per year. Interestingly, our overall estimate is influenced far less by the Norwalk-like virus case estimate itself. It would require a 100-fold reduction in the estimated number of Norwalk-like virus cases to reduce the overall estimate from 76 million to 63 million. A third assumption concerns the frequency of acute gastroenteritis in the general population. The rate we used is based in part on recent data from the FoodNet population survey, a retrospective survey involving more than 9,000 households. The overall rate of diarrhea as recorded by the survey was 1.4 episodes per person per year; however, we used the survey's far lower rate of 0.75 episodes of diarrheal illness per person per year. Furthermore, we limited our definition of acute gastroenteritis to symptoms of diarrhea or vomiting and reduced the rate to account for concomitant respiratory symptoms. As a result, our final assumed rate of 0.79 episodes of acute gastroenteritis per person per year is very similar to respiratory-adjusted estimates derived from the prospectively conducted Tecumseh (0.74) and Cleveland (0.71) studies (27). All three studies are based on household surveys, and thus the rates of illness are not influenced by changes in health-care delivery. Compared with rates of diarrheal illness from studies conducted in Great Britain, our estimated rate is higher than in one recent study (31) but lower than another (32). In addition to these assumptions, our analysis has several limitations. Differences in available surveillance information prevented us from using the same method to estimate illness and death from bacterial, parasitic, and viral pathogens. Furthermore, because of a paucity of surveillance information, we did not include specific estimates for some known, occasionally foodborne pathogens (e.g., Plesiomonas, Aeromonas, or Edwardsiella), nor did we develop specific estimates for known noninfectious agents, such as mushroom or marine biotoxins, metals, and other inorganic toxins. However, many of these agents cause gastroenteritis and are therefore captured in our overall estimate of foodborne illness. With the exception of a few important pathogens (Appendix), we have not estimated the number of cases of chronic sequelae, although these may be part of the overall burden of foodborne diseases. Finally, future research will refine our assumptions and allow for more precise estimates. Methodologic differences between our analysis and previously published studies make it difficult to draw firm conclusions regarding overall trends in the incidence of foodborne illness. In general, the differences between our estimates and previously published figures appear to be due primarily to the availability of better information and new analyses rather than real changes in disease frequency over time. For example, E. coli O157:H7 was estimated to cause 10,000 to 20,000 illnesses annually, based on studies of patients visiting a physician for diarrhea. Recent FoodNet data have allowed a more detailed estimation of mild illnesses not resulting in physician consultation. Our estimate of nearly 74,000 illnesses per year incorporates these milder illnesses and should not be misconstrued as demonstrating a recent increase in E. coli O157:H7 infections. Whatever the limitations on retrospective comparisons, the estimates presented here provide a more reliable benchmark with which to judge the effectiveness of ongoing and future prevention efforts. Further refinements of foodborne disease estimates will require continued and improved active surveillance. Beginning in 1998, the FoodNet population survey was modified to capture cases of vomiting not associated with diarrhea; further enhancement to capture concomitant respiratory symptoms should refine the FoodNet survey data. Expansion of laboratory diagnostic capacity could lead to better detection of certain pathogens, estimates of the degree of underreporting for additional diseases, and estimates of the proportion of specific diseases transmitted through food. Heightened surveillance for acute noninfectious foodborne diseases, such as mushroom poisoning and other illnesses caused by biotoxins, could further improve estimates of illness and death from foodborne illness. Emergency department-based surveillance systems (33) or poison control center-based surveillance might provide such information. Finally, identifying new causes of enteric illness and defining the public health importance of known agents (e.g., enteroaggregative E. coli) would improve foodborne disease prevention efforts. Appendix Methods, assumptions, and references for pathogen-specific estimates Bacterial Pathogens Pathogen: Bacillus cereus Reported cases: Cases not routinely reported. Because it is a mild illness, reported cases assumed to be 10 times the average annual number of outbreak-related cases reported to CDC, 1983-1992 (10,25). Total cases: Assumed to be 38 times the number of reported cases by extrapolation from studies of salmonellosis. Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data). Case-fatality rates: Determined from outbreaks reported to CDC, 1982-1992 (10,25), including those associated with nursing homes (34). Percent foodborne: Although infection occasionally occurs through other routes, case estimates presented are based on foodborne outbreaks and are therefore assumed to reflect only foodborne transmission. Pathogen: Clostridium botulinum Reported cases: Average annual number of cases of foodborne botulism reported to CDC, 1992-1997 (7). Total cases: Because it is a severe illness, assumed to be two times the number of reported cases. Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data). Case-fatality rate: Based on outbreaks reported to CDC, 1982-1992 (10,25). Percent foodborne: 100% by definition. Pathogen: Brucella spp. Reported cases: Average annual number of cases reported to CDC, 1992-1997 (7). Total cases: Assumed to be 14 times reported cases, based on published estimates that 4% to 10% of cases are reported (35). Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data). Case-fatality rate: Historically 2% to 5% (36) Percent foodborne: Overall, consumption of milk or cheese products from Mexico implicated in 45% of cases reported from California from 1973 to 1992 (37). Because the proportion of cases due to foodborne transmission was higher in the latter half of this period, we assumed that currently 50% of cases are foodborne. Comments: Reports from California or Texas account for most of cases in recent years. Pathogen: Campylobacter spp. Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported to CDC, 1992-1994 (CDC, unpub data). Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate (24.1 cases per 100,000 population) to 1997 U.S. population (23). Total cases: Assumed to be 38 times the number of reported cases, based on studies of salmonellosis. Resulting estimate is roughly comparable with midpoint rate estimate from Tauxe (38) for C. jejuni (1,020 cases per 100,000 population), applied to 1997 population. Assumes minimal contribution from non-jejuni Campylobacter. Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Based on case-fatality rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Percent foodborne: Although waterborne outbreaks occur, foodborne transmission accounts for most of the sporadic cases (38). Comments: Guillain-Barré syndrome (GBS) is an acute flaccid paralysis that can occur several weeks after infection with various agents, including Campylobacter. The incidence of GBS has been estimated at 1.7 cases per 100,000 population, and serologic studies suggest that ~30% of patients with GBS have evidence of recent infection with Campylobacter (39). Based on these figures, we estimate that ~1,360 cases of Campylobacter-associated GBS occurred in the United States in 1997. Pathogen: Clostridium perfringens Reported cases: Cases not routinely reported. Because it is a mild illness, number of reported cases assumed to be 10 times the average annual number of outbreak-related cases reported to CDC, 1983-1992 (10,25). Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis. Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data). Case-fatality rate: Based on reported outbreaks, 1983-1992 (10,25). Percent foodborne: 100% (40). Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission of C. perfringens, type A. Pathogen: Escherichia coli O157:H7 Reported cases: Passive surveillance estimate based on average number of cases reported to CDC through the National Electronic Telecommunications System for Surveillance (NETSS), 1995-1998; data from the Public Health Laboratory Information System (PHLIS) were used for those states not reporting to NETSS during this time period (7). Passive surveillance data for 1998 are provisional. Active surveillance estimate based on an extrapolation of a weighted average of the FoodNet rate for the years 1996-1997 to the 1997 U.S. population (23,24). A weighted average was used because the overall FoodNet rate is disproportionately influenced by a high rate in a single northern state with a relatively small population. Because the incidence of infection is thought to be generally higher in northern states (41), we weighted the crude rate derived from FoodNet by the total population of each participating state. The weighted rate (1.34 cases per 100,000 population) was used when extrapolating the FoodNet rate to the total U.S. population. Total cases: Studies conducted in FoodNet sites suggest that 13-27 cases of E. coli O157:H7 infection occur in the community for each confirmed case that is reported (22). To estimate total cases, we multiplied the number of reported cases, as determined through active surveillance, by 20, the midpoint of this estimate. Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Case-fatality rate based on mortality associated with sporadic cases reported to FoodNet, 1996-1997 (23,24). Percent foodborne: Based on outbreaks of known source reported to CDC, 1982-1997 (CDC, unpub. data). Person-to-person transmission assumed to be secondary to foodborne transmission (2). Comments: Our estimate of total cases is considerably higher than previous estimates based on patients seeking care for diarrhea. Our estimate includes patients with far milder illness and should not be interpreted as indicating an increase in incidence. Hemolytic uremic syndrome (HUS) occurs in ~4% of all reported cases. Based on our estimate of total cases and active surveillance cases, between 2,954 and 147 patients are expected to contract HUS each year. Pathogen: E. coli, Shiga toxin-producing serogroups other than O157 (STEC) Reported cases: Cases not routinely reported; many clinical laboratories cannot identify. Total cases: Assumed to be half as common as infection with E. coli O157:H7. Early studies suggest that the incidence of non-O157 STEC infections is 20%-30% that of E. coli O157:H7 in North America (42, 43); however, more recent studies using different techniques suggest that this figure should be 50% (44,45). Hospitalization rate: Assumed to be comparable with E. coli O157:H7, but may be lower (46). Case-fatality rate: Assumed to be comparable with E. coli O157:H7, but may be lower (46). Percent foodborne: Assumed to be comparable with E. coli O157:H7. Comment: Although non-O157 STEC can cause hemolytic uremic syndrome, the relative frequency of this complication is unknown. Reports from Canada suggest that non-O157 STEC are the cause of at least 7% (47) and possibly as many as 20% (48) of HUS cases. Pathogen: E. coli, enterotoxigenic Reported cases: Not routinely reported. Outbreak-related cases based on average for 18 outbreaks reported to CDC from 1975 through 1997 (CDC, unpub. data). Reported cases assumed to be 10 times the number of outbreak-related cases. Total cases: Assumed to be 38 times the number of reported cases by extrapolation from studies of salmonellosis. Hospitalization rate: Low; assumed to be 0.5% of cases. Case-fatality rate: Serious illness is generally restricted to infants in developing countries. Based on experience with reported outbreaks, assumed to be 1 in 10,000 cases in the United States. Percent foodborne: Nearly all outbreaks reported to CDC from 1975 through 1997 have been foodborne (CDC, unpub. data); many sporadic cases are associated with travel to other countries where both water and foodborne exposures are likely. Pathogen: E. coli, other diarrheogenic Reported cases: Not routinely reported. Assumed to be at least as common as enterotoxigenic E. coli (ETEC) based on limited information from studies in North America and Europe (49). Total cases: Assumed equal to ETEC. Hospitalization rate: Assumed equal to ETEC. Case-fatality rate: Assumed equal to ETEC. Percent foodborne: Very little data available. As few foodborne outbreaks have been reported, it is assumed that only 30% of cases are foodborne. Comment: This category includes enteropathogenic, enteroaggregative, and enteroinvasive E. coli, as well as poorly defined pathogenic groups (50). Although little is known about the incidence of these infections in the United States, these pathogens have been linked to both outbreaks and sporadic illnesses. Limited studies suggest that the importance of some of these organisms in the United States is seriously underestimated (see Nataro and Kaper [49]). Although clearly a heterogeneous collection of organisms, we assume that these pathogens as a group have similar modes of transmission and mortality rates as ETEC. Pathogen: Listeria monocytogenes Reported cases: Rates from FoodNet, 1996-1997, (23,24) and comparable sentinel site surveillance (51), extrapolated to the 1997 U.S. population. Total cases: Because it is a severe illness, assumed to be 2 times the number of reported cases. Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Based on published reports (51), 1996-1997 FoodNet data (23,24), and recent outbreaks (CDC, unpub. data). Percent foodborne: Although foodborne transmission accounts for all reported domestic outbreaks (52), the potential for nosocomial transmission has been demonstrated (53). Comments: Figures include both perinatal and nonperinatal disease. FoodNet data on hospitalization indicate that nearly 90% of reported cases result in hospitalization (24). Pathogen: Salmonella Typhi Reported cases: Average number of cases reported to CDC, 1992-1997 (7). Total cases: Because it is a severe illness, assumed to be two times the number of reported cases. Hospitalization rate: Rate of hospitalization based on published outbreak reports (54,55). Case-fatality rate: Based on outcomes of 2,254 cases reviewed by Mermin (56). Percent foodborne: Although waterborne outbreaks have been reported in the United States, foodborne transmission is believed to account for most cases (3). Comments: Over 70% percent of reported cases are associated with foreign travel (56). A. Pathogen: Salmonella, nontyphoidal B. Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported to CDC, 1992-1997 (57). Active surveillance estimate based on extrapolation of the average 1996-1997 FoodNet rate to the 1997 U.S. population (23). Total cases: Assumed to be 38 times the number of reported cases based on FoodNet data (Voetsch, manuscript in preparation) and the "sequential surveillance artifact" multiplier derived by Chalker and Blaser (21). Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1996-1997 (23,24). This rate is lower than the previously published rate of 1.3% (58). Percent foodborne: Although occasionally associated with exposure to pets, reptiles, and contaminated water, salmonellosis is primarily a foodborne disease (59). Pathogen: Shigella spp. Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported annually to CDC, 1992-1997 (57). Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate to the 1997 U.S. population (23). Total cases: Because Shigella frequently causes bloody diarrhea, total cases assumed to be 20 times the number of reported cases, based on similarity to E. coli O157:H7. Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1996-1997 (23,24). Percent foodborne: Assumed to be 20%. Although most cases are due to person-to-person transmission (60), foodborne outbreaks are responsible for a substantial number of cases (61). Pathogen: Staphylococcus aureus (enterotoxin) Reported cases: Not routinely reported. Assumed to be 10 times the number of foodborne outbreak-related cases reported to CDC, 1983-1992 (10,25). Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis. Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25), (CDC, unpub. data), and published reports (62). Case-fatality rate: Determined from reported outbreaks to CDC, 1977-1992 (10,25,63). Percent foodborne: 100% by definition. Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission. Comment: The number of outbreak-associated cases of staphylococcal food poisoning reported to CDC has decreased substantially since 1973 (Bean and Griffin, 1990). This decrease is unlikely to be an artifact of decreased recognition: there has been no compensatory increase in the number offoodborne outbreaks of unknown etiology with an incubation period consistent with staphylococcal food poisoning (CDC, unpub. data). Pathogen: Streptococcus, Group A Reported cases: Not routinely reported. Assumed to be 10 times the number of foodborne outbreak-related cases reported to CDC, 1982-1992 (10,25). Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis. Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and CDC, unpub. data. Case-fatality rate: Determined from outbreaks reported to CDC, 1982-1992 (10). Percent foodborne: 100% foodborne by definition. Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission. Pathogen: Vibrio cholerae, toxigenic O1 or O139 Reported cases: Based on cases reported to CDC, 1988-1997 (7). Total cases: Assumed that the number of clinically significant illnesses is two times the number of reported cases. Hospitalization rate: Based on cases reported to CDC, 1992-1994 (64). Case-fatality rate: Based on cases reported to CDC, 1992-1994 (64). Percent foodborne: Assumed to be primarily foodborne. Most reported cases linked to foodborne outbreaks, and at least 65% of sporadic cases may be foodborne (64). Comments: 96% of cases acquired abroad (64). Pathogen: Vibrio vulnificus Reported cases: Cases reported to CDC from 22 states, 1988-1996 (65). Total cases: Because it is a severe illness, assumed to be two times the number of reported cases. Hospitalization rate: Based on overall rate among cases reported to CDC, 1988-1996 (65). Case-fatality rate: Based on overall rate among cases reported to CDC, 1988-1996; death rate higher among cases due to foodborne transmission (65). Percent foodborne: Based on Shapiro et al. (65). Comment: Most cases are reported by Gulf States (Florida, Alabama, Louisiana, Texas). Pathogen: Vibrio, other spp. Reported cases: Passive surveillance estimate based on cases reported to CDC, 1988-1996 (CDC, unpub. data). Active surveillance estimate based on 1996 FoodNet rate extrapolated to the 1997 U.S. population (23). FoodNet data from 1997 not included because of a large outbreak of Vibrio parahaemolyticus infections that could falsely elevate the overall rate. Total cases: Because it is a moderately severe illness, total cases assumed to equal 20 times the reported cases, a degree of underreporting comparable with E. coli O157:H7 infections. Hospitalization rate: Based on rate among non-vulnificus, non-cholerae O1 cases reported by Hlady (66). Case-fatality rate: Based on rate among non-vulnificus, non-cholerae O1 cases reported by Hlady (66). Percent foodborne: Based on history of shellfish consumption for cases reported by Hlady (66) Comment: Because of larger sample size, data from Hlady (66) used in preference to FoodNet data for hospitalization and death rates. Pathogen: Yersinia enterocolitica Reported cases: Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate to the 1997 U.S. population (23,24). Total cases: Assumed to be 38 times the number of reported cases, based on studies of salmonellosis. Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24). Case-fatality rate: Low, assumed to be 0.5% (23). Percent foodborne: Assumed to be 90%. Nearly all reported outbreaks in United States have been linked to contaminated foods, and pork is specifically believed to be the source of most infections (67). Parasitic Pathogens Pathogen: Cryptosporidium parvum Reported cases: Passive surveillance estimate based on the average annual number of cases reported to CDC, 1995-1997 (7). Active surveillance estimate based on extrapolation of the average 1997-98 FoodNet rate to the 1997 U.S. population (6,24). Total cases: Published studies suggest that ~2% of all stools tested for Cryptosporidium are positive (68, 69). We assume this rate of infection applies to all patients visiting a health-care provider for acute gastroenteritis. Using an estimate of ~15 million physician visits for diarrhea each year (see text), we estimate there are approximately 300,000 cases of cryptosporidiosis per year. This figure is 45-fold higher than the estimated number of reported cases based on FoodNet active surveillance, a multiplier only slightly larger than the one used for salmonellosis. Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1997-1998 (6,24). Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1997-1998 (6,24). Percent foodborne: Based on very limited information (70-72), we assume that 10% of cases are attributable to foodborne transmission, with the rest due to consumption of contaminated water or person-to-person transmission. Comment: Cryptosporidiosis in AIDS is associated with a severe protracted course of diarrhea (73). Pathogen: Cyclospora cayetanensis Reported cases: Passive surveillance estimate based on average annual number of cases reported to CDC, 1995-1997 (7). Active surveillance estimate based on extrapolation of average 1997-1998 FoodNet rate to the 1997 U.S. population (6,24). Total cases: Assumed to be 38 times the number of reported cases based on studies of salmonellosis. Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1997 (24). Case-fatality rate: Very low (74,75). Assumed to be 0.05%, comparable with Clostridium perfringens. Percent foodborne: Assumed 90% foodborne, based on recent reported outbreaks (74,75). Pathogen: Giardia lamblia Reported cases: Not routinely reported. Total cases: Sensitive surveillance in two sites (Vermont and Wisconsin) suggests a rate of 40 cases per 100,000 persons per year (76,77). In addition, an estimated 5% of all cases are reported. Thus, approximately 100,000 cases will be detected each year, representing 2,000,000 actual cases. Hospitalization rate: An estimated 5,000 cases per year are severe enough to require hospitalization. Case-fatality rate: Exceedingly low. Assumed to be no more than 10 deaths annually. Percent foodborne: Assumed to be 10%. Recreational water is probably the major source of transmission (76-78); however, several foodborne outbreaks have been reported (79,80). Pathogen: Toxoplasma gondii Reported cases: Not routinely reported. Total cases: Based on national serologic data collected during the 1994 NHANES, approximately 40% of persons [Image]60 years old are seropositive for toxoplasmosis (CDC, unpub. data). Assuming equal rates of infection over time, at least 0.6% of the population experiences an acute infection each year, representing approximately 1,500,000 infections per year. Approximately 15% of infections are symptomatic. Hospitalization rate: Varies widely according to host immune status. Data from NHDS indicate that from 1992 to 1996, toxoplasmosis was the first listed diagnosis for approximately 5,000 hospital discharges each year. We have used this figure as a conservative estimate of the number of actual hospitalizations. Case-fatality rate: Varies widely according to host immune status. Of the approximately 5,000 hospital discharges annually for which toxoplasmosis is the first listed diagnosis, approximately 750 involve a deceased patient. We have used this figure as a conservative estimate of the number of actual deaths. Percent foodborne: Although the proportion associated with eating contaminated food varies by geographic region, we assume an overall average of 50%. Recent unpublished data from Europe suggest that 60% of acute infections are from contaminated food (Ruth Gilbert, pers. comm.). Comment: Typically, infection with Toxoplasma gondii produces an asymptomatic illness or a mild viral-like febrile illness with lymphadenopathy. Acute diarrhea is not commonly associated with acute infection. Estimates from the Massachusetts Department of Health suggest that one case of congenital toxoplasmosis occurs for every 10,000 births (81). Extrapolating to 4,000,000 live births in the United States, an estimated 400 children are born with congenital toxoplasmosis. Based on calculations by investigators from Stanford University, each year approximately 6,000 women who experience an acute infection during pregnancy and who do not receive treatment give birth to a child with congenital toxoplasmosis, which results in chronic sequelae (82). During an outbreak of toxoplasmosis in British Columbia, of an estimated 2,900-7,700 infections, 19 cases of retinitis were reported. If there are at least 150,000 symptomatic cases annually, from 300 to 1,050 cases (0.2% to 0.7%, respectively) of ocular toxoplasmosis could occur. If there are 300,000 cases, from 600 to 2,100 ocular cases could occur. Thus, there could be from 300 to 2,100 ocular cases of toxoplasmosis annually. An estimated 4,000 persons with AIDS develop Toxoplasma encephalitis annually. In summary, from (400+300+4,000) = 4,700 to (6,000+2,100+4,000) = 12,100 persons develop chronic sequelae due to toxoplasmosis each year. Pathogen: Trichinella spiralis Reported cases: Based on NETSS surveillance data, approximately 40 cases are reported annually. Total cases: Because it can be a severe illness, assumed to be two times the number of reported cases. Hospitalization rate: Based on outbreak-related cases reported to CDC, 1982-1992 (10). Case-fatality rate: Assumed to be 0.3% based on data from a large series in Europe. Percent foodborne: 100% (83) Comment: Clinically, acute trichinosis may be asymptomatic or may have acute gastrointestinal symptoms, followed by a parenteral phase of fever and myalgias. In 10% to 20% of cases neurologic or cardiac symptoms develop, many severe and potentially leading to chronic illness. Viral Pathogens Pathogen: Rotavirus Reported cases: Not routinely reported. Total cases: Because every child has at least one symptomatic infection (84-86), the number of cases is assumed to equal the 1997 U.S. birth cohort (3.9 million). Hospitalizations: 50,000 (87,88). Case-fatality rate: Very low: 20 to 40 deaths per year (89). Percent foodborne: probably very low (<1%) (90). Pathogen: Astrovirus Reported cases: Not routinely reported. Total cases: Because every child has at least one symptomatic infection, the number of cases is assumed to equal the 1997 US birth cohort (3.9 million). Hospitalizations: Assumed to equal 25% of number of hospitalizations for rotavirus (= 12,500) (91). Case-fatality rate: Very low (<10 deaths per year). Percent foodborne: Probably very low (<1%) (91). Pathogen: Norwalk-like viruses (NLV). Reported cases: Not routinely reported. Total cases: Very few data are available for assessing the disease burden associated with Norwalk-like viruses, and very few studies have been conducted using the most sensitive diagnostics for NLVs. One community-based study from the Netherlands found 17% of cases of acute gastroenteritis were associated with Norwalk-like viruses, compared with 6% of controls, using reverse transcriptase polymerase chain reaction (RT-PCR) for detection of NLVs (92). An Australian study detected NLVs in 15% of hospitalized patients using immune electron microscopy (93). Studies have generally been conducted exclusively among young children or used less sensitive detection methods (electron microscopy); in these studies, NLVs have been detected in ~1% to 5% of participants (94-98). However, a recent study incorporating RT-PCR for viral detection among children 2 months to 2 years of age found that 21% of cases of acute gastroenteritis were associated with NLVs (99). Given these data, we assume that 11% of all episodes of acute primary gastroenteritis are due to NLVs (using the data from the best of the studies) (92). Hospitalizations: NLV assumed to account for 11% of 452,000 annual hospitalizations for viral gastroenteritis (100). Case-fatality rate: Low. NLV assumed to account for 11% of an estimated 2,800 fatal cases of viral gastroenteritis each year (100). Percent foodborne: We assume that the proportion of all NLV-associated illness that is foodborne is 40%. This estimate is based on a recent report which found that 47% of NLV-associated acute gastroenteritis outbreaks in the United States in which the modes of transmission were known were foodborne (101). Since we would assume that foodborne-associated outbreaks might be more likley to be reported than Norwalk-like virus-associated outbreaks with other mechanisms of spread, the proportion was lowered to 40%. This estimate is in general agreement with other reviews (102-104). No data are available to directly determine the proportion of cases of NLV-associated disease attributable to foodborne transmission. Pathogen: Hepatitis A Reported cases: Based on cases reported to CDC, 1992-1997 (7). Total cases: Assumed to be three times the number of reported cases (105). Hospitalizations: Thirteen percent; based on data from CDC Sentinel Counties Studies (106); Case-fatality rate: 0.3%; based on data from the viral Hepatitis Surveillance Program and the CDC Sentinel Counties Studies (105,107). Deaths calculated by applying the case-fatality rate to reported cases. Percent foodborne: Foodborne transmission accounts for approximately 5% of outbreaks of known source (105). Note that the source is not determined in approximately 50% of hepatitis A outbreaks, and foodborne transmission could account for a far higher percentage of cases. Acknowledgments We thank Fred Angulo, Beth Bell, Thomas Breuer, Cindy Friedman, Roger Glass, Eric Mintz, Steven Ostroff, Morris Potter, David Swerdlow, Tom Van Gilder, and two anonymous reviewers for their comments. 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Mead, Division of Bacterial and Mycotic Diseases, Centers for Disease Control and Prevention, Mail Stop A38, 1600 Clifton Road, Atlanta, GA 30333, USA; fax: 404-639-2205; e-mail: pfm0@cdc.gov. Figure [Fig] Figure: Estimated frequency of foodborne illness in the United States. --------------------------------------------------------- Synopses Infections Associated with Eating Seed Sprouts: An International Concern Peter J. Taormina,* Larry R. Beuchat,* and Laurence Slutsker† *University of Georgia, Griffin, Georgia, USA; and †Centers for Disease Control and Prevention, Atlanta, Georgia, USA ------------------------------------------------------------------------ Recent outbreaks of Salmonella and Escherichia coli O157:H7 infections associated with raw seed sprouts have occurred in several countries. Subjective evaluations indicate that pathogens can exceed 10(sup 7) per gram of sprouts produced from inoculated seeds during sprout production without adversely affecting appearance. Treating seeds and sprouts with chlorinated water or other disinfectants fails to eliminate the pathogens. A comprehensive approach based on good manufacturing practices and principles of hazard analysis and critical control points can reduce the risk of sprout-associated disease. Until effective measures to prevent sprout-associated illness are identified, persons who wish to reduce their risk of foodborne illness from raw sprouts are advised not to eat them; in particular, persons at high risk for severe complications of infections with Salmonella or E. coli O157:H7, such as the elderly, children, and those with compromised immune systems, should not eat raw sprouts. With changing food production and eating habits, new pathogens and newly recognized vehicles of infection have emerged. Recent outbreaks of foodborne illness associated with eating fresh produce have heightened concerns that these foods may be an increasing source of illness (1). In the last decade, multiple outbreaks linked to raw seed sprouts have occurred in countries throughout the world (Table 1). Raw seed sprouts have become a popular food item in the United States; in a recent population-based survey, 7% of respondents had eaten alfalfa sprouts in the 5 days before the interview (2). We summarize the epidemiologic and microbiologic data from these outbreaks and review efforts to prevent sprout-associated illness. Sprout-Associated Outbreaks Seed sprouts have been implicated as vehicles of transmission in outbreaks of foodborne illness (Table 1). One of the first reported outbreaks, in 1973, was associated with sprouts grown by using a home sprouting kit (3). Soy, mustard, and cress sprouts submitted by one person with gastrointestinal illness were found to contain large numbers of aerobic spore-forming bacteria. Bacteriologic examination of seeds in previously unopened sprouting kits revealed that the soy seeds were contaminated with Bacillus cereus in pure culture, while the mustard and cress seeds had B. cereus as a minor part of their flora. After germination, all the sprouts contained large numbers of the pathogen. Fecal specimens from patients were not analyzed for B. cereus because the laboratory that processed the samples did not consider it an enteric pathogen. Bacteriologic investigation revealed that during seed germination B. cereus proliferated to >10(sup 7) per g of sprouts. In 1987, Harmon et al. (4) recovered B. cereus from 57% of commercially sold alfalfa, mung bean, and wheat seeds intended for sprout production. Salmonellosis In 1988, raw mung bean sprouts were implicated in an epidemiologic study as the cause of an outbreak of Salmonella Saint-Paul infection in the United Kingdom (5). In addition, S. Virchow was isolated from samples of raw bean sprouts and was associated with seven cases of infection. Sprouts were produced from mung bean seeds imported mainly from Australia and Thailand. In a retail survey of mung bean sprouts in Thailand, several serotypes of Salmonella were isolated from 8.7% of samples tested (6). An outbreak of S. Gold-Coast in England and Wales in 1989 was associated with eating mustard cress sprouts grown from seed imported from The Netherlands. The outbreak serotype was isolated during routine sampling of cress sprouts from the factory 2 weeks before the outbreak occurred (7). Cultures of cress seeds did not yield the pathogen. Table 1. Reported outbreaks of illness associated with seed sprouts, 1973–1998 ----------------------------------------------------------------------- Likely No. of source culture- of confirmed Type of contami- Year Pathogen cases Location sprout nation Ref. (sup a) ----------------------------------------------------------------------- 1973 Bacillus cereus 4 1 U.S. Soy, cress, Seed 3 state mustard 1988 Salmonella 143 United Mung Seed 5 Saint-Paul Kingdom 1989 S. Gold-Coast 31 United Cress Seed and/or 7 Kingdom sprouter 1994 S. 595 Sweden, Alfalfa Seed 8,9 Bovismorbificans Finland 1995 S. Stanley 242 17 U.S. states, Alfalfa Seed 10 Finland 1995-96 S. Newport 133(supb) >7 U.S.states, Alfalfa Seed 11 Canada, Denmark 1996 S. Montevideo and ~500 2 U.S. Alfalfa Seed and/or 13 S. Meleagridis states sprouter 1996 Escherichia coli ~6,000 Japan Radish Seed 16 O157:H7 1997 E. coli O157:H7 126 Japan Radish Seed 17 1997 S. Meleagridis 78 Canada Alfalfa Seed 15 1997 S. Infantis and 109 2 U.S. Alfalfa, Seed 14 S. Anatum states mung, other 1997 E. coli O157:H7 85 4 U.S. Alfalfa Seed 18 states 1997-98 S. Senftenberg 52 2 U.S. Clover,alfalfa Seed and/ * states or sprouter 1998 E. coli O157:NM 8 2 U.S. Clover, Seed and/ * states alfalfa or sprouter 1998 S. Havana, S. Cubana, and S. 34 5 U.S. Alfalfa Seed and/ * Tennessee states or sprouter ----------------------------------------------------------------------- (sup a)The number of culture-confirmed cases represents only a small proportion of the total illness in these outbreaks, as many ill persons either do not seek care or do not have a stool culture performed if they do seek care. (sup b)Includes only culture-confirmed cases in Oregon and British Columbia. *Mohle-Boetani J., pers. comm. In Finland, eight sprout-borne Salmonella outbreaks occurred from 1980 to 1997 (8). In 1994, two large outbreaks of salmonellosis were linked to alfalfa sprouts (282 cases in Sweden and 210 cases in Finland) (9). Both outbreaks were caused by S. Bovismorbificans; the implicated sprouts were grown from Australian alfalfa seeds. In 1995, a large international outbreak of S. Stanley infections in Finland and 17 states in the United States was caused by alfalfa sprouts grown from contaminated seeds (10). S. Stanley isolates from patients in Finland and the United States had an indistinguishable DNA pattern by pulsed-field gel electrophoresis (PFGE) and an unusual antimicrobial resistance pattern that was identical among outbreak strains but differed from S. Stanley strains isolated from nonoutbreak-related cases. Sprouts that caused the outbreaks in both countries were grown from seeds obtained from the same shipper in The Netherlands, suggesting the seeds were contaminated at some point during growing, harvesting, or processing. In late 1995 and early 1996, outbreaks of salmonellosis in Denmark and Oregon and British Columbia, Canada, were associated with eating alfalfa sprouts contaminated with S. Newport (11). Patients in this multinational outbreak had eaten alfalfa sprouts grown from four separately numbered lots of alfalfa seeds. The seeds implicated in the North American outbreaks were shipped by the same Dutch firm implicated in the S. Stanley outbreak. A retrospective study determined that substantial increases in S. Newport infections occurred in Denmark and several states in the United States during the time that these seeds were likely to have been sprouted and eaten (11). PFGE patterns of S. Newport isolates from the Oregon and British Columbia outbreaks were indistinguishable from each other (11) and from isolates obtained during S. Newport outbreaks in late 1995 in Georgia and Vermont in the United States and in June 1995 in Denmark. Cultures of the implicated seeds yielded S. Newport (12). In June 1996, the largest recorded sprout-associated outbreak in the United States occurred in California, resulting in >450 culture-confirmed cases of infection with Salmonella serotypes Montevideo and Meleagridis (13). The same strain of S. Meleagridis was isolated from patients and from alfalfa sprouts obtained from retail stores and the sprouting facility. Investigation at the sprouter revealed unsanitary sprouting practices and suboptimal employee hygiene. At the farm where the implicated alfalfa seed was grown, chicken manure was used to fertilize the field before planting. Horses grazed in adjacent fields, and their manure was collected and stored next to the alfalfa field. An outbreak of Salmonella serotypes Infantis and Anatum, which occurred from February through June of 1997 in Kansas and Missouri, was associated with eating contaminated alfalfa sprouts produced by a local sprouter (14). On the basis of epidemiologic, traceback, and laboratory findings, the source of Salmonella contamination in this outbreak was determined to be alfalfa seeds. In October 1997 in Alberta, Canada, an outbreak of S. Meleagridis infections was linked to eating alfalfa sprouts, and the outbreak serotype was isolated from retail product (15). During the same period, cases of S. Meleagridis infection with the same phage type occurred in persons who had eaten sprouts produced by sprouters in two other provinces but grown from the same alfalfa seed lot as the one implicated in Alberta. In Northern California, in late 1997 and June 1998, two clusters of S. Senftenberg infections were associated with eating an alfalfa and clover sprout mixture; because the two types of sprouts were always mixed before sale, it was not possible to determine which type of seed was implicated (Mohle-Boetani J, pers. comm.). Cultures of clover and alfalfa seeds used to grow the implicated sprouts did not yield S. Senftenberg. In May 1998, a cluster of S. Havana infections among patients in Arizona and California was linked to eating alfalfa sprouts (Mohle-Boetani J, pers. comm.). An outbreak of S. Cubana infections occurred from May to September 1998 among residents of Arizona, California, and New Mexico, also linked to eating alfalfa sprouts from the same grower implicated in the S. Havana outbreak. Alfalfa sprouts eaten by patients in both clusters were grown from the same seed lot, and cultures of seed from this implicated lot yielded S. Havana, S. Cubana, and S. Tennessee (Mohle-Boetani J, pers. comm.). Enterohemorrhagic Escherichia coli Infection Escherichia coli O157:H7 infection has also been related to eating sprouts. In the world's largest reported outbreak of E. coli O157:H7 infections, which occurred in Japan in 1996, white (daikon) radish sprouts were epidemiologically linked to approximately 6,000 of the nearly 10,000 cases reported (16). The pathogen was not detected in cultures of implicated seeds. In the following year, white radish sprouts were again implicated in an outbreak of E. coli O157:H7 infection affecting 126 people in Japan (17). In July 1997, simultaneous outbreaks of E. coli O157:H7 infection in Michigan and Virginia were linked by independent epidemiologic investigations with eating alfalfa sprouts grown from the same lot of seeds (18). Molecular subtyping by PFGE revealed that strains from outbreaks in both states were indistinguishable. The simultaneous occurrence of two geographically distinct outbreaks linked to the same lot of alfalfa seeds and caused by the same strain of E. coli O157:H7 strongly suggested that contaminated seeds were the source. In June 1998, a cluster of E. coli O157:NM infections in Northern California and Arizona was associated with eating an alfalfa and clover sprout mixture produced by the same sprouter implicated in the S. Senftenberg outbreak (Mohle-Boetani J, pers. comm.). E. coli O157:NM isolates from the patients had indistinguishable PFGE patterns. Attempts to Control Microorganisms During Sprouting Alfalfa and other types of seeds intended for sprouting are considered raw agricultural commodities. Seeds are harvested and transported from fields to sprouting facilities by methods similar to those used by the cereal grain and fresh produce industries. Grains, fruits, and vegetables may become contaminated with pathogenic microorganisms, e.g., B. cereus, Salmonella, or E. coli O157:H7, while growing in fields or orchards or during harvesting, handling, processing, and distribution (19,20). Alfalfa seeds generally contain 10(sup 2) to 10(sup 5) aerobic mesophiles per gram (21,22). Piernas and Guiraud (23) reported that the microflora on rice seed exceeded 10(sup 7) colony-forming units (cfu)/g. This naturally occurring population can rapidly increase during germination and sprouting, which is characterized by high moisture and a temperature generally in the range of 21°C to 25°C. Consequently, if seeds become contaminated with a pathogen, the sprouting process provides excellent conditions for its growth and distribution. Populations of microorganisms on other seeds and sprouts have been studied. Potter and Ehrenfeld (24) detected non-O157 E. coli in 5 of 48 samples of mung bean seeds and mature bean sprouts, indicating possible fecal contamination. Alfalfa sprouts and bean sprouts in retail stores have been shown to contain microbial populations of 10(sup 8) to 10(sup 9) cfu/g (25); 6 of 23 retail samples of alfalfa sprouts contained >10(sup 5) fecal coliforms per gram. Onion sprouts can contain >10(sup 9) aerobic microorganisms per gram (20). Mung bean sprouts from restaurants may contain >10(sup 6) cfu/g (26). Jaquette et al. (27) demonstrated that populations of S. Stanley in the range of 10(sup 2) to 10(sup 3) cfu/g can increase slightly during 6 hours of soaking, by approximately 103 cfu/g during a 24-hour germination period, and by an additional 10(sup 1) cfu/g during a 72-hour sprouting stage, resulting in a 5- to 6-log overall amplification during the sprouting process. Pooled Salmonella serotypes inoculated onto mung beans and alfalfa seeds increased substantially during seed germination (21). Growth characteristics of E. coli O157:H7 on radish sprouts have been studied. Itoh et al. (28) demonstrated the presence of E. coli O157:H7 not only on the surfaces but also in the inner tissues and stomata of cotyledons of radish sprouts grown from seeds inoculated with the bacterium. When radish seeds or radish sprout roots were soaked in a suspension of E. coli O157:H7, the edible parts (cotyledons and hypocotyl) became heavily contaminated (>7 log cfu/g) (29). Taormina and Beuchat (30) showed that E. coli O157:H7 inoculated onto alfalfa seeds reached 10(sup 6) to 10(sup 7) cfu/g within 48 hours after the sprouting process began. Populations on mature sprouts subsequently held at 9±2°C for 6 days remained essentially unchanged. Growth of E. coli O157:H7 to 10(sup 7) cfu/g of alfalfa sprouts has also been reported by Ingram et al. (31). Chemical Treatment as an Intervention Numerous studies have been done to determine the effectiveness of a wide range of chemicals in killing pathogenic bacteria on seed sprouts and seeds intended for sprout production (Table 2). The efficacy of these chemicals as influenced by concentration, temperature, and time of exposure to contaminated seeds has been investigated. No single treatment has been demonstrated to reliably reduce populations of pathogens by more than approximately three logs. Piernas and Guiraud (32) investigated different methods of disinfection of rice seeds. They observed 10(sup 2) to 10(sup 3) reductions in aerobic plate counts from rice seeds after treatment with 1,000 ppm NaOCl or 10,000 ppm (1%) H2O2 at room temperature. Ethanol was very effective in killing naturally occurring microorganisms, although it inhibited seed germination. Becker and Holzapfel (33) surveyed commercial prepackaged sprouts (alfalfa, lentils, wheat, peas, raphanus, sunflower, mung bean, and red radish) and found Enterobacteriaceae and pseudomonads to be the dominant groups of bacteria, with counts of 10(sup 4) to 10(sup 5) cfu/g. Washing sprouts in water did not remove bacteria; this treatment has been shown to reduce numbers of E. coli and Salmonella by no more than 1 log (24). Treatment of bean sprouts with ozone has been shown to decrease microbial populations (34). Chlorine treatment, however, is ineffective in killing large numbers of naturally occurring microflora on seeds. Splittstoesser et al. (35) reported that treatment of sprouting mung beans with soak and rinse water containing 100 ppm chlorine reduced the natural microflora by <1 log; treatment of mature sprouts with 5,000 ppm chlorine resulted in a 2-log decrease (36). Table 2. Control of microorganisms in seed sprouts, by type of treatment and treatment results --------------------------------------------------------------------- Organism, origin Treatment Results of treatment Ref. --------------------------------------------------------------------- Aerobic bacteria, rice 1,000 ppm NaOCl or 102 to 103 32 seeds 10,000 ppm H2O2 reductions in aerobic plate counts; germination inhibited Enterobacteriaceae, Washing in water Ineffective in 33 pseudomonads, removing bacteria commercial sprouts Aerobic bacteria, mung 100 ppm chlorine or Reduced microflora 35 bean sprouts 5,000 ppm chlorine by <1 log and 2 logs, respectively Salmonella Stanley, Chlorine and hot No reduction at low 27 alfalfa seeds water levels; reduction of S. Stanley achieved with 2,040 ppm chlorine Salmonella, alfalfa 1,800 ppm Ca(OCl)2 Salmonella 37 seeds or 2,000 ppm NaOCl populations reduced or 6% H2O2 or 80% by >3 logs, but ethanol pathogen not eliminated E. coli O157:H7, 500, 1,000, or Populations reduced 38 alfalfa seeds >2,000 ppm Ca(OCl)2; but not eliminated; 500 ppm acidified germination ClO2; >100 ppm and decreased; pathogen 500 ppm acidified unaffected by dry ClO2; 30% or 70% storage at 5ºC ethanol; >1% H2O2; 8% H2O2 for 10 min; dry storage E. coli O157:H7, 2,000 ppm NaOCl; 200 Populations 30 alfalfa seeds at and 2,000 ppm substantially various stages of Ca(OCl)2; 500 ppm reduced but not sprouting acidified ClO2 eliminated S. Stanley, alfalfa Heat, 54 to 71ºC 54ºC for 5 min 27 seeds reduced population from 260 to 6-9 cfu/g; treatment for 10 min reduced viability of seed E. coli O157:H7, Irradiation at >1.0 Pathogen controlled 39 alfalfa seeds and kiloGray without affecting sprouts germination --------------------------------------------------------------------- The efficacy of chemicals in killing Salmonella on alfalfa seeds has been reported by several researchers. Jaquette et al. (27) evaluated chlorine and hot water treatments for their effectiveness in killing S. Stanley inoculated onto alfalfa seeds at populations of 102 to 10(sup 3) cfu/g. Significant reduction (p<0.05) in population was observed when seeds were treated with 100 ppm chlorine for 5 or 10 minutes, and further reduction occurred after treatment with 290 ppm chlorine. Populations of 10(sup 1) to 10(sup 2) cfu of S. Stanley per g were reduced to undetectable levels (<1 cfu/g) after seeds were treated with 2,040 ppm chlorine solution. On the basis of these findings, in March 1996 the U.S. Food and Drug Administration recommended that sprout growers soak alfalfa seeds in 500 to 2,000 ppm chlorine solution for 30 minutes before sprouting. However, in none of the subsequent U.S. outbreaks listed in Table 1 was there documented evidence that this recommendation had been followed. In another study, 10-minute treatment in solutions containing Ca(OCl)2 or NaOCl at concentrations of 1,800 and 2,000 ppm chlorine, respectively, as well as 6% H2O2 or 80% ethanol, reduced Salmonella populations on alfalfa seeds by >3 logs (37) but did not eliminate the pathogen. Taormina and Beuchat (38) studied the efficacy of various chemical treatments in eliminating 2.0 to 3.2 log10 E. coli O157:H7 per g from alfalfa seeds and survivability of the pathogen on seeds during prolonged storage. Significant reductions (p<0.05) in population of E. coli O157:H7 on inoculated seeds were observed after treatments with 500 or 1,000 ppm chlorine [as Ca(OCl)2] for 3 but not 10 minutes and with 2,000 ppm Ca(OCl)2, regardless of pretreatment with a surfactant. Populations were reduced after treatment with 30% or 70% ethanol for 3 or 10 minutes, although germination percentage dramatically decreased. Treatment with 0.2% H2O2 for 3 or 10 minutes significantly (p<0.05) reduced populations of E. coli O157:H7 on alfalfa seeds, and the organism was not detected by direct plating after treatment with 1% H2O2. However, the pathogen was detected by enrichment in seed treated with 8% H2O2 for 10 minutes. The initial populations of 3 log(sub 10) cfu of E. coli O157:H7/g of dry seeds stored at 5°C remained relatively constant for 20 weeks. Taormina and Beuchat (30) investigated the growth of E. coli O157:H7 on alfalfa seeds at various stages during sprouting as affected by NaOCl, Ca(OCl)2, acidified NaClO2, acidified ClO2, Na3PO4, or H2O2. Spray application of 2,000 ppm NaOCl, 200 and 2,000 ppm Ca(OCl)2, or 500 ppm acidified ClO2 to germinated seeds significantly (p<0.05) reduced the population of E. coli O157:H7. None of the chemical treatments evaluated eliminated E. coli O157:H7 on alfalfa seeds and sprouts. Application of heat to kill pathogens on alfalfa seeds has been investigated. Treatment of seeds containing approximately 260 cfu of S. Stanley per g at temperatures from 54°C to 71°C for 5 or 10 minutes was studied by Jaquette et al. (27). Treatment at 54°C reduced the number to 6 to 9 cfu/g. Treatment at 57°C for 5 minutes reduced populations to <1 cfu/g. Heating seeds at 54°C, 57°C, or 60°C for 5 minutes did not substantially reduce the viability of seeds; however, treatment at these temperatures for 10 minutes reduced viability from 96% (control) to 88%, 84%, and 42%, respectively. Although heat treatment appears to be effective in killing S. Stanley on alfalfa seeds, the range of temperatures that can be used is narrow, i.e., 57°C to 60°C for 5 minutes. Lower temperatures may not kill the pathogens, and higher temperatures or longer exposure time (10 minutes) decreased germination. Heating (55°C) alfalfa seeds containing 2.2 to 2.3 log10 cfu of E. coli O157:H7 per g in solutions containing up to 20,000 ppm chlorine, 1,200 ppm acidified sodium chlorite, 500 ppm acidified ClO2, 5% H2O2, or 8% Na3PO4 for 3 minutes did not eliminate the pathogen (38). The use of gamma irradiation to eliminate E. coli O157:H7 on alfalfa seeds and sprouts has been investigated (39). Studies at the U.S. Department of Agriculture have shown that doses approved for irradiating meat (which are higher than the 1.0 kiloGray dose allowed for fruits and vegetables) control Salmonella and E. coli O157:H7 on alfalfa sprouts. Both pathogens are more resistant to irradiation on dry seeds than on sprouts. At doses required to eliminate E. coli O157:H7, germination of seeds was not affected. These preliminary results need to be confirmed by other studies. Conclusions Eating seed sprouts has been associated with numerous outbreaks in the United States and other countries, resulting in thousands of culture-confirmed illnesses; multiple pathogens have been involved, including E. coli O157, B. cereus, and many serotypes of Salmonella. Although most outbreaks have been associated with alfalfa sprouts, other raw seed sprouts have also been linked to illness. Sprouts follow a complex path from farm to table that includes growing, harvesting, processing, and shipping of seeds, followed by sprouting and distribution of the finished product. Contamination can occur at any of these points in production and distribution. Measures that may h