Foodborne Infections and Intoxications

By Academic Press

The accelerated globalization of the food supply, coupled with toughening government standards, is putting global food production, distribution, and retail industries under a high-intensity spotlight. High-publicity cases about foodborne illnesses over recent years have heightened public awareness of food safety issues, and momentum has been building to find new ways to detect and identify foodborne pathogens and eliminate food-related infections and intoxications. This extensively revised 4e covers how the incidence and impact of foodborne diseases is determined, foodborne intoxications with an introduction noting common features among these diseases and control measures that are applicable before and after the basic foodstuff is harvested.

• Provides a summary of the

• Language: English
• Publisher: Academic Press
• Release date: Mar 6, 2013
• ISBN: 9780123914767

Book preview

1

Foodborne Disease: Epidemiology and Disease Burden

Chapter 1 Estimates of Disease Burden Associated with Contaminated Food in the United States and Globally

Chapter 2 The Foods Most Often Associated with Major Foodborne Pathogens

Chapter 3 Microbial Food Safety Risk Assessment

Chapter 4 Development of Risk-based Food Safety Systems for Foodborne Infections and Intoxications

Chapter 1

Estimates of Disease Burden Associated with Contaminated Food in the United States and Globally

Elaine Scallan¹, Martyn Kirk² and Patricia M. Griffin³, ¹Colorado School of Public Health, Aurora, CO, USA, ²The Australian National University, Canberra, ACT, Australia, ³Enteric Diseases Epidemiology Branch, Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA

Introduction

Estimates of the overall burden of disease from foodborne agents are important for directing food safety policy and prioritizing interventions. However, estimating the burden of foodborne disease is challenging for several reasons. First, there are over 250 agents, including a variety of bacteria, viruses, parasites, and chemicals, that may contaminate food and cause foodborne illness. Second, transmission routes other than contaminated food may result in human infections for many of these agents. For example, Escherichia coli O157:H7 infections may be acquired by ingesting contaminated food or water or by direct contact with infected animals or persons. Third, a fraction of illnesses are confirmed by laboratory testing and reported to public health agencies and most surveillance systems do not attempt to determine the proportion of infections that are transmitted through food. Finally, unknown or unrecognized agents are likely to cause an important additional fraction of illnesses due to contaminated food. Indeed, many important foodborne pathogens, such as Campylobacter and E. coli O157, were only recognized in recent decades [1,2].

Surveillance for laboratory-confirmed infections provides essential information for assessing trends in diseases and detecting outbreaks. Information derived from surveillance may assist regulatory efforts to prioritize and evaluate interventions. However, because only a fraction of illnesses are diagnosed and reported, periodic assessments of the total number of illnesses, including those that are not laboratory-confirmed, are also needed to help set public health goals, allocate resources, and measure the economic impact. Several countries, including Australia, the Netherlands, the United Kingdom, and the United States, have conducted prospective population-based or cross-sectional studies to supplement surveillance and estimate the overall human health impact of foodborne disease [3]. In 2006, the World Health Organization (WHO) convened a meeting of foodborne disease experts that recommended the formation of the Foodborne Disease Epidemiology Reference Group (FERG) to advise WHO about how to estimate the global burden of foodborne disease [4]. The FERG began estimating the global burden of foodborne disease in 2007.

The purpose of this chapter is to describe the methods used by various countries to estimate the burden of foodborne disease. We begin by describing estimates of foodborne illness in the United States and then compare these methods and estimates with those in some other countries. We also discuss the WHO FERG initiative to estimate the global burden of foodborne disease.

Estimates of foodborne disease in the United States

In 2011, the US Centers for Disease Control and Prevention (CDC) published new estimates of the numbers of foodborne illnesses caused by contaminated foods consumed in the United States (hereafter, domestically acquired foodborne illnesses) [5,6]. Together, major known pathogens and unspecified agents transmitted by food were estimated to cause 47.8 million illnesses each year, resulting in 127,839 hospitalizations and 3037 deaths (Table 1.1).

Table 1.1

Estimated Annual Number of Illnesses, Hospitalizations, and Deaths Caused by Major Known Pathogens and Unspecified Agents Transmitted by Food (United States) [5,6].

aIncludes all possible sources of illness, including infections acquired overseas.

b90% credible interval indicating range of uncertainty around estimate.

cShowing estimates for seven pathogens causing most foodborne illnesses, hospitalizations, or deaths.

dNA = not available.

Major known pathogens

Data from surveillance, surveys, and other sources were used to estimate the number of domestically acquired foodborne illnesses, hospitalizations, and deaths caused by 31 major known pathogens, including 21 bacterial, 5 viral, and 5 parasitic pathogens (see Table 1.1) [6]. These known pathogens were estimated to cause 9.4 million (90% credible interval [CrI]: 6.6–12.7 million) domestically acquired foodborne illnesses, 55,961 hospitalizations (90% CrI: 39,534–75,741), and 1351 deaths (90% CrI: 712–2268) each year. Norovirus was estimated to cause the most foodborne illness (58%), while nontyphoidal Salmonella spp. was the leading cause of hospitalization (35%) and death (28%). Seven pathogens—Campylobacter spp., Clostridium perfringens, E. coli O157, Listeria monocytogenes, nontyphoidal Salmonella spp., norovirus, and Toxoplasma gondii—were estimated to cause 90% of domestically acquired foodborne illnesses, hospitalizations, and deaths due to the major known pathogens.

Estimating illness using the burden-of-illness pyramid

Most known pathogens had laboratory-based surveillance data available; therefore, the total number of illnesses was estimated using the burden-of-illness pyramid approach (Figure 1.1). Several steps are necessary for an illness to be included in laboratory-based surveillance: the ill person must seek medical care, a specimen must be submitted for laboratory testing, the laboratory must test for and identify the causative agent, and the illness must be reported to the public health authorities. Estimating the frequency of cases of foodborne disease that are not reported to public health from laboratories provides insight into under-reporting in the surveillance system. Similarly, assessing differences in medical care–seeking behavior, specimen submission, laboratory testing, or laboratory test sensitivity characterizes under-diagnosis at each step of the surveillance system. Accounting for the proportion of cases missed in traditional surveillance due to under-diagnosis and under-reporting builds the burden-of-illness pyramid. This allows for an extrapolation from laboratory-confirmed illnesses (at the top of the burden-of-illness pyramid) to estimate the overall number of illnesses in the community (at the bottom of the burden-of-illness pyramid). To extrapolate, a multiplier, the inverse of a proportion, is calculated for each surveillance step. For example, if the laboratory test sensitivity of a particular pathogen was estimated to be 80%, the multiplier for this surveillance step would be 1.25 (i.e., for every case of infection diagnosed an estimated 1.25 cases would have been tested for that pathogen).

Figure 1.1 Surveillance steps that must occur for laboratory-confirmed cases to be reported to surveillance.

In the United States, data on laboratory-confirmed illnesses caused by 25 of the 31 known pathogens were available from one or more of five surveillance systems: the foodborne diseases active surveillance network (FoodNet), the national notifiable disease surveillance system (NNDSS), the cholera and other vibrio illness surveillance (COVIS) system, the national tuberculosis surveillance system (NTSS), and the foodborne disease outbreak surveillance system (FDOSS). Similar to other countries, laboratory-based surveillance systems in the United States rely largely upon passive reports of diseases from clinical laboratories to state and local health departments, which are, in turn sent to the CDC. To assure that all laboratory-confirmed cases occurring within the FoodNet surveillance area are reported, personnel actively contact all laboratories in the catchment area. Therefore, when data were available in more than one surveillance system, active surveillance data from FoodNet were used, except for Vibrio spp., for which COVIS was used because of geographical clustering of Vibrio infections outside the FoodNet sites. Data on outbreak-associated illnesses from FDOSS were used only for pathogens with no data available from the other systems due to not being specifically reported or only manifesting as outbreaks.

Because FoodNet conducts active surveillance, the pathogens under FoodNet surveillance were assumed to have no under-reporting. Because COVIS and NNDSS are passive surveillance systems, an under-reporting multiplier (1.1 for bacterial and 1.3 for parasitic pathogens), derived by comparing the incidence of all nationally notifiable illnesses ascertained through FoodNet with that reported to NNDSS, was applied to those pathogen counts. For the five bacterial pathogens for which only outbreak data were available, an outbreak under-reporting multiplier was created by determining the proportion of illnesses in FoodNet caused by Campylobacter, Cryptosporidium, Cyclospora, Listeria, Salmonella, Shigella, Shiga toxin-producing E. coli (STEC), Vibrio, and Yersinia that were also reported as outbreaks associated to FDOSS. It was assumed that all Mycobacterium bovis illnesses were reported to NTSS.

To adjust for medical care seeking and specimen submission, the proportion of persons reporting an acute diarrheal illness (defined as ≥3 loose stools in a 24-hour period and lasting longer than one day or resulting in restricted daily activities) in the past month who sought medical care and submitted a stool sample for that illness were estimated using data from FoodNet surveys of the general population (FoodNet Population Surveys). Because persons with more severe illness are more likely to seek care [7], the rate of medical care seeking and stool sample submission was estimated separately for persons with bloody and non-bloody diarrhea; these proportions were used as surrogates for severe and mild presentations of most illnesses. These multipliers were derived by examining data on the proportion of patients with diarrhea seeking care and submitting specimens with different symptom profiles from population-based surveys. Multipliers for medical care seeking and stool sample submission (for those with mild and severe illness) were then applied to the pathogen-specific proportions of patients with laboratory-confirmed infections who were estimated to have severe or mild illness. Some severe foodborne diseases were assumed to have high rates of medical care seeking and specimen submission (e.g., 90% of patients with invasive L. monocytogenes were estimated to seek medical care and 80% were estimated to have a specimen taken for laboratory testing). Laboratory testing and test sensitivity rates were estimated using data from FoodNet and other surveys of clinical diagnostic laboratory practices.

The US estimates would not have captured mild illnesses associated with some pathogens. For example, mild cases of botulism are often recognized as part of outbreaks, but these persons seldom seek medical care and so are not captured by surveillance except during outbreaks [8,9]. Likewise, Listeria can cause febrile gastroenteritis but these illnesses are rarely diagnosed at least in part because Listeria is not detected by routine stool culture methods [10]. Cases of early spontaneous abortion or miscarriage caused by Listeria infection may also be under-represented.

By augmenting surveillance with information from surveys and other sources, this burden-of-illness approach has been used to estimate the overall number of illnesses caused by specific pathogens. For example, for each laboratory-confirmed case of nontyphoidal Salmonella infection, there were an estimated 29 cases of illness in the community that were not reported.

Alternative approaches to estimating illnesses

Infections caused by diarrheagenic E. coli other than STEC and Enterotoxigenic E. coli (ETEC), Toxoplasma, astrovirus, rotavirus, sapovirus, and norovirus were not routinely captured by any surveillance system; therefore, alternate approaches were used to estimate illnesses. Illness caused by diarrheagenic E. coli other than STEC and ETEC was assumed to be as common as illness caused by ETEC. Illnesses caused by Toxoplasma were estimated using nationally representative serologic data from the National Health and Nutrition Examination Survey (NHANES) from 1999–2004 [11] and an estimate that 15% of persons who seroconvert develop clinical illness [12]. It was assumed that 75% of children experience an episode of clinical illness caused by rotavirus by 5 years of age [13]; the same estimate was used for astrovirus and sapovirus. Norovirus illnesses were estimated by applying the mean proportion (11%) of all acute gastroenteritis caused by norovirus from studies in other industrialized countries [14–17] to estimates of acute gastroenteritis from FoodNet Population Surveys.

Estimating hospitalizations and deaths

Accurately estimating hospitalizations and deaths caused by foodborne pathogens is particularly challenging. National data on outpatient visits resulting in hospitalization, hospital discharges, and death certificates are likely to substantially underestimate the pathogen-specific numbers because, for pathogen-specific diagnoses to be recorded, health care providers must order the appropriate diagnostic tests, and coding must be accurate. Without detection of a pathogen, infections may be coded as non-infectious illnesses [18]. Furthermore, gastrointestinal illness may exacerbate a person’s chronic illnesses through dehydration or electrolyte imbalance, resulting in hospitalization or death well after the resolution of the acute illness, so it may not be coded as a contributing factor. Therefore, for most pathogens, the numbers of hospitalizations and deaths were estimated from the proportion of laboratory-confirmed illnesses reported to surveillance where a person was hospitalized or died. Because some persons with illnesses that were not laboratory-confirmed would also have been hospitalized and died, the number of hospitalizations and deaths was doubled to account for under-diagnosis.

Estimating the proportion of illnesses that are domestically acquired and foodborne

Data from published studies and surveillance were used to determine the proportion of illnesses acquired while traveling outside the United States for each pathogen. The remaining proportion was considered domestically acquired. The proportion of domestically acquired illnesses that were transmitted by food for each pathogen was based on data from surveillance, risk factor studies, and a review of current literature. Assumptions about the proportion of illnesses transmitted by food have an important impact on the estimates, but data on which to base these estimates are often lacking and it is not known how representative these data are of total illnesses and if the foodborne fraction is similar across age groups. For example, the proportion of some illnesses transmitted by animals may be higher among children (e.g., E. coli O157) [19], and the proportion that spreads from one person to another may be higher among institutionalized elderly (e.g., norovirus) [20].

Unspecified agents

Unspecified agents causing acute gastroenteritis were estimated to cause 38.4 million domestically acquired foodborne gastroenteritis illnesses, 71,878 hospitalizations (90% CrI: 9924–157,340), and 1686 deaths (90% CrI: 369–3338) each year [5] (see Table 1.1). This unspecified agents category includes a heterogeneous group of less well-understood agents. First, there are agents, many of which cause acute gastroenteritis, that are recognized as known or possible causes of foodborne illness, but for which there were insufficient data to make reliable estimates of incidence. This category includes infectious agents such as Aeromonas spp., Edwardsiella spp., and Plesiomonas spp., and non-infectious agents such as mushroom and marine biotoxins, metals, and other inorganic toxins. Second, some known agents may not be routinely recognized as having a transmission route through food. For example, the detection of Clostridium difficile in retail meat products suggests that it may sometimes be transmitted by that route [21]. Third, there are microbes, chemicals, and other substances known to be in food that could at some time be shown to cause acute illness. Agents of foodborne illness continue to be discovered. In addition, outbreaks occur in which specimens are obtained in a timely manner yet no causative agent can be identified (e.g., Brainerd diarrhea) [22,23]. Therefore, it is likely that additional agents of foodborne illness remain undescribed and may be responsible for gastroenteritis of unknown etiology [24].

Unspecified acute gastroenteritis illnesses

To estimate the number of gastroenteritis illnesses caused by unspecified agents, the estimated number of illnesses caused by 24 major known pathogens that typically or often cause diarrhea or vomiting was subtracted from the overall number of acute gastroenteritis illnesses estimated using data from FoodNet Population Surveys. The FoodNet Population Surveys are 12-month, random-digit-dial telephone surveys of the general FoodNet population that collect information on episodes of diarrhea and vomiting and on other gastrointestinal symptoms in the past month. The annual number of acute gastroenteritis illnesses was derived by multiplying the average monthly prevalence by 12, where an episode of acute gastroenteritis was defined as diarrhea (≥3 loose stools in 24 hours) or vomiting in the past month; both had to last >1 day or result in restricted daily activities. Persons with a chronic condition in which diarrhea or vomiting was a major symptom and persons with concurrent symptoms of cough or sore throat were excluded. The annual number of acute gastroenteritis illnesses (178.8 million episodes) was estimated by applying the average rate (0.6 episodes per person per year) from the combined surveys to the 2006 US population estimate. Subtracting 37.0 million estimated illnesses caused by the 24 known gastroenteritis pathogens left 141.8 million acute gastroenteritis illnesses caused by unspecified agents.

Unspecified acute gastroenteritis hospitalizations and deaths

The number of acute gastroenteritis hospitalizations and deaths caused by unspecified agents was estimated using a similar approach to that used for unspecified gastroenteritis illnesses. The number of acute gastroenteritis hospitalizations was estimated using data from three sources: the CDC’s National Center for Health Statistics (NCHS) National Hospital Discharge System (NHDS); the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS); and combined data on hospitalizations from NCHS National Ambulatory and National Hospital Ambulatory Medical Care Surveys (NAMCS/NHAMCS). A hospitalization was considered an acute gastroenteritis episode if one of the ICD-9-CM codes listed below was listed as one of the first three diagnoses. The number of acute gastroenteritis deaths was estimated using multiple cause-of-death data from the National Vital Statistics System, where acute gastroenteritis was listed as the underlying or a contributing cause.

Acute gastroenteritis hospitalization was defined using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnostic codes 001–008 (infectious gastroenteritis of known cause); 009 (infectious gastroenteritis); 558.9 (other and unspecified non-infectious gastroenteritis and colitis); and 787.9 (other symptoms involving digestive system: diarrhea), excluding 008.45 (Clostridium difficile colitis) and 005.1 (botulism). Other and unspecified non-infectious gastroenteritis and colitis was included because many unknown infectious illnesses may be coded as non-infectious. Acute gastroenteritis death was defined as ICD-10 diagnostic codes A00.9–A08.5 (infectious gastroenteritis of known cause); A09 (diarrhea and gastroenteritis of presumed infectious origin); and K52.9 (non-infectious gastroenteritis and colitis, unspecified), excluding A04.7 (enterocolitis due to Clostridium difficile) and A05.1 (botulism).

The mean annual rate of acute gastroenteritis hospitalizations from 2000 to 2006 within each survey was 203 per 100,000 persons from NHDS, 187 per 100,000 from NIS, and 109 per 100,000 from NAMCS/NHAMCS. Using a statistical model to combine the data from the three surveys and applying the results to the United States population resulted in an estimated 473,832 acute gastroenteritis hospitalizations occurring each year. Subtracting the 215,799 estimated hospitalizations due to the 24 known gastroenteritis pathogens leaves 258,033 acute gastroenteritis hospitalizations due to unspecified agents. The mean annual death rate due to gastroenteritis was 1.5 per 100,000 persons. Therefore, 5072 acute gastroenteritis deaths were estimated to occur each year in the United States. Subtracting the 1498 deaths due to the 24 known gastroenteritis pathogens leaves 3574 acute gastroenteritis deaths due to unspecified agents.

Domestically acquired foodborne illness caused by unspecified agents

Because there were no data with which to directly estimate the proportions of unspecified agents that were both domestically acquired and foodborne, these proportions were assumed to have distributions similar to the 24 known gastroenteritis pathogens. Applying the proportion of illnesses, hospitalizations, and death from the 24 known gastroenteritis pathogens that were domestically acquired (98%, 97%, and 95%, respectively) and foodborne (25%, 23%, and 50%, respectively) yields an estimate of 38.4 million domestically acquired foodborne illnesses (90% CrI: 19.8–61.2 million), 71,878 hospitalizations (90% CrI: 9924–157,340) and 1686 deaths (90% CrI: 369–3338) caused by unspecified agents.

Estimation in other countries

Several other countries have estimated the burden of disease from contaminated food, including England and Wales, the Netherlands, New Zealand, Jordan, Greece, Australia, and France [25–30,32]. The methods vary considerably, from the assessment of incidence and health impact of a few selected diseases at a regional or subregional level to extensive consideration of all possible pathogens for the whole country. Internationally, there has been a trend towards the use of disability-adjusted life years (DALY) as a summary measure of disease in the population that combines morbidity and mortality data from acute illness and sequelae [29,31].

Australia and England and Wales are the only other countries to have conducted a comprehensive assessment of the numbers of illnesses, hospitalizations, and deaths from contaminated food, including an estimate of illness from unspecified agents. Similar to the United States, the Australian study found that norovirus was the leading cause of foodborne illness, accounting for 30% of illnesses caused by known pathogens. In the study from England and Wales, norovirus accounted for only 8% of known foodborne illnesses, primarily due to the low proportion of these viral infections that were estimated to be foodborne (10.8%) [25]. However, a reexamination of stools from the Infectious Intestinal Disease (IID) study using molecular techniques documented higher rates of infection than initially thought, which would affect estimates of overall foodborne disease burden [14]. The incidence of gastroenteritis specifically due to norovirus infection from all sources from this re-analysis of the IID study and the recent IID2 study ranges from 45–47 cases per 1000 person years, or one episode per person every 20 years [32,33].

Nontyphoidal Salmonella and Campylobacter were estimated to be leading causes of foodborne illnesses in Australia, England and Wales, and the United States, although nontyphoidal Salmonella accounted for a greater proportion of illness in the United States. Recent serologic data from Europe suggests that Salmonella infections are far more common than estimated by burden-of-illness pyramid methods; however, many of these infections may be asymptomatic [34]. Another common cause of foodborne illness in all three countries was C. perfringens. Because clinical laboratories do not usually test stools for this pathogen or its toxin, it is typically only detected when it causes a foodborne outbreak [6,25,35]. In England and Wales, foodborne C. perfringens infection was estimated to be more common than foodborne norovirus infection and to cause 22% of all deaths due to foodborne disease [25,36].

The studies in Australia and England and Wales also attributed a large burden of foodborne illness to unspecified agents (73% in Australia and 48% in England and Wales versus 80% in the United States) and have estimated a similar proportion of acute gastroenteritis to be transmitted by food (32% and 26%, respectively, versus 25% in the United States). While it is difficult to direct interventions toward unspecified agents, it is important that policymakers consider the likely total burden due to contaminated food as a driver for regulatory changes [37].

While most acute gastroenteritis is mild and does not require a visit to a physician or any treatment, the annual incidence is large in most countries worldwide. In a recent systematic review, the incidence of diarrhea due to all causes in adolescents and adults in various countries ranged from 0.27–0.88 episodes per person per year [38]. Globally, the incidence of diarrheal disease is highest in children and results in significant mortality each year, particularly in developing countries [39]. While the mode of transmission is difficult to establish in developing countries, partly due to greater exposure to pathogens through unsafe water and inadequate sanitation, contaminated food plays an important role in the transmission of disease [40].

There are important benefits to assessing the national burden of foodborne illness. Knowing the burden of a specific foodborne disease helps food safety agencies prioritize intervention programs, and allows estimation of costs and benefits. In some instances, the results of an estimation process can be quite surprising. For example, the Netherlands assessed the burden of foodborne diseases using DALYs; the analysis showed that toxoplasmosis resulted in the highest burden of all foodborne diseases due to the incidence in neonates and the chronic nature of the disease [29]. This estimation of foodborne disease burden highlighted the importance of preventing Toxoplasma infections through food safety interventions.

Assessing and documenting the burden of foodborne disease provides weight to regulatory initiatives, which are often required to provide evidence of economic and social benefit. Estimating the burden of foodborne disease can also help national authorities understand the performance of surveillance systems for protecting public health. Similar to the United States, Australia and England and Wales assessed the rate of under-diagnosis and under-reporting to surveillance for enteric infections. The surveillance multipliers were considerably lower in Australia, where for every case of salmonellosis reported to surveillance, 6.9 cases were estimated in the community, and in England and Wales, where for every reported case, 3.9 community cases were estimated [17,41]. Knowledge about reporting to public health surveillance has proven important in justifying regulatory measures to prevent contamination of foods, as well as in helping disease investigators understand how well the system is performing.

Global efforts

The WHO and partner organizations have made it a priority to estimate the burden of foodborne diseases at the national level and globally. The WHO training network—the Global Foodborne Infections Network (GFN; see: http://www.who.int/gfn/en/)—runs international courses for epidemiologists and microbiologists working in ministries of health to assist them with conducting surveillance and investigations of foodborne illnesses. The courses include modules on estimating the incidence of foodborne illness, which have contributed to work attributing illnesses caused by several pathogens to food and water in the Latin American region [42].

In 2007, WHO established FERG (see: http://www.who.int/foodborne_disease/burden/en/index.html) to estimate the global burden of foodborne disease [4]. As a result, WHO has initiated several complementary systematic reviews to estimate the global burden of several diseases that are commonly transmitted by food, including those caused by chemical contamination. Some of the agents included in the estimation are peanuts (allergic reactions), cyanide, Toxoplasma, Salmonella, Shigella, and STEC. To strengthen the evidence base for estimating the foodborne disease burden, WHO has initiated studies estimating the national burden of foodborne disease in four countries: Albania, Japan, Thailand, and Uganda. These studies will provide national estimates of the burden of foodborne disease in DALYs and will improve the evidence base for policymakers and regulatory agencies [4].

Recent efforts to estimate the global incidence of nontyphoidal strains of Salmonella enterica estimated that there were 93.8 million cases and 155,000 deaths annually, of which 86% might be foodborne [43]. There was a lack of data, particularly from the most populous regions of the world, which highlighted the difficulties of estimating foodborne disease at the global level. Similar to US and other efforts, this study relied on various data sources, including a novel use of rates of salmonellosis in Swedish nationals returning from holidays overseas to estimate disease incidence in destination countries, and estimated incidence for 21 different regions of the world [43]. Despite the difficulties in estimating incidence and outcome on this scale, the analysis presented convincing evidence that Salmonella infection results in substantial burden in both developing and developed countries.

Methodological considerations

In any assessment of the burden of foodborne illness, the first step is to identify the aim of the estimation process, as this will clarify which illnesses and agents will be included, the target population, and the intended audience. Depending on the aims, steps in assessing the burden of foodborne disease could include:

• Estimation of the incidence of illness caused by various pathogens, along with their various outcomes, such as hospitalizations, deaths, and sequelae,

• Attribution of illnesses caused by specific pathogens to foodborne transmission,

• Assessment of illnesses characterized by diarrhea or vomiting caused by unknown and unspecified agents, and

• Accounting for uncertainty by providing bounds around point estimates.

A key challenge to producing robust estimates of numbers of illnesses due to food is that it is necessary to attribute a proportion of illnesses caused by each agent to foodborne transmission. For many enteric diseases, there are multiple modes of transmission. Many efforts have relied on assessment of opinions of panels of foodborne disease experts, with modeling of uncertainty around the resulting proportions [44]. However, given the wide range of pathogens and foods, few experts have in-depth knowledge of all aspects. As a result, some expert elicitations have resulted in widely conflicting opinions [45]. In recent years, greater attention has been given to alternative means of attributing the proportion of disease due to food for various pathogens using data from outbreak surveillance, molecular subtyping, and systematic reviews of case-control studies [46]. However, many of these approaches have only been shown to work for certain pathogens, such as Salmonella spp., Listeria monocytogenes, and Campylobacter spp. [47–49].

For some pathogens, researchers have attempted to specifically identify the burden due to specific foods and animal reservoirs, which is very useful to agencies managing risks in the food supply [36]. A good example is the attribution of human Listeria monocytogenes infections in England and Wales to specific foods using a Bayesian source attribution model. This study estimated that the most important food sources of listeriosis in the whole population were refrigerated packaged foods bought in stores (23% of infections), finfish (17%), and beef (15%) [48].

Several types of outcome measures can indicate the burden of illness associated with foodborne agents, with the main ones including:

• Numbers or incidence of illnesses, hospitalizations, and deaths in a certain time period and population,

• DALYs lost—a measure of the number of years lived with a disability and the years of healthy life due to a disease in a set time period, and

• Cost—the direct and indirect costs due to a disease in a set time period.

An advantage of the DALY as a measure of burden of illness is that it collapses into a single metric, measures of disability and mortality, including those due to sequelae. DALYs can be difficult for non-scientific audiences to understand, because they are composite metrics with no easily understood values. DALYs can be very helpful to assess the relative burden among various foodborne agents, but there are still areas requiring improvement, such as development of appropriate disability weights and incorporation of co-morbidities into disease models.

For certain outcome measures, such as cost of illness and DALYs, assumptions must be made about societal willingness to pay or about disability weights for various outcomes [50]. Comparing infectious and non-infectious disease burden using DALYs to allocate resources for public health spending may be problematic due to the short-lived nature of many infectious diseases and the pre-existing preventive programs in place focusing on food safety. Lawmakers easily understand data presented as costs, and it may be necessary to transform disease incidence and impact into costs to achieve consensus about public health interventions. However, even estimating costs for foodborne diseases associated with specific foods can be difficult due to the epidemic potential of some pathogens. For example, Salmonella contamination of alfalfa and other sprouted seed has resulted in many episodic outbreaks, but the direct and indirect costs are difficult to estimate on an annual basis. This has proven difficult for food safety regulators proposing food safety interventions based on cost–benefit analysis.

Conclusions

The burden-of-illness pyramid approach outlined in this chapter, combined with assessment of unspecified (including unknown) agents, provides a means for national governments to quantify the impact of contaminated food on the population. Conducting these assessments requires development of methods that incorporate many different types of information, such as case surveillance, population-based surveys, investigated outbreak surveillance, expert opinion, and hospitalization and mortality statistics.

Assessing the burden of disease is complex and requires consideration of the availability of data. The resulting estimates can be useful to regulatory agencies in prioritizing and explaining the impact of interventions to improve the safety of the food supply. Several countries have conducted national assessments of the burden of foodborne disease. Some have already been useful for policymakers. In the United States, estimates published in 2011 are being used to help direct policy and interventions and are contributing to other analyses, including evaluating the economic cost of these diseases, attributing illnesses to various food commodities, and estimating the burden of disease caused by sequelae. It is important to note, however, that just as these estimates addressed some of the limitations and data gaps highlighting the United States foodborne illness estimates published in 1999, there is still much future work required to address limitations and data gaps.

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Chapter 2

The Foods Most Often Associated with Major Foodborne Pathogens

Attributing Illnesses to Food Sources and Ranking Pathogen/Food Combinations

Michael B. Batz, Emerging Pathogens Institute, University of Florida, FL, USA

Introduction

A risk-based approach to food safety, as called for by the FDA Food Safety Modernization Act and numerous national and international public health bodies, is based on the prioritization of limited resources in ways that most benefit public health [1–7]. This calls for an understanding of which pathogens in which foods are responsible for the greatest burden of foodborne disease. Identifying the most significant pathogen/food pairs involves three steps. First is the estimation of the annual incidence of disease caused by major foodborne pathogens [8,9]. Second is the estimation of integrated measures of public health—such as cost of illness or quality-adjusted life years (QALYs)—that allow for the direct comparison of diseases with very different symptoms, severities, and chronic sequelae [10]. Third is foodborne illness source attribution: estimation of the proportion of illnesses due to each pathogen that can be linked with a specific food source [11,12]. This chapter presents a systematic, national assessment of the relationship between the burden of disease from major foodborne pathogens and food consumption across the entire US food supply [13–15]. It includes a discussion of integrated measures of disease burden, an overview of methods of foodborne illness source attribution, an analysis of US outbreak data, and a ranking of pathogen/food pairs based on outbreak and expert attribution.

Integrated measures of disease burden

Estimates of the number of annual illnesses, hospitalizations, and deaths, as presented in Chapter 1, are critical but incomplete metrics of disease burden. They do not allow for the direct comparison of pathogens—such as norovirus and Listeria monocytogenes—with very different symptoms, severities, and outcomes. They also exclude important congenital disease and long-term health outcomes of many foodborne diseases [16]. Integrated measures of disease burden allow for comparisons between foodborne pathogens and with other public health concerns [10].

Health-adjusted life year (HALY) metrics, such as QALYs and disability-adjusted life years (DALYs), are based on the principle that health-related quality of life can be measured on a scale from 0 (death) to 1 (perfect health) [17]. HALYs are computed by multiplying the preference weight for a given health state by the duration of that health state, in years. HALY loss is measured as the difference between the HALY for baseline health (either population average or perfect health) and the HALY for an adverse health state [18]. Both QALYs and DALYs have been used for prioritization of foodborne and zoonotic pathogens (e.g., [15,19]; Kemmeren et al., 2009; [20–23]).

Economists prefer willingness-to-pay (WTP) to HALY and other monetary measures because it is consistent with welfare theory; it is based on the tradeoffs that individuals must make between health and other goods [24,25]. Cost of illness (COI), in contrast with HALYs and WTP, does not measure intangible costs (e.g., pain and suffering), but quantifies measurable monetary costs such as health care costs and lost productivity (e.g., sick days). COI is relatively straightforward to compute but reflects a lower bound on socioeconomic costs, whereas WTP is a more complete measure but available for few health states due to the difficulty and costs of estimating it [26,27]. COI values have been estimated for foodborne pathogens in a number of countries ([28–30]; Kemmeren et al., 2009;