Foodborne disease outbreaks in flour and flour-based food products from microbial pathogens in the United States, and their health economic burden.

The most comprehensive and inclusive estimates for the economic burden of foodborne illness yield values as high as $97.4 billion USD annually. However, broad incidence and cost estimates have limited use if they cannot be attributed to specific foods, for the purposes of food safety control. In this study, we estimated the economic burden of foodborne illnesses resulting from flour and flour-based food products in the United States from the years 2001 to 2021. The outbreak, illness burden, and health economic data are combined to generate these estimates. Our model combined outbreak data with published Centers for Disease Control and Prevention multipliers to estimate the annual number of illnesses associated with flour-borne pathogens. We then integrated illness severity data with an updated economic model that accounts for costs related to medical care, productivity loss, loss of life, along with the quality of life loss that entails pain and suffering. In total, 752 cases and 223 hospitalizations from flour-related illnesses were reported from 2001 to 2021, with an average of 37.6 cases of reported cases annually. However, the actual number of cases, accounting for underreporting and underdiagnosis, can be as high as 19,440 annually. Pathogens involved in these outbreaks are Salmonella, E. coli O157:H7, and E. coli O121. Our estimates suggest average annual economic losses, including healthy years of life lost, of $108 and $258 million using two alternative models.

Facilitating Evaluation of Hemolytic Uremic Syndrome Long-Term Health Outcomes Through Social Media Support Groups.

Individual burden and cost of hemolytic uremic syndrome (HUS)-a medical condition characterized by acute kidney failure-can be substantial when accounting for long-term health outcomes (LTHOs). Because of the low incidence of HUS, evaluation of associated LTHOs is often restricted to physician and outbreak cohorts, both of which may not be representative of all HUS cases. This exploratory study recruited participants from private social media support groups for families of HUS cases to identify potential LTHOs and costs of HUS that are not currently measured. Additionally, this study sought to identify case characteristics that may confound or modify these LTHOs and costs of HUS. Respondents self-selected to complete an online cross-sectional survey on acute and chronic illness history, treatments, and public health follow-up for HUS cases. Posttraumatic stress among respondents (typically case parents) was also evaluated. Responses were received for 74 HUS cases from 71 families representing all geographic regions, and levels of urbanicity within the US self-reported symptoms were typical for HUS, while 35.1% of cases reported antibiotic treatment at any point during the acute illness. Hospital transfers were reported by 71.6% of cases introducing possible delays to care. More than 70% of cases reported experiencing at least one LTHO, with 45% of cases reporting renal sequelae. Posttraumatic stress symptoms were frequently reported by respondents indirectly affected by HUS. Potentially large economic costs that are not addressed in existing analyses were identified including both financial and more general welfare losses (lost utility). While biases in the study design limit the generalizability of results to all HUS cases, this study provides new insights into unmeasured LTHOs and costs associated with HUS. These results suggest that robustly designed cohort studies on HUS should include measures of psychosocial impacts on both the affected individual and their family members.

Food Attribution and Economic Cost Estimates for Meat- and Poultry-Related Illnesses.

ABSTRACT: The economic burden of foodborne illness has been estimated to be as high as US$90 billion annually. For policy purposes, it is often important to understand not only the overall cost of illness but also the costs associated with individual products or groups of products. In this study, I estimate the cost of foodborne illnesses from 29 pathogens associated with nongame meat and poultry products that are regulated by the U.S. Department of Agriculture. To complete this, I merge results from a food attribution model with results from an illness model and an economic burden of illness model. The food attribution model uses outbreak and expert elicitation data to attribute foods to pathogens. The illness model is a replication of the 2011 study published by the Centers for Disease Control and Prevention. The economic cost model is an updated version of previously published studies that include costs for medical care, lost productivity, loss of life, and pain and suffering. The primary attribution model, based largely on Interagency Food Safety Analytics Collaboration assumptions, estimates that meat and poultry products are vectors for 30.9% of all foodborne illnesses. This translates into 2.9 million annual illnesses, yielding economic costs of up to $20.3 billion. The costliest food-pathogen pairs include Campylobacter spp. in poultry ($6.9 billion), Salmonella spp. in chicken and pork ($2.8 and $1.9 billion, respectively), and Toxoplasma gondii in pork ($1.9 billion). Results based on alternative attribution and economic model assumptions are also presented, generating meat and poultry attribution estimates ranging from 27.1 to 36.7% and economic costs of $8.1 to $22.5 billion.

An Economic Evaluation of Food Safety Education Interventions: Estimates and Critical Data Gaps.

The economic evaluation of food safety interventions is an important tool that practitioners and policy makers use to assess the efficacy of their efforts. These evaluations are built on models that are dependent on accurate estimation of numerous input variables. In many cases, however, there is no data available to determine input values and expert opinion is used to generate estimates. This study uses a benefit-cost analysis of the food safety component of the adult Expanded Food and Nutrition Education Program (EFNEP) in Ohio as a vehicle for demonstrating how results based on variable values that are not objectively determined may be sensitive to alternative assumptions. In particular, the focus here is on how reported behavioral change is translated into economic benefits. Current gaps in the literature make it impossible to know with certainty how many people are protected by the education (what are the spillover effects?), the length of time education remains effective, and the level of risk reduction from change in behavior. Based on EFNEP survey data, food safety education led 37.4% of participants to improve their food safety behaviors. Under reasonable default assumptions, benefits from this improvement significantly outweigh costs, yielding a benefit-cost ratio of between 6.2 and 10.0. Incorporation of a sensitivity analysis using alternative estimates yields a greater range of estimates (0.2 to 56.3), which highlights the importance of future research aimed at filling these research gaps. Nevertheless, most reasonable assumptions lead to estimates of benefits that justify their costs.

Effect of a Publicly Accessible Disclosure System on Food Safety Inspection Scores in Retail and Food Service Establishments.

The increased frequency with which people are dining out coupled with an increase in the publicity of foodborne disease outbreaks has led the public to an increased awareness of food safety issues associated with food service establishments. To accommodate consumer needs, local health departments have increasingly publicized food establishments' health inspection scores. The objective of this study was to estimate the effect of the color-coded inspection score disclosure system in place since 2006 in Columbus, OH, by controlling for several confounding factors. This study incorporated cross-sectional time series data from food safety inspections performed from the Columbus Public Health Department. An ordinary least squares regression was used to assess the effect of the new inspection regime. The introduction of the new color-coded food safety inspection disclosure system increased inspection scores for all types of establishments and for most types of inspections, although significant differences were found in the degree of improvement. Overall, scores increased significantly by 1.14 points (of 100 possible). An exception to the positive results was found for inspections in response to foodborne disease complaints. Scores for these inspections declined significantly by 10.2 points. These results should be useful for both food safety researchers and public health decision makers.

An Economic Evaluation of PulseNet: A Network for Foodborne Disease Surveillance.

The PulseNet surveillance system is a molecular subtyping network of public health and food regulatory agency laboratories designed to identify and facilitate investigation of foodborne illness outbreaks. This study estimates health and economic impacts associated with PulseNet. The staggered adoption of PulseNet across the states offers a natural experiment to evaluate its effectiveness, which is measured as reduction of reported illnesses due to improved information, enhanced industry accountability, and more-rapid recalls. Economic impacts attributable to PulseNet include medical costs and productivity losses averted due to reduced illness. Program costs are also reported. Better information and accountability from enhanced surveillance is associated with large reductions of reported illnesses. Data collected between 1994 and 2009 were assembled and analyzed between 2010 and 2015. Conservatively, accounting for underreporting and underdiagnosis, 266,522 illnesses from Salmonella, 9,489 illnesses from Escherichia coli (E. coli), and 56 illnesses due to Listeria monocytogenes are avoided annually. This reduces medical and productivity costs by $507 million. Additionally, direct effects from improved recalls reduce illnesses from E. coli by 2,819 and Salmonella by 16,994, leading to $37 million in costs averted. Annual costs to public health agencies are $7.3 million. The PulseNet system makes possible the identification of food safety risks by detecting widespread or non-focal outbreaks. This gives stakeholders information for informed decision making and provides a powerful incentive for industry. Furthermore, PulseNet enhances the focus of regulatory agencies and limits the impact of outbreaks. The health and economic benefits from PulseNet and the foodborne disease surveillance system are substantial.

State estimates for the annual cost of foodborne illness.

An understanding of the costs associated with foodborne illnesses is important to policy makers for prioritizing resources and assessing whether proposed interventions improve social welfare. At the national level, measured costs have been used by federal food safety regulatory agencies in regulatory impact analyses. However, when costs differ across states, use of national cost-of-illness values for state-based interventions will lead to biased estimates of intervention effectiveness. In this study, the costs of foodborne illness at the state level were estimated. Using a more conservative economic model, the average cost per case ranged from $888 (90% credible interval [CI], $537 to $1,419) in West Virginia to $1,766 (90% CI, $1,231 to $2,588) in the District of Columbia. A less conservative model generated average costs per case of $1,505 (90% CI, $557 to $2,836) in Kentucky to $2,591 (90% CI, $857 to $5,134) in Maryland. Aggregated across the states, the average national cost of foodborne illness was estimated as $55.5 billion (90% CI, $33.9 to $83.3 billion) using the conservative model and $93.2 billion (90% CI, $33.0 to $176.3 billion) using the enhanced model.

The heterogeneity in financial and time burden of caregiving to children with chronic conditions.

We examine the financial and time burdens associated with caring for children with chronic conditions, focusing on disparities across types of conditions. Using linked data from the 2003 to 2006 National Health Interview Survey and 2004-2008 Medical Expenditure Panel Survey, we created measures of financial burden (out-of-pocket healthcare costs, the ratio of out-of-pocket healthcare costs to family income, healthcare costs paid by insurance, and total healthcare costs) and time burden (missed school time due to illness or injury and the number of doctor visits) associated with 14 groups of children's chronic conditions. We used the two-part model to assess the effect of condition on financial burden and finite mixture/latent class model to analyze the time burden of caregiving. Controlling for the influences of other socio-demographic characteristics on caregiving burden, children with chronic conditions have higher financial and time burdens relative to caregiving burdens for healthy children. Levels of financial burden and burden sharing between families and insurance system also vary by type of condition. For example, children with pervasive developmental disorder or heart disease have a relatively low financial burden for families, while imposing a high cost on the insurance system. In contrast, vision difficulties are associated with a high financial burden for families relative to the costs borne by others. With respect to time burden, conditions such as cerebral palsy and heart disease impose a low time burden, while conditions such as pervasive developmental disorder are associated with a high time burden. This study demonstrates that differences exist in caregiving burden for children by type of chronic condition. Each condition has a unique profile of time and financial cost burden for families and the insurance system. These results have implications for policymakers and for families' savings and employment decisions.

Precautionary savings against health risks: evidence from the Health and Retirement Study.

The precautionary savings model predicts that households accumulate wealth to self-insure against unexpected declines in future income and unforeseen expenditures. The goals of this study are twofold. First, we investigate whether the near-elderly who face higher health risks save more. Second, we examine the factors that contribute to health risks that the near-elderly face. We use data from the Health and Retirement Study to construct two measures of health risks. Our results do not support the hypothesis that household savings increase with the health risks that they face. Individuals who confront higher health risks in the future are those who are already in fair or poor health status or those who have a health condition such as diabetes or lung disease. Lower earnings and high medical expenditures caused by current poor health status prevent households from accumulating savings for future health adversities.

Economic burden from health losses due to foodborne illness in the United States.

The Centers for Disease Control and Prevention (CDC) recently revised their estimates for the annual number of foodborne illnesses; 48 million Americans suffer from domestically acquired foodborne illness associated with 31 identified pathogens and a broad category of unspecified agents. Consequently, economic studies based on the previous estimates are now obsolete. This study was conducted to provide improved and updated estimates of the cost of foodborne illness by adding a replication of the 2011 CDC model to existing cost-of-illness models. The basic cost-of-illness model includes economic estimates for medical costs, productivity losses, and illness-related mortality (based on hedonic value-of-statistical-life studies). The enhanced cost-of-illness model replaces the productivity loss estimates with a more inclusive pain, suffering, and functional disability measure based on monetized quality-adjusted life year estimates. Costs are estimated for each pathogen and a broader class of unknown pathogens. The addition of updated cost data and improvements to methodology enhanced the performance of each existing economic model. Uncertainty in these models was characterized using Monte Carlo simulations in @Risk version 5.5. With this model, the average cost per case of foodborne illness was $1,626 (90% credible interval [CI], $607 to $3,073) for the enhanced cost-of-illness model and $1,068 (90% CI, $683 to $1,646) for the basic model. The resulting aggregated annual cost of illness was $77.7 billion (90% CI, $28.6 to $144.6 billion) and $51.0 billion (90% CI, $31.2 to $76.1 billion) for the enhanced and basic models, respectively.

Heterogeneous rates of time preference and the decision to smoke.

Individuals with higher personal rates of time preference will be more likely to smoke. Although previous studies have found no evidence of a relationship between smoking and rates of time preference, analysis of implicit rates of time preference associated with workers' wage fatality risk trade-offs indicates that smokers have higher rates of time preference with respect to years of life. Current smokers have an implied rate of time preference of 13.8% as compared to 8.1% for nonsmokers. Current smokers who are blue-collar workers have rates of time preference with respect to years of life of 16.3% compared to 7.8% for nonsmoking blue-collar workers.

Economic cost of foodborne illness in Ohio.

Past efforts to evaluate the economic burden of risks from foodborne illness in the United States have generally taken the form of studies focused on a single or a small number of "important" pathogens. As a result, the economic impact of many less prominent pathogens has not been sufficiently explored. Consequently, currently available studies only provide cost estimates for fewer than 4 million of the 76 million cases of foodborne illness, are incomplete, and, as a result, underestimate the efficacy of broad-based intervention programs. We present a cost-of-illness model that enhances the oft-cited U.S. Department of Agriculture Economic Research Service model. Our model uses a more comprehensive set of pathogens, includes pathogen-specific hospitalization costs, and includes measures to account for lost quality of life. We also use Monte Carlo simulations to evaluate the effects of uncertainty in our analysis. We find the estimated annual expected economic cost of foodborne illness for Ohio to be between $1.0 and $7.1 billion, which translates into a per-Ohio resident cost of $91 to $624. Our results can be used to evaluate the effectiveness of broad-based food safety programs.

Evaluation of an educational intervention using the enhanced food safety cost-of-illness model.

In recent years, a number of federally sponsored state-based food safety education programs have conducted economic evaluations aimed at demonstrating the efficacy of their approaches. These evaluations have typically been based on the "Virginia method," a comprehensive, but overly simplistic means of estimating benefit-cost ratios for food safety and nutrition education programs. In this article, we use the enhanced food safety cost-of-illness model, coupled with a more complete food safety education intervention model to evaluate the efficacy of the Ohio Family Nutrition Program. We find that, under most reasonable assumptions, the derived benefit-cost ratios imply that this program is socially beneficial. The model presented here is of particular use because it can be replicated to evaluate other broad-based food safety programs.

Evaluating chronic disease for heterogeneous populations: the case of arthritis.

BACKGROUND: Cost-effectiveness evaluation for health care programs often involves the use of quality-adjusted life-year (QALY) estimates to measure morbidity losses from health conditions. Current techniques for measuring morbidity losses are often subjective, inflexible, impractical, and subject to bias. OBJECTIVE: We sought to examine the impact of population heterogeneity on QALY values for arthritis sufferers by estimating an alternative health-adjusted life-year (HALY) measure based on self-assessed health status. RESEARCH DESIGN: We present a feasible approach for the assessment of improved QALY estimates for chronic conditions affecting heterogeneous populations. An ordered probit model, using data from the National Health Interview Survey (NHIS), is used to calculate expected HALY losses from arthritis for distinct population subgroups. These measures are used to scale existing QALY measures that have been calculated for distinct homogeneous populations. RESULTS: : We find that QALY losses from chronic arthritis vary by age, time since onset, and type of arthritis. When we apply these results to prevention programs aimed at reducing the incidence of Salmonella enteritidis infections (and the resulting reactive arthritis sequelae), we find that age-invariant QALYs underestimate the true discounted lifetime QALY losses from arthritis by 15%. CONCLUSIONS: Our results indicate that a failure to account for population heterogeneity can lead to biased health loss estimates. The modified HALY measure presented here can be used to help inform policymakers faced with heterogeneous populations.