M15 - Symposium: Integrating Epidemiological Data in Risk Assessment, Part 1 - Sponsored by the Food Water and Dose Response Specialty Groups
Salon A 1:30 - 3:00 pm
|Chair(s): Christina McLaughlin, Debra Street|
The role of epidemiology in hazard identification is commonly known, however, more work is needed to address the role of epidemiology in other areas of risk assessment, i.e. Hazard characterization, Exposure assessment and Risk characterization. Within the risk assessment framework, the role of epidemiology will be presented and discussed. The role of epidemiology in Exposure Assessment is of particular interest. This two session symposium will address questions on how to incorporate epidemiological data into microbial, chemical and other type of risk assessments as they relate to different types of exposure such as dietary, environmental and occupational pathways. Related to hazard characterization, the use of Epidemiological data to characterize dose response functions and to estimate the benefits of environmental contaminant mitigation efforts will be addressed. Typically, data from laboratory experiments are used to answer questions related to dose response, yet after examining Epidemiological data, different conclusions may be drawn in answering the same questions. In addition to trying to reconcile this gap, most recent techniques in integrating Epidemiological data and Risk assessments will also be addressed.
M15.1 Addressing Uncertainty in Epidemiologically Based Risk Assessments. Leslie Stayner* , Martine Vrijheid, Dan Stram; 1National Institute for Occupational Safety and Health email@example.com|
Abstract: The use of epidemiologic data for quantitative risk assessments (QRA) is becoming increasingly common. Part of the reason for this increase is that using human studies avoids the uncertainties associated with extrapolating from animals to humans. However, using epidemiologic data in QRA introduces a whole other set of uncertainties, which are largely related to the observational nature of epidemiologic data. Of particular concern are issues related to inadequate sample size, unresolved confounding or other biases, inadequate length of follow-up, and errors in the ascertainment of exposures. The issue of errors in the estimation of exposures has been of large concern particularly in occupational studies. We are evaluating methods for estimating confidence intervals that reflect both uncertainties related to random error, and potential errors in exposure using Monte Carlo maximum likelihood methods. These methods will be illustrated using an epidemiological study of nuclear power plant workers.
M15.2 Identifying and cultivating non-public domain sources of public health epidemiological data. Charlotte Spires; Food and Drug Administration firstname.lastname@example.org|
Abstract: Identifying and cultivating potential sources of non-public domain health related data can result in a wealth of valuable epidemiological data for use in public health risk assessments. Many allied health private sector entities accrue medical and/or patient data as a consequence of providing and billing for medical and medical support services. Pharmacies, insurance companies, healthcare support service groups (such as those that provide home nursing care) collect a variety of patient data such as signalment, diagnosis, medical history, drug usage and family medical history. These health care provider databases may be very extensive and may provide a representative sample of the local, regional or national population. The goal of epidemiologist/risk assessor interaction with these more unconventional data sources include gathering the data needed for the risk assessment, establishing a relationship with the organization based on mutual benefit and trust, maintaining collaboration with the data source so that additional data for future updates of the risk assessment may be obtained, ensuring that data for future projects will be available, and utilizing the organization as a referral to other non-public domain data sources. To this end, certain principles should be adhered to when identifying and establishing a relationship with potential non-public domain data sources. Initiating contact with the organization, presenting the mutual benefits of collaboration for the purpose of data mining, consideration of patient confidentiality and legal constraints, negotiating the terms of data handling, establishing communication channels between involved parties, formatting of interim and final data deliverables, and, post-data collection follow-up activities are crucial steps in the completion of a successful data collection endeavor.
M15.3 A Review of the Integration of Epidemiology and Risk Assessment for Foodborne Microbial Hazards. Greg Paoli; Decisionalysis Risk Consultants, Inc. email@example.com|
Abstract: The management of microbial hazards provides considerable opportunity to integrate epidemiological analysis with standard risk assessment techniques. This paper will review a variety of applications in which these complementary approaches have been employed. Examples include: the use of epidemiological data to derive and adjust dose-response relationships; the use of serotyping data together with risk assessment methodology to estimate attributable risk among commodities; incorporation of epidemiologically determined risk factors within risk assessment models; the use of molecular epidemiology and risk assessment to improve the understanding of sources of contamination; the use of surveillance data for validation of risk assessment predictions; and recent advances in computational epidemiology involving Bayesian inference combined with simulation to improve the detection of outbreaks or terrorist attacks. At times, risk assessment and epidemiological approaches have led to contradictory findings. Examples of these situations will also be described and assessed.
M15.4 Survey of Listeria monocytogenes in Ready-to-Eat Foods: Exposure Assessment in FoodNet Sites . Yuhuan Chen*, William Ross, Virginia Scott; National food Processors Association firstname.lastname@example.org|
Abstract: This study was conducted to develop data relative to the risk of listeriosis to support a science-based strategy for addressing Listeria monocytogenes in foods in the U. S. Eight categories of ready-to-eat foods were collected over 14 – 23 months from retail markets at Maryland and Northern California FoodNet sites. The product categories included luncheon meats, deli salads, fresh soft “Hispanic-style” cheeses, bagged salads, blue-veined cheeses, soft mold-ripened cheeses, smoked seafood and seafood salads. The presence and levels of L. monocytogenes in the samples were determined by rapid DNA-based assays in combination with cultural methods. A total of 31,705 samples were tested, of which 577 were positive. The overall prevalence was 1.82%, with prevalence ranging from 0.17 to 4.70% among the product categories. The confidence intervals for the overall prevalence were 1.68-1.97%. L. monocytogenes levels in the positives varied from less than 0.3 MPN/g to 1.5x105 cfu/g. L. monocytogenes levels were adequately described by the distribution Beta (0.29, 2.68, –1.69, 6.1). An exponential dose-response model was developed, with the model parameter (R-value) estimated to be 1.76x10-10 for the population at higher risk. This study was the first in the U. S. to collect exposure data concurrent with illness data in the same FoodNet sites, providing a unique opportunity for integrating epidemiological data in risk assessment.