Terrorism Risks and Cost‐Benefit Analysis of Aviation Security

We evaluate, for the U.S. case, the costs and benefits of three security measures designed to reduce the likelihood of a direct replication of the 9/11 terrorist attacks. To do so, we assess risk reduction, losses, and security costs in the context of the full set of security layers. The three measures evaluated are installed physical secondary barriers (IPSB) to restrict access to the hardened cockpit door during door transitions, the Federal Air Marshal Service (FAMS), and the Federal Flight Deck Officer (FFDO) Program. In the process, we examine an alternate policy measure: doubling the budget of the FFDO program to $44 million per year, installing IPSBs in all U.S. aircraft at a cost of $13.5 million per year, and reducing funding for FAMS by 75% to $300 million per year. A break‐even cost‐benefit analysis then finds the minimum probability of an otherwise successful attack required for the benefit of each security measures to equal its cost. We find that the IPSB is costeffective if the annual attack probability of an otherwise successful attack exceeds 0.5% or one attack every 200 years. The FFDO program is costeffective if the annual attack probability exceeds 2%. On the other hand, more than two otherwise successful attacks per year are required for FAMS to be costeffective. A policy that includes IPSBs, an increased budget for FFDOs, and a reduced budget for FAMS may be a viable policy alternative, potentially saving hundreds of millions of dollars per year with consequences for security that are, at most, negligible.     

Risk‐Based Decision Support Tools: Protecting Rail‐Centered Transit Corridors from Cascading Effects

We consider the value of decision support tools for passenger rail system managers. First, we call for models that follow events along main rail lines and then into the surrounding environment where they can cascade onto connected light rail, bus, auto, truck, and other transport modes. Second, we suggest that both probabilistic risk assessment (PRA‐based) and agent‐based models have a role to play at different scales of analysis and for different kinds of risks. Third, we argue that economic impact tools need more systematic evaluation. Fourth, we note that developers of decision support tools face a challenge of balancing their desire for theoretical elegance and the tendency to focus only on high consequence events against decisionmakers’ mistrust of complex tools that they and their staff cannot manage and incorporate into their routine operations, as well as the high costs of developing, updating, and applying decision support tools to transport systems undergoing budget cuts and worker and service reductions.     

Ecological Risks of Diazinon from Agricultural Use in the Sacramento – San Joaquin River Basins, California

A probabilistic risk assessment was conducted to evaluate the likelihood and ecological significance of potential toxic effects of diazinon in the Sacramento-San Joaquin system. Diazinon, an organophosphorus insecticide, is used in the Sacramento-San Joaquin River Basin as a dormant spray on almonds and other tree crops, as well as for other agricultural and urban applications. Diazinon and other pesticides have been detected in the Sacramento and San Joaquin Rivers and their tributaries. Diazinon exposure was characterized based on monitoring programs conducted in 1991-94. Diazinon effects were characterized using laboratory toxicity data for 63 species, supplemented by results from field mesocosm and microcosm studies. The assessment addressed the possibility that reductions in invertebrate populations could lead to impacts on species of fish that feed on those invertebrates. The risk assessment concluded that fish in these rivers are not at risk from the direct effects of diazinon in the water. Invertebrates are at greater risk, especially in agriculturally dominated streams and drainage channels during January and February. Cladocerans--including Daphnia magna and Ceriodaphnia dubia, two common bioassay species--are especially sensitive to diazinon and other organophosphates and are likely to be subject to acute toxic effects in some locations at some times. Any ecological damage that may occur, however, is brief and limited to cladocerans. None of the fish species of concern depend on cladocerans as critical components of their diet. Invertebrates that are not affected by observed concentrations of diazinon (copepods, mysids, amphipods, rotifers, and insects) are preferred foods for fish in the Sacramento-San Joaquin system.     

Premature Deaths,Statistical Lives,and Years of Life Lost: Identification,Quantification, and Valuation of Mortality Risks

Mortality effects of exposure to air pollution and other environmental hazards are often described by the estimated number of “premature” or “attributable” deaths and the economic value of a reduction in exposure as the product of an estimate of “statistical lives saved” and a “value per statistical life.” These terms can be misleading because the number of deaths advanced by exposure cannot be determined from mortality data alone, whether from epidemiology or randomized trials (it is not statistically identified). The fraction of deaths “attributed” to exposure is conventionally derived as the hazard fraction (R – 1)/R, where R is the relative risk of mortality between high and low exposure levels. The fraction of deaths advanced by exposure (the “etiologic” fraction) can be substantially larger or smaller: it can be as large as one and as small as 1/e (≈0.37) times the hazard fraction (if the association is causal and zero otherwise). Recent literature reveals misunderstanding about these concepts. Total life years lost in a population due to exposure can be estimated but cannot be disaggregated by age or cause of death. Economic valuation of a change in exposure-related mortality risk to a population is not affected by inability to know the fraction of deaths that are etiologic. When individuals facing larger or smaller changes in mortality risk cannot be identified, the mean change in population hazard is sufficient for valuation; otherwise, the economic value can depend on the distribution of risk reductions.     

Current and Future Particulate‐Matter‐Related Mortality Risks in the United States from Aviation Emissions During Landing and Takeoff

Demand for air travel is projected to increase in the upcoming years, with a corresponding influence on emissions, air quality, and public health. The trajectory of health impacts would be influenced by not just emissions growth, but also changes in nonaviation ambient concentrations that influence secondary fine particulate matter (PM_2.5) formation, population growth and aging, and potential shifts in PM_2.5 concentration‐response functions (CRFs). However, studies to date have not systematically evaluated the individual and joint contributions of these factors to health risk trajectories. In this study, we simulated emissions during landing and takeoff from aircraft at 99 airports across the United States for 2005 and for a 2025 flight activity projection scenario. We applied the Community Multiscale Air Quality (CMAQ) model with the Speciated Modeled Attainment Test (SMAT) to determine the contributions of these emissions to ambient concentrations, including scenarios with 2025 aircraft emissions and 2005 nonaviation air quality. We combined CMAQ outputs with PM_2.5 mortality CRFs and population projections, and evaluated the influence of changing emissions, nonaviation concentrations, and population factors. Given these scenarios, aviation‐related health impacts would increase by a factor of 6.1 from 2005 to 2025, with a factor of 2.1 attributable to emissions, a factor of 1.3 attributable to population factors, and a factor of 2.3 attributable to changing nonaviation concentrations which enhance secondary PM_2.5 formation. Our study emphasizes that the public health burden of aviation emissions would be significantly influenced by the joint effects of flight activity increases, nonaviation concentration changes, and population growth and aging.     

Informing Ex Ante Event Studies with Macro‐Econometric Evidence on the Structural and Policy Impacts of Terrorism

Economic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event‐specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates of return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or ex ante surveys. This article explores a new method. We elucidate the magnitude of CGE‐relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future ex ante event assessments. Ex post econometric studies of terrorism by Blomberg et al . yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the United States. This allows us to: (i) compare values for these shifts with input assumptions in earlier ex ante CGE studies; and (ii) discuss how future ex ante studies can be informed by our analysis.     

Sensitivity Analysis and Estimation of Extreme Tail Behavior in Two‐Dimensional Monte Carlo Simulation

Two‐dimensional Monte Carlo simulation is frequently used to implement probabilistic risk models, as it allows for uncertainty and variability to be quantified separately. In many cases, we are interested in the proportion of individuals from a variable population exceeding a critical threshold, together with uncertainty about this proportion. In this article we introduce a new method that can accurately estimate these quantities much more efficiently than conventional algorithms. We also show how those model parameters having the greatest impact on the probabilities of rare events can be quickly identified via this method. The algorithm combines elements from well‐established statistical techniques in extreme value theory and Bayesian analysis of computer models. We demonstrate the practical application of these methods with a simple example, in which the true distributions are known exactly, and also with a more realistic model of microbial contamination of milk with seven parameters. For the latter, sensitivity analysis (SA) is shown to identify the two inputs explaining the majority of variation in distribution tail behavior. In the subsequent prediction of probabilities of large contamination events, similar results are obtained using the new approach taking 43 seconds or the conventional simulation that requires more than 3 days.     

Awareness and Perceptions of the Risks of Exposure to Indoor Radon: A Population‐Based Approach to Evaluate a Radon Awareness and Testing Campaign in England and Wales

The current study aimed to evaluate the locally directed radon roll‐out program that was conducted between 2001 and 2005 in England and Wales to increase radon awareness and testing rates. A representative sample of 1,578 residents aged 16 and older were interviewed who lived in radon‐affected areas of 15 local authorities in England and Wales that were eligible for participation in the program. The study systematically sampled across participating and nonparticipating local authorities, “actionable” and “nonactionable” radon‐affected areas, and geographic regions with different campaign histories (Wales, Southwest England, and the rest of England). As a multistage sampling strategy was used, the data were analyzed from a multilevel perspective. This study found that participants living in participating local authorities had higher levels of awareness and were more likely to have tested their home for radon than participants living in nonparticipating local authorities. Similar results were found for participants living in “actionable” areas as compared to those living in “nonactionable” radon‐affected areas. The study further found that radon awareness and testing rates were the highest in Southwest England and the lowest in Wales. This study suggests that the radon roll‐out program has been effective in raising awareness and testing rates, and that ongoing domestic radon campaigns in Southwest England may have raised radon awareness and testing in these areas, showing important reinforcement effects of multiple risk communication campaigns.     

Oral Poliovirus Vaccine Evolution and Insights Relevant to Modeling the Risks of Circulating Vaccine‐Derived Polioviruses (cVDPVs)

The live, attenuated oral poliovirus vaccine (OPV) provides a powerful tool for controlling and stopping the transmission of wild polioviruses (WPVs), although the risks of vaccine‐associated paralytic polio (VAPP) and circulating vaccine‐derived poliovirus (cVDPV) outbreaks exist as long as OPV remains in use. Understanding the dynamics of cVDPV emergence and outbreaks as a function of population immunity and other risk factors may help to improve risk management and the development of strategies to respond to possible outbreaks. We performed a comprehensive review of the literature related to the process of OPV evolution and information available from actual experiences with cVDPV outbreaks. Only a relatively small fraction of poliovirus infections cause symptoms, which makes direct observation of the trajectory of OPV evolution within a population impractical and leads to significant uncertainty. Despite a large global surveillance system, the existing genetic sequence data largely provide information about transmitted virulent polioviruses that caused acute flaccid paralysis, and essentially no data track the changes that occur in OPV sequences as the viruses transmit largely asymptomatically through real populations with suboptimal immunity. We updated estimates of cVDPV risks based on actual experiences and identified the many limitations in the existing data on poliovirus transmission and immunity and OPV virus evolution that complicate modeling. Modelers should explore the space of potential model formulations and inputs consistent with the available evidence and future studies should seek to improve our understanding of the OPV virus evolution process to provide better information for policymakers working to manage cVDPV risks.     

Toward an Epidemiology of Safety and Security Risks: An Organizational Vulnerability Assessment in International Airports

International airports are complex sociotechnical systems that have an intrinsic potential to develop safety and security disruptions. In the absence of appropriate defenses, and when the potential for disruption is neglected, organizational crises can occur and jeopardize aviation services. This investigation examines the ways in which modern international airports can be “authors of their own misfortune” by adopting practices, attitudes, and behaviors that could increase their overall level of vulnerability. A sociotechnical perspective, the macroergonomic approach, is applied in this research to detect the potential organizational determinants of vulnerability in airport operations. Qualitative data nurture the case study on international airports produced by the present research. Findings from this study highlight that systemic weaknesses frequently reside in areas at the intersection of physical, organizational, and social spaces. Specific pathways of vulnerability can be drawn across these areas, involving the following systemic layers: individual, task, tools and technology, environment, and organization. This investigation expands the existing literature on the dynamics that characterize crisis incubation in multiorganization, multistakeholder systems such as international airports and provides practical recommendations for airport managers to improve their capabilities to early detect symptoms of organizational vulnerability.     

The Perceived Health Risks of Indoor Radon Gas and Overhead Powerlines: A Comparative Multilevel Approach

Radon and overhead powerlines are two radiation risk cases that have raised varying levels of concern among the general public and experts. Despite both involving radiation—a typically feared and unseen health hazard—individuals' perceptions of the two risk cases may invoke rather different factors. We examined individual and geographic-contextual factors influencing public perceptions of the health risks of indoor radon gas and overhead powerlines in a comparative research design, utilizing a postal questionnaire with 1,528 members of the general public (response rate 28%) and multilevel modeling techniques. This study found that beliefs about the two risk cases mainly differed according to the level of "exposure"—defined here in terms of spatial proximity. We argue that there are two alternative explanations for this pattern of findings: that risk perception itself varies directly with proximity, or that risk is more salient to concerned people in the exposed areas. We also found that while people living in high radon areas are more concerned about the risks of indoor radon gas, they find these risks more acceptable and have more trust in authorities. These results might reflect the positive effects of successive radon campaigns in high radon areas, which may have raised awareness and concern, and at the same time may have helped to increase trust by showing that the government takes the health risks of indoor radon gas seriously, suggesting that genuine risk communication initiatives may have positive impacts on trust in risk management institutions.     

Air Toxics and Health Risks in California: The Public Health Implications of Outdoor Concentrations

Of the 188 hazardous air pollutants (HAPs) listed in the Clean Air Act, only a handful have information on human health effects, derived primarily from animal and occupational studies. Lack of consistent monitoring data on ambient air toxics makes it difficult to assess the extent of low-level, chronic, ambient exposures to HAPs that could affect human health, and limits attempts to prioritize and evaluate policy initiatives for emissions reduction. Modeled outdoor HAP concentration estimates from the U.S. Environmental Protection Agency's Cumulative Exposure Project were used to characterize the extent of the air toxics problem in California for the base year of 1990. These air toxics concentration estimates were used with chronic toxicity data to estimate cancer and noncancer hazards for individual HAPs and the risks posed by multiple pollutants. Although hazardous air pollutants are ubiquitous in the environment, potential cancer and noncancer health hazards posed by ambient exposures are geographically concentrated in three urbanized areas and in a few rural counties. This analysis estimated a median excess individual cancer risk of 2.7E-4 for all air toxics concentrations and 8600 excess lifetime cancer cases, 70% of which were attributable to four pollutants: polycyclic organic matter, 1,3 butadiene, formaldehyde, and benzene. For noncancer effects, the analysis estimated a total hazard index representing the combined effect of all HAPs considered. Each pollutant contributes to the index a ratio of estimated concentration to reference concentration. The median value of the index across census tracts was 17, due primarily to acrolein and chromium concentration estimates. On average, HAP concentrations and cancer and noncancer health risks originate mostly from area and mobile source emissions, although there are several locations in the state where point sources account for a large portion of estimated concentrations and health risks. Risk estimates from this study can provide guidance for prioritizing research, monitoring, and regulatory intervention activities to reduce potential hazards to the general population. Improved ambient monitoring efforts can help clarify uncertainties inherent in this analysis.     

Air Pollution and Mortality: Quantification and Valuation of Years of Life Lost

To analyze the loss of life expectancy (LLE) due to air pollution and the associated social cost, a dynamic model was developed that took into account the decrease of risk after the termination of an exposure to pollution. A key parameter was the time constant for the decrease of risk, for which estimates from studies of smoking were used. A sensitivity analysis showed that the precise value of the time constant(s) was not critical for the resulting LLE. An interesting aspect of the model was that the relation between population total LLE and PM2.5 concentration was numerically almost indistinguishable from a straight line, even though the functional dependence was nonlinear. This essentially linear behavior implies that the detailed history of a change in concentration does not matter, except for the effects of discounting. This model was used to correct the data of the largest study of chronic mortality for variations in past exposure, performed by Pope et al. in 1995; the correction factor was shown to depend on assumptions about the relative toxicity of the components of PM2.5. In the European Union, an increment of 1 microg/m3 of PM2.5 for 1 year implies an average LLE of 0.22 days per person. With regard to the social cost of an air pollution pulse, it was found that for typical discount rates (3% to 8% real) the cost was reduced by a factor of about 0.4 to 0.6 relative to the case with zero discount rate, if the value of a life year was taken as given; if the value of a life year was calculated from the "value of statistical life" by assuming the latter as a series of discounted annual values, the cost varied by at most +/-20% relative to the case with zero discount rate. To assess the uncertainties, this study also examined how the LLE depended on the demographics (mortality and age pyramid) of a population, and how it would change if the relative risk varied with age, in the manner suggested by smoking studies. These points were found to have a relatively small effect (compared to the epidemiological uncertainties) on the calculated LLE.     

Statistical Modeling of Fire Occurrence Using Data from the Tōhoku,Japan Earthquake and Tsunami

In this article, we develop statistical models to predict the number and geographic distribution of fires caused by earthquake ground motion and tsunami inundation in Japan. Using new, uniquely large, and consistent data sets from the 2011 Tōhoku earthquake and tsunami, we fitted three types of models—generalized linear models (GLMs), generalized additive models (GAMs), and boosted regression trees (BRTs). This is the first time the latter two have been used in this application. A simple conceptual framework guided identification of candidate covariates. Models were then compared based on their out‐of‐sample predictive power, goodness of fit to the data, ease of implementation, and relative importance of the framework concepts. For the ground motion data set, we recommend a Poisson GAM; for the tsunami data set, a negative binomial (NB) GLM or NB GAM. The best models generate out‐of‐sample predictions of the total number of ignitions in the region within one or two. Prefecture‐level prediction errors average approximately three. All models demonstrate predictive power far superior to four from the literature that were also tested. A nonlinear relationship is apparent between ignitions and ground motion, so for GLMs, which assume a linear response‐covariate relationship, instrumental intensity was the preferred ground motion covariate because it captures part of that nonlinearity. Measures of commercial exposure were preferred over measures of residential exposure for both ground motion and tsunami ignition models. This may vary in other regions, but nevertheless highlights the value of testing alternative measures for each concept. Models with the best predictive power included two or three covariates.     

Comparative Risks of Cancer from Drywall Finishing Based on Stochastic Modeling of Cumulative Exposures to Respirable Dusts and Chrysotile Asbestos Fibers

Sanding joint compounds is a dusty activity and exposures are not well characterized. Until the mid 1970s, asbestos‐containing joint compounds were used by some people such that sanding could emit dust and asbestos fibers. We estimated the distribution of 8‐h TWA concentrations and cumulative exposures to respirable dusts and chrysotile asbestos fibers for four worker groups: (1) drywall specialists, (2) generalists, (3) tradespersons who are bystanders to drywall finishing, and (4) do‐it‐yourselfers (DIYers). Data collected through a survey of experienced contractors, direct field observations, and literature were used to develop prototypical exposure scenarios for each worker group. To these exposure scenarios, we applied a previously developed semi‐empirical mathematical model that predicts area as well as personal breathing zone respirable dust concentrations. An empirical factor was used to estimate chrysotile fiber concentrations from respirable dust concentrations. On a task basis, we found mean 8‐h TWA concentrations of respirable dust and chrysotile fibers are numerically highest for specialists, followed by generalists, DIYers, and bystander tradespersons; these concentrations are estimated to be in excess of the respective current but not historical Threshold Limit Values. Due to differences in frequency of activities, annual cumulative exposures are highest for specialists, followed by generalists, bystander tradespersons, and DIYers. Cumulative exposure estimates for chrysotile fibers from drywall finishing are expected to result in few, if any, mesothelioma or excess lung cancer deaths according to recently published risk assessments. Given the dustiness of drywall finishing, we recommend diligence in the use of readily available source controls.     

Characterizing Poliovirus Transmission and Evolution: Insights from Modeling Experiences with Wild and Vaccine‐Related Polioviruses

With national and global health policymakers facing numerous complex decisions related to achieving and maintaining polio eradication, we expanded our previously developed dynamic poliovirus transmission model using information from an expert literature review process and including additional immunity states and the evolution of oral poliovirus vaccine (OPV). The model explicitly considers serotype differences and distinguishes fecal‐oral and oropharyngeal transmission. We evaluated the model by simulating diverse historical experiences with polioviruses, including one country that eliminated wild poliovirus using both OPV and inactivated poliovirus vaccine (IPV) (USA), three importation outbreaks of wild poliovirus (Albania, the Netherlands, Tajikistan), one situation in which no circulating vaccine‐derived polioviruses (cVDPVs) emerge despite annual OPV use and cessation (Cuba), three cVDPV outbreaks (Haiti, Madura Island in Indonesia, northern Nigeria), one area of current endemic circulation of all three serotypes (northern Nigeria), and one area with recent endemic circulation and subsequent elimination of multiple serotypes (northern India). We find that when sufficient information about the conditions exists, the model can reproduce the general behavior of poliovirus transmission and outbreaks while maintaining consistency in the generic model inputs. The assumption of spatially homogeneous mixing remains a significant limitation that affects the performance of the differential equation‐based model when significant heterogeneities in immunity and mixing may exist. Further studies on OPV virus evolution and improved understanding of the mechanisms of mixing and transmission may help to better characterize poliovirus transmission in populations. Broad application of the model promises to offer insights in the context of global and national policy and economic models.     

Decidedly Different: Expert and Public Views of Risks from a Radioactive Waste Repository

A questionnaire with items that had been used in a national survey of the general public was administered to persons attending an American Nuclear Society meeting. The items asked about risks associated with high-level nuclear waste (HLNW), trust in nuclear-waste program managers, costs and benefits of a repository project, and images of a HLNW repository. The results suggest that nuclear industry experts may have very different opinions from the general public about most of these items and their images of a repository indicate a vastly different conceptual framework within which their opinions are formed.     

Reproductive and Developmental Risks from Ethylene Oxide: A Probabilistic Characterization of Possible Regulatory Thresholds

Ethylene oxide is a gas produced in large quantities in the United States that is used primarily as a chemical intermediate in the production of ethylene glycol, propylene glycol, non-ionic surfactants, ethanolamines, glycol ethers, and other chemicals. It has been well established that ethylene oxide can induce cancer, genetic, reproductive and developmental, and acute health effects in animals. The U.S. Environmental Protection Agency is currently developing both a cancer potency factor and a reference concentration (RfC) for ethylene oxide. This study used the rich database on the reproductive and developmental effects of ethylene oxide to develop a probabilistic characterization of possible regulatory thresholds for ethylene oxide. This analysis was based on the standard regulatory approach for noncancer risk assessment, but involved several innovative elements, such as: (1) the use of advanced statistical methods to account for correlations in developmental outcomes among littermates and allow for simultaneous control of covariates (such as litter size); (2) the application of a probabilistic approach for characterizing the uncertainty in extrapolating the animal results to humans; and (3) the use of a quantitative approach to account for the variation in heterogeneity among the human population. This article presents several classes of results, including: (1) probabilistic characterizations of ED10s for two quantal reproductive outcomes-resorption and fetal death, (2) probabilistic characterizations of one developmental outcome-the dose expected to yield a 5% reduction in fetal (or pup) weight, (3) estimates of the RfCs that would result from using these values in the standard regulatory approach for noncancer risk assessment, and (4) a probabilistic characterization of the level of ethylene oxide exposure that would be expected to yield a 1/1,000 increase in the risk of reproductive or developmental outcomes in exposed human populations.     

Risk of Fetal Mortality After Exposure to Listeria monocytogenes Based on Dose-Response Data from Pregnant Guinea Pigs and Primates

One‐third of the annual cases of listeriosis in the United States occur during pregnancy and can lead to miscarriage or stillbirth, premature delivery, or infection of the newborn. Previous risk assessments completed by the Food and Drug Administration/the Food Safety Inspection Service of the U.S. Department of Agriculture/the Centers for Disease Control and Prevention (FDA/USDA/CDC)^{( 1 )} and Food and Agricultural Organization/the World Health Organization (FAO/WHO)^{( 2 )} were based on dose‐response data from mice. Recent animal studies using nonhuman primates^{( 3 , 4 )} and guinea pigs^{( 5 )} have both estimated LD₅₀s of approximately 10⁷ Listeria monocytogenes colony forming units (cfu). The FAO/WHO^{( 2 )} estimated a human LD₅₀ of 1.9 × 10⁶ cfu based on data from a pregnant woman consuming contaminated soft cheese. We reevaluated risk based on dose‐response curves from pregnant rhesus monkeys and guinea pigs. Using standard risk assessment methodology including hazard identification, exposure assessment, hazard characterization, and risk characterization, risk was calculated based on the new dose‐response information. To compare models, we looked at mortality rate per serving at predicted doses ranging from 10^?4 to 10¹² L. monocytogenes cfu. Based on a serving of 10⁶ L. monocytogenes cfu, the primate model predicts a death rate of 5.9 × 10^?1 compared to the FDA/USDA/CDC (fig. IV‐12)^{( 1 )} predicted rate of 1.3 × 10^?7. Based on the guinea pig and primate models, the mortality rate calculated by the FDA/USDA/CDC^{( 1 )} is underestimated for this susceptible population.