Mechanistic Modeling of Emergency Events: Assessing the Impact of Hypothetical Releases of Anthrax

Abstract

A modular system for source-to-dose-to-effect modeling analysis has been developed based on the modeling environment for total risk studies (MENTOR),(1) and applied to study the impacts of hypothetical atmospheric releases of anthrax spores. The system, MENTOR-2E (MENTOR for Emergency Events), provides mechanistically consistent analysis of inhalation exposures for various release scenarios, while allowing consideration of specific susceptible subpopulations (such as the elderly) at the resolution of individual census tracts. The MENTOR-2E application presented here includes atmospheric dispersion modeling, statistically representative samples of individuals along with corresponding activity patterns, and population-based dosimetry modeling that accounts for activity and physiological variability. Two hypothetical release scenarios were simulated: a 100 g release of weaponized B. anthracis over a period of (a) one hour and (b) 10 hours, and the impact of these releases on population in the State of New Jersey was studied. Results were compared with those from simplified modeling of population dynamics (location, activities, etc.), and atmospheric dispersion of anthrax spores. The comparisons showed that in the two release scenarios simulated, each major approximation resulted in an overestimation of the number of probable infections by a factor of 5 to 10; these overestimations can have significant public health implications when preparing for and responding effectively to an actual release. This is in addition to uncertainties in dose-response modeling, which result in an additional factor of 5 to 10 variation in estimated casualties. The MENTOR-2E system has been developed in a modular fashion so that improvements in individual modules can be readily made without impacting the other modules, and provides a first step toward the development of models that can be used in supporting real-time decision making.

First Responder Knowledge and Training Needs for Bioterrorism

“…For outdoor releases of anthrax, the modeling performed in this study found similar results as the literature (Wein et al 2003;Isukapalli et al 2008). Based on the survey results, some evidence exists that participants underestimated the risk downwind and overestimated how far it transfers perpendicular to the wind.…”

Quantitative Models of the Dose-Response and Time Course of Inhalational Anthrax in Humans

“…Furthermore, without the full data set it is not possible to evaluate whether alternative dose-response models would have fit the data better than the log-probit model, which has been outperformed by other models in fitting other data sets [18]. Two studies [11], [15] applied a log-probit model based on the Jemski data to analyses of human exposure scenarios, although they applied ID 50  = 8,600 (the upper limit of the 95% confidence interval reported by Glassman).…”

“…ID estimates for age-dependent models rely on estimates of the age distribution of the United States population from the 2010 census. Criteria used to evaluate the models are 1) the parameter values are derived from dose-response data; 2) the shape of the dose-response curve is consistent with Sverdlovsk data; 3) the model is derived from mechanistic assumptions; and 4) the model estimates the incubation period.aPapers [11], [15] citing model J instead used ID 50  = 8,600, which is just within the 95% confidence limits reported in [26].bModels B2 and B3 estimate the time from exposure to infection take-off and death, but not the incubation period (time from exposure to onset of symptoms).cPapers [11], [15] citing model E1 instead used ID 50  = 8,600, which is within the range reported in the original paper.dFor model E5 , the original paper [32] estimated the time-dependent parameter θ from data and did not specify an estimate for r , but papers applying this model [11], [15] used the r value given above under an assumption of ID 50  = 8,600, comparable to other models based on expert opinion.…”

“…Reports of natural infections [3]–[6] and large scale accidental or intentional releases causing infections [7], [8] provide limited insight into the risk. To evaluate the threat posed by potential release scenarios, risk assessors, public health analysts, biodefense modelers, and other researchers require robust quantitative dose-response analyses to estimate the magnitude and timeline of potential consequences and the effect of public health intervention strategies [9]–[11], such as the administration of prophylactic antibiotic regimens to potentially exposed cases [12], and to interpret the significance of sampling results for detecting B. anthracis spores in indoor environments [13], [14]. For these analyses, it is particularly important to estimate the probability of infection after low dose exposures, which could cause the majority of cases after a large-scale release [15], [16].…”

Enhancement of ICRP's Lung Deposition Model for Pathogenic Bioaerosols

“…Development of risk models is considerably complicated, as factors such as the size of the city population and its distribution, wind speed and direction, aerosol characteristics, temperature and humidity, population distribution within age groups, lung deposition pattern, and types of prophylaxes (e.g., vaccines, protective medical devices such as respirators) used are all factors that should be considered (Isukapalli et al 2008). This article focuses on one critical aspect of risk assessment: deposition of bioaerosols in the lungs.…”