Multimodal Transportation and Bioterrorism Defense

Welcome to the NSF Multimodal Transportation and Bioterrorism Defense Website
at Embry-Riddle Aeronautical University in Prescott Arizona.  Our modern transportation networks are complex and intermodal, involving combinations of automobiles, buses, airplanes, and light and heavy rail.  Today's transportation managers and public policy makers require both strong intuition and operational knowledge to prepare for and respond to bioterrorism attacks on this critical infrastructure.

This website provides an interactive model for understanding intermodal transportation networks and determining patterns for travelers subjected to a bioterrorism release. Using these tools, people will acquire knowledge relating to a variety of modes of transportation and understand some of the differing characteristics of the vehicles that serve these important terminals, stations, and depots. This model is the key to grasping the gravity of the bioterrorism threat in our society. Furthermore, the model will help people comprehend interrelationships between the different modes of transportation and related critical security concerns.

The initial version of this website is a step toward helping people synthesize a variety of data relating to human biology, transportation systems, public administration, and emergency response. With further experience, people will operationalize the knowledge gained in order to determine preventative strategies and implement corrective actions.


Given realistic data people will be able to choose a scenario corresponding to a transportation hub.  Then a generic pathogen with typical lethality, incubation time, and contagiousness, along with a transporter or terminal, and time for releasing the pathogen needs to be selected to simulate the attack of the pathogen on the passengers in that particular transporter or terminal.  People will be able to navigate through a 6 day schedule of trips according to the frequency of the given scenario, viewing the target trip and effects of the attack in context.


Go directly to load the applet (Java required) or read the instructions below.


Please report any difficulties, suggestions, or praise to Robin.Sobotta@erau.edu.

Definition of Bioterrorism:

1. The unlawful release of biologic agents or toxins with the intent to intimidate or coerce a government or civilian population to further political or social objectives. Humans, animals, and plants are often targets. 2. Use of microorganisms or toxins to kill or sicken people, animals or plants. The main difference between biological terrorism and conventional terrorism (i.e. bombs, hijackings, etc.) is the duration from the time of attack to the presentation of victims of the attack. Depending on the agent, the incubation period can be up to 60 days. It is highly probable that hospitals, not traditional first responders, will be the first to recognize a bioterrorism event secondary to the unfolding epidemiology and gradual increase in attack rates of a communicable agent.
www.ben.edu/semp/htmlpages/glossaryb1.html

Terrorism using deadly bacteria or virus.
www.knowconflict.com/Impact_of_Terrorv110/glossary.html

Homeland Security's description of a biological attack, mentions different methods of delivery (modes of transport even) and the spread of disease based on travel,
http://midlifementor.com/newsletters/issue26.html

MMBT User's Guide:


• Introduction
• Definition of Bioterrorism
  
• Background/Purpose
• Getting Started
• Layout
• Settings
• Making Selections
• Scenario Choices
• Pathogen Choices
• Time to Release Pathogen
• Transporter Choices
• Creating the Schedule
• Releasing the Pathogen
• Interpreting the Results
• MMBT Model and Visualization
  

MMBT Model and Visualization:

• The MMBT Model and Visualization
• Computation
• Transporter Scheduling
• Passenger Assignment
• Arrivals
  • Local: (from auto, bus, light/heavy rail)
  • Remote:
• Departures
  • Local
  • Remote
• Attack
• Visualization
  • Data Tables
  • Pathogen
  • Transportation Information
  • Transportation Frequency
    
  • Schedule Tree
  • Region Graphic
    

Getting Started if your browser doesn't run Java
If using Microsoft Internet Explorer, to run this demonstration and interact with the model, you will need a Java-enabled browser.  To determine if your browser is Java-enabled, go to Tools, Internet Options, Advanced, and scroll down until you locate the Microsoft VM section.  If 'Java console enabled' is not selected, please select it and restart your computer for it to take affect.

If it is already selected and you are still unable to view our model,  download the Java runtime environment that will enable you to view it properly.  When installing it, please make sure to select it as your default Java console for Microsoft Internet Explorer, Netscape, and Mozilla to ensure success.

Netscape and Opera browsers should already be enabled with a Sun Microsystems Java console.  If one is not present or if the page still cannot be viewed, the problem may be due to a firewall or security policies.  Please contact your system administrator on how to fix this problem.

Layout
The design of the Multimodal Transportation and Bioterrorism Defense (MMBT) Model is a Border Layout with NORTH, SOUTH, EAST, WEST, and CENTER regions:

The layout for the MMBT model is as follows:

• NORTH - Contains the settings for the following:

• <>Tabbed scenarios (left panel) with a tree of  Transporters for traffic in each scenario
  
• Buttons in center panel to Create Schedules for selected scenario and to Release Pathogen selected in right panel
• Pathogen selection in right panel + time of release + transporter selected from scenario tree

Computation

The underlying model replicates the behavior of realistic transportation hubs using the data in the tables at the bottom of the applet.  Time progresses from 0 minutes to (default) 6 days with the following actions simulated  at time t:

return to top


Transporter Scheduling

Hubs have four levels of frequency - NON, SMALL, MEDIUM, LARGE - associated with frequency of transporters and types of transporters serviced.  Each transporter has a frequency, such as 5 per minute, or every 4 hours. In each schedule, an instance of each transporter is created at the appropriate times from the frequency table  and the selected scenario. The duration of the transporter's journey is calculated from its SPEED and AVG_HAUL.  Arrival locations are randomly generated (i.e. the model does not simulate a geographically based system).  Passengers are included in one of five categories - ARRIVING, GREETING, WAITING, LEAVING, EXITED.  For more information, on the different categories, click here.


Passenger Assignment

Each transporter has a passenger load calculated from the transporter's LOAD_FACTOR and CAPACITY.


Arrivals

Passengers are "created" to fill each transporter.


Local: (from auto, bus, light/heavy rail)

Remote:

• Arriving passengers become ARRIVING.
• Each arriving passenger has a meeter/greeter selected from the current WAITING . Locals who have been in WAITING for more than 30 minutes are randomly selected to become GREETING

Departures

Local

Transporters are filled from two equal divisions

• passengers who have been in ARRIVING for more than 60 minutes
• locals who have been in GREETING for more than 30 minutes
These passengers become LEAVING_TO_LOCAL for the duration of their local journey, say n minutes, and then become EXITTED_LOCAL at time t+n.


Remote

Passengers who have been in WAITING for more than 60 minutes are randomly selected to fill each transporter. Those selected become LEAVING_TO_REMOTE for the duration of the aircraft journey, say n minutes, then become EXITTED_REMOTE at time t+n.


Attack

A pathogen attack consists of

• an identified transporter (type)
• a release time
• an identified pathogen
The next available transporter scheduled to depart after the release time becomes the target transporter. Each transporter has a number of passengers calculated from its CAPACITY and  hub's LOAD_FACTOR. All passengers are considered EXPOSED from time of release until end of the INCUBATION after which the pathogen's  LETHALITY determines the number of FATALITIES and SURVIVORS.


Visualization

Data Tables


Pathogen

• Name (A,B,C,D,E)  for reference in attack.
• Incubation: days  from exposure until symptoms manifest
• Lethality % of exposures that result in death. Assumption: there is no period of  sickness,  with incubation ending in either death or survival)
• Contagious (yes/no) a fact indicating the potential spread of the pathogen's disease (not represented in the model)
  

Transporter Information
The transporter information table includes information pertaining to the mode of transportation (aircraft, bus, rail, etc.),  the type of transportation (aircraft - widebody, narrowbody, regional jet, etc.), the specific name of each transport (wb550, nb150, local auto, etc.), as well as the range, speed, capacity, and average haul of each transporter.

Transporter Frequencies (Hub characteristics)
The transporter frequency table includes information pertaining to name of the transporter (see above), and its load factor.  The transporter's LOAD_FACTOR determines how full the transporters will be while traveling.  The default is at 70 per cent of all transporter's max capacity. When customization becomes available LOAD_FACTOR in one of the features that will be editable, as well as the frequencies of the transporters leaving the terminal.  Frequency of the transporters are in the form "every X hours" or "X per day", with X being a set number.


Schedule Tree



The tree provides a hierarchical view of the passenger assignments and pathogen attacks over the time of the simulation divided into DAY, HOUR, 10 MINUTES. Text at each node of the tree condenses the status of the passengers at the end of the time period:

Terminal

• number currently WAITING (arrived on local transporters)
• number designated as GREETING (arrived on local transporters, randomly selected to match an ARRIVING passenger)
• number currently ARRIVING (from remote transporters, not yet transported to local destinations)
Enroute

• local, assigned to a local transporter, either scheduled (bus, rail, subway) or a local auto
• remote, assigned to a transporter headed to a location beyond the terminal and its local area
Exitted
• local, arrived at a local destination
• remote, arrived at a remote location
Pathogen status
• Summary of number exposed and fatalities/survivors relative to release time and incubation period of a pathogen used in an attack
• Description of the pathogen, if the release is occurring during the time period covered by the node

Region Graphic



Transporters leave a point of origin (terminal) at location(0,0) to remote locations randomly selected at the correct distance for the transporter's speed and avg_haul. This produces concentric circles with randomly distributed points. Each point has a color associated with a particular type of transporter (see the Transporter Information Table).  The transporter circles and points change as the schedule progresses, shown by clicking different nodes or using the up/down arrow to "walk" the tree.



Each state represents the cumulative distribution of all transporters left the terminal to the point of time (determined by the tree node, shown in the upper left of the graphic). The region's radius (about 4000mi) is also shown in the upper left corner. Boxes represent flights in progress or ending at the end time, while gray circles represent completed flights.

Attacks are shown by:

• a solid, red box that tracks the progress of the target transporter (where the pathogen was released)

• a yellow arrow tracks the progress of the pathogen's incubation period toward a yellow box indicating the end of incubation and time of effect (when exposed passengers will expire or survive)

• a red, square outline depicts a pathogen attack at the terminal - in the future if the terminal is attacked, all transporters leaving the terminal after the point of attack will all be red.
  

Copyright Notice: The content of this module and all associated materials are Copyright (c) 2004, Susan Gerhart, Robin Sobotta, Lawrence Gesell, Kelley Harbin, except otherwise noted. For information on distribution permission and requirements, please contact Dr. Susan Gerhart at gerharts@erau.edu.

Contacts: Questions, comments, or feedback to Dr. Susan Gerhart.  Authors: Dr. Susan Gerhart, Dr. Robin Sobotta, Dr. Lawrence Gesell, and student Kelley Harbin.

Background reading: For a good background reading on Bioterrorism, read "2002 Bioterrorism After the Anthrax Attacks: Complete Revised Guide to Biological Weapons and Germ Warfare" published by the U.S. Government or "21st Century Complete Guide tp Bioterrorism, Biological and Chemical Weapons, Germs and Germ Warfare, Nuclear and Radiation Terrorism" also published by the US Government.