Smallpox Martyr Bio-terrorism Modeling in Python
Joe Fetsch
Computer Systems Lab 2010
Purpose
What is the danger now? Isn't smallpox gone forever?
Explanation of Purpose
Ok, so what are you doing to help?
Scenario
How are the terrorists going to attack?
Scenario, Cont'd
How will people react to that?
Why is that such a danger?
Scenario Cont'd
But that can't cause too many problems, right?
How could that possibly get worse?
Scenario Cont'd
But it's not over yet...
Scenario Cont'd
And it still gets worse.
Other Projects
Government simulations involving smallpox exist, and government simulations involving quarantines and vaccination exist, but not
both at the same time.
NetLogo Use
NetLogo was used to develop a basic understanding of the disease modeling system, but will not be used to create the smallpox model
NetLogo Virus Model
Smallpox
Much research was done to fully understand the Variola virus in all forms and its effects on a population
Child suffering from Smallpox
Each dot represents an Agent
Project Structure The infection, after
Prodrome phase, will then progress into a more mature phase:
Ordinary Modified Malignant Hemorrhaging Confluent
Agent Movement
Agent Movement Ignorance and randomness
World Structure
• Social Model • Effects on rate of infection
• Agents with few others near them
Visual Representation
Green agents are healthy
Yellow agents are in early stage where not contagious or visible
Orange agents are in the prodromal phase, exhibiting flu symptoms
Red agents are infected, contagious and visible
Blue agents are immune
Sugarscape-based model
Timeline
Research Smallpox to understand disease in order to better implement in program
Using NetLogo, obtained a basic understanding of the model of infection
Using Python, created basic model
Timeline
• Developed a model for infection, hoping to clarify my values and prove them accurate with past data
• Modeled fatality rates
• Implemented quarantine and vaccination possibilities
Testing
Simulation has begun, average fatality rate in a city around 35-40%
Man suffering from hemorrhagic smallpox also known as black pox – 100% fatal
Still unknown:• Vaccination is unlikely
• The chaos in the city would negate military assistance for some time
• Speculation
Simulations
• Several different times of initiation for vaccine and quarantine are used to account for several different possible scenarios.
Testing
• Fatality rates are between 35 and 40%
• All agents become infected within 6 or 7 months
• 90% of agents become infected within 4 and a half months
• The graph on the next page shows the results of many unhampered tests, showing the population statuses over time
Quarantine
• The quarantine simulation shows a world in which a military quarantine has isolated everyone from each other.
Quarantine
• The visual representation stops moving, yet diseased agents continue to progress.
• The line graph shows a red line at the time at which the quarantine begins.
Description of the graph
In the graph above, the population of the city has gone from 5000, the initial value, to 4052; a fatality rate of 20%. However, the population in this situation has been quarantined after two months of the simulation, while the rate of infection was still increasing, which would lead to many more cases of smallpox and many more fatalities. Throughout the simulation, about half of the agents became infected, which raises the relative fatality rate to slightly less than 40%.
Quarantine Results
In the following slides, the results from calculating several possible outcome times (30 days, 45 days, 60 days, and 75 days) ran 6 times to prevent outliers from significantly affecting the results are shown.
The results before show the world immediately before the quarantine, and the results after show the world 40 days after, long enough to ensure that the remaining infected agents will survive for the remainder of the simulation.
Therefore, the infected agents will be labeled immune.
Before the Quarantine
30 45 60 750%
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deadimmuneinfectedprodromecarriershealthy
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40 Days After Quarantine
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Beginning of Quarantine: Days after attack
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Fatality/Infection Rates
The fatality rates for quarantine simulations:
30 days: 102 (2%) 45 days: 350 (7%) 60 days: 643 (13%) 75 days: 992 (20%)
The infection rates for the simulations:
30 days: 279 (6%) 45 days: 995 (20%) 60 days: 1766 (35%) 75 days: 2698 (54%)
Vaccine
The vaccine simulation shows a mass distribution of immunizations to the smallpox virus.
Vaccine
The visual representation continues moving, and diseased agents continue to progress.
The line graph shows a green line at the time at which the vaccine is distributed.
Vaccine Results
In the following slides, the results from calculating several possible outcome times (60 days, 75 days, 90 days, and 105 days) ran 6 times to prevent outliers from significantly affecting the results are shown.
The results before show the world immediately before the vaccination, and the results after show the world 40 days after, long enough to ensure that the remaining infected agents will survive for the remainder of the simulation.
Therefore, the infected agents will be labeled immune.
Ring VaccinationWhile ring vaccination has been successfully used
before to prevent the spread of smallpox, a mass vaccination method is required because of the nature of the first infection:
Because starting points for the infection are
1) spread out over a large area inside one city
and
2) at major transit locations (airports, etc)
The possibility to confine the infectious people before they spread it further is very low.
Before Vaccination
60 75 90 1050%
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deadimmuneinfectedprodromecarriershealthy
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After Vaccination
60 75 90 1050%
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deadimmune
Beginning of Vaccination: Days after attack
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Fatality Rates
The fatality rates for the vaccine simulations:
60 days: 540 (11%) 75 days: 991 (20%) 90 days: 1247 (25%) 105 days: 1396 (28%)
The infection rates for the simulations:
60 days: 1747 (35%) 75 days: 2951 (59%) 90 days: 3873 (77%) 105 days: 3991 (80%)
Conclusions
Obviously, the earlier a vaccine is developed or the earlier a quarantine is implemented, the more lives can be saved.
However, this possibility for saving lives must be weighed against the moral considerations of confining people who may or may not want to be confined.
We all know that there are going to be the outliers who complain about being held against their will... that's why I simulated the vaccine.
To Be Continued...
If further work was to be done, more data could be gathered to create a more accurate and less choppy graph of the expected results of the experiment
Without taking real-life data (about five kinds of illegal), very little information exists as to how the disease actually spreads, and in order to create a more specific scenario (school, etc), much more understanding is required.