1. Smallpox Martyr Bio-terrorism Modeling in Python Joe Fetsch Computer Systems Lab 2010

2. Purpose What is the danger now? Isn't smallpox gone forever?

3. Explanation of Purpose Ok, so what are you doing to help?

4. Scenario How are the terrorists going to attack?

5. Scenario, Cont'd How will people react to that? Why is that such a danger?

6. Scenario Cont'd But that can't cause too many problems, right? How could that possibly get worse?

7. Scenario Cont'd But it's not over yet...

8. Scenario Cont'd And it still gets worse.

9. Other Projects Government simulations involving smallpox exist, and government simulations involving quarantines and vaccination exist, but not both at the same time.

10. 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

11. Smallpox Much research was done to fully understand the Variola virus in all forms and its effects on a population Child suffering from Smallpox

12. 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

13. Agent Movement Ignorance and randomness

14. World Structure Social Model Effects on rate of infection Agents with few others near them

15. 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

16. 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

17. 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

18. 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

19. Still unknown: Vaccination is unlikely The chaos in the city would negate military assistance for some time Speculation

20. Simulations Several different times of initiation for vaccine and quarantine are used to account for several different possible scenarios.

21. 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

23. Quarantine The quarantine simulation shows a world in which a military quarantine has isolated everyone from each other.

24. 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.

25. 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%.

26. 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.

27. Before the Quarantine

28. 40 Days After Quarantine

29. 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%)

30. Vaccine The vaccine simulation shows a mass distribution of immunizations to the smallpox virus.

31. 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.

32. 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.

33. Ring Vaccination While 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.

34. Before Vaccination

35. After Vaccination

36. 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%)

37. 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.

38. 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.