Seeker Blog

This is the sixth post in the SeekerBlog Homeland Security series. Click here for the complete set.

Scientific American published the "virtual epidemiology" research of Barrett, Eubank and Smith in the March 2005 Issue: "If Smallpox Strikes Portland" (subscription required).

Suppose terrorists were to release plague in Chicago, and health officials, faced with limited resources and personnel, had to quickly choose the most effective response. Would mass administration of antibiotics be the best way to halt an outbreak? Or mass quarantines? What if a chance to nip a global influenza pandemic in the bud meant sending national stockpiles of antiviral drugs to Asia where a deadly new flu strain was said to be emerging? If the strategy succeeded, a worldwide crisis would be averted; if it failed, the donor countries would be left with less protection.

Public health officials have to make choices that could mean life or death for thousands, even millions, of people, as well as massive economic and social disruption. And history offers them only a rough guide. Methods that eradicated smallpox in African villages in the 1970s, for example, might not be the most effective tactics against smallpox released in a U.S. city in the 21st century. To identify the best responses under a variety of conditions in advance of disasters, health officials need a laboratory where "what if" scenarios can be tested as realistically as possible. That is why our group at Los Alamos National Laboratory (LANL) set out to build EpiSims, the largest individual-based epidemiology simulation model ever created.

The EpiSims project has reached the stage where their social network modeling is producing useful policy input. In particular, this report on a simulated smallpox attack on Portland, Oregon is fascinating. How should cities prepare for such an attack? What are the most effective strategies once a pathogen like smallpox is detected? Is mass vaccination a good policy? What about mass quarantine? How does the response-time of the health authorities affect the death toll?

As you can see from the above summary graphic of the EpiSims simulation, we learned that the most effective strategy is rapid isolation of infected individuals. Next in importance was the speed of public health response. Variations in the vaccination response strategies had little effect on the death toll.

A brief sketch of the simulation parameters:

To answer such questions, we constructed a model of smallpox that we could release into our synthetic population. Smallpox transmission was particularly difficult to model because the virus has not infected humans since its eradication in the 1970s. Most experts agree, though, that the virus normally requires significant physical contact with an infectious person or contaminated object. The disease has an average incubation period of approximately 10 days before flulike symptoms begin appearing, followed by skin rash. Victims are contagious once symptoms have appeared and possibly for a short time before they develop fever. Untreated, some 30 percent of those infected would die, but the rest would recover and be immune to reinfection.

Vaccination before exposure or within four days of infection can stop smallpox from developing. We assumed in all our simulations that health workers and people charged with tracking down the contacts of infected people had already been vaccinated and thus were immune. Unlike many epidemiological models, our realistic simulation also ensures that the chronology of contacts will be considered. If Ann contracted the disease, she could not infect her co-worker Bob a week earlier. Or, if Ann does infect Bob after she herself becomes infected and if Bob in turn infects his family member Cathy, the infection cannot pass from Ann to Cathy in less than twice the minimum incubation period between disease exposure and becoming contagious.

With our disease model established and everyone in our synthetic population assigned an immune status, we simulated the release of smallpox in several hub locations around the city, including a university campus. Initially, 1,200 people were unwittingly infected, and within hours they had moved throughout the city, going about their normal activities. We then simulated several types of official responses, including mass vaccination of the city’s population or contact tracing of exposed individuals and their contacts who could then be targeted for vaccination and quarantine. Finally, we simulated no response at all for the purpose of comparison. In each of these circumstances, we also simulated delays of four, seven and 10 days in implementing the response after the first victims became known. In addition, we allowed infected individuals to isolate themselves by withdrawing to their homes.

For the in-depth report, please see the captioned article, and for more details, refer to the Los Alamos National Laboratory site: "Controlling smallpox: Strategies in a Virtual City Built from Empirical Data". If you have broadband, the site offers a 250MB movie file showing an animation of the model results, at 6 frames per day at 4 hour intervals for 70 days. (The vertical bars displayed on a Portland map represent the number infected at each location, and the color represents the fraction of infected people who are infectious.)