S IMULATION OF THE S PREAD OF A V IRUS T HROUGHOUT I NTERACTING P OPULATIONS WITH V ARYING L EVELS AND T ARGETS OF V ACCINATION Jack DeWeese Computer Systems Lab,

A BSTRACT The project’s aim is to go beyond the traditional agent- based model of virus simulation. Factors such as time of day, profession, age, population density, length of time for infection, and even hospitals will be part of the model. With the completion of a working model, virus vaccinations can be modeled to determine the best and most efficient methods of curbing/stopping the spread of the virus.

B ACKGROUND During my research I came across a virus simulation which modeled time of day and people going to work each day, and after contacting the programmer, I began working off of this code in order to have more time to work on advancing the model to reach my original goals.

R ESEARCH My research is composed of primarily two categories: Factual information on different viruses (in order to properly implement them) and research on other virus simulations to gather ideas on what worked and what did not work for different programmers. The main viruses I am currently focused on are smallpox, influenza, and the common cold.

R ESEARCH ( CONT.) Airplanes will not be modeled due to research suggesting they are not as “infectious” as commonly believed because of their filtration systems. Schools will be modeled because they do pose a higher risk of infection than normal because of the “concentration” of children.

P ROJECT D EVELOPMENT My project creates a population varying in age and profession, and a “habitat” for them to have houses, workplaces, schools, and hospitals. There is a day schedule (weekends are not accounted for) by which the agents go to work (or school depending on their age), and if they are currently infected, they make a pseudo-random decision to stay home or not. Infection spreads in the homes, offices, hospitals, and schools.

T ESTING AND A NALYSIS My preliminary results are promising; the model is of course fully-functional, and has implemented many of the functions I had aimed to implement into it. I am currently working on testing various viruses and then changing the population density (by increasing the size of the population, without increasing the size of the habitat accordingly).

R ESULTS The vaccination modeling aspect of my program is the final step and is what makes the model applicable to real-life scenarios. Because I the model has significantly more detail than a more basic agent-based model, or a model that uses differential equations, the results are more precise for the behavior of the virus and its reaction to the vaccine.

The above picture shows a low-density population with a virus that has a long (i.e. greater than 10 days) infection period, in which it can spread the virus. This model includes hospitals, but not the age display.

The above picture shows a high-density population with a virus that has a long (i.e greater than 10 days) infection period, in which it can spread the virus. This model includes hospitals, but not the age display. Note that the virus travels to a much greater portion of the population (and while it cannot be seen from the screenshot, it has occurred in a much shorter timeframe).