# Model of Disease Propagation to Predict the Speed of an Outbreak**Team:** 6
**School:** Albuquerque Academy
**Area of Science:** Medicine and Computer Science
**Interim:**
1. Definition of the Problem
Influenza is an infectious disease that spreads through a population via minscule droplets of infected saliva that are released from the infected person’s mouth and nose. This means that it can be spread from a distance, so it can be easily and rapidly transported from one person to the next. Influenza can be dangerous when it gets out of hand, and in some cases deadly. A way to predict the speed and scale of an outbreak would help medical authorities be prepared for an outbreak with sufficient materials and an idea of how long it could take for the virus to go out of control.
2. Plan for Computationally Solving the Problem
We have chosen to investigate the propagation of a disease. We will accomplish this using computer modeling to predict how fast a disease will propagate through a selected region. This is important because areas that are prone to disease can know how to prepare for potential outbreaks with the most effective measures. We plan to model this problem as effectively as possible. We will create this model using C++, with numerous variables to show how fast the virus will spread. We will complete our task by dividing the work equally and using medical data on previous outbreaks, population and transportation maps, and information on how the disease spreads to create a mathematical model, then a full-fledged program. Our program will utilize an Agent-based modeling system with multiple Agents each representing a person. These Agents will move on a semi random path over a grid. When two or more Agents, of which one at least is infected, are within a suitable distance of each other, the program will use each Agent’s properties to calculate the likelihood of the uninfected Agent catching influenza from the infected Agent. These properties will include immunity and the amount of time an infected Agent will take to get well, among others.
3. Description of the Progress Made to Date
Presently, an initial C++ OpenGL virus predictor has successfully been created. This code contains an Agent Factory where each Agent is an instance of a C++ struct. A mock-up database of Agents is read into each Agent's struct from an ASCII flat file that was created. Initial condition attributes utilized within the C++ code for each Agent include the following: name, contagious (yes/no), normalized latitude and longitude coordinates, health (1-10), and time-to-get-well. The attribute not yet used is travel, however currently a random number generator is independently used to model the movement of each Agent at each time iteration. When the program starts, the mock-up database is read and Agents are created with their initial conditions and their Lat/Lon positions are displayed in a normalized coordinate plane within an OpenGL window. Infected Agents are red symbols and healthy Agents are green. As the simulation runs, the Agents' positions are visually displayed as red or green symbols. Each simulation step is in the milliseconds and each Agent can move only a few steps. At each increment of time an infected Agent may move and touch (or get close to) a healthy Agent, when that occurs, the health of the healthy Agent goes down. When an Agent's health is zero, it gets infected. Each Agent has their own stop watch where after a period of time they get well. No consideration has been given yet to Agents who do not survive. During this simulation, Agents can be seen moving around the OpenGL window, some of which are infected (red), others which are healthy (green).
Other progress attained is the identification of raw data which was downloaded in ASCII file format containing Influenza Virus Databases from the Center for Disease Control and Prevention (CDC) and the Influenza Research Database (IRD) [Squires et al. (2012) Influenza research database: an integrated bioinformatics resource for influenza research and surveillance. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750-2659.2011.00331.x. ] The raw data obtained was entered into the database on a weekly basis. This is the granularity of updates observed so far. This initial data has been compiled and converted into Microsoft Excel plots for initial analysis. Additionally, we have identified data on transportation. This may be used to determine where an Agent may travel. Our mathematical model is currently under progress, and is waiting for the data to be compiled. It will calculate the probability of infected Agents spreading their infection.
4. Expected Results
The goal of this project is to create a rule based mathematical model of the spread of disease through a community. The program will use an Agent based modeling system to determine the likelihood of each Agent’s infection, and model the spread from Agent to Agent over a certain amount of time using the probabilities we have calculated. It would then be able to state how many Agents have become infected after a certain amount of time has passed. We expect, when our efforts are compiled and amalgamated into a final result, a functional program should predict an outbreak of influenza within a given error. It will output using symbols on a graphical display, with colors to represent their state of infection. The program will utilize medical information about influenza, as well as data on past epidemics and travel data. It will use a mathematical model to determine the probability of infected Agents infecting uninfected Agents.
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6. Team Members:
Dylan Hendrickson, Marcus Dominguez-Kuhne, Craig Short, Maxwell Johnson
7. Sponsoring Teacher:
Mr. Jim Mims.
**Team Members:**
Max Johnson Marcus Dominguez-Kuhne Dylan Hendrickson Craig Short
**Sponsoring Teacher:** Jim Mims
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