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#Plague Tracker Tool

#What It Does This tool lets you visualize how an infectious disease would spread through the population. It lets you tune some characteristics about the disease and the simulation, and then it will run a simulation against a dataset. Finally, it plots the results on a google map.

##How It Does It Microsoft released a dataset, called GeoLife GPS Trajectories, where users agreed to install an app which recorded their locations every few seconds. By using this, it basically lets us know where they were at every second of every day. Then, we can look at the locations of an infected person to see if they came in close proximity to another person. If so, we "infect" this other user, and then they too can spread the simulated infection.

###User Guide More information can be found in the report.pdf file.

####Description of Input Fields

  1. User id is the identification number representing a user. This number is unique per individual and is used to track users.

  2. Time When Infected is the time the user is believed to have become contagious with the virus. This is the time the tool will use as a starting point to locate the infected user and map out the other users who became infected as a result.

  3. Max Infection hops is the number of times a disease can hop to another user before it loses its efficacy. For example, user A is the infected person and comes in contact with user B (1st hop). User B then comes in contact with user C (2nd hop) and user C comes in contact with user D (3rd hop). The idea is that some diseases may mutate after hopping too many times, losing their deadliness. Most diseases don’t lose their efficacy though, and so a large value such as 10,000 should generally be entered.

  4. Infection proximity is the distance that 2 users need to get within each other in order for an infection to spread. This number varies by disease as some spread within close contact, while others have larger ranges due to being airborne.

  5. Incubation Time is the minimum amount of time that a user must carry the disease before they can spread it to other users. For example, some disease are not contagious until symptoms are shown, which may take hours or days. However, other diseases are instantly contagious, and so you could enter a value such as 0 minutes to simulate this.

  6. Limit Max Infected Users is an upper bound on how many users the simulation will infect. Because diseases can spread exponentially, there’s a possibility that the resulting map of infected users could be saturated with too many data points, making it unreadable. This parameter simply stops the simulation once this many users become infected.

  7. Simulation Duration is how long the simulation will run for. For example, if you entered a start time of 10am, Dec 1st for the originally infected user, and then entered 7 hours for the simulation duration, then when the simulation finishes running, the map presented to you depicts which users are infected with the disease, at 5pm Dec 1st (7 hours later).

After you submit the form and the app finishes computing the results, it presents a map, with a marker at each location where an infection spread to a new user. It also draws lines between users, which lets you see who infected whom. You can also click a marker, to see the userid of whom that marker represents.

####Quick Start If you enter userid 55, 66, or 888, the rest of the form fields will be ignored, and precomputed data will be plotted on the map instantly. If you want to see the app compute results in real time, you’ll need to enter a real userid and start time.

Some suggested values:
userid: 1
time: 2008-11-01T00:42:35
analysis duration: 00:10

You can also use Internal Data Exploration Tool to find other userids to enter. This is explained in the report.pdf file.

#####This was a group project for cmpe 272 at San Jose State University.
Authors: Amy Chou, Carita Ou, Chris Rehfeld, Liping Sun

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