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Revision as of 11:44, 13 October 2017
Vast2011 MC1: Characterization of an Epidemic Spread
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To be a Visual Detective
Contents
Overview
Smartpolis is a major metropolitan area with a population of approximately two million residents. During the last few days, health professionals at local hospitals have noticed a dramatic increase in reported illnesses. Observed symptoms are largely flulike and include fever, chills,sweats, aches and pains, fatigue, coughing, breathing difficulty, nausea and vomiting, diarrhea, and enlarged lymph nodes. More recently, there have been several deaths believed to be associated with the current outbreak. City officials fear a possible epidemic and are mobilizing emergency management resources to mitigate the impact. You have been charged with providing an assessment of the situation. We provide you with two datasets. The first one contains microblog messages collected from various devices with GPS capabilities. These devices include laptop computers, handheld computers, and cellular phones. The second one contains map information for the entire metropolitan area. The map dataset contains a satellite image with labeled highways, hospitals, important landmarks, and water bodies. We also provide supplemental tables for population statistics and observed weather data.
Task
Origin and Epidemic Spread
Identify approximately where the outbreak started on the map (ground zero location). Outline the affected area. Explain how you arrived at your conclusion.
Epidemic Spread
- Present a hypothesis on how the infection is being transmitted. For example, is the method of transmission person-to-person, airborne, waterborne, or something else? Identify the trends that support your hypothesis.
- Is the outbreak contained? Is it necessary for emergency management personnel to deploy treatment resources outside the affected area? Explain your reasoning.
Mini Challenge 1 Background
Before we start, what do you need to know?
1. The Gates
Based on the data description and reserve map, the restricted gates are highlighted in red.
2. The time
3. The Cars
4. The Visitors The visitors were segmented as follows based on the nature of their movements in the reserve.
The graph below shows the composition of each cluster by car types.
5. The Data
Timestamp: the date and time the sensor reading was taken
Car-id: the assigned car ID from the entry gate
Car-type: Vehicle type as enumerated above. “P” is appended when it is a park vehicle
Gate-name: name of the sensors taking the reading. See the map
6. The Reserve Map
