This project aims to model flu epidemic in the U.S during 2016-2017.
We have based our model on SIR model and we have tested our model with Graph Network simulation
The folder Code gathers all python code to simulate flu epidemic on Graph network episim.py simulates a random graph with a SIR model.
sir_comp.py and sir_subgraph.py is the code related to SIR Model.
- Data comes from https://www.cdc.gov/flu/, Center for disease control and prevention.
- The file WHO_NREVSS_Clinical_Labs_all_states.csv give the number of positive case of flu in each state during each week of 2016-2017
- The file dataView2065_3.csv give the vaccinetad ratio in each states.
- Data comes from https://snap.stanford.edu/data/higgs-twitter.html.
The Higgs dataset has been built after monitoring the spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. The messages posted in Twitter about this discovery between 1st and 7th July 2012 are considered.