Repository to accompany the blog series: Epidemic Modeling
These blog posts were recently featured in the Data Exchange Podcast by Ben Lorica in two episodes:
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Computational Models and Simulations of Epidemic Infectious Diseases
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Assessing Models and Simulations of Epidemic Infectious Diseases
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Epidemiology002.ipynb - Visualizing individual CoVID-19 patient data
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Epidemiology003.ipynb - CoVID-19: Forecasting the death toll
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Epidemiology101.ipynb - Epidemic Modeling 101: Or why your CoVID19 exponential fits are wrong
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Epidemiology102.ipynb - Epidemic Modeling 102: All CoVID-19 models are wrong, but some are useful
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Epidemiology103.ipynb - Epidemic Modeling 103: Adding confidence intervals and stochastic effects to your CoVID-19 Models
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Epidemiology104.ipynb - Epidemic Modeling 104: Impact of Seasonal effects on CoVID-19
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Epidemiology105.ipynb - Epidemic Modeling 105: Competing CoVID-19 Strains
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Epidemiology 201.ipynb - Epidemiology 201: Network Structure, Super-spreaders and Contact Tracing\
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Epidemiology 202.ipynb - Epidemiology 202: Network Models, the effect of degree correlations
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Jupyter notebook includes all the code used to generate the figures in the blog posts. Run the code online using
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EpiModel.py - Python module encapsulates all the code necessary to numerically implement arbitrary compartmental epidemic models
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NetworkEpiModel.py - Python module encapsulates all the code necessary to numerically implement arbitrary epidemic models on networks
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