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A package which can compute the spread of a disease in a population

Project description

DEMICESTIMATOR

Introduction

This package contains standalone code for computing data of any epidemic through various Epidemic Models (SIR, SEIR etc) . The data can be further used for studying, graphing, stimulating and predicting the spread of any epidemic.

SIR Model: A simple mathematical description of the spread of a disease in a population is the so-called SIR model, which divides the (fixed) population of N individuals into three "compartments" which may vary as a function of time.

SEIR Model: For many important infections, there is a significant incubation period during which individuals have been infected but are not yet infectious themselves. During this period the individual is in compartment E (for exposed). This is where SEIR model is used.

For The Users

The package can be installed via:

pip install epidemic_estimator

The package can be used to call the functions of available Epidemic Models

Example for SIR Model

import demicestimator as de
de.sir_model(0.5,1/4,1000,0,1,160)
print(de.sir_df)

Here you can call the function for SIR model using ee.sir_model()

Parameters:

  • Effective contact Rate
  • Recovery Rate
  • Total population
  • Recovered
  • Infected
  • No. Of Days

Probable Epidemic Data is computed from the code above which can be used to plot graph, create stimulation and so on.

Updates

Further updates with support for other models like SEIR and SIS is coming soon.

License

MIT

Project details


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