"An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem."
-John Tukey
SEIR Model applied for SARS-Covid2
This new purpose is a modification of a already existing model known as SEIR. This acronym stands for Susceptible, Exposed, Infected and Recovered. The differential equation system is shown below:
The following link is to download a copy of the SEIR code for python, this model allows you to modify the multiple parameters and graph the results.
SEIR vs SEIQRDC
epidemiology model
The past April 13, Xavier Rodó and Leonardo López published a paper modifying the SEIR model and expand it to a SEIORDC model, in this particular model the factors: Quarantined, Confinement and Death calculation. This modifications allows to analyze other parameters that explain even more the pandemy dynamic. The model purpose is shown below:
The purpose of the code (Python) built, is to download th update data of any country across de world, extract the data (total cases and total deaths) ir order to make modification in some of the coefficients shown before in order to fit the model to the downloaded data.
The following link is to download a copy of the SEIQRDC code for python, this model allows you to modify the multiple parameters and graph the results.
Whats is next?
The purpose of the written code is to download the up-to-date data of any country and estimated the 4 parameters explaind before, for this model fitting models will be used, like the gaussian approach.
References
A MODIFIED SEIR MODEL TO PREDICT THE COVID-19 OUTBREAK IN SPAIN AND ITALY: SIMULATING CONTROL SCENARIOS AND MULTI-SCALE EPIDEMICS, López, L; Rodó, X. (April 13,2020)