Streamlit app which helps you calculate the effect of lockdown in the wake of CoViD-19 (Corona) virus pandemic
The webapp was created with a single SEIR function, which is useful for early days but does not represent well when a dynamic and varying degree of social distancing and vaccinations are in place. A sum of multiple SEIR functions with a range of parameters, either learned or obtained from a fit to observed data may give a better estimate. Here is the source code, use it the way you like to improve it :)
- You can move the contacts slider to see the affect of reduced interaction on total infection and critical case numbers.
- You can see how under resourced the country is in terms of ICUs.
- In the sidebar choose the lockdown date (or any date if you want a short term windowed analysis).
- Chart shows the "Expected" infections from the SIR model and real world "Confirmed" infections.
- Move the slider so that the circles for Expected and Confirmed come as close as possible to eachother (I will later replace this with curve_fit).
- The value will automatically be transferred to the main UI window "Contacts" slider.
- Italy's original (before lockdown),the number for contacts was ~19 (compare how this compares with the number of "Contacts" after lockdown)
- Now move the "Contacts" slider on the main UI page to estimate how long this may last and how many can get critically ill.
- Be safe everyone.
The app is using data from John Hopkins University's public repository.
Here is my article on medium that uses this repository: https://diwaker-phd.medium.com/how-long-will-the-corona-lockdown-last-8f23ef1730aa
I was inspired from these repositories:
https://github.com/YiranJing/Coronavirus-Epidemic-COVID-19
https://github.com/pdtyreus/coronavirus-ds
https://github.com/CSSEGISandData/COVID-19
https://github.com/amtam0/coronavirus-world-map
and more snippets from stackoverflow and streamlit docs.