calculate_ifr_from_prevalence_streamlit.py

# Berekenen van percentage vd bevolking dat COVID heeft gehad adh van de prevalentie
# Tevens berekening van IFR
# René Smit, 18 april 2021 - MIT License

# Oorspronkelijke code door Guido Smeets
# https://twitter.com/Guido_Smeets/status/1383784146972004359

from tabulate import tabulate
import pandas as pd
import streamlit as st
from helpers import select_period_input, select_period

def main():
    url = "https://data.rivm.nl/covid-19/COVID-19_prevalentie.json"
    df = pd.read_json(url)

    df = select_period(df, "Date")

    inhabitants = (st.sidebar.number_input('Total population', 17_483_471))

    days = (st.sidebar.number_input('Number of days contagious', None,None, 8))

    deaths = (st.sidebar.number_input('Number of deaths', None,None, 30_000))




    df["prev_low_cum"] = df["prev_low"].cumsum()
    df["prev_up_cum"] = df["prev_up"].cumsum()
    df["prev_avg_cum"] = df["prev_avg"].cumsum()

    number_low = round(df["prev_low_cum"].max() / days )
    number_avg = round(df["prev_avg_cum"].max() / days)
    number_up =  round(df["prev_up_cum"].max() / days)

    perc_low = round((df["prev_low_cum"].max() / days ) / inhabitants * 100,4)
    perc_avg = round((df["prev_avg_cum"].max() / days) / inhabitants * 100,4)
    perc_up = round( (df["prev_up_cum"].max() / days) / inhabitants * 100,4)



    ifr_low = round(deaths / (df["prev_low_cum"].max() /days) * 100,4)
    ifr_avg = round(deaths / (df["prev_avg_cum"].max() /days) * 100,4)
    ifr_up = round(deaths / (df["prev_up_cum"].max() /days) * 100,4)

    st.subheader("Aantal COVID besmettingen en IFR berekening")
    st.write("Berekenen van percentage vd bevolking dat COVID heeft gehad adh van de prevalentie vanaf 17 februari 2020 zoals gemeld in https://data.rivm.nl/covid-19/COVID-19_prevalentie.json")
    st.write("De cummulatieve prevelantie wordt gedeeld door het aantal dagen dat men gemiddeld besmettelijk is (instelbaar in het linkermenu)")
    st.write("Tevens berekening van IFR (aantal overledenen instelbaar in het linkermenu)")

    data = {'_':["Low", "Avg", "High"],
            'Number': [number_low, number_avg, number_up],
            '% of population': [perc_low, perc_avg, perc_up],
            'IFR': [ifr_low, ifr_avg, ifr_up]}
    df = pd.DataFrame(data)
    st.write (df)
if __name__ == "__main__":
    main()