car_and_ptr.py

# CAR (Case Ascertainment Ratio) hand-entered by CO from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239078/bin/NIHPP2020.04.29.20083485-supplement-1.pdf
# PTR (Positive Test Rate) hand-entered by CO from https://covidactnow.org/?s=830154

CAR_and_PTR = {
    'AK': [0.18, 0.032],
    'AR': [0.13, 0.071],
    'AZ': [0.09, 0.115],
    'DE': [0.09, 0.179],
    'HI': [0.13, 0.019],
    'IA': [0.08, 0.129],
    'KY': [0.06, 0.155],
    'MD': [0.07, 0.231],
    'ME': [0.2, 0.054],
    'MI': [0.17, 0.239],
    'MN': [0.19, 0.078],
    'MT': [0.09, 0.033],
    'ND': [0.23, 0.041],
    'NH': [0.08, 0.117],
#    'NJ': [0.12, 0.40], # at least; omitting as this seems like a weird datapoint
    'NM': [0.09, 0.058],
#    'NY': [0.19, 0.40], # at least; omitting as this seems like a weird datapoint
    'OK': [0.11, 0.059],
    'RI': [0.12, 0.156],
    'SD': [0.04, 0.249],
    'TN': [0.13, 0.071],
    'TX': [0.06, 0.111],
    'UT': [0.19, 0.061],
    'VA': [0.11, 0.211],
    'VT': [0.19, 0.048],
    'WV': [0.11, 0.047],
    'WY': [0.12, 0.029],
}

car = [CAR_and_PTR[k][0] for k in CAR_and_PTR.keys()]
ptr = [CAR_and_PTR[k][1] for k in CAR_and_PTR.keys()]

import numpy as np
[m, b] = np.polyfit(ptr, car, deg=1)
print(m, b)
# -0.3304898802394048 0.15667841037843105

def trim(num):
  return"{:.2f}".format(num)
print("Most optimistic:", trim(1/b))
print("Least optimistic:", trim(1/(b+m*0.25)))
# Most optimistic: 6.38
# Least optimistic: 13.50

import matplotlib.pyplot as plt
plt.plot(ptr, car, 'o')
x=np.linspace(0, 0.25, num=50)
plt.plot(x, m*x+b)
plt.xlabel('PTR')
plt.ylabel('CAR')
plt.show()