Covid-19 infection for New Orleans
Objectives
1) Using only community death rates data and Decision Machine, learn the daily disease source strength and infection rate from the observed death toll.
2) Based on factual evidence, prove that public health policy and the response of citizens is helping to decrease the infection rate.
3) Alert health officials and the public to changes in the infection rate curve especially as it flattens and ultimately bends downward.
4) Monitor infection rate for any resurgence.
5) Report a top for the infection rate curve.
6) Measure the infection rate response as public health policy changes, therapies are introduced, we return to work, and our daily lives look familiar again.
Covid-19 Geiger Counter machine learned source strength and infection are based on 3% mortality. We use the deaths data from The New York Times, based on reports from state and local health agencies. Plots use the date when the data was made publicly available.
Analysis and Plots
Orleans
The source strength (population approx. 395,000, times the inferred incidence rate) decelerates further into Recovery. Top was on April 22nd. The infection energy slips to -0.5. The infection ratio at -0.03. We are ending our coverage on the New Orleans Community to refocus on US States. Congratulations New Orleans and surrounding counties for a job well done! We saw recovery first in your counties, and happy to see you keep it going. Best wishes to you.
Jefferson
The source strength (population approx. 440,000, times the inferred incidence rate) decelerates into Recovery. The infection energy at -0.1, and the infection ratio jumps to 0.0. Important not to give the peak infection any human oxygen. We want to see the green curve always under the red from now on.
Louisiana
The source strength (population approx. 4.7 million, times the inferred incidence rate) rolling over a top into Recovery. The latest hot-spots include Terrebonne, Calcasieu, St. James and St. Landry (see US counties web page).