Date of analysis: 01 October 2020
Top 20 Worldwide (sorted by Cases)
Malaysia and UAE (sorted by Cases)
Why I created the Covid-19 analysis?
Most Covid-19 graphs analyses are time-series, i.e. the cumulative total is plotted on the vertical y-axis and date on the horizontal x-axis. I haven’t seen graph analysis comparing daily count (on y-axis) and cumulative total (on x-axis).
After watching the Minutephysics YouTube video about How To Tell If We’re Beating COVID-19, I had the idea to link the daily count and cumulative total.
From my own analysis, I’m beginning to seeing the daily count and cumulative total provide a more realistic leading indicator to eyeballing the trend – Are we improving? Worsen? “Flattening the curve” will happen over time (the “black line” on graph below). Yet, the “blue line” provides greater clarity for immediate trend signal – are we trending up or trending down. Trending down means the Covid-19 controls are effective, whilst trending up means there is a need for better Covid-19 controls.
The blue line fits the Covid-19 data to approximate the trend. As daily count declines, the blue line will drop, which is a positive sign. When there is no new daily Cases or Deaths being reported, the blue line will move closer to the horizontal x-axis to form a small letter “n”. That is the goal we want to achieve, the small letter “n” blue line!
Graph with black line: Cumulative total on vertical y-axis and time-series on horizontal x-axis.
Graph with blue line: Daily count on vertical y-axis and cumulative total on horizontal x-axis.
The blue line smoothing is based on local regression (loess) technique (reference).
Comparative: Malaysia Cases Lockdown Day 199
Malaysia lockdown: 18 March 2020
China Hubei lockdown: 23 January 2020
Italy lockdown: 9 March 2020
Given the lockdown started on separate dates, comparatively the Covid-19 controls in Malaysia are effective and the blue curve is trending in the right direction.
Comparative: Malaysia Deaths Lockdown Day 199