Right-click to view graphs full size.
An analogy of a rocket launch is appropriate. The accelerations of the first stage of a rocket is relatively slow as it needs to break free from the bonds of gravity. The second stage already has plenty of momentum behind it and acceleration is considerably easier with the effect of gravity further behind.
The same thing is happening with COVID-19 in the US. When starting with very few cases, it’s easier to keep hospitals from getting overwhelmed. Now that we have started this next surge with a baseline of over 2000 cases/day, it will accelerate considerably faster. This will put most of the healthcare system in the country in overload in the next few weeks, leading to very difficult decisions about who will receive care and who will die. That’s not just for people who have COVID-19 either, it will be a challenge for anyone needing a hospital bed.
Each state has two graphs. The first has vertical light blue bars. They are known as an epidemic curve and each bar is simply the number of cases (known as “incidence”) on a given day. They are measured against the scale to the left.Some of these bars are colored. These are all three weeks after the actual event, because that is the average amount of time to see the impact of one of these changes.Green: The date that a major social restriction was put in place.Red: The date that a major social restriction was relaxed.Yellow: These represent different events that bring people close together. Currently, from left to right: St. Patrick’s Day, Easter weekend, and Memorial Day weekend.
The orange line is the seven-day moving average.The blue line is a derivative function. It helps measure the rate of change in cases. It uses the scale on the left. There is a gray line at zero. When this line is above zero, cases are increasing, when below, decreasing. The distance from the zero line is directly proportional to the rate of increase or decrease.
There are small yellow dots every seven days. There is a seven-day cycle in cases that is relatively easy to spot. These yellow dots occur at the normal peaks.There is another wave that is much harder to distinguish and lengthens each cycle.
The large green dots represent where there is a trough and cases will be pulled lower for a few days on either side, the red dots are peaks and have the same kind of effect. You can sometimes see this effect on the orange line, but you have to keep in mind that other cycles and events are influencing cases at the same time.
The curving red line is a seven-day moving average of the blue slope line with the dots.
Finally, you can see the blue and red lines extending to the right. This is a ten-day forecast.
The second graph with the gray background is an epidemic curve of deaths, again measured on the left axis. This has the same general features as the cases graph.
The orange line is the seven-day moving average of deaths.
The black line is the slope derivative like the blue one in cases. The red line is the seven-day moving average of that line.
This graph also has a ten-day forecast.
The data set is pulled from Johns Hopkins University. If you would like to validate that, you can go to their website, click on “US” in the left column, go to the bottom right corner of the screen and click on “Daily Cases.” That will turn the orange graph into an epidemic curve and you will see it matches mine perfectly. If you want to expand it, go to the top right corner of the graph window and a tool will pop up. You’ll only be able to do this from the desktop site, not the mobile one.
https://coronavirus.jhu.edu/map.html
One particularly important thing to note in the case graphs is that the green dots are the trough of a wave and will make it look like things are heading downward because of the strength of that wave in some states. That influences the derivative that is used, so assume that downward looking trends are only an artifact of that trough and it will change in a few days.








































































































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