Social Rules–>Cases–>Death

I’ll try to tie together all of the pieces related to how changing social controls can influence survival or death. I’ve done a graph like this before that indicated how it changed the case volume, but this will tie all three together. This graph combines a lot of information and may take some time to digest.

Since that time, I’ve found a bit of updated data so a few of the colored bars may appear to be in different locations, but they are minor and what is important is the trend. New Jersey has been filtered out of the data set for this graph because a change in their case definition skewed the data

The colored vertical bars are superimposed over gray ones in the background. The height of them is the number of deaths each day, which are on the left y-axis.

All of the colored bars are three weeks after some type of social event that could influence the course of the pandemic. I have found that interval to be very predictive of showing up in the number of cases.

The yellow bar at the left end represents the date of impact of St. Patrick’s Day on case counts. The three on the right are the dates of impact of Memorial Day weekend.

The green bars represent dates three weeks after a state first implemented some sort of significant social control, such as stay at home orders, closing businesses, etc. The darker the bar for a given day, the more states that enacted those measures. If over five states had measures on the same day, the excess were moved and added to the closest day with room to the left or right to keep the color scaling consistent.

The brown bars are similar, but represent the projected impact date three weeks after the first measure was released in the state, again a similar heat map to indicate how many on a given day.

The moving red line is a derivative function from calculus. It is the slope representing the data from that day and the 20 days prior (3 weeks), and is measured on the right axis. When That line is above zero (the horizontal green line), the number of cases goes up, when it is below, they go down. The speed of the increase or decrease is directly proportional to the distance of the red line from the green line at that date. This line has been shifted to the right, to more easily visualize the impact of the number of cases on deaths, which lags for three weeks.

It is readily apparent that when the green vertical lines are clustered (3 weeks after restrictions started), it caused the red line to move rapidly down into the area where cases would be decreasing. This also had an impact on the seven day averages of deaths, which is the black line moving through the data. It’s very clear that this black line started moving downward when the red line went below zero.

The next part to observe is the spread of the vertical brown lines, particularly when the most states were clustered together around May 20th. As restrictions were eased in many states by that date, the rate at which the number of cases had been declining started turning a corner to where they would be increasing, which should be readily apparent in the red sawtooth pattern after that date.

The important part is that while that red line stays below the green one, it will appear to many that the situation is under control because the number of deaths is falling. As that red line crosses above the green, the number of deaths will increase as well.

The first spike above the green line is a result of the record number of cases in the US the past few days. The rest is a forecast. The number of new cases will seem to stabilize the next few days and then start to rise on July 1, with almost unbelievable numbers of new cases the following days, cresting again July 4-July 5th, before settling again. Those first few days in July will then cause the hospitals that haven’t already run into problems to be overwhelmed two weeks later. July is going to be a very bad time to need hospitalization for anything across most of the country.

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