The red line represents an exponential growth curve projection, based on available daily deaths data from the New York Times.
The solid blue dots, joined by the blue line, represent the actual number of reported COVID-19 deaths per day.
The dotted lines are "control limits" that are mathematically tied to the projected growth rate. If COVID-19 deaths are on a "stable" path of exponential growth, then the solid blue line should stay within the dotted "control limit" lines.
Naturally, the blue line moves back and forth across the red line projection, reflecting expected real-world variation (noise).
Decades of quality improvement data science (i.e., industrial engineering) have established several rules for detecting material "signals" using control charts. For example, if the blue line (deaths) crosses a dotted line (a control limit), that would signal that something has occurred that has made the exponential growth "system" unstable. Perhaps a stay-at-home order might decelerate the daily death count, flattening the blue line and crossing the lower control limit. Or, the lifting of a stay-at-home order might accelerate the daily death count, raising the blue line and crossing the upper control limit.
Other data signals that would indicate we've turned the corner would be eight sequential points to the right of the red line; or six sequential points, each falling farther to the right (i.e., away from the red line). The converse of any of these rules would mean the situation is getting worse.
MDmetrix's artificial intelligence automatically identifies "signals" in the data so that leaders and frontline clinicians can understand and adapt their approaches to COVID-19.
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The red line represents an exponential growth curve projection, based on available daily deaths data from the New York Times.
The solid blue dots, joined by the blue line, represent the actual number of reported COVID-19 deaths per day.
The dotted lines are "control limits" that are mathematically tied to the projected growth rate. If COVID-19 deaths are on a "stable" path of exponential growth, then the solid blue line should stay within the dotted "control limit" lines.
Naturally, the blue line moves back and forth across the red line projection, reflecting expected real-world variation (noise).
Decades of quality improvement data science (i.e., industrial engineering) have established several rules for detecting material "signals" using control charts. For example, if the blue line (deaths) crosses a dotted line (a control limit), that would signal that something has occurred that has made the exponential growth "system" unstable. Perhaps a stay-at-home order might decelerate the daily death count, flattening the blue line and crossing the lower control limit. Or, the lifting of a stay-at-home order might accelerate the daily death count, raising the blue line and crossing the upper control limit.
Other data signals that would indicate we've turned the corner would be eight sequential points to the right of the red line; or six sequential points, each falling farther to the right (i.e., away from the red line). The converse of any of these rules would mean the situation is getting worse.
MDmetrix's artificial intelligence automatically identifies "signals" in the data so that leaders and frontline clinicians can understand and adapt their approaches to COVID-19.