“Many schemes, ranging from simple to complex, using process behavior charts with Covid data have been tried. But regardless of their complexity, they all come up against the fact that epidemiological data do not represent a steady-state system where we need to discover if assignable causes are present. Process behavior charts simply ask the wrong questions here. When dealing with data from a dynamic system where the causes are well understood, the data will create a running record that can be interpreted at face value. The long-term changes will be sufficiently clear so that further data analysis becomes moot.
So, while specialists may use epidemiological models, when it comes to data analysis by nonspecialists we do not need more analysis, but less. We need to draw the graphs that let the data speak for themselves, and then get out of the way. As always, the best analysis is the simplest analysis that provides the needed insight.”
Michel Baudin‘s comments: Don Wheeler is correct that process behavior charts are not a fit for data about the pandemic. Non-specialists, however, cannot ignore epidemiological models for several reasons:
Their key concepts have found their way into news media and political speeches. The German chancellor discusses R_{0} on TV, the British Prime Minister talks about "herd immunity," and everybody in the US wants to "flatten the curve." As citizens, we need to know what they mean and notice when our leaders don't.
The epidemiological models are useful to anticipate what happens when organizations resume operations after a pandemic-induced shutdown.
That's why I took a stab at learning and sharing about them in a few recent posts:
Aug 3 2020
Process Behavior Charts and Covid-19 | Donald J. Wheeler | Quality Digest
“Many schemes, ranging from simple to complex, using process behavior charts with Covid data have been tried. But regardless of their complexity, they all come up against the fact that epidemiological data do not represent a steady-state system where we need to discover if assignable causes are present. Process behavior charts simply ask the wrong questions here. When dealing with data from a dynamic system where the causes are well understood, the data will create a running record that can be interpreted at face value. The long-term changes will be sufficiently clear so that further data analysis becomes moot.
So, while specialists may use epidemiological models, when it comes to data analysis by nonspecialists we do not need more analysis, but less. We need to draw the graphs that let the data speak for themselves, and then get out of the way. As always, the best analysis is the simplest analysis that provides the needed insight.”
Sourced : Quality Digest
Michel Baudin‘s comments: Don Wheeler is correct that process behavior charts are not a fit for data about the pandemic. Non-specialists, however, cannot ignore epidemiological models for several reasons:
That's why I took a stab at learning and sharing about them in a few recent posts:
#covid19, #coronavirus, #epidemiology, #pandemic
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By Michel Baudin • Press clippings • 0 • Tags: Coronavirus, COVID-19, Epidemiology