by Mark P. McDonald | July 17, 2020 | Comments Off on Data driven leaders unite! – the opportunity missed to date with COVID-19.
COVID-19 data presentations should anger fans of data and data driven decisions. Media and politicians resenting this simplistic and incomplete data squander perhaps the best opportunity to show the public what it means to manage based on information. The time to address this is now.
Covid-19 data is an excellent opportunity to illustrate managing with information. The situation is simple and clear, the data is easily understood and of interest to everyone. Yet the data presented in the media, describing in policy decisions by politicians, etc. leaves a lot to be desired. The Johns Hopkins COVID-19 resource center visualization of Covid-19 data is an execellent resource but also an example. Here is what I mean.
Simple data visualizations can limit understanding and change
The data visualizations concentrate on the trends in the number of cases. The example below is taken from July 17th at 3:00 am ET for the state of Illinois. The data is tracking the number of cases and the 3-day moving average.
This is the type of chart everyone is sharing. Its message – more cases bad. That is the right message, but it is incomplete. Data should show how we get the number of cases down and control the spread. Better decisions come from better data – quality over quantity. Decisions and actions come from having the data that influences the results you are seeing. In the case of COVID-19, that data includes: the number of tests conducted, testing positivity rate, number of hospitalizations etc. IT is information describing the dynamics of the infection. That is what we have to change – the dynamics.
Three scenarios as examples
I am not public health expert. The scenarios below are not a public health policy prescription. Rather they illustrate the decisions we make when we artificially limit information. Consider the following scenarios related to the decision to open or close the state.
- Scenario 1: The number of cases is going up. The number of tests is going up. The positivity rate is staying the same.
- Scenario 2: The number of cases is going up. The number of tests is going up. The positivity rate is going up.
- Scenario 3: The number of cases is stable. The number of tests is going down. The positivity rate is going up.
If all you look at is the number of cases and the trend line, then you open up your state in Scenario 3. Wrong decision. Scenario 3 is the most dangerous scenario. A rising positivity rate indicates that lower testing numbers hide the actual number of cases. Opening would be a bad idea. Its a bad idea even if the positivity rate were stable.
Scenario 2, you would close down and tighten public health measures as the positivity rate is going up as testing is uncovering the true number of people infected. You are better off than scenario 3 as you have a more complete view on the situation.
Scenario 1, does not necessarily mean closing. It may indicate the need to stay the course. Those closed, stay closed. Those open, you should implement tighter measures, but perhaps remain open. You need to get the number of cases down, regardless, but reduction may be is made through improving compliance with public health measures like mandatory mask wearing and crowd restrictions rather than wholesale shutdowns.
Why this matters
The number of cases must go down. Each case represents a human tragedy. The number of cases will only decline when people change their behaviors. They need information to change those behaviors. Without information the public, and certain segments within it, become jaded and cases persist. Jaded because the information to understand is not presented.
If data and data driven solutions are our future, then we as individuals, society, business decision makers, etc. need to understand it. The COVID-19 situation represents a great opportunity to inform people about infection data, how their actions change that data and why it is important. It is a potential common lesson of how to use data. If data does not matter in the case of COVID-19, then it will matter less in other areas.
Without a clear understanding, we leave the public with simple scare tactics and politicization. Personal, social and group behavior does not change without understanding.
Let us start talking and sharing the data and using it to explain how we first manage and then defeat this virus.
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