A Clinical Data Science Approach to the COVID-19 Situation

Written by Sascha Ahrweiler – PHUSE Education Director

As a PHUSE member, and especially if you planned to attend the PHUSE US Connect in Orlando, you will have observed challenges due to the COVID-19 spread first-hand. You might ask yourself whether the cancellation of big events, the limitations in travelling or football matches without any supporters in the stadium are worth the effort. Eventually, about 60 to 70% of us are supposed to get the virus and according to the current data at hand, most of us probably won’t show severe symptoms. So, why all the hysteria and panic out there?

As clinical data scientists, we could all take a data-science-driven approach to better assess what is currently happening around us. This morning I read an excellent article in a German newspaper which nicely explains how a data-science-driven approach might help here (https://projekte.sueddeutsche.de/artikel/wissen/coronavirus-die-wucht-der-grossen-zahl-e575082/). Unfortunately, it is written in German, but I would like to share the essence of this article with you.

In a nutshell, it all goes back to the exponential growth of the COVID-19 spread. The following figure shows the exponential spread of COVID-19 cases in Italy. You can see how quickly the amount of cases grew between 15th February and early March. Not all of these cases are severe, of course, but a good portion of people will require intensive care as a consequence of an infection. If no containment countermeasures are taken, the speed of the exponential growth might lead to more than 1.5 million infections by mid-May.

It is important to keep in mind that each country only has a limited number of intensive care beds available. In Germany, for example, on average, less than 6,000 of the total 28,000 available intensive care beds were available back in 2017. The rest of the beds were being used for patients who required intensive care.

So, if you think about it, the current containment measures are all about speed. We have to ensure that COVID-19 spreads as slowly as possible, otherwise all health systems might be at risk of not keeping up with everything. This is nicely illustrated in the next figure. If the dotted line represents the number of available intensive care beds, a fast disease spread puts health systems at risk, while a slow and prolonged disease spread helps tremendously. It is not a question of our individual health staying the same: all containment measures are a matter of ensuring the population’s health can be accommodated by the healthcare system.



I hope that this information is helpful to better understand and assess the reason for and value of all the contingency measures. No one likes the cancellation of events or travel limitations. As our PHUSE Chairman, Stephen Bamford, wrote, the cancellation of our Orlando PHUSE US Connect was one of the toughest decisions we have ever taken as the PHUSE Board. Taking a clinical data science approach and following the above-mentioned line of argumentation, I assume you all agree that there are data-driven decision criteria to support all global and country-specific measures.

 

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