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  • Guy Tsafnat

Dude, where's my data?

It has been several busy weeks for Evidentli and many others working a multitude of problems associated with COVID-19. Unfortunately, much remains unknown about the disease and the barriers are still mostly to do with the availability of high quality data.

A lot of emphasis has been put lately on the number of tests done in every region. Testing is important both for the purpose of providing care and, as the beginnings of data, also for informing public policy. There is no doubt testing is important. Inconsistencies begin to arise when questions like who gets tested (baseline) mean that important figures like mortality rate, transmission rate, and risk of requiring intensive care, still remain unknown. Without these figures predictions of the effects of re-opening the economy, schools, shops etc. are inaccurate at best.

Consistency of data means that it is easier to attribute social, medical, geographical and other factors to their role in the disease. It means that effective measures can be taken and a return to safe and normal life is accelerated.


Further reading: Importance of Data Quality for Analytics (Springer, 2016)


#covid19 #ai #healtchare #publicpolicy #dataquality #bigdata #ml #analytics #standardization #dataintegrity #consistency #deeplearning #decisionmaking #databases #datalakes #covidtesting #reopen



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