More testing doesn’t skew the data to “make us look bad.” It gives us the critical information we need to fight COVID19.

A friend’s question sent me down a data rabbit hole this morning. Fortunately, I thoroughly enjoy crunching the numbers, since analyzing pandemic data predictions led to my first book. Fond memories.

The question was essentially: If we test more than a smaller EU nation, won’t that skew the number of cases to make it look we’re doing worse than the that country? 

My longish answer:

If the positivity rate (% of population demonstrated infected by testing) of two populations was the same, then testing 100 people in Italy and 100 people in the U.S. would result in the same number of infected people…and if you tested more in either country, you will definitely get more cases. In this scenario, if you tested 100 more people in the U.S. and didn’t test any more in Italy, the U.S. would appear to have double the number of cases…but the pandemic situation would be the same in both countries. You have the same levels of virus present in the population. 

However, that’s not what we’re seeing here in the U.S.

Italy tested 57.5K yesterday and found 251 cases, and the U.S. tested 614K and found 33,539. Italy’s positivity rate yesterday was .43%, meaning one out of every 200 people tested showed up positive. The U.S. rate was 5.5%, which means about one out of every 20 people tested positive. If you had to choose between grocery store where 1 out of 20 people was infected, or 1 out of 200 was infected…which would you choose? I know where I’m shopping. 

And IF Italy had somehow tested 614K people yesterday like we did in the U.S., they would have seen around 2,600 cases, because the prevalence of the virus in their population is so low (.43% based on a data snapshot).

Gauging the positivity rate is only truly possible when testing is done on a large scale. Not only does it give health officials a rough sense of where the country or state stands in terms of infection, it indicates whether enough testing has been done. A very high positivity often indicates that testing has fallen behind…unless you truly have a 20% infected population. It should guide health policy. When the positivity rate is high or increasing, you have an out of control outbreak. Italy and most of the EU countries I’d shown before have reduced their positivity rates to well below 1%. The UK is at .77%. Some of those countries have slowed testing because of this…it’s not necessary to proactively test widespread when you get that low. Still a good idea to keep testing, but you don’t need the same massive effort we’re seeing in the U.S. right now. Because we’re nowhere close to under control, particularly in states that didn’t take this seriously from the start. 

Here are the current positivity rates for select U.S. states based on yesterday’s data, which corresponds with charts of states that have contained or are well on their well to containing the pandemic, plus states that are not on the way:

CT .6%
MI 1.1%
NY 1.4%
NJ 1.8%
CA 4.4% (they’ve just implemented a mandatory mask policy)
TX 10%
FL 20%
AZ 21%

Some of the raw data is included below. The outbreak states make up less than half of the tests in the country (remove CA and way less) but nearly 70% of all new cases. 


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