You end up missing critical data points like the per 100k population mortality rates (from Friday morning):
New York 12, Louisiana 6.6, New Jersey 6, Michigan 4.2, Washington 3.5, Connecticut 3.1, Massachusetts 2.2, Colorado 1.7, Georgia 1.67, Nevada 1.27, Illinois 1.23, Delaware 1.2, Pennsylvania 0.7, Ohio 0.7, Florida 0.68, Kentucky 0.68, Alabama 0.65, South Carolina 0.6, Wisconsin 0.53, California 0.5, Oregon 0.5, Maine 0.5, Idaho 0.5, Virginia 0.48, Arizona 0.45, Kansas 0.44, New Hampshire 0.36, Iowa 0.34, New Mexico 0.33, Minnesota 0.32, Nebraska 0.32, Missouri 0.31, Texas 0.24, North Carolina 0.15, Hawaii 0.14
Italy 23, Spain 22, Belgium 8.8, France 8, the Netherlands 7.8, Switzerland 6.2, UK 4.5, Sweden 3, Denmark 2.1, Ireland 2, Portugal 2, Austria 1.8, Germany 1.3, Norway 0.9, Canada 0.37, Finland 0.34, Australia 0.11, New Zealand ~0
Most of the US is seeing very low per capita mortality rates and no surge in cases. You wouldn't know that by the headlines though.
There's also this tweet additionally showing how population size of a country has no relationship to pace of disease spread. https://mobile.twitter.com/jburnmurdoch/status/1246185741304...
Since there is a shortage on tests, at some point countries might decide to only test people coming into the hospital.
Another thing about the deaths is also troubling: In the Netherlands doctors were complaining that deaths with symptoms of Corona were not counted as corona deaths, because they were not tested and found positive (again a problem with the shortage of tests).
So a bending of the curve might just be explained by a new strategy of who to test.
I think the best way to count is to look at total hospitalizations, and subtract the average of normal years. And with corona deaths the same way: subtract the total with the average in a normal year.