These graphs give a bit of an indication, but you cannot really trust them.
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.
It also needs per capita figures, which is dramatically more important than absolute figures, unless everyone happens to know the population figures of each country by memory.
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 another surprising reason why per capita numbers aren't useful - for exponential growth on the typical type of graph starting at some "initial" number of cases, it makes no difference! For example, if one country was counted a two equal half-sized countries, their graphs would be the same shape but shifted to the right by a few days. However, they would also reach their "initial" number of cases where the graphs start at a few days later - shifting them left by the same amount! The result would be the same line as the full-sized country.
Good points, but that could be generalized to say that we might as well look only at the worldwide spread. But we look at countries because policies tend to follow those boundaries, so we can see how different choices affect outcome. In the case of the US, we should ignore the national total and look at individual states, because that is where nearly all the policy decisions are made. This might be true of other nations, as well.
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.