The New York Times published a collection of graphs comparing new COVID-19 cases over time by country. The article asks the question “Which Country Has Flattened the Curve for the Coronavirus?”

If you are interested in COVID-19 numeracy, I suggest reading the comments section. There are good insights there.

Here is my own response.

Thank you for posting your study. I started blogging about “COVID-19 numeracy” in response to the rather poor way media outlets have portrayed the disease numerically. We are in this fight for the long haul (12 to 18 months) and need metrics that guide our actions.

Please listen to the recommendations in this comment section. Many of us have spent years in measurement and statistics.

Raw numbers, e.g., the number of (new) confirmed cases, are not always meaningful or useful. We know that the number of new confirmed cases per-day will rise dramatically as testing increases. The number of new confirmed cases needs to be “normalized” against the number of tests performed. I suggest tracking the ratio of new confirmed cases divided by the number of tests.

I strongly agree that we need to track the progress of COVID-19 on a daily basis. (A seven day moving average is a good idea.) The total (cumulative) number of cases/deaths — as tracked and reported by most media outlets — will not be useful 2, 3, 4 months into the crisis, especially when there will be “waves” of resurgence and subsidence. We need to understand the dynamics of the pandemic.

Health authorities need to report the number of tests per day, the number of positive cases for that day and the number of negative cases. The raw number of tests per day will tell us if authorities are meeting their commitment to increase the number of tests and allow us to compute ratios, etc.

Should we ever get to the point of spare testing capacity beyond diagnosis, we need to conduct periodic community studies, something akin to a political poll. Take a random sample of the community and determine the number of symptomatic and asymptomatic cases (by age, by sex, etc.) Such polling will allow us to track the actual infection rate in the population at large.