2. Death Statistics and Trends

(3/15/20) As I’ve expressed before, I’m not satisfied with the reporting of COVID-19. Not surprising, but also appalled at the so-called experts who either like to pontificate or like to shock the public into dooms day scenarios without doing the calculations.

I tapped into the WHO (World Health Organization) data base and downloaded some key data on excel files (I will be updating these daily). Below are plots of death rates cumulatively (linear and log) and per day (linear and log). In my previous post (below) I stated that this is the only hard data we have and a potentially important way to assess trends. If we assume this is representative of incidence upon infection (at least two weeks earlier), we can use this as a prevalence (cumulative) and incidence (daily) indicator that we can then extrapolate later (by about 2-3 weeks) to get the present-day infection numbers. Here is how I worked it up and my commentary:

  • China: If we can believe the numbers, they have radically controlled the number of outbreaks and deaths. I thought there might be state deception so I was looking for dislocations in the data that did not fit any reasonable (if not normal) distribution as a red flag to fudging the numbers; but not actually seeing that. Seems believable at this point.
  • U.S. is not in big trouble, yet. These are high growth rates, but working off of very low numbers. However, there is a definite acceleration. Will follow carefully over next few weeks.
  • WW is not super alarming but maybe pulled down by China recovery statistics.
  • Italy – This country has a huge problem. An accelerating epidemic and a case study how this could escalate to any other country. Important to find out how this got so out of hand before government intervention came into play.
  • South Korea is getting a handle on things. It is at less than 10% of Italy now and receding faster. Another example of government intervention working.

One of the conclusions for the U.S. is that the number of real infections (much greater than those confirmed by tests) is not 100x as some pundits say, but maybe 10x. How do we know? By determining the death rate for today, representing incidence two weeks ago and then extrapolating to today. Quick calculation is if 6 deaths a day today represents incidence about 3 weeks ago and if giving an upward estimate of 15 deaths/days over the next 3 weeks and a mortality rate of 1% says 420 deaths over the next 3 weeks and therefore today there must be 42,000 with COVID-19. My gut says must be more, but the numbers based on deaths seem less alarming then we are reading in the press, at least in the U.S. If it is truly more then it suggests the mortality rate may be less than 1%. So, it doesn’t matter. What really matters is the death rate and when does that start to roll over. Need at least 2 more weeks of data to get good trends.

1. COVID-19 Testing in the U.S.


The Table above shows how poorly we are doing implementing COVID-19 tests in the U.S. vs. other countries. So in the U.S. today we have about 3,000 confirmed cases and 57 deaths. The former is a leading indicator and the latter a lagging indicator, which is why you can’t divide them to get a mortality rate. All the confirmed US cases are by tests. You can see tests are administered to only 0.0005% of the U.S. population. So how to calculate the true prevalence? Generally by using the death rate and dividing by the presumed mortality rate. In that case it doesn’t look so bad if we only have 57 deaths. That would say about 5,700 cases (assuming a 1% mortality rate). But some people estimate that real cases in the US are 10-100x confirmed cases and I can’t disagree. If so there should be a lot more deaths coming up. The best metric will be death growth rate. Today there were 8 more deaths in the U.S, which would say about 800 new cases per day 2-3 weeks ago assuming death comes 2-3 weeks after infection. If I track this for a few days I can get the growth rate, which would give prevalence and incidence for 2-3 weeks ago. I can then extrapolate prevalence today based on the trend. I’m sure someone else is doing this but I can’t find anything.