Covid-19 in Kentucky. The Bad News Gets Even Worse.

At the time of my last article on July 16, I reported the record-breaking rise in new Coronavirus cases in Kentucky. That was on a Tuesday. I amended the article twice to show that the epidemic surge was no illusion. Indeed, over the weekend the curve of new cases continued to go nearly straight up in a clear exponential manner. Yesterday’s (Monday) new case count leapfrogged over any previous high to 977. Kentucky has the dubious distinction this morning to be listed by the New York Times as among the very top states with the most rapidly increasing number of Covid-19 cases. This is not something for which recognition is desirable!

Technical note:
For these initiatives, I have been calculating daily new cases as the increase in Total New Cases from the Total of the previous day. This number is usually a few below what the Governor’s report terms “New Cases.” I understand that latter group includes duplicates, out of state cases, corrections, or perhaps other exceptions that do not ultimately show up in the Total (aggregate) Cases. This likely source of confusion can be seen in the data of the national data aggregators and probably in the data of the CDC. I did not want to include duplicates and my efforts to obtain better data from Frankfort have not been successful. The differences between KHPI’s counts of new cases and Frankfort’s are small and the shape of the curves remains essentially identical.

I have been updating the on-line interactive versions daily on KHPI’s Public Tableau website. I began this series of articles in part as a self-educational project to explore how emerging epidemiological data could be usefully portrayed and used to monitor how and where our public health efforts were succeeding (or not) in a timely way. The result was a larger number of visualizations than most readers might want to see. beginning today, I trimmed out a number of graphics that seemed less useful at this stage of the epidemic. I place below a few of the graphics that include yesterday’s new, and indeed frightening case numbers. The new link link just above opens the most up-to-date interactive versions of all the data and visualizations.

Here is a traditional Bar Chart of the number of new cases per day current up to yesterday, July 19. Click on it to enlarge in a separate screen.

Here is the plot using a rolling 7-Day average.

The 7-Day average for a given day is the total number of new cases for that day and the previous six days divided by seven.

Another way count new cases is to total the results of a full calendar week– Sunday through Saturday. Although this can smooth out the day-to-day variation in counts, the totals for any remaining weekdays of the most recent week will not be fully included. This visualization delays recognition of the most recent changes but is useful for historic reviews.

Yesterday, only new cases and deaths were reported. A fuller report is expected this evening. It looks like hospitalizations and ICU utilization are going up, and I am concerned about th trend upwards in deaths. We should not be surprised if all three of these indicators rise meaningfully.

Peter Hasselbacher. MD
President, KHPI
Professor Emeritus, UofL
Robert Wood Johnson Health Policy Fellow
July 20, 2020

One thought on “Covid-19 in Kentucky. The Bad News Gets Even Worse.”

  1. Peter these articles are very helpful. As a retired cardiologist I’m used to data being shown as “risk stratification.” For example “I’m 52 years of age, have hypertension and never exercise, what’s my risk of sudden death or having a heart attack?”
    It seems to me that the corona virus data does not answer any important questions. What percentage of deaths occurred in nursing home residents, prison inmates, homeless people, males age 30-40 etc…”
    There are clear groups who are at high risk to get infected and die but there are other groups less likely to get sick.
    Every day we are told how many people got infected yesterday and how many deaths occurred. This information is totally useless.

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