Is the Covid-19 Epidemic Still Expanding in Kentucky and Its Neighborhood?

Kentucky and many other states are backing away from public health measures of varying strictness that were adopted in March or April during the exponential expansion phase of the Covid-19 pandemic in the United States. It is appropriate and even necessary to begin this process, but it needs to be done with an acceptable degree of safety. There is no doubt that measures taken so far have at least “bent” the curve, slowing down if not ultimately decreasing the mortality and morbidity of this overtly infectious disease. I believe Kentucky has benefited greatly from our collective efforts despite opposition on several fronts including armed protest. The expectation and promise is that we and the nation will be able to detect “surges” of the epidemic in a timely way and to be able to reinstate restrictions on public interactions that have proven effective. I wish I could be more confident that we can be successful in either instance.

It‘s not over yet.
In the nation as a whole, albeit to a lesser degree in Kentucky, both the number of aggregate cases and deaths continue to increase. Our ability both as a nation and Commonwealth to test for, identify, and report the presence of Covid-19 in the community and to trace exposed persons is still far behind what is needed to detect and respond to localized outbreaks before they show up two or three weeks later as increases in hospitalizations and deaths. It is from such localized hotspots that epidemic expansion can be continuously fueled. More troublesome is a background of resistance from individuals and groups which, for a variety of ideological, religious, political, or business reasons, hold the nation hostage by refusing to follow evidence-based public health initiatives that are effective only when done collectively. Unfortunately, we face these problems with a weakened and fragmented public health system and an inequitably distributed healthcare system overall.

How will we see a “surge” coming?
As the world tiptoes its way through its “reopening'” in the middle of an active pandemic that has no demonstrably effective specific treatment or vaccine yet, how can we feel comfortable that things are not getting unacceptably worse? I do not believe this is a straightforward undertaking. As testing and reporting increase, it is inevitable that new cases will continue to be discovered in new places here and around the world. The most objective indicators of epidemic expansion commonly reported are the number of deaths or hospitalizations attributed to Covid-19. However, either of these, even if consistently reported, are late markers of community epidemic status. The virus has first to find a human host, to incubate asymptomatically, to be recognized in the healthcare system as a clinical infection, to be reported to some public health entity, to be evaluated in the context of current community experience, to be recognized as a diversion from the status quo, and only then to pass some threshold to take effective public health action. Seems to me that by this time, the virus is already out of the barn, racing down the track, and harder to stop.

Who is keeping track?
Compounding the difficulty is that there appears to be no national standard for how to define the items to be reported or even to report them at all. For example, not all states have been reporting hospital or ICU admissions. I can find no federal database at the Center for Communicable Diseases that local communities of public health researchers can draw on. The challenge of aggregating a national experience has been assumed by institutions such as Johns’ Hopkins University, or the New York Times, or The Atlantic magazine that are collecting relevant data directly from individual state and international public health sources. Reporting on weekends is not common nationally and has led to large swings in daily new cases or deaths making timely detection of deviations from the expected much more difficult. Even if a single state, county, or community is doing everything right, it is at the mercy of its neighbors. What happens in Indiana, Ohio, Illinois, Missouri, Tennessee, Virginia, or West Virginia– indeed anywhere in the world– does not stay in those places. At least one of our neighboring states appears still to be in a state of active exponential growth even before “opening up.” How then can we compare our experience with that of other countries, states, or communities?

Below is a plot of aggregate cases of Covid-19 in neighboring states. I use data from the Covid-19 Tracking Project as of May 5th. I plan to work with this or similar data further in the days ahead to compare what unfolds. View the interactive series of data visualizations here.

How about Kentucky now?
Readers of these pages will have watched me try to interpret Kentucky’s own data collected from Governor Andy Beshear’s evening reports. [There is no consolidated Covid-19 database of Kentucky’s epidemic experience available to me. Is it available to anyone?] I conclude that we have markedly slowed down the rate of expansion of the epidemic in our state, but have not yet entirely stopped its ongoing growth. As testing is now rapidly improving, we should expect to see more new cases emerge, especially in places where two or three are now gathering together. More troubling is a recent rise in deaths and continuing new ICU admissions. Take a look at what I have published and tell me what you would follow or substitute.

Basic Reproductive Number.
As I wait to be better informed, I use this opportunity to suggest an additional marker of epidemic status that is being used worldwide to monitor the opening-up of communities around the world. I suggest an estimate of the current Basic Reproductive Number of the virus, or “R.” A reproductive number represents the average number of people that a single infected person can infect. If R is greater than one, an epidemic is still expanding exponentially. (Think compound interest!) If R is less than one, the epidemic may be on a course to burn itself out. An R of zero indicates that there are no more new cases.

The most accurate estimation of R (R0 or R-naught) requires higher math and a fuller knowledge of epidemic parameters that is only available in retrospect. The version of basic R that I have incorporated into KHPI’s data visualizations of Kentucky’s experience is that recommended by Germany’s Robert Koch Institute– that country’s version of our CDC. [Robert Koch was the 1905 Nobel Prize winner in Medicine and is considered to be a founding father of the sciences of bacteriology and infectious disease.] This version of R depends only on the number of new cases detected daily. It compares the 4-day rolling average value of new cases on one day with the corresponding average value four days before. Brought down from an initial high of 3.5 in March, Kentucky’s “R” is currently hovering on both sides of 1 trying to decide where it wants to go. I would not venture to say at this time. View an interactive version of the figures below here.

Here is how Kentucky’s “R” compares to a 7-Day rolling average of new cases.

We are by definition all in this together and will get through it together– one way or the other. We owe it to each other to do it respectful of each other’s needs and safety.

Peter Hasselbacher, MD
Emeritus Professor of Medicine, UofL
President, KHPI
20 May 2020

[Addendum May 21, 2020: During last evening’s Governor’s report, the number of patients in ICUs reported fell from 269 to 98 in a single day. They did not go home overnight! It was revealed that the hospital reporting process was broken somewhere along the line. Since availability of hospital beds is one of the more important planning priorities and should be a marker to detect new outbreaks, this is not a minor matter. All hospitals use or should be using electronic medical records. My practicing physician friends often complain that these record systems seem designed primarily to capture billing and payer accountability matters, often getting in the way of direct patient care. If the different brands of hospital electronic record systems are not able to support universal public heath needs, I think we need different systems, perhaps even a single one! It is one thing for one brand of EMR not to be able to talk to other proprietary ones. It is another if they are impediments to public health data needs.]

What Can We Learn from Mini-Coronavirus Updates?

Some weeks ago, when public health experts were still visible in Washington, a reasonable-sounding set of guidelines for opening up the national economy was offered. Sadly, the White House seems now to place all responsibility on the individual states with minimal if any major Federal help. It is walking away from, if not contradicting, the advice of the best public health scientists the nation has to offer. I fear that things are going to get interesting quickly and that we will land in an uncharted place somewhere between good and disastrous.

With individual states beginning to open up their economies in different ways and to different degrees, it is apparent that our ability to identify new cases of Covid-19 infection early, to do so in unexpected places, and to be willing and able to do something about it will be critical.

What is a “Mini-Update?”
The Wall Street Journal and other publications often offer a “Coronavirus Daily Update” sidebar with a simple list of Total Cases, Total Deaths, and Recoveries for both the United States and globally. When applied to a given geographic area, these three totals are important elements for predictive epidemiologic models. The fact that the numerous models offered today differ widely (or even turn out to be wildly wrong) confirms the truism that any model is no better than the assumptions it makes and the data available to it. By themselves, these high-altitude aggregate numbers are not fine-grained enough to help us predict the future for Kentucky. I do suggest there are some insights to be gained by examining them. In any event, the numbers are sobering.

What might we learn?
Readers of these articles may notice that I have been educating myself (and I hope some of you) about how we can best use the limited and imperfect epidemiologic data available to us to monitor the opening our economy. Are we are on the right path– or are we falling off the wagon? This is today the major healthcare challenge facing us as a nation. What might we learn from countries where the epidemic started earlier? How are we similar or dissimilar?

The typical mini-update extracted below was taken from the May 7 print edition of the Wall Street Journal. [Yes I read the Journal daily… and the New York Times, and the Courier- Journal!] We are given world-wide numbers of Cases, Deaths, and Recoveries and the same numbers from the United States. Aside from the impact of seven-figure aggregate cases, what other insights might be extracted? Here are a few that occur to me which I think are relevant to tracking our epidemic in Kentucky.

Data from Wall Street Journal 5-7-2020
Continue reading “What Can We Learn from Mini-Coronavirus Updates?”

How Can We Tell If Our Covid-19 Epidemic Status is Under Control?

What would a recurrent surge of infections look like?

As fifty states with varying intensity of public health approaches to decrease the impact of this highly contagious disease begin to loosen their restrictions, how will we be able to recognize the very real threat of a “second-peak” surge of infections?

Most real experts agree that aggressive testing, new-case finding, and tracking of contacts (backwards and forwards) will be important– indeed critically essential. Small local micro-outbreaks need to be identified quickly and dealt with aggressively. This is going to be a challenge for a number of reasons!

We have become accustomed to seeing a variety of graphs and tables in our public media used to show the status of the epidemic and the hoped-for success in dealing with it. Such macro-presentations will continue– including by me! The problem is that by the time the significance of a given graph becomes evident, the horse may already be out of the barn and running. Nonetheless, what we can’t count, we can’t control. One important metric thought to justify a loosening of restrictions is a sustained two-week decrease in the number of new cases in a given locality. What would this look like in the different possible data visualizations?

Various reports and models use different valid analytical approaches, but care is needed not to unintentionally misinterpret the results. Such graphic representations are used not just to see how things are today, but to predict where we will be in the future. For example, when we visualize positive cases, we can look at daily counts or cumulative counts. Because daily counts vary widely depending on the timeliness of reports and weekend interruptions, using weekly averages is common. When we try to predict where the graphs are going, do we start with the first case, or begin with the 100th to allow matters to settle down? To deal with the difficulty of comparing small numbers that rise exponentially to big ones at the same time, it is common to use logarithmic scales in graphs. What does a “plateau” of cases look like in such different visualizations? Based on current status, how can we tell if things are really getting better– or how much worse they might be?

I prepared the following data visualizations to educate myself what a plateau of the counts of cases, deaths, or tests would look like. What would a 14-day decrease look like? I invite the reader or viewer to step through the seven different graphic representations of the number of current Covid-19 cases in Kentucky and two different futures. I hope the annotated figures are self-explanatory. In these hypothetical scenarios, I used the actual Kentucky case counts from the first reported case through May 4th. I then assumed that the number of new cases would plateau at 170 per day for the next 14 days, and that thereafter the number of new cases daily would decrease by 10 each day until there were no new ones. I was not 100 percent certain in advance what they would look like! I hope you find them useful too. The fully interactive versions can be accessed on the Institute’s Tableau Public website.

Warning: The rest of this article gets quite technical. I am asking for advice from other data nerds about how to monitor the nations’s easing up on its social distancing. Even if you do not look at the 7 figures in detail, at least notice how the same data can be looked at in different ways and the nature of the numbers we have to work with. Trends will be magnified or minimized by the choice of axes or other data transformations!

Continue reading “How Can We Tell If Our Covid-19 Epidemic Status is Under Control?”

Reopening Kentucky’s Economy in the Current Covid-19 Epidemic.

How will we know if we are still ahead?

It had to start sometime, but pressure from partisan and a variety of other assemblies have surely advanced the nation-wide schedule for lifting restrictions of non-medicinal management of the Covid-19 epidemic. It is happening in Kentucky too. While there are state differences in degree, the number of new cases identified continues to increase overall. We are “bending the curve.” Because availability of viral testing continues to be limited, as more testing done more cases will be found. How best should we monitor our populations to detect, localize, and quantitate any significant second peak in the curve of disease incidence? I cannot say that I know!

Kentucky has been fortunate to have acted early and aggressively to deal with our rising number of cases. Despite relative success compared to other states, the number of known cases in Kentucky is rising and will continue to do so while our still-modest ability to test for the virus increases. A 7-Day rolling average of daily new cases remains high. Timely identification of new cases will be essential to deal with the brushfire outbreaks that are certain to occur in the months ahead– whatever we do. Depending on the day of the week, the number of tests done, and reporting from new hot-spots, the number of new cases per day varies widely, making predictions uncertain..

What other measures could we track? Some potential independent statistics that are less directly correlated with frequency of testing, and which we are already collecting include deaths and hospital utilization. These are, however, manifestations of more severe disease and will necessarily lag in time from any overall increase in viral infections.

Continue reading “Reopening Kentucky’s Economy in the Current Covid-19 Epidemic.”

It Cannot Yet Be Said That We Have Reached Plateau In Kentucky’s Covid-19 Epidemic.

[See addendum at end for an update.]

It has been 46 days since the first case of Covid-19 infection was reported in Kentucky and 36 days since the first death– not as long as it seems for those of us riding out the storm at home or still on the job.! Nonetheless, we are hearing increasingly broad demands to walk away from the non-medical public health approaches we are using to mitigate the impact of this highly infectious agent. However, given the very limited availability of viral testing, of what is at best a decrease in the exponential growth rate of new cases, and continuing sporadic jumps in the number of new deaths daily; it is not at all clear that we have broken the back of Kentucky’s part of this pandemic. It does appear that our personal and other community sacrifices have awarded us success compared to other states! We have avoided a disabling flood of very sick Covid-19 patients on the capacity of our hospitals– one of our most important goals. However, in my opinion and as based on the raw numbers available to me, we do not have the evidence in-hand to declare that we have reached the plateau needed to justify anything more than thoughtful planning for progressive gradual stand-downs. The lack of a fully functioning viral testing and reporting system has not reached anyone’s minimal expectations. We are flying blind. Governor Beshear’s reports over the weekend through Tuesday evening show continuing substantial volatility in the counts.

Continue reading “It Cannot Yet Be Said That We Have Reached Plateau In Kentucky’s Covid-19 Epidemic.”

New Cases and Deaths in Kentucky Declining but Availability of Testing is an Issue.

The number of new cases of corona virus announced by the Governor last evening was not as high as was feared. There was concern that changes in data collection techniques would cause an artifactual “catch-up” spike. The aggregate numbers of both cases and deaths is still rising but not as strongly exponential as before.  The daily count of new cases may be leveling off, but the number of viral tests performed daily is also declining.  Current case mortality is hovering at 5% of identified cases. The percent of viral tests that are positive has been slowly rising– currently 8.2%. Both of these latter two statistics reflect the fact that sicker and high-risk individuals are still being preferentially tested.  As long as we are hamstrung by lack of testing capacity and timely reporting, Kentucky is in no position to open up its economy by relaxing the fundamental epidemiological principles necessary to control this extraordinarily infectious agent.

This morning I simplified and updated the data visualizations currently on the Tableau Public pages of KHPI.  I include some of the semi-log plots that I discussed yesterday, but as it happens, the aggregate numbers of cases and deaths are falling off even this trend line.  Visual inspection confirms that the plots are rising less steeply especially for the number of aggregate cases. (Aggregate deaths might be expected to lag new case discovery.)  Muddying the water however, is the fact that rather than increasing, the number of tests performed (and reported publicly) is actually declining!  What is not looked for is rarely found.  We are still largely flying in twilight– if not the dark.

Cases and Deaths.
The graph below gives an overview of the aggregate numbers of new cases and deaths. The recent points are falling away from the exponential trend line. This has to be a positive sign.

Aggregate Number of Tests.
It is not a positive sign that the rate of performing new tests (as reported publicly) is not increasing as it must. We want to see exponential growth in the number of test done!

New cases and tests.
The daily number of new cases lacks the higher spikes of the week before but remains volatile. The daily number of tests reported is demonstrably declining. It is reasonable to wonder if any appreciable decline in cases may be related to a decrease in testing. I pause here to ask a question that perhaps can be answered by someone in Frankfort. Are all “Cases” defined by a positive viral lab test, or is a clinical diagnosis of Covid-19 infection without a positive test enough of a ticket to make it to the New Case list? It surely is a given that many Kentuckians are infected or killed by Covid-19 than are included in the data available publicly!


What is the problem with testing?
The Governor and Commissioner were obviously disappointed if not frustrated.  I do not blame them.  I am not the first nor the last to point fingers at our Federal Government’s role in deemphasizing or even delaying our national response to the threat of a pandemic. What happened to our scientific and medical leadership that smaller and less wealthy countries had strong testing capacity while we staggered with faulty tests that were worse than nothing?  That story will eventually be told in full, but the current paradoxes are indeed frustrating.  Governor Beshear pointed out the availability of having 15 of the Abbot Company’s rapid-testing machines, but only 20 of the testing kits containing the chemicals needed to actually perform individual tests.  Who has these machines? Are we paying to have them sit unused?  Who is responsible for providing the specimen collection kits and testing reagent kits.  Are they even available anywhere?  The Governor also made a point that while some labs were turning out and reporting results in 24 hours, that others were taking 10 days.  Naturally it takes time to set up any new test and insure that it is working properly.  What entity has arguably failed us– the free market, or the public health agencies of our nation?  I suggest that devolving some public functions to the free market has actually been dysfunctional.

Is it safe to open up?
The suggested  guidelines and thresholds announced by the White House yesterday about how to proceed in the days ahead are at first blush surprisingly reasonable.  If they are actually supported remains to be seen.  I have not had an opportunity to study them myself.  An emphasis is on gradual stepwise changes.  I suspect that most of the critical metrics and capabilities that will justify initial changes are dependent on knowing who is a virus carrier, where they are, and where they have been.  Sadly, it appears that we are far from that capability now. Will we be ready in 12 days till May?  Of course not!  Yes we need to get on to our new normal.  I will be listening to Drs. Fauci and Stack, and Governor Beshear.  Who would you trust your lives to?

Peter Hasselbacher, MD
Emeritus Professor of Medicine, KHPI
President, KHPI
April 18, 2020

Comment: The visualizations on the Tableau Public website are generally updated daily and will differ from the figures included in this article.

Tracking Kentucky’s Covid-19 Epidemic

How will we know when we have won?

[Addendum: I have updated the Tableau Pubic presentation with data from Friday April 17. The increase in cases and deaths was not as great as the Governor feared. It looks to me like the rate of increase in both cases and deaths no longer fits an exponential trend curve. Things look like they are slowing down! Overall however, both measures continue to increase. I will address this new data later.]

I have been tracking and commenting on the number of cases and deaths from Kentucky’s coronavirus epidemic. Despite my best effort’s and some requests, the only data I have from Kentucky proper is what has been announced from the governors office during his evening greetings. Given our national slow start in timely testing for the virus, we must assume that the numbers as presented are incomplete– indeed only the tip of the iceberg. We have been warned over the past two evenings, that as data collection is now more systematized, that tonight we should expect a large number of “catch up” cases. For that reason I have not yet updated the numbers in my earlier articles or on my Tableau Public website. 

In the meantime, I have been evaluating further the approaches I have been using to visualize the numbers released. Because we are still in the exponential expansion phase of this epidemic and because of some unavoidable scatter in the data, it is very difficult to determine if we are bending our new-case curve, let alone flattening it. It is certain that we have not yet reached the peak incidence of this epidemic.

Are we bending our curve yet?
When a curve on a simple graph plot is going straight up, it is difficult to know when it will stop. For this reason, I have begun using what is called a semi-log plot that allows simultaneous visualization both high and low numbers, and transforms an exponential curve into a straight line. This is a technique used by experienced epidemiologists (of which I am admittedly not one).  In doing so, I wanted to feel more confident with the significance of the observation that the data-points of both new cases and deaths from earlier this this week appeared to be falling below the predicted trend-line. That would be nice!  There are lots of understandable reasons why that may not be happening including more testing, clusters of deaths in long-term care facilities, more impatient violations of large group gatherings, and the like.

My goal here.
While I am waiting for tonight’s updated numbers, I wanted to try some alternate methods of visualizing the data and get a feel for how reliable they might be in identifying and impact of what we are all trying to do together. I am feeling more confident that using semi-logarithmic plots and applying exponential regression analysis can be useful in identifying trends.  Because I find that experts commonly, if not by standard, exclude cases before the 100th when attempting to predict the future.  (Early data may be collected in a less formal manner and the randomness inherent in low numbers may offer less predictive value.)  I placed a presentation on my Tableau Public website that steps through my thinking. This is what I expect to try in future articles.

Even with all the caveats.
Looking at the various plots and making assumptions about how infectious agent like Covid-19 might be, I was stunned (but should not have been) at the power of exponential (compound) growth.  I start from a single case from a hypothetical virus and uses purely hypothetical data. Even if a single infected person passes the disease to only one out of a thousand other people, the number of new cases in Kentucky would be in the tens or hundreds of thousands within 40 days.   In addition, I am impressed at how fast things can sneak up on you!

Continue reading “Tracking Kentucky’s Covid-19 Epidemic”

Covid-19 Cases in Kentucky Still Rising Exponentially

I do not believe we are in any position in Kentucky to let go of the alligator we are wrestling. I am still waiting for better clarity of what we are actually facing.

Both new cases and deaths from Covid-19 infection continue to rise sharply in Kentucky. Observed mortality of confirmed cases remains above 5%. Simple daily plots of the numbers of cases by themselves cannot indicate whether we are turning a corner or flattening a curve. Comparison with other states and the nation as a whole does suggest our efforts to mitigate the disease are having an effect. Plotting the data on a logarithmic scale makes visualizing small and large numbers together on the same scale more accessible to analysis. More to the point here, such semi-log plots of the numbers enable us to observe whether the rate of increase in cases or deaths is actually slowing down. Over the past few days, there have been tantalizing suggestions that in fact that both cases and deaths are in fact doing so. Additional reported numbers over the next few days will clarify this hoped-for shift. Nonetheless, we have not achieved plateaus of either daily reported cases or deaths. In fact, semi-log plots of the number of new cases over the 30 days since the 100th new case show continued exponential growth with doubling times of every 5 days. Unless the very recent possible dip in new cases is real, at the current rate of increase, Kentucky will reach 10,000 total cases as early as May 4th. It seems to me that now is not the time to throw in the towel. It is appropriate to begin planning for an eventual data-driven, gradual, and stepwise reversal of our current non-medicinal efforts to deal with this stunningly infectious new disease, but otherwise it’s not very smart to do so precipitously. We have much more to learn about what is happening behind the scenes and our testing capability is still on its baby legs.

Continue reading “Covid-19 Cases in Kentucky Still Rising Exponentially”

Waiting For a Definitive Turn of the Coronavirus Corner In Kentucky

A higher than expected observed mortality rate does not accurately reflect overall case mortality. There are other things to worry about at this point- like some folks selfishly ignoring the prohibition of large group meetings!

[Addendum April 10, 2020: Governor Beshear announced this evening 90 new deaths, the largest in a single day by far.]

Since my article of April 3, the number of tallies of daily cases and deaths has increased. The figure below reflects the numbers released last evening on April 6 by Governor Andy Beshear. Click on the graphic to enlarge it. [An interactive graphic with updated data and alternate visualizations can be accessed here.]

The data underlying this figure can be viewed on my Tableau Public Website using the interactive link above. The data I present are the unchanged numbers as announced at the end of each day at the Governor’s public briefings. It should be noted that these announced counts have been continuously subject to adjustment by the Commonwealth to correct for duplications, late entries due to weekends, or other minor edits, but remain reasonably accurate as we go day to day.

It would be nice to believe that the slight downturn in the green “Positive Tests/Cases” line reflects the “flattening of the curve” that we are all working for. Things should become more apparent over the next few days. Recognize however, that Kentucky is testing many more people for viral infection. Yesterdays announcement noted that some 18,000 people had tests, compared to 2,556 just one week ago! The lesson here is “Seek and ye shall find.” There has always been– and still are– many more infected people in the community than we knew of. Many if not most of these have no or minimal symptoms. We should expect to see the number of new cases go up, especially if the new testing contract with Gravity Diagnostics works as hoped. A continuing increase in new cases should not be used to justify backing off from our efforts to protect each other from ourselves!

The Observed Mortality Rate depicted in the red line above represents the known number of deaths up to that day as a percent of the total number of known positive tests for virus at that time. The fact that this calculated mortality rate is still rising– indeed higher than the mortality rate in places whose epidemics have been running longer– is actually expected and should not cause disproportionate alarm at this point. Because of the lack of earlier testing, the true number of community infections was much underestimated. Only the most severe cases were identified and we expect a higher mortality in this subset of patients.

Recall too that the symptom-free incubation period between exposure and symptoms can range from 2 to 14 days. Similarly, infected people who eventually die do not generally do so on the first day of their symptoms. In a sense then, the Observed Mortality Rate curve is catching up with the number of unrecognized infections that occurred at a time of low testing. This observed mortality rate is surely higher than the actual case mortality rate which is a measure of how many infected people eventually die of their Coronavirus infection. What I expect to occur is that the Observed Mortality Rate will in near weeks begin to decline and level off at a considerably lower level. Epidemiologists all over the world are waiting to see what that level will be and who is most vulnerable.

I would like to have seen a more dramatic decline in numbers nationally, but we were as a country late to the game and it shows. My hometown of New York City, where I learned to be a physician and know its hospitals, is taking a terrible beating. In Kentucky we learned from the experiences of other nations, cities, and institutions and made the hard decisions early. I give our Public Health Department and the Governor’s offices much credit. I am following their advice and you should too.

Peter Hasselbacher, MD
Emeritus Professor of Medicine, UofL
April 7, 2020

If I have made an error in math or terminology or understanding, please help me correct it.