42% of covid 19 deaths were in nursing homes and assisted living facilities

The United States has reported 102,294 deaths from Covid 19 on 5/29/2020.  Each day that passes, more is learned of the virus and how it exactly impacts our society.

A very surprising fact became apparent this week, that was not previously noticed or highlighted..

42% of covid 19 patients were in nursing home or assisted living facilities.  This is an incredible statistic, as the number of patients in these places only account for 0.6% of the total US population.

Nursing homes are residential facilities for those needing 24/7 on-site medical supervision; assisted living facilities are for those not needing 24/7 medical supervision.  An estimated 2.1 million people live in nursing homes and the vast majority (>90%) are over the age of 65.

This finding has many important implications.  First although it has been known for some time that the most at risk group was over 65 with some pre existing conditions, it turns out that being in a nursing home is a significant risk factor.  This means the fatality risk of not being in a nursing home is lower.  Less than 1% of the population accounts for 42% of all covid 19 deaths.

Because nursing homes are remain ‘hot spots’ for covid deaths and cases, it may be difficult for some states or area to achieve mandates such as no covid deaths for a number of days.  The deaths may be limited to within specific nursing homes and not a reflection of areas outside the nursing home.

In addition to maintaining social distancing and handwashing, it remains prudent ot wear a mask if you are around others and most important, elderly in nursing homes and restricted spaces should receive extra care and attention to avoid infection.

In the US, two states, New York and New Jersey and nursing homes have contributed to well over 50% of the covid deaths.  This raises the question regarding the overall effectiveness of general  business shutdowns and stay-at-home policies.  Only additional data and study will be able to sort this all out.

There are an estimate 49 million people in the US over the age of 65.  Over 80% of the US covid 19 deaths are from people over the age of 65.  This would correspond to 81,000 deaths.  This corresponds to a fatality of .2%/million people over 65.

However, the fatality rate of being in a nursing home is 6.76% or 30x higher than not being in a nursing home.

The following presents the percentage of deaths that occurred in nursing homes for all 50 states.  The highest fatility rate was in Minnesota where an incredible 81% of covid deaths occurred in nursing homes and the lowest being NY with 20%.  Interestingly, NY has a low percentage of covid 19 deaths in nursing homes because the number of deaths in NY outside of nursing homes is also the highest in the nation.  This will be discussed in further detail below.

Looking at this another way, nn the basis of covid 19 nursing deaths/million people, New Jersey has the highest with 954 deaths/million and Wyoming is the lowest with 7.  This can be seen in the map below.

Some comments on some key individual states.


Nursing home and assisted living covid 19 deaths account for almost 40% of the 2400 of the states covid deaths.  There are an estimated 155,000 people living in Florida nursing homes.  This is .07% of the population of Florida accounting for 40% of the deaths.



49% of all Covid 19 deaths in California occurred in nursing homes or assisted living facilities.  387 nursing homes have reported deaths with many of them clustered around Los Angeles.

The highest nursing home death toll in the state remains at Redwood Springs Healthcare Center in Tulare County, where 28 residents have died.



In Minnesota, 80% of the covid 19 deaths have occurred in nursing homes and assisted living facilities.  The number of residents in these institutions are less than 1% of the population of Minnesota.

 New York

On May 10, there were an estimated 5300 covid 19 deaths in New York nursing homes and assisted living facilities.  This is almost 3x more than the deaths in the entire state of Florida.  However, so many have died outside of nursing homes (highest in the country), that the percentage of covid 19 in NY nursing homes is one of the lowest in the country.


The U.S. is not an outlier in terms of its nursing home-related COVID-19 fatalities. A study by researchers at the International Long Term Care Policy Network of fatalities in Austria, Australia, Belgium, Canada, Denmark, France, Germany, Hong Kong, Hungary, Ireland, Israel, Norway, Portugal, Singapore, South Korea, Spain, Sweden, and the United Kingdom found that 40.8 percent of reported COVID-19 fatalities took place in nursing homes.

Final note:  I am NOT trying to downplay the seriousness of Covid 19.  Each death tragic.  However, these discussions are hoped to provide information about the numbers and comments you receive by other means in some context.  Also, it is hoped that this information will lead to better policies, decisions and improved health of our country.

Covid 19. Curve is flattened. Hospitalizations Down!

In March, the public was told that closing of nonessential businesses and stay-at-home orders were necessary to ‘flatten the curve’ for Covid 19 cases and deaths.  Besides saving lives, flattening the curve was thought to be necessary as computer models predicted that our hospitals and emergency rooms would not be able to treat all the people necessary.  Along with stay-at-home orders and mandatory business closures, emergency hospitals were built and Navy hospital ships were dispatched to New York and Los Angeles.

This is a long blog that will provide the basis for the observations:

  1.  The curve of covid 19 cases and deaths has flattened
  2.  Hospitalizations are decreasing and the health system was stretched but not overwhelmed
  3. 7 states that did not have shutdowns and stay-at-home orders continue to have low numbers of covid 19 cases and deaths.
  4. Several states have begun to reopen businesses and there has been no signficant overall increase in cases or deaths

It is critical that people continue to social distance, wash hands regularly and wear masks in crowded areas or in enclosed spaces.

After months of enduring business closures, travel restrictions, stay-at-home orders, and the stoppage of nonemergency medical care,  the ‘curve’ has flattened.  It is difficult to make hard conclusions based on the number of reported cases as the total number of tests are going up daily, so it is difficult to tell if there is an increase in the number of reported cases because more people are getting infected, or if the increases are simply due to running more tests.  However, the number of deaths and hospital utilization are two better assessments of how we are doing against covid 19.

On 5/23/2020, there were 98685 reported US deaths attributed to Covid 19.  Note that this number is an estimate.  Several states have revised their fatality reports to lower the number of deaths due to covid 19.  This was done to separate those patients who actually died from covid 19 from those patients who died for other reasons, but tested positive for covid 19.

A granular look at the data shows that New York and New Jersey account for 41% of these deaths even though they only have 9% of the US population.  They are clearly not behaving like most of the other states.  The states with the 4 highest deaths/million people are:

StateTotal DeathsDeaths/millionPopulation (millions)
New York29112149619.5
New Jersey1108312488.9

These 4 states account for 50% of the total US deaths and represent 12% of the population.

It is also reminded that 7 states did not have a statewide ‘lockdown’ and stoppage of businesse.  These states were Arkansas, Iowa, Nebraska, South Dakota, North Dakota, Utah and Wyoming.  All of these states have a low number of cases and mortality rates in comparison with the other states.  These states did close selective activities such as schools, tattoo parlors and gatherings of more than 10.  However, other businesses were allowed to stay open and follow CDC guidelines for social distancing, masks, etc.

There has been no significant increases in deaths or hospitalizations since Georgia, Texas and Florida began their phasing in plans for reopening businesses in the beginning of May.  The following charts shows that overall, the number of daily deaths is decreasing.  The ‘curve’ is definitely flattening.  The reopening of businesses has NOT resulted in an increase in the effects of covid 19.

The 5 states with the highest number of deaths are:

New York281341446
New Jersey102601155

There were 7 states that did not have statewide shutdown of nonessential businesses.  These states did shut down schools and limited crowd sizes.  Some selected businesses were shut down, but, by in large, businesses were allowed to decide whether to follow health guidelines and stay open.

StateDeathsDeaths/millionPopulation (millions)Rank Deaths/mil
North Dakota4255.838
South Dakota4450.940

There has always been concern that when stay-at-home orders are removed, that there would be an increase in the number of cases, deaths and hospitalizations.  Since Georgia, Texas and Florida began to lift restrictions at the beginning of May, there has not been a general increase in cases, deaths or hospitalizations.

Texas began it first phase of business opening on May 1.  The daily deaths from May 1 to May 14, appear to be about the same as between April 14 and May 1 (before the reopening of business).   As reported in a blog about New York, the distribution of cases through Texas varied greatly.   There are 254 counties in Texas that have reported a total of 1527 deaths on 5/23/2020.  However, like in most states, the covid 19 cases are not evenly distributed around the state.   Three counties (Harris, Tarrant, Dallas accounted for 40% of the cases and 53% of the deaths.  7 counties account for 60% of the deaths. 153 counties have reported fewer than 50 cases and less than 10 deaths.  If you live in Texas, it makes a difference where you live.

Texas has a reported deaths/million value of 46.  This ranks Texas 40th in this category.  (NY is first with 1446 deaths/million).  The following graph indicates that the average deaths/day in Texas has been decreasing for the past week, even as more businesses open.

Florida has reported a total of 2233 deaths.  Like Texas, 3 counties account for 54% of the deaths.  Similarly, the data looks similar for Florida after the beginning of phase 1 opening on May 4.  The following graph shows the 7 day average of deaths/day is the lowest it has been since the early April.  Florida reports a fatality rate of 91 deaths/million.  This ranks Florida 28 out of 50.

It is interesting to compare this data against 3 states who have maintained stay-at-home and business shutdown orders.  These states have announced that they will maintain their stay-at-home orders for another month or more.

StateDeathsDeaths/millionRank deaths/mil

These values are comparable to those states that have begun to reopen businesses.  Again, it is reminded that these are averages for the entire state.  Within each state, there are a few ‘hot spots’ that have a higher number of deaths and there are many more areas which have very few deaths.


The number of covid 19 patients being hospitalized is decreasing in most areas.  It is important to remember that a large factor in issuing mandatory business shutdowns and stay-at-home orders was to avoid overwhelming the healthcare system predicted by computer models.  Fortunately, the models have been largely incorrect.  There have been no reported cases where a patient could not be admitted to a hospital or have access to a ventilator if needed.   Emergency hospitals set up in New York, Louisana, and California were essentially not needed.  The hospital ships USN Comfort in New York and USN Mercy in Los Angeles received very few patients.

At the current levels, even if there is a modest increase in cases due to business reopening., there appears to be sufficient available space in hospitals.

Early assessment of business reopenings.  The early indications are that there has not been a significant increase in the number of cases, deaths or hospitalizations in Georgia, Texas and Florida.  Those 7 states that did not have business shutdowns or stay-at-home orders continue to exhibit low numbers of infections and deaths.

In each of these states, there are definitely ‘hot spots’ that still have high numbers of infections and deaths, but the majority of the states seem to have decreasing number of cases and deaths.  How these states are managed will determine the success reopening.  Each state must establish a plan that reflects the level of infection and fatalities of local areas.  This means that not all parts of each state will be operating under the same guidelines.   ‘Hot spots’ must be reopened more carefully and monitoring will be key.

When businesses open, it will be the people that determine the success of reopening.

People must maintain social distancing.

People must continue to wash their hands regularly.

If you are feeling sick, don’t go out or go to work and don’t; come into contact with anyone.

Wear a mask if you are an enclosed space particularly if you can not maintain social distancing at all times.

The indications are that businesses can safely open if people remain vigilant and follow the guidelines.

The ‘curve’ has been flattened and the hospitals are not overwhelmed.  Given that these were goals of the shutdown, business reopening should begin cautiously and the people must be responsible for their own actions.




Covid 19 Testing. The good, bad and unknown.

One of the most talked about issues around Covid 19 is testing.  Everyone seems to want a test.  However, little is said about the details of the tests, such as kinds of tests, good/bad tests and what do you do with the results.  The answers to these questions will help answer the questions about how important the tests are to reopening of businesses of keeping a business open.

A reliable, fast diagnostic needs to be established and available to manage the reopening of businesses.  The ability to identify infections before they become clusters, or clusters before they become outbreaks will be significant in how successful we will be in reopening businesses.

The tests.  There are two kinds of tests being talked about in the news and the reporting does not always make it clear which test they are talking about.  In most cases, they are talking about a DIAGNOSTIC test.  A diagnostic test will determine whether or not the Covid 19 virus is present at the time of the test.  The other kind of test is generally termed a serology (blood) test.  The serology tests determine the presence of antibodies that are created if the patient had been been previously infected with Covid 19.

Diagnostic Testing.  Most diagnostic tests use a method abbreviated RT-PCR (Reverse Transcription-Polymerase Chain Reaction) that will detect the presence of the DNA from the virus.  There are several manufacturers of these tests around and THEY ARE NOT THE SAME in reliability.  The difference in testing methods and reliability should be remembered when analyzing data from different sources.

In most cases, the testing being discussed are the results of diagnostic testing.  That is, diagnostic methods are used  when the daily number of confirmed cases is provided.  For instance, diagnostic tests were used to report the 1,391,316 confirmed cases of Covid 19 in the US (5/12/20).

A diagnostic test will determine if a virus is present at the time of testing.  It can not tell if the person was infected and then recovered nor is it predictive of if the patient will get the disease tomorrow or any time in the future.    If you are showing severe symptoms, you should go get medical attention whether or not you have been tested.  If you are feeling ill in any way, you should stay-at-home regardless of whether or not you are tested.  If you test negative, there are also uncertainties.  You may have been infected just before the test and the virus has not spread enough to be detected, or you could get infected tomorrow.  If you have no symptoms but are positive in a diagnostic test, you are among the 80% of infected people who have no or minor symptoms.

Serology – Antibody Testing

Serology tests are blood-based tests that can be used to identify whether people have been exposed to Covid 19 by looking for specific antibodies.  The mechanisms for antibodies was topic of an earlier blog regarding vaccines.  Covid 19 Vaccine. Where are we in the process? How will they work? What’s taking so long? The presence of antibodies would indicate that the patient had been infected with Covid 19.  As mentioned above, because the vast majority of people who are infected have no or minor symptoms, antibody testing is the only way to determine how many people are actually infected.  Earlier blogs have indicated that the actual number of people infected as determined from antibody testing is up to 20x higher than the number of infections detected with diagnostic testing.New York: Nearly 3 million infections – not 276,000

It is important to know:

  1. It is not known if the presence of antibodies makes the patient immune from further infection.
  2. If the patient does become immune to Covid 19, it is not known how long the immunity will last.
  3. The immediate benefit from antibody testing will be to determine how many people were infected.

Specificity and Sensitivity.  These are KEY factors in the reliability of tests but are seldom discussed in the news.   Specificity is a measure of how reliable the test is.  In other words,  if the test indicates you have the disease, do you really have the disease?  Or is the test somewhat unreliable because it can provide a positive result when you don’t have the disease.  This is termed a false positive result.    Specificity is a measure of how many false positives a test will give.  A test with a specificity of 80% means that only 80% of those who tested positive actually are positive.  20% show an incorrect positive result.

Sensitivity is a measure of how reliable the test is, if the test says that you are negative.  It is a measure of the false negatives.  A test with a sensitivity of 90% means that 90% of the people who test negative, truly do not have the disease but 10% of the negatives are really positives and have the disease.  Some of the reports from South Korea suggests their test had a sensitivity of 80-85%.

Each test should be evaluated for both it’s specificity and sensitivity.  It is possible for a test to have a high specificity but a low sensitivity.

These seem like details, but a 5% false negative means that if 1,000,000 people test negative, there are really 50,000 people who are actually infected.  Labs, doctors and patients should be very aware of the specificity and sensitivity of the tests they are administering.  There are over 20 different tests being conducted around the world, each with it’s own, sometime unknown specificity and sensitivity.  This makes comparative data very difficult.

As the choice of what test to run is determined locally (state, county, hospital), differences in specificity and sensitivity between tests likely exist.

There is an old joke in testing labs about what level of service a client can request. For each test, you can choose how fast you get the results back, how accurate the results are and the cost of the test.  Unfortunately, you can only choose two of the three choices.  This is true for Covid 19 testing as well.

Test Approval Process.

It would normally take more than a year or more to get a diagnostic test to get FDA approval.  This is because of the number of patients and time in clinical trials that are required to demonstrate sensitivity and specificity.  Under the FDA Emergency Use Authorization guidelines, manufacturers only need to test 30 laboratory samples and demonstrate 95% specificity (positives) and 100% sensitivity (negatives).  That means that the test must detect 95% of the samples that contain the virus.  A 100% sensitivity means that there can be no false negatives.  I am unaware of any test whose accuracy has been evaluated by an independent organization (eg not the company who manufacturers the test).

For diagnostic tests, it is important to know that the virus used in these laboratory tests are not from patients but from lab sources.  It is also not clear that all labs are using the same concentration of virus in all of their tests.  Last, the tests are conducted under laboratory conditions without issues of sample collection and other factors present when testing patients.  There is no requirement that any clinical data from patients be part of the Emergency Use Authorization approval process.  This does not mean that the tests are unreliable, it just means the tests have not been as fully evaluated as they would have in an non-emergency environment and we don’t know the number of false positives and negatives we are getting (other than the data supplied by the manufacturer).

There are also factors not related to the actual diagnostic test that can effect the test results.

  1. When the patient was infected.  If the patient was infected very recently, there may not be enough of the virus to detect.
  2. Where the virus is. Most tests are from nasal swabs.  However, as the disease progresses, the virus moves into the lungs, so the viral load in the nasal passages goes down.
  3. Incorrect sample collection. If the nasal swab is too superficial (not deep enough) then the virus may not be detected.
  4. Rapid testing after collection. The tests usually must be run within 8 hours, unless it is refrigerated in which case it much be tested within 72 hours.  Testing outside the windon decreases the chance of detection.

More attention must be paid to determine the specificity and sensitivity of all tests.  Too many false negatives will release infected people into the population and too many false positives can overwork or overload the health care system.  The situation is made more difficult with the increasing number of new tests being introduced in the US and around the world.

The same specificity and sensitivity issues apply to the Serology-antibody tests.  Again, there are over 20 different tests of this type being run around the world.  Like the diagnostic tests, they are being approved for use under emergency use authorization so specificity and sensitivity values are being supplied the manufacturer who makes the tests under laboratory conditions.  This does not make the tests unreliability and I am not criticizing the manufacturers, but independent evaluation under normal clinical evaluation guidelines should be done.

It is a difficult time as development and distribution speed is now prioritized over normal safety and effectiveness procedures.  This undoubtedly has allowed the use of some tests that would not have been approved under more normal conditions.

There are two examples of what can happen if specificity and sensitivity are not well established.  In May, the United Kingdom reported that it had purchased 2 million antibody test kits from China for $20 million (₤16 million).  However, the purchase was apparently made before independent UK analysis was done.  When the kits were received, independent tests showed both too many false positive and too many false negatives.  The 2 million kits are useless. https://www.bloomberg.com/news/articles/2020-04-07/new-test-hopes-dashed-as-u-k-finds-antibody-kits-don-t-deliver

The city of Laredo, Texas also bought 20,000 antibody test kits from China for $500,000.  These kits were not approved by the FDA in any way.  The city took a risk to secure antibody testing.  Once received, the tests, like the ones purchase in the UK, turned out to be unreliable and useless.  The kits were, nonetheless, seized by the FDA.

It is not my intention to criticize the incredible speed at which these highly complex tests are being developed. I have not discussed the actual technology, but it is quite incredible.  We usually just see a box or a device without knowing the complex test that is going on inside.   The balance of speed of development and reliability is a point the world is trying to find.  The purpose of this blog is to discuss the factors involved in testing that have not been often discussed and to provide some background to the daily news regarding testing.








Covid 19 vs Spanish Flu: A Societal Comparison

Although a century apart there are often comparisons made between the Spanish Flu of 1917-18 to today’s Covid 19 pandemic.  Often, the experiences of the Spanish Flu have been mentioned/used as justifications or reasons behind Covid 19 policies.

Despite being the epidemic that caused the most American deaths, the details of the Spanish Flu are not well known and the details of how the disease was handled are even less well known.  This blog provides a brief summary of the history, effects and management of the Spanish Flu, and the lessons that can or can’t be learned from the experience.  This discussion will not compare the technical differences between the two diseases.

The actual number of cases and deaths due to the Spanish Flu are not known because of relatively poor record keeping at the time, it was a global pandemic and it happened in the midst of World War I.  However, many estimates indicate over 500 million people worldwide were infected and somewhere between 30 and 100 million died.  In the US, it is estimated that 25 million (28% of the population) were infected causing 670,000 deaths.  In contrast with Covid 19, the Spanish Flu was most deadly for those ages between 20-40.  The mortality rate for 15-34 year olds in 1918 was 20x higher than any other previous year.  The mass movement of millions of soldiers and conditions of World War I contributed to the wide spreading of the disease.  An estimated 50% of the US soldiers who died in Europe during the war died from the Spanish Flu.

This is a long blog, but if you read on, there are 5 sections.  The history section is a bit long but you can skip down to the other discussions as your interests guides you.

  1. History of the Spanish Flu
  2. How the Spanish Flu was handled by the Government
  3. 1917 vs 2020.
  4. Quarantines
  5. Lessons Learned

History It is important to note that Spanish Flu happened during World War I. At the beginning of World War I in 1914, President Woodrow Wilson declared that the US would remain neutral in the conflict.  However, in 1917 there were a series of incidences of involving US lives and ships being destroyed by Germany which led to the US declaration of war on April 2, 1917.  However, preparation of US troops was well underway before the declaration was made.  The war would play a large part in spreading the disease around the world.

It is not specifically known what the original source of the Spanish Flu was. That is, it is not known where the first case in the world appeared.  There are theories that the disease began in France in 1916 or China of Vietnam.  Many theories also suggest that the disease could have started in the US (although it is not known how it got to the US).  One of the earliest (some say the earliest) report of this disease was January 1917 in Haskell County, Kansas.  An outbreak of an unknown disease was so severe that it was reported to the US Public Health Service.  This is believed to be one of the first recorded notices anywhere of an unusual respiratory disease.  Several men from Haskell went to a military, Camp Funston in central Kansas.  On March 4, days after they arrived the first soldier known to have the what we now call the Spanish flu, reported ill.  Within 2 weeks, over 1000 soldiers on the base were admitted to the hospital with thousands more sick in the barracks.  38 soldiers died.  It is likely that infected soldiers from here infected 24 of 36 large training camps, sickening thousands and killing hundreds.  Many of these infected soldiers then brought the disease to Europe.  In June 1917, 14,000 US troops landed in France. By May 1918, a million US soldiers had landed in Europe.  By the end of the war on November 11,1918 more than 2 million American soldiers had served on the battlefields of Europe.

The ‘first wave’ outbreak at Camp Funston and in Europe through early 1918 did not cause serious concern because although many were infected, there were relatively few deaths.  For instance in 1918 the British Grand Fleet reported over 10,000 sailors had fallen ill but only 4 had died.  It was not until the King of Spain, Alfonso XII, contracted the disease that the disease became noteworthy.  Spain was also neutral in the war and was free to publish information about infections without censorship from other countries.  Because most of the early detailed reports were from Spain, it became known as the Spanish Flu (even though it did not begin there.)

In August 1918, the second wave, more deadly than the first, began in areas of Europe.  It is speculated that the ‘first wave’ virus had mutated into a more lethal version.

In late August 1918 military ships departed from the English port of Playmouth carrying troops with a virulent form of the Spanish Flu and went to cities like Brest, France, Boston, USA and Freetown Africa.  In Boston, shortly after their arrival sailors and civilians marched together through the streets of Boston for a ‘Win the War Rally’.  Soon, the surrounding Boston area and New England would feel the full force of the disease.  In September 1918, a Navy ship from Boston carried infected sailors to Philadelphia.  Although sailors began to die within days of arriving at Philadelphia, city officials did not truthfully report the deadly disease.  In fact, they publicly dismissed the seriousness of the disease and  on September 28, they famously held a large parade in the middle of the city attended by an estimated 200,000 people.  Within 72 hours of the parade, every bed in Phialdelphia’s 32 hospitals were filled and in a week, 2600 Phildadelphians had died of the Spanish flu.  A week later another 4500 had died.  By March 1919, over 15,000 Philadelphians had died from the disease.

The disease spread all over the country from the Atlantic to the Pacific and from Canadian to Mexican borders.  Spain, Britain and France were all particularly hit hard with the disease but the disease also spread to Asia, Africa, South American and the South Pacific.

It is highly likely that the war conditions contributed significantly to the spread of the disease.  First, millions of soldiers from the US were transported to Europe.  Once in Europe, soldiers and civilians were often in cramped, damp and crowded conditions making the spread of disease easy.  The poor sanitation and malnutrition also helped to spread the infection. Further, there were vast movements of people both civilian and military due to fighting. During the summer of 1918, many troops returning home brought the disease back to the countries they came from.    All of these factors likely contributed significantly to spread of the disease.

It is interesting to note that is speculated that President Woodrow Wilson was infected during the Versaille Peace Conference at the end of the war.  This possibly contributed to Wilson accepting some surprising terms in the treaty.

Overall, the Spanish Flu is likely to be deadliest epidemic in the history of world.  Estimates are that 1-3% of the world’s population died from the Spanish Flu.  So many younger people died in the US in 1918 that the average US life expectancy was reduced by 10 years.

It is not clear why the second wave of the virus was so much more lethal than the first.  There is some speculation that there may have been a mild and deadly version of the virus, but this has not been definitively confirmed.  In the ‘developed’ world, the mortality rate was generally believed to be about 2%.  In other counties, the mortality rate has been estimated to have caused up 14% of a population (Fiji islands) to die.

Eventually, toward the end of 1918 the number of deaths caused by the virus began to decrease.  This is believed to be because there were so many people that had already been infected and/or the virus may have mutated again to be less invasive to the lungs.  It eventually ‘devolved’ to be part of the seasonal flu.  There was never a vaccine developed for the Spanish Flu.


How was the Spanish Flu handled by the state and federal government? There was no national policy for dealing with the Spanish Flu. It was left to the states to come up with how and when to deal with the disease.   It was common practice for politicians, administrators and those responsible for the public safety to deny, deceive or out right lie about the dangers of Spanish Flu. City and government officials did not disclose the danger to the general public so that public spirits would not be diminished and that support for the war would be encouraged.  That’s why the parades in Boston and Philadelphia were held despite the fact that city officials were aware of the potential danger from the Spanish Flu.

There was policy that started with President Woodrow Wilson that authorized, even encouraged lying to the public.  When the United States entered the war, Woodrow Wilson created the Committee on Public Information, which was inspired by an adviser who wrote, “Truth and falsehood are arbitrary terms. The force of an idea lies in its inspirational value. It matters very little if it is true or false.”

Official government posters and advertisements urged people to report to the Justice Department anyone “who spreads pessimistic stories…cries for peace, or belittles our effort to win the war.”  The real fatalities and illness of the Spanish flu fell into this ‘pessimistic story’ category.

An example of this is that the director of Public Health in Philadelphia, continually reassured the public that the illnesses being reported were ‘contained’ or would be decreased and that it would ‘nipped in the bud’.  Under these misdirections,  he authorized and put on the large parade that infected thousands of Philadelphians.  Across the country, the lie that disease was nothing to worry about was commonly told my officials.  This lie was told in large cities like New York and Los Angeles as well as less populated areas like Arkansas.  Even the U.S. Surgeon General Rupert Blue said, “There is no cause for alarm if precautions are observed.”

Eventually, the people caught on because the true effect of the Spanish flu could not be hidden.  For instance, 53% of San Antonio, Texas got infected and death could come quickly and dramatically.  It was also evident how serious the disease was when towns ran out of coffins and people could not be buried fast enough.

It was only when the threat of the flu could not be denied that procedures to try and curb the infection (flatten the curve in today’s terminology) were put into place.  Each state and city had their own instructions but they included a mix of the following procedures.

  1. Wear masks
  2. Don’t shake hands
  3. Stay in doors
  4. Closed schools and theaters and limited public gatherings

There were places that instituted these practices early, such as San Francisco, St. Louis, Milwaukee and Kansas City.  These early adopters had 30% to 50% lower disease and mortality rates than cities that enacted fewer restrictions and/or started their restrictions later.  It should be noted that other than schools, theaters, churches and bars there were few other businesses that were forced to shutdown.  Compliance to these restrictions was highly variable from city to city and enforcement was often a problem.

1917 vs 2020.

The world is a difference place now that it was in 1917.  In 1917 the world was at war and millions of people were being moved to fight or flee from the war in Europe.  The conditions of the war overcrowding, dampness, malnutrition provided ample opportunity for infections to spread.  Millions of people were transported into and out of the US that were infected with the Spanish flu.  Especially, after the war infected soldiers returned to their homes all over the US.  The movement of millions of people in a short period of time is exactly the opposite of a travel ban.

The political atmosphere was generally not to tell the truth regarding the disease and to downplay it’s seriousness.  This lack of candor was accompanied by organizing large gatherings of people despite knowing that there was a serious infectious disease in their presence.  It was not easy for the public get accurate information about the effects of the Spanish Flu.

There was a shortage of doctors compared today but the shortage was made even worse in the US as a large number of doctors were in the Army and overseas.  There were also fewer hospital beds per capita in 1918.

The 1917 level of medical knowledge and medical technology was very low compared today.  The ability to test for the disease was virtually nonexistent in 1917.

Social distancing and masks appear to have been effective in 1917 and appear to be effective now.  However, the shutdown of nonessential businesses around the world has never been done before.  Given all the other societal and technical differences between 1917 and now, it is not clear how effective a nationwide shutdown of businesses in 1917 would have been with hundreds of thousands of infected people returning home.

Unlike the situation in 1917, there is a lot of information regarding Covid 19 from around the world easily accessible via the internet and television.  Unlike 1917, the statistics of Covid 19 are posted often and the public has direct knowledge of the effect of the disease in their city, county and state.


The most effective efforts had simultaneously closed schools, churches, and theaters, and banned public gatherings along with the use of masks.  There were no large scale shutdowns of other businesses, although some places staggered business hours.  At later stages of the epidemic, they tried to isolate those who had the disease but I can not find many efforts to quarantine (isolate) those who were not infected.


Public officials in charge of public health must be honest with the public and give truthful assessment of the disease.

Disease must be recognized and mitigating policies must be put in place to slow the spread of the virus.

You can slow down and reduce infections if you do social distancing and wear masks.

No gatherings of large numbers of people if you can not also social distance and wear masks.

We should be wary of how decisions are made and be aware if a decision is politically driven or public health driven.

There were many societal differences between 1917 and 2020.  The main difference being World War I and the associated movement of people, along with crowded and poor conditions.  The 1917 public was not well informed of the number of infections and number of fatalities caused by the Spanish Flu.


New York Covid. Most new infections occuring in the home.

66% of recent admissions to New York were patients who were staying at home.

Yesterday (5/5/20), Governor Andrew Cuomo reported on results of studying patient information of recent Covid 19 admissions to New York hospitals.  The data was from 1300 patients who were admitted for Covid 19 at 100 hospitals across the state.  It was very surprising that the majority of these patients were adhering to the stay-at-home policy.  The results raises the question of how beneficial stay-at-home polices actually are.

A granular look at the results provide the following:

83% of the patients surveyed were either retired (37%) or unemployed (46%). 

17% were employed.

4% said they were taking public transportation.

18% of the patients came from a nursing home. 

The vast majority of the patients were over the age of 51.

The ethnic distribution is provided in the table below.

Ethnicity% Population% Covid Infected

These results are opposite to what was expected.  It was expected that a high percentage of the new covid 19 patients would be essential workers (not stay-at-home) or those that took public transportation.  Those that were employed and/or taking public transportation were the least effected people. It was unexpected that 83% of the patients would be retired or unemployed.

New York has ‘flattened the curve’ by showing decreases in infections, deaths and hospitalizations.  For instance, for the entire New York state, there were 15,021 hospitalizations on May 22 and there were 8656 on April 6.

Public transportation was not associated with new covid 19 cases.  This result is in line with Japan’s low infection and death rate despite running a fully operational and heavily used mass transportation system.The Japan Experience: No mass shutdown. No mass isolation. Fewer cases and fatalities. What can we learn?  The results also suggest that blacks may have a higher risk factor as blacks had 21% of the new infections but are only 14% of the population.  The number of patients coming home from nursing homes is also very high.  These are people who are at the most at risk and should be the most protected.

A warning that this study was based on only 1300 patients but it raises important questions.  A larger number of patients would have to be surveyed to confirm these surprising results.  Also, there needs to be more granularity to the data.  For instance, the type of dwelling, single family home, apartment, condo, number of people in the same residence etc.

This is not an argument against stay-at-home policies.  The study is too small and not detailed enough to come to this conclusion.  However, it does indicate that it may not be as simple as ‘stay-at-home and you won’t get infected’.  In fact, this study suggests that in this group of patients, if you stayed-at-home you were more likely to be infected.  Perhaps this is not an ‘all or nothing’ policy.  Unclear why stay at home does not appear to be currently effective in NY but Japan with no stay-at-home policy has low infection and death rates.  Only a larger, better designed study will answer this question.

For now, this is another piece of the puzzle.



Covid 19 vs Flu: Granular Data Analysis

There has been much contention when Covid 19 is compared to the seasonal flu.  One view is that it is much worse than the flu and the opposite view is that it no worse than a bad flu season.  Here is a granular look at the numbers.

By definition, flu is defined as a contagious viral infection of the upper or lower respiratory track.  Deaths caused by flu are similar to Covid 19 caused deaths in that it they induce fatal respiratory failure.  Flu is caused by more than one type of virus.  This definition is broad and Covid 19 could be considered a flu by this definition.  However, is really isn’t important if Covid 19 is classified or considered a flu or not.

A more important question is “Does Covid 19 have a higher fatality rate than the flu?”

The CDC tracks the number of flu infections and deaths each year and the data is available online.  The flu season generally occurs between November and February of each year.  Since 2010, the number of deaths attributed to the flu have varied from a low of 9000 in the 2011-12 season to a high of 61,099 in the 2017-2018 flu season. There was an estimated 45-60 million people infected with the flu in 2017-18. Since 2010, there have been an average of over 37,000 deaths per flu season.  This is an important benchmark because the country did not shut down under these conditions.  It serves also serves as a benchmark for comparison to Covid 19 to answer the fatality question.

The flu is more fatal to those over 65.  In the 2017-18 season,  50,903 of 61,009 (85%) flu deaths were in people over the age of 65.  Again, there were not programs to especially protect this older segment of the population.  It is also interesting to note that 80% of the deaths caused by Covid 19 are also in the over 65 age group.

On May 4, 2020, there were 69198 confirmed Covid 19 deaths in the US.  These deaths occurred between February and May (3+ months), a bit shorter than the November-February flu season.  This is also higher than the 61,099 flu deaths from the 2017-18 season.  The number of Covid 19 deaths is still rising so there it is clear that Covid 19 has caused more fatalities than the 2017-18 flu.  The final number of Covid 19 deaths has yet to be determined.

However, a more granular look at the data provides a further perspective.  Specifically, comparing the number of flu deaths in 2017-18 with Covid 19 deaths, by state.

In a previous blog, it was clear that the distribution of Covid 19 deaths was not uniform across the US.  In fact, New York and New Jersey account for 48% of all Covid 19 deaths while only having 9% of US population.  That is, 32,800 of the Covid 19 deaths were from New York and New Jersey.  The rest of the country had 36,584 deaths.  This is significantly lower than the 61,099 flu deaths in 2017-2018.   In  other words, the statistics from New York and New Jersey make Covid 19 more deadly than the flu.  However, if you do not live in New York, or New Jersey, Connecticut and Massachusetts, there will likely be more flu deaths than Covid 19 deaths. Granular Covid 19 data. How NY and New Jersey effect US Covid 19 statistics and why it matters.

Only 12 states have more Covid 19 deaths than  they did in the 2017-18 flu season. https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm


The following graphs show the 5 states with highest numbers  Covid 19 fatalities and the number of flu fatalities.  The Covid 19 deaths (red) far surpass the number of flu deaths (blue).

In the other 38 states, more people died from the flu than Covid 19. 

In 29 of these 38 states, there were 2-37 times more flu fatalities than Covid 19.

The following graphs shows a graph of several of the larger of the 38 states states that show the number of 2017-18 flu deaths far surpasses the number of Covid 19 deaths These include Georgia, Texas and Florida which have begun to reopen business.  Some highlights: California (2215 Covid 19 deaths vs 6340 flu deaths).  Florida (1399 Covid 19 deaths vs 3057 flu deaths).  North Carolina (442 Covid 19 deaths vs 2076 flu deaths).

This make answering the question of whether Covid 19 is more ‘deadly’ than the seasonal flu more difficult to answer in an absolute sense.

There are other differences between the diseases.

There is little doubt that Covid 19 is more contagious in that one Covid 19 patient infects more patients than one flu patient.  However, the magnitude of this difference depends on the assumptions used to do the calculation.

It appears that up to 80% of those infected with Covid 19 have no or minor symptoms.

It also appears that respiratory failure, if it comes, can come faster with Covid 19 than the flu.

The actual number of people who have been infected with Covid 19 is still being determined.  This value will come from continued antibody testing of the general population. However, the preliminary numbers indicate that the number of people infected with Covid 19 will be less than the 45-60 million who can get infected with the flu.

Last, it must be remembered that the flu mortalities are with the use of a flu vaccine.  As the flu vaccine is highly variable in its effectiveness (15-50%), it is probable that the flu fatalities could be higher than Covid 19 (including NY and New Jersey) if there were no vaccine.  However, with each antibody study, the number of people who have been infected with Covid 19 seems to increase.  This drives the overall fatality rate down.  From the antibody data available, the fatality rate is area dependent but is clearly well under 1%.  This is significantly lower than the 10-15% rates being discussed in February.New York: Nearly 3 million infections – not 276,000

The flu comes back every year and tens of thousands die.  The ‘herd immunity’ effect has not taken effect despite having over 50 million people a year being infected and the use of a vaccine.

The answer to the question ‘does Covid 19 have a higher fatality rate’ does not have a simple answer.  The current best answer is that it depends on where you live.  If you live in New York or New Jersey, Covid 19 clearly has a higher fatality rate.  However, in most of the other states, there were many more flu fatalities in 2017-18 (even with a vaccine) than there are Covid 19 deaths.

As more and more restrictions are removed, it is very likely that the results will vary depending on location.  As you read about the numbers, remember they are not the same everywhere, so beware of conclusions based on national numbers being applied to everyone, everywhere.

As more and more data is gathered, it appears that in states other than New York and New Jersey and perhaps one or two other states, the seasonal flu can be just as deadly if not more deadly than Covid 19.

These numbers are encouraging.  We have lived with the ravages of the seasonal flu every year and it appears that we are on our way to making Covid 19 behave similarly, except for perhaps the New England states.

Granular Covid 19 data. How NY and New Jersey effect US Covid 19 statistics and why it matters.

We receive daily report of the number of cases and fatalities caused by Covid 19 for the entire world.  As businesses begin to open, it is important to know that the risks of infections is NOT the same everywhere.  There are clearly areas where infections are likely and others where infections will be very unlikely.

As an example, the numbers of cases and fatalities in New York and New Jersey dominate the statistics for the entire US.

On 5/4/2020, the US statistics were:


A more granular look.  New York state has reported 24,874 deaths.  This is 36% of all the deaths in the US.  NJ has reported 7926 deaths.  Together New York and New Jersey account for 48% of all the deaths in the US.  In fact, if New York and New Jersey were a country they would have a combined 32800 deaths and would have more deaths than any other country in the world.  New York and New Jersey only have 9% of the US population yet account for 38% of Covid 19 deaths.  In other words, the number of deaths shown in the graph would be reduced by half if New York and New Jersey were not included.

It is reminded that these are the confirmed cases of Covid testing.  As reported earlier, the actual number of infections, as determined by antibody testing, in New York state is over 2.6 million.  Antibody testing across the US has not been completed but the distribution of those actually infected may be different from the current pictures.New York: Nearly 3 million infections – not 276,000

New York state is also an interesting example of how different the Covid 19 impact can be in different regions of the same state.  Yesterday, NY reported on the results of antibody testing of 15000 patients from all the different regions of NY to assess the actual number of people who have been infected with Covid 19.  In New York City, Westchester or Long Island over 11% of the people have been infected (19.9, 13,8 and 11.4 respectively).  However if you live in any other area of New York, less than 3% of the population has been infected.

All 50161
New York1268
New Jersey897
Washington, DC377

However, 32 states have fatalities of less than 100 deaths/million people.

12 of these states have less than 50 deaths/million.

Although each death is tragic, fatality rates of less than 100/million are in the range of (and perhaps less than) seasonal flu values.

All of this data clearly shows that there are states and areas within states where Covid 19 is far more deadly than others.  Fortunately, most of the United States does not share the same high mortality rates.  The risk for opening businesses is clearly not the same for every area.

This does not mean, however, that precautions should be taken as these business openings continue.  There is little doubt that there will be some additional infections as more personal interactions occur but grocery stores, pharmacy and other essential businesses have remained open all of this time and I’m unaware of any outbreaks from these sources.  Also, countries like Japan have low infections and fatality rates without having to shutdown the country.  Also countries like Sweden which has instituted far fewer restrictions has not fared worse than countries with strict lock down policies. Sweden: A Different Covid 19 Plan I’m just pointing out that there is hope for reopening businesses without reigniting infections. The Japan Experience: No mass shutdown. No mass isolation. Fewer cases and fatalities. What can we learn?

It will be crucial to be vigilant to identify any signs of outbreak and infection and do ‘infection tracking’ for infected persons to go into quarantine.

Monitor and adapt.  I believe that a good strategy would be for each business to monitor any infections occurring related to their business.  If infections seem to be low or not occurring, policies may adapt to be less strict.  If infections seemed to increasing and related to business then policies may adapt to be more restricitive.  In each case, monitor and adapt will allow the implementation of the best balance of health safety and business.

Know the specifics of the area where you live.  The general numbers you hear in the news may not reflect where you are.  More knowledge will help manage your risks and fears.


Remdesivir approved for Covid 19. How effective is it?

Today, the FDA authorized the emergency use of remdesivir for the treatment of patients who have Covid 19 symptoms severe enough to be given supplemental oxygen or placed on a ventilator.  Remdesivir is an emergency treatment for severe cases of Covid 19 and is not a cure or a vaccine.  https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-issues-emergency-use-authorization-potential-covid-19-treatment

Let me start with the conclusion.  According to the announcement of results from a NIAID study,  Remdesivir appears to shorten the average recovery time in patients with severe Covid 19 symptoms.  It does not appear to reduce fatalities and there may be adverse side effects.  The benefit to patients with less severe symptoms of Covid 19 are unknown.  Although any helpful treatment is welcome and needed, the actual impact of remdesivir is not clear.

The FDA issued the approval under the Emergency Use Authorization (EUA) .  This allows the FDA to grant authorized use of medical treatments and products during medical emergencies which are NOT approved by the FDA under normal regulatory procedures.  The EUA allows the FDA to approve a product for emergency use to short cut the time to market to address a medical emergency.   EUA does not mean that the FDA has determined remdesivir to be safe and efficacious, but its ‘safe enough to try’ under emergency circumstances. The FDA grants EUA based on the information they have on hand to determine that the use of the product will be more likely be beneficial than harmful.  There is no adequate, approved, and available alternative to the emergency use of remdesivir for the treatment of COVID-19.  The authorization can immediately be withdrawn if on more widespread use, results are not favorable.

What is remdesivir?  Remdesivir is a molecule that was developed in the pursuit of treatment of the Ebola Virus.   Ebola Clinical trials with remdesivir were conducted in 2013-2016.  Remdesivir was approved for Ebola treatment.   In 2018-2019 another outbreak of the Ebola virus occurred but during that time remdesivir use was stopped when alternative drugs were found to be more effective.  However, until this week,  the clinical efficacy with humans with Covid 19 has never been established by accepted clinical trial protocols.


Remdesivir has had mixed results in treating Covid 19 patients with severe disease.  Severe disease is defined as patients with low blood oxygen levels or needing oxygen therapy or more intensive breathing support such as a mechanical ventilator.  Some reports seemed to indicate that remdesivir reduced the time to recovery for seriously ill Covid 19 patients, while other studies showed no benefit.  None of the studies have shown a significant difference in fatality rates and some serious adverse events have been reported.

NIAID Study. Two recent reports of clinical trials have been recently reported.  The National Institute of Allergy and Infections Diseases (NIAID) issued a preliminary  report on a randomized, double blinded clinical trial comparing remdesivir with a placebo (a pill that looks like remdesivir but doesn’t actually have remdesivir in it)  in 1063 Covid 19 patients.  This type of study design is meant to minimize possible bias by the doctors, patients and other factors to make the best determination if the drug is better than doing nothing.

The group that received remdesivir recovered in an average of 11 days compared to 15 days for patients who received the placebo.  The remdesivir group had a lower mortality rate than the placebo group (8% vs 11% respectively) but this difference was not statistically significant.  This means that if a larger study is done, there is a chance that this apparent benefit will disappear.  It is important to note that this was a summary report and the full details of the study have not yet been published, provided or peer reviewed.

It appears that the FDA provided the Emergency Use Authorization based on this data that, for seriously ill Covid 19 patients, remdesivir reduced the recovery time and average of 4 days (11 days vs 15) than patients who received no treatment.  As the details were not provided, it is not known what percentage of the patients had their recovery reduced nor do we know the range of recovery times involved.  We also do not know how the demographics of the patients in the trial compared to the general public in terms of age, gender, ethnicity, pre existing conditions etc.  These details will hopefully be disclosed when the full study results are published.

‘China Study’ Almost simultaneously, a paper in the British medical journal Lancet, became the first published (the NIAID paper above has not been reviewed and published), peer reviewed article with a randomized, double blinded, multicenter clinical trial comparing remdesivir to placebo.  Note: this paper is often referred to as the ‘Chinese Study’ as many of the authors were Chinese and the study was partially funded by the Chinese Academy of Sciences.  However, the research  was done by a collaboration of a large group of researchers from several universities in China, United Kingdom (Cambridge, Oxford) and the USA (Virginia) and funded by UK and USA sources as well.  The full publication allows a more granular look at the actual data obtained in the study, not just the summary conclusion.  I will include a more detailed discussion here to demonstrate issues that may be in the NIAIDS study once the full publication is provided. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31022-9/fulltext

In the Lancet publication, 237 patients were at least 18 years old and positive for Covid 19 with severe symptoms.  These symptoms were severe enough that the patient required supplemental oxygen or mechanical ventilation.   Patients were admitted into the program within 12 days of onset of symptoms.  Patients were randomly assigned in a 2:1 ratio to either the remdesivir (158 patients) treatment group of the placebo group (79 patients).  Patients received an initial intravenous dose of 200mg (or placebo) on day 1 and then 100mg on days 2-10.  The two outcomes assessed were clinical improvement and speed of recovery.  It is important to note that the study was terminated before reaching the planned study end because of a higher incidence of severe adverse events in the remdesivir group.

Time to improvement21 (13-28)23 (15-28)NO
28 day mortality22 (14%)10 (13%)NO
Improvement Rate103 (65%)45 (58%)NO
Adverse event - Stop Test18 (12%)4 (5%)YES

The patients in the remdesivir group had a numerically shorter average time to improvement (21 vs 23) , but not statistically different.  (note: No statistical significance is an indication that the difference may be due to chance rather a true reflection of a difference). The mortality rates were the same.  The clinical improvement rate was better for the remdesivir group but, again, the difference was not statistically significant.  The one difference that was significant was that there were more complications with the remedesivir group that required that the remdemsivir be discontinued.

The paper concluded that there was no significant clinical benefit from treatment with remdesivir.  A larger study would need to be done to confirm remdesivir has a shorter time to clinical improvement.  It is important to note that there were only 237 patients in the trial and the trial was stopped short of completion.  Nonetheless, there is so little remdesivir data available, the results should not be ignored.  It is interesting to note that the time to clinical improvement range from 13-28 days for the remdesivir group and 15-28 days for the placebo group.  This means that there people in the remdesivir group that were not helped and there were patients in the placebo group that recovered faster than the remdesivir group.  This is the nature of clinical trials and why it takes larger numbers of patients over longer periods of time to determine true differences between groups.  We can not judge the NIAID study until all the data is provided.

The conclusions on remedesivir are:

  1. The FDA has granted Emergency Use Authorization for remdesivir.  This mean that physicians can use the drug if they deem it necessary for the care of patient with severe Covid 19 symptoms.
  2. The Emergency Use Authorization means that there is not enough data from clinical trials to grant approval but the FDA has determined that there is enough information to determine that the potential benefits of remdesivir out weigh the potential risks.
  3. The main benefit appears to be that remdesivir can shorten the recovery time by a few days in seriously ill Covid 19 patients..
  4. The results on this recovery time benefit were not consistently reported by the few other studies that have compared remdesivir vs placebo in a randomized control study.
  5. The full adverse effects are not known and in one study there were more severe adverse events in the group receiving remdesivir.
  6. There is a question of whether or not remdesvir lowers the fatality rate.
  7. More study is required and is on going. Some key unknowns how does remdesivir effect Covid 19 patients that do not have severe symptoms?  What is the effectiveness as a function of patient age, gender and ethnicity?  Is the current dose optimized?  Will there be more adverse events as the number of patients is increased?  Will some patients respond more positively of negatively due other existing medical complications?

Remdesivir may speed the recovery of patients with severe Covid 19 symptoms.  The safety and efficacy are not known.  This may help many people recover but will unlikely improve fatality rates and side effects are unknown.



Covid 19 Vaccine. Where are we in the process? How will they work? What’s taking so long?

As the US passes 60,000 Covid 19 deaths and we begin to selectively reopen parts of the country, the race for Covid 19 vaccine is at full speed.  However, questions regarding how vaccines work, how they are made, how well they work and the approval proess are generally not known. Knowing this information will help set expectations for development speed and possible effectiveness.

Recent History.  In the last 10 years, several epidemics have caused rapid research and development of vaccines for SARS (Severe Acute Respiratory Syndrome), H1N1 influenza (Swine Flu), Ebola, Zika, and now SARS-CoV-2 (Covid 19).  In each case a vaccine was ultimately developed.  However, the SARS and Zika epidemics ended on their own before vaccine development was completed and the Ebola vaccine was made available around the time the Ebola epidemic was winding down on its own.

A separate discussion will be provided in another blog regarding the vaccines for seasonal flu.  For now, know that the seasonal flu, with a vaccine, comes back every year and causes 25,000-60,000 deaths each season.  Due to changes in the flu and the corresponding vaccine, the effectiveness of the flu vaccine has been as low as 15% for season and averages around 40% effective overall. https://www.cdc.gov/flu/vaccines-work/vaccineeffect.htm

History.  A vaccine is something that is introduced into the body that causes the body’s immune system to fight off infection by producing specific antibodies.   The first ‘modern’ vaccine was developed by a British physician, Dr. Edward Jenner in 1796.  He discovered that if he infected people with the related but much less deadly cow pox virus, these patients would develop an immunity to the very deadly small pox.  It is a long and difficult process to make a vaccine.  At the start of the 20th century, yellow fever and polio killed and infected millions.  However, diseases such as these diseases, small pox and measles are virtually eliminated from the developed world (where the vaccines are available).

What are vaccines and how do they work?  The human body has amazing ability to generate specific ways to kill harmful bacteria and viruses.  These harmful bacteria and viruses are often termed as pathogens.    Specifically, the body can make special proteins called antibodies which are made specifically to fight off a specific pathogen.  That is, the body makes a different antibody to fight off each kind of pathogen.

Antigens are characteristic molecular structures on the surface of pathogens.  It is the antigen on the virus that attacks and infects healthy cells causing the disease.  Fortunately, we have a type of white blood cell, called a B Cell Lymphocyte that can not only recognize antigens but also produces a specific antibody that binds to the specific molecular structure of the antigen.  Once the antigen is bound by an antibody, the antigen can no longer infect another cell.  Another feature of this system is that once antibodies are produced, the body will recognize these antigens if they appear again and immediately makes more antibodies to fight off the infection.  This is how we get immunity.  This simplified process description is depicted in the figure below.  A part of the virus (pathogen) is seen at the bottom of the photo.  On the surface of the pathogen are the antigens.  A cell is shown carrying antibodies (the purple Y shaped structures).  You can see that the one end of the antibody matches the shape of an antigen and binds to it.  This inactivates that antigen.  The B cell is then seen bursting releasing antibodies that can seek out and bind to other antigens.

There are three general approaches to make vaccines:

Weakened Virus.  In this method, viruses are weakened so they reproduce very poorly inside the body and will not cause illness.  However, they reproduce enough to produce antibodies.   The vaccines for measles, mumps, German measles (rubella), rotavirusoral polio (not used in the U.S.), chickenpox (varicella), and influenza (intranasal version) vaccines are made this way.   Vaccines made in this way cannot be used on people that already have weakened immune systems like cancer and HIV patients.

Inactivate (dead) Virus In this method, the viruses are killed (usually chemically) and introduced into a healthy patient.  The dead virus can not cause infection but the antigens are still on the surface and antibodies are made. The inactivated polio, hepatitis A, influenza (shot), and rabies are vaccines made from inactive viruses.  Vaccines produced in this manner can be given to those who are immunocompromised.  The limitation of this approach is that it requires the handling of large amounts of live virus and typically requires several doses to achieve immunity.

Use Part of the Virus. In this method, just one part of the virus containing the antigen is removed and used as a vaccine. These ‘parts’ can be DNA, RNA, recombinant DNA and protein units, to name a few.  The hepatitis B, one shingles vaccine (Shingrix®) and the human papillomavirus (HPV) vaccines are made this way.  This strategy can be used when an immune response to one (known) part of the virus is responsible for production of the antibody.  These vaccines can be given to people with weakened immunity and appear to induce long-lived immunity after two doses.  Most of the candidates in Phase I testing use this strategy (although in very different ways).

AN IMPORTANT CAVEAT.  This is a very, very simplified discussion of vaccines.  The actual mechanisms of action, chemistry, biochemistry and molecular biology are quite complex and well beyond the scope of this blog.  If you are interested, there are many references to the details on line.

Development of a Covid 19 Vaccine

On April 8, there were 115 Covid 19 possible vaccine candidates know/discussed.  However, only 78 of these are known to have become actual development projects.  It is unclear how many of these projects are still on going. Only 7 candidates have entered the first phase of human testing somewhere in the world. https://www.nature.com/articles/d41573-020-00073-5

There are several barriers to development of this vaccine.

It is not clear exactly how to prepare the vaccine.  Optimizing the antigen is difficult as it is not yet clear how much (or what part) of the full antigen protein is needed to illicit the appropriate antibody production.  Of the 7 vaccines in Phase I trials, no two use the same antigen preparation method.

There is always concern about causing side effects.  Preclinical trials during the SARS vaccine development raised concerns over exacerbating lung diseases.  As Covid 19 kills through a respiratory mechanism, this is an important concern.

It is not known how much of the vaccine (assuming you have the right one) is needed and if you need to use more than one dose to achieve immunity.

If you achieve immunity, it is not known how long the immunity will last.

Typically, vaccine development is a lengthy (10 year) expensive process.  As the manufacturing method is dependent on the actual way the antigen is prepared, manufacturers generally wait until they are fairly certain they have a successful vaccine before they invest the costly development and construction of manufacturing facilities and distribution plans.  There have been reports that some companies are taking a large risk by starting to develop manufacturing before they are even out of phase I trials in order to get the vaccine out as fast as possible.  It is quite a financial risk to do this as they may construct a facility that does suit their actual final product.

There are 3 Phases required for Vaccine Approval.

Phase 1.  A human trial with a small group (typically less that 100) of HEALTHY patients.  This is to insure that there are no ill effects of the vaccine and to see if any patients develop Covid 19 infections.   This phase usually takes a few months.

Phase 2.  This will involve a larger group of patients followed for a longer period of time.  The results from Phase I will help determine the number of patients and the length of the study.  Typically, this Phase involves hundreds of patients and can take 1-2 years.  However, due to the urgent need for the vaccine, shorter evaluations may be possible with the right study design and accepting higher risks.

Phase 3.  In this Phase thousands of patients will be vaccinated and the patients should be representative of the total population in terms of age, gender, ethnicity etc.  This will provide information on the effectiveness of the vaccine.  Again, the results of Phase 2 will dictate the exact number of patients and study time needed.

FDA Review.  At the end of Phase 3, the FDA will evaluate the results and provide approval, assuming safety and efficacy and patient protocols are demonstrated..

Phase 4.  The vaccine producer is generally required to continue clinical trials to look for additional side effects and study the longer term effects of the vaccine.

The global vaccine R&D effort is unprecedented in terms of scale, speed and diversity of candidates. Given the worldwide urgency, the most optimistic estimates are that vaccines could be available under ‘emergency use’ in the first half of 2021. This would represent an incredible change from the traditional vaccine development pathway time of over 10 years.  Introduction at this speed will require new development requirements, testing criteria and regulatory flexibility.   There is not substitute for letting nature act on its own time scale.  As the saying goes, ‘you can’t get 9 women and have a baby in a month’.

We should not forget that we do not want to sacrifice safety and efficacy for speed.

It is amazing that such a complex problem can have so many possible solutions being pursued simultaneously.  We truly live in amazing time in history.

Next: how well should we expect the vaccine to work?  The current antibody testing of larger number of patients has indicated that actual fatality rate is well under 1% and may be in the range of the seasonal flu.  This is very good news as the seasonal flu numbers include the use of a flu vaccine.  For Covid 19 to the same fatality rate without a vaccine provides some reason for optimism that with a covid 19 vaccine, it will be less deadly than the seasonal flu.New York: Nearly 3 million infections – not 276,000