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.
% 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.
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.
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.
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.
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.
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 improvement
28 day mortality
Adverse event - Stop Test
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:
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.
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.
The main benefit appears to be that remdesivir can shorten the recovery time by a few days in seriously ill Covid 19 patients..
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.
The full adverse effects are not known and in one study there were more severe adverse events in the group receiving remdesivir.
There is a question of whether or not remdesvir lowers the fatality rate.
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.
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:
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
The big question that is on everyone’s mind is what is going to happen when America ‘gets back to business’ and people have the freedom to move about as they please. It may take awhile before we get back to the freedom to work and live like we did just 3 months ago, but I am confident we will get there. In the mean time, what can expect we in the next few weeks? Of course, it’s impossible to know for sure, but examining how different states and countries have handled the infection may provide some insight into at least the breadth of things that might occur and provide some concepts we could use.s
I believe that looking at places where there have been less restrictions placed on the people AND where people have been less impacted (number of covid 19 cases and fatalities per million people) show us that we can live with open businesses where Covid 19 is no worse than the seasonal flu. I believe that Japan provides an example. I know we can’t mimic Japan in many ways, but there are experiences which we could learn from. It is a story of how a different approach, mind set and cultural behaviors combine to give a final result.
Relatively little has been said about Covid 19 in Japan with its population of 126.7 million. Most businesses have remained open, yet the Covid 19 infection and fatality rates are much, much lower than in the US (in the range of seasonal flu). Some estimates are that less than 20% of Japanese businesses have been closed.
As of March 28, 2020, the Covid 19 stats for Japan vs the US are shown below. It is important to note that the US has done far more testing than Japan, but neither country has done much antibody testing, so the true infection rate is not known for either country. Nonetheless, the statistics for Japan are very good. Covid 19. How many people are actually infected? Santa Clara County
Covid 19 cases
Cvoid 19 deaths
The difference in number of deaths/million people is dramatically lower in Japan than the US.
They used a ‘cluster-based approach’ to manage Covid 19.. The principal of this approach is that infection is spread from certain people being more contagious than others. This concept was used to explain why many passengers on cruise ships are not infected despite having close contact with infected persons.
These more highly contagious people form clusters of infected people which go on to infect others. Under this cluster based approach, each cluster of infections is identified and tracked to the original infection source(s) and these highly contagious people (and those they infected) are isolated. This approach requires rapid targeted testing. The government has a dedicated department which does this monitoring.
This cluster-based approach is conditioned on clusters of infection get detected at an early stage. In February 2020, a cluster based approach was used when an outbreak was identified in Hokkaido, Japan.. The source was located, containment measures employed (like closing all travel on/off the island, specific quarantine) and the outbreak was rapidly contained.
It is noteworthy that South Korea used their version of the cluster based approach to contain their Covid 19 outbreak where they found 1 woman who infected over 1000 others and 60% of the cases in South Korea could be traced back to two churches. Again, targeted testing and quick identification of clusters of infections were keys to success. South Korea: Covid 19 Containment vs Privacy
The Japan version of social distancing is called avoiding‘the three C’s’ : Closed spaces with poor ventilation; Crowded places and Close Contact places. This is somewhat opposite to US instructions where we have been told to socially isolate but have closed parks, playgrounds and beaches. Most, but not all Japanese elementary and high schools have closed, but the closures are only planned for 2-4 weeks depending on the local government. It is not clear, school closures have (or will) influenced infections of fatalities given the relative low numbers of both.
There are also cultural practices that helped Japan limit the spread of the virus. Large numbers of Japanese were already in the habit of wearing masks before Covid 19. Western behaviors such as shaking hands, hugging, kissing and other forms of physical contact are not part of Japanese social behavior. It is also interesting to note that on the famously crowded public Japanese transit systems, talking is considered to be poor etiquette so again, transmission methods are greatly reduced when no one is speaking and they are wearing masks.
Another cultural consequence of covid 19 isolation policy is suicide. In Japan, the suicide rate has always been proportional to the unemployment rate. Suicide rates have already increased in Japan even though the increased unemployment rate is still low compared to the US. There is a real fear that Japanese suicide rates will increase dramatically if there is a US type of business shutdown. Given the small number of Covid 19 deaths in Japan, it remains to be seen if the lives saved by sheltering in place are offset by lives lost due to suicide.
It is true there has been an increase in the number of cases and deaths the past few days, but the numbers would have increase dramatically to reach the numbers of cases (108/million vs 2116/million) and fatalities in the US. Due to these increases, this week, Prime Minister Abe declared a ‘state of emergency’ granting local governments power to make their own decisions about restrictions, but there have been few nationwide mandatory shutdowns and only an appeal to ‘stay home’. The state of emergency has also been set to be only 2 weeks long. The Prime Minister’s opponents are calling for a larger shutdown but so far Abe has resisted. Although the number of cases and deaths are increasing, Japan is still doing very well compared with most other countries it’s size.
Recent days have seen reports that some Japanese hospitals in major cities are running short of personal protective equipment. However, this may be a failure of poor planning and procedures rather than a failure of the cluster based approach. The early success of the cluster based approach may have lulled the government into complacency and they failed to procure equipment and supplies when they could. They are now playing ‘catch up’ to get supplies when they could have done so earlier. Japan has far fewer ICU beds/100,000 people than the US and they are concerned about needing more ICU beds than they have, but they are not at that point yet. The US has demonstrated that large numbers of hospital beds can be erected in short periods of time should they become needed.
The Japan model is based on geographic and social conditions which could be difficult to apply here. However, I think there are clear experiences we can benefit from.
My summary is:
You can limit the effect of the virus without mass shutting down businesses and sheltering in place as long as you have the ability to immediately identify outbreaks and identify and isolate the source of the cluster.
Infections can be minimized by avoiding the ‘three c’s’: Closed in Spaces, Crowded Spaces and Close contact with other. Their version of social distancing.
Infections can be minimized by reducing physical social greetings, kissing, hugging and handshakes.
Mass transit can still be used if other behavioral changes are made.
If you feel sick, stay away from others
If you feel sick, do not go to work.
Japan is an example where people can live in an environment where Covid 19 is no worse than the seasonal flu (bad as that is) without a shutdown of the economy and staying indoors. There’s always a chance of an outbreak in a closely packed country of 127 million people, but they have done well so far. Only time will tell if Japan’s approach was successful, but I am hopeful.
I am encouraging on our scientists and politicians to include the Japan experience in their thought and decision making process as they develop and implement plans to reopen America.
As the nation and the world turns toward reopening the world to business, there has been a lot discussion of whether we could ‘return to normal’, but what does that mean exactly and how do we know when get back to normal? We have lived with numerous causes of death that are higher in number than we are seeing for Covid, yet we did not shut down our country for any of these other causes. In other words, we accepted as ‘life’ that there are many things cause death but we continue to go through life without stopping.
We should not have to complete end or stop Covid 19 before we ‘return to normal’. ‘Norma’l includes yearly deaths many times that caused by Covid 19.
We get daily briefings and headlines about Covid new cases and new deaths from the US and around the world. To date (April 27, 2020) there have been 1,004,942 Covid 19 cases and 56,527 deaths. However, the view of the number of actual cases has drastically changed in the last week. The availability of antibody tests, which can determine if someone has been infected, has resulted in several reports that the actual number of people that were infected may be somewhere between 16 to 80X higher than this value (up to 21% of the population). This means the actual number of Covid 19 cases may in the range of 16,000,000 to 80,000,000. This makes the fatality rate between .34 and .07%. This is in the range of the seasonal flu. New York: Nearly 3 million infections – not 276,000
The early concern over Covid 19, which caused the nationwide lockdown were basically two concerns. The first was the seemingly high fatality rate which was generally reported to be between 5 and 10% back in March. The second was the concern that the number of infected patients would overwhelm our health and hospital systems, and whether we could treat everyone who needed help.
As it turns out now, fortunately, neither of those concerns happened. The fatality rate is most likely be well under 1% and may be in the range of the seasonal flu. There was not one city, including the hottest spot, New York where there was a shortage of beds, intensive care units or ventilators.
The shelter in place and closing of businesses undoubtedly helped to slow the spread of the virus, but perhaps not as much as we previously thought. Before antibody testing, we were operating under the fact the 1 million people had been infected. In a country of 370 million, this would seem to say that the lockdown was very effective. However, the antibody testing now suggests that the number of people infected may be as much as 80 million! This means that the lockdown was not nearly effective as we thought. It also means that the vast majority of those who were infected did not need hospital care and had no or minor symptoms.
As plans are being considered to how reopen America’s business, the question is what state of health are we going to return to or accept?
To try and answer this question, it is useful to examine the top 10 causes of death in the US in 2018. The CDC reports:
Lower Respiratory (COPD)
Covid 19 4/27/2020
Covid 19 Numbers still increasing, but rate of increase has slowed
Note that as a society, we did not shut down our businesses or go into lockdown over these numbers. In particular, it interesting to note that in the 2018 season, flu claimed more lives than Covid 19 has caused to date (although Covid 19 is sure to increase further). We also did not stop driving cars even though over 100,000 per year die from car accidents.
It would seem reasonable that if Covid 19 statistics could be brought into line with these other causes of death that we would be back to ‘normal’.
A key factor to consider is that Covid was much more fatal to those over 65. Currently 79% of the Covid 19 deaths were in people over the age of 65. The 65 and older group represents just 16% of the population. The data strongly suggests that those over 65 may suffer more fatalities. The younger you are, the less likely that Covid will be fatal, even if you get infected.
When businesses open up, both businesses and individuals may have different behaviors depending on the age of the people involved.
Although, there has been a long and strong voicing that Covid 19 is not the flu, it acts more and more like a flu the more we study it. It has been thought that Covid 19 was more contagious than the flu, but the recent finding that the number of infections known may be off by many millions, it is not clear how much more contagious it is. As I always state, comparing Covid 19 to the flu is NOT downplaying the seriousness of Covid 19 – instead it is a reminder that the seasonal flu has always been deadly (25,000-60000 fatalities a season and up to 60 million infections) and will continue to be so.
I will discuss vaccines in an upcoming blog, but it is critical to note that the data regarding the seasonal flu is WITH an annual vaccine. There is no current vaccine for Covid 19, so Covid 19 statistics should look much better once a vaccine is found. However, it is very important to know that the seasonal flu vaccine does NOT always work well. The effective of the seasonal flu vaccine has varied from 10 to 50% depending on the year. Hopefully, the Covid 19 vaccine will perform much better.
More good news. It seems that each day, the results of another study of the actual extent of Covid 19 infection show that the actual number of people infected is much greater than we expected.
As always, this is good news.
Until now, Miami-Dade county in Florida has reported 10,600 cases of Covid 19. However today, a University of Miami reported on a study designed to determine the actual extent of infection by selecting a wide range of patients with and without symptoms for antibody testing.
They found that 6% of those tested were positive for the antibody. Assuming that their study group was representative of the Miami Dade county, this would mean that 165,000 were infected with Covid 19 instead of the 10,600 reported. About 50% of the people tested reported having no symptoms for 14 days before being tested.
This data is consistent with the data reported for Santa Clara (2-5 %) and Los Angeles County (4%) in California and New York (up to 21%) as well as testing in Robbi Italy (10%) and Gangelt Germany (14%). Although each study tested only a few thousand representative people, in all cases, the number of people tested ranged from 4 to 21% of the population- representing 10 to 80X the number of cases that have been reported.
This means that the ‘curve’ that we have been trying to flatten is NOT representative of the actual number of infections that have occurred. Taking an average of 5% infection for discussion sake, this would mean that in the US alone, there have been 18,750,00 infections, not 953,851. This would also make the fatality rate .28%. If it turns out that 10% of the population was infected, the fatality rate would be .14%. Recall that New York city reported an infection rate of 21%.
Caveat: All of these studies represent cross sections of different areas of the US, Italy and Germany. More data is necessary from many more places with wider demographic of study subjects until the actual infection rate is known.
However, even as we watch the daily count of new cases increase, it is certainly the case that the cases being measured are 10 to 80 times less than the actual number of people being infected. Again, this is good news. It means that 50-80% of the people who get infected have no or minor symptoms and that the fatality rate gets closer and closer to the values we associate with seasonal flu. This is especially good news as the seasonal flu numbers are WITH a flu vaccine. To date, there is no proven vaccine for Covid 19. The numbers for Covid 19 can only improve with more antibody testing and the introduction of a vaccine.
This also has implications on reopening businesses as sheltering in place may have been effective, but perhaps not nearly as effective as it was thought to be.
New York: Infection rate 10x higher than previously thought. This is good news.
New York reported their first results in larger scale antibody testing to see how many people may have had actually had a Covid 19 infection. 43% of the tests were conducted in New York City while 32.8% of the test were taken out of the city. The presence of the antibody means the person had and recovered from Covid 19 infection. In most cases, the person was unaware they were infected. This is GOOD NEWS. It means that most people who get infected have no or minor symptoms and it makes the fataility rate (the % of people who die after getting infected) much, much lower. See my earlier blog on antibody testing. Covid 19 Tests: What we can and can’t say.
The results reflected large differences between different areas of the state. The number of people who tested positive for the antibody was:
New York City: 21%
Long Island: 16.7%
Rest of New York 3.6%
This corresponds to 1.7 million people in New York City and more than 2.6 million statewide who have been infected. These number are much, much higher than the 275,000 confirmed cases that his reported today.
The tests show that the spread of covid 19 was not very different for different age groups:
45-54 age: 16.7%
65-74 age: 11.9%
Over 75 age: 13%
Less than 45 ranged from 8 to 15%
It is reminded here that this is percentage in each age group that had the antibody – they are the survivors. The fatality rate among the groups is very different, with those over 65 accounting for 40% of the deaths. The fatality rates will be discussed in a future blog.
Black, latino and multiracial New Yorkers had a 22% average positive tests while White accounted for 9.1% of the positive results. Although it is clear there is a racial component to the infection rate, strict comparison of the numbers should be done carefully, as most of the testing was done New York City which has more minorities.
Importantly, this make the fatality rate around .5%, 10x lower than what was known just a couple of weeks ago.
This does not negate the severe impact the disease has had on the public but it does provide more insight into the disease.
Caveat: This study and others should be considered preliminary studies. They clearly show a high number of infections but only in limited locales. Much more data from more locations and wider demographic inclusion will be necessary before the actual numbers of infections are known. The results may also vary from country to country or county to county. However, all indications so far are that the number of infections determined by antibody testing is far higher than the number of confirmed cases being reported.
Overall, let me say that I am for reopening businesses as soon as it is safe enough to do so and I try to make data driven decisions. Several states including Georgia and Texas have allowed the reopening of some businesses. However, the list of businesses seems odd to me. Why are hair salons, tattoo parlors, bowling alleys, massage parlors and gyms among the first businesses to be allowed to reopen?
It seems peculiar to me that after weeks of hearing we will follow the data, that these businesses are opening with essentially with no specific data and no plan to actually collect the specific data. I’m for opening business but I prefer it be done in a manner where there are not so many risk factors and so few answers. For instance, with all the testing that has been done (over 4 million and counting) has any gym or massage parlor ever been a source of an outbreak? If the answer is no, that would be good to know. If the answer is yes, then why open them now?
It seems odd to open these businesses for two reasons. First, in three of the businesses, hair salons, massage parlors and tattoos, it seems impossible to maintain 6’ of social distancing while conducting business. In fact, the customer is likely to spend most of their time within 6’ of business staff. I can imagine how bowling alleys and gyms may be able to maintain social distances, but both of these businesses involve a lot of touching of surfaces by the clients (bowling balls, bowling shoes, score sheets, weights, pull up bars, bikes, rowing machines etc.) Each of these surfaces would have to be disinfected after every use – will this be done? Is it even practical
The second oddity about these businesses is that there are not a lot employees involved. Texas has 28000 people that work in hair salons and George has less than 10,000. With respective population of 29 million and 10.6 million, this will help a small fraction of the unemployed, but hardly a significant contribution. Similarly, there were just over 6900 registered masseuses in Texas and only 2700 in Georgia.
There are around 2500 health clubs in Texas with a membership of over 5.3 million. However, it is not clear how often these people go. However, 5 million people is a significant number. If the early antibody testing holds up under further investigation, somewhere between 4 and 14% of the 5 million people were or are infected with Covid 19…that makes roughly 200,000-700,000 gym members who have had or have Covid 19. Actual Number of Los Angeles Infections: over 400,000
I could not find any statistics about the number of bowling alleys but in my own county of 1 million residents, I believe that there are two bowling alleys. I know it’s not Texas or Georgia but I find it hard to believe (no criticism intended for people who work in bowling alleys) opening bowling alleys is not going help unemployment numbers much.
Some have called this a social experiment, but it’s not being conducted like an experiment. In an experiment, you have a question you are trying to answer and you have measurements that you will make to get an answer. I have not heard of any additional testing or tracking that is going on with these openings and comparisons to the people who use these businesses and those that don’t..
If this was truly and experiment:
Because of the built-in lack of social distancing, workers should be tested for Covid 19 and the antibody before they can start work. Workers should be continued to be checked every 5 days to make sure they have not picked up the infection.
Customers should also closely be tracked. Preferably the customers would also be tested for Covid 19 5 days after the appointment (or work out, or tattoo) to see if they have the antibody indicative of infection. If there is an outbreak somewhere, it would be good to know if there was a hair salon or gym that was the epicenter (like the church in Korea). South Korea: Covid 19 Containment vs Privacy
If after this testing, the Covid 19 does not seem to spreading, then I’ll be ok with it.
I am not OK with opening these businesses that do not put very many people back to work but can increase the exposure to Covid 19 especially if they aren’t going to follow what happens.
It seems there’s a lot of other types of businesses that could be reopened (with guidelines) that would benefit larger number of people as both employees and customers.
The good news is that over 80% of the people who get infected will have no or minor symptoms and the fatality rate is overall getting lower, but at risk groups should remain very vigilant.
I am hopeful that the opening of these businesses will be successful. However, I wish I had more confidence in that wish. The results from the first openings will have a large impact on how reopening other businesses will be conducted.