Where Has COVID-19 Had Its Highest Death Rates Since The Delta Variant Appeared?

 

The COVID-19 Fatality Rates in the Time of the Delta Variant and Vaccine Availability

The COVID-19 infection has passed over the United States in several waves. The death rates before and since the appearance of the Delta variant and the general availability of the vaccine tell a dramatic story. 

So, before and after. What date to choose? For this analysis, I chose February 23, 2021 as the dividing point. This was the date when the highly contagious delta variant of the coronavirus first appeared in the United States. Delta variant infections now account for 99% of infections in the U.S.  By this date, the massive wave that began in November was well in decline. America COVID-19 deaths had peaked on January 12th, 2021 with 4490 in a single day. 

Cumulative US Deaths, from Worldometers .info

Death Rates Before and After February 23, 2021.

Which states have fared better or worse, before and since February 23, 2021? Below is table with the states ranked in order according to the numbers of COVID-19 deaths per 100,000 (100,000 being the standard epidemiological number) from before and after February 23, 2021. The end date for this analysis was October 1st, 2021. The phase one numbers are universally higher: 72.7% of all deaths occurred before 2/23/21.

Table 1.

The above numbers are taken from worldometers.info. They are in 99% in agreement with the gold standard data maintained by Johns Hopkins, but worldometers is easier to navigate to a specific date for a specific state. (Note: the totals in worldometers appear a bit higher because they include Puerto Rico, U.S. territories. They seem to double count veterans. This analysis is the fifty states and District of Columbia.) 

I have been critical of Florida's response to COVID before this, but I was surprised that with all the competition they managed to rank the worst over the past seven-plus months. 

Vaccination Rates Versus Biden Vote

It is hard to look at the list and not notice that most of the states that have performed poorly recently are Republican-led. Trump won the state election in 12 out of the top 14 in the 2020 election, the exceptions being the hotly contested elections in Georgia and Nevada. (Twenty-five states went for Trump and twenty-five for Biden. DC, included in this analysis, went for Biden.)

So, what's going on in the Trump states? Do the states where Trump won have lower vaccination rates? The table below includes vaccination rates, state ranking of vaccination, percentage of votes that went to Biden in each state, and the ranking of those states. The vaccination rates came from Johns Hopkins and were current for October 1st. The voting percentages for Biden came from Wikipedia.

Table 2.

The correspondence is fairly remarkable. The eighteen states with the lowest vaccination rates all swung for Trump. The eighteen states with the highest vaccination rates all swung for Biden. Florida, ranked a modest 33rd, has the highest rate of vaccination among states that went to Trump. 

A fairly tight correlation between state vote for Biden and percent vaccinated. District of Columbia is on the far right.

Vaccination rates correspond to death rates after 2/23/21. (Going too much before February, the vaccine was not generally available)

Table 3.

Table 3 tells some fascinating stories. First of all is the big picture: states with death rates that correspond to their vaccination rate. Among the 20 who are doing most poorly in death rates are 14 states which are also in the bottom for vaccination rates. Among the 20 who have the lowest death rates are 13 who have the highest percentage vaccination.

Dividing this data up in another way, 31 states and the District of Columbia performed roughly as expected with death rate rankings corresponding to vaccination rates (plus or minus 10). This included states with high vaccination rates and low death rates (e.g., Vermont, ranked 3rd in vaccination and 1st in fewest deaths) or those with low vaccination rates and high deaths (e.g. Mississippi 49th in vaccination and 50th in death). 

*Worse and better were defined as having 10 or less in difference between rankings.

Nine states performed markedly worse in deaths compared to their rankings in vaccinations. Most notably was Florida (32), New Jersey (21), New Mexico (20), Virginia (20), Massachusetts (14), Kentucky (13), New York (13), Texas (12), and Nevada (12). With the high number for Florida, it suggests that the state is making poor decisions beyond the question of vaccinations.

Ten states performed markedly better in their rankings of deaths versus ranking of vaccinations. These were most notably North Dakota (44 ranks higher!), Alaska (22), Nebraska (21), Wisconsin (19), Wyoming (19), South Dakota (17), Utah (17), Iowa (16), Indiana (13), and Ohio (11). Out of the top eight of these, seven were contiguous.

(Note: these numbers were updated on October 6 due to a miscalculation)

Is There a Herd Immunity?

There are two ways to be vaccinated against COVID-19: by a prepared vaccine or by getting the disease. States that have outperformed their official vaccination rates in recent months are often those which have had the highest infection per population. 

An explosion of infections occurred in the upper Midwest beginning in October 2020, with over 1% of the population becoming infected per week. And this can only reflect what was measured at a time when health care services were saturated. "Silent" infections were likely not tested. Going back to the beginning of infection, North Dakota is ranked 2nd in infections per population. South Dakota is 6th, Utah 11th, and Wyoming 12th. With the exception of New Hampshire, all states that outperformed their vaccination rates (by having fewer deaths) are in the top 25 of infection rates.

Herd immunity, better phrased as vaccination by infection, carries a huge price. Although this analysis has focused on the ultimate price, death, hospitalization, economic destruction, short-term suffering and long term impairment are all possible with COVID-19 infection.

Martin Hill Ortiz is a professor of Pharmacology at the Ponce Health Sciences University. He teaches vaccinations and has researched viruses for over 30 years. 

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It's Getting Bad Again: A Report for COVID-19 Cases for the Week Ending October 10th

 The story thus far, abridged. Abridged, because you know much of the story thus far. 

In early March of 2020, at a time when few tests were available and all positive tests had to be confirmed through the Centers of Disease Control and Prevention, the SARS-CoV-2 seeded itself throughout the United States. (From hereon, I'm going to call the virus by its commonly used name, coronavirus.)

At first, individual cases were reported by states in their Department of Health Twitter accounts. The alarm was downplayed. Texas pointed out that, when it had its first case, there was only one case statewide and there was no great danger (the tweets are at the end of this post). Over the course of the month of March, each state put together its own website with its own style of reporting or not reporting essential information (with Texas being among the last to put together a dedicated web-page). West Virginia was the last to report a case: March 17th.

 

Since March, coronavirus has been responsible for over 10% of all deaths in the United States. (Derived from Table I, CDC) 

From mid- to late-March each state initiated its own flavor of lockdown. Deriving these numbers from state reports, I found the cases went from an median weekly rate of 31.8* per million population per state for the week ending March 21st, to an early peak of 459.3 for the week ending May 2nd. The infections and mortality in the initial hotspots greatly declined. For the week ending May 9th, (when testing was much more available) Montana registered 3 new cases statewide. (Spoiler alert: for the week ending October 10th they would have 1808 new cases.)

*The March numbers were mostly likely underestimated due to limited testing. 

The Trump administration and many state governments were chomping to reopen businesses. There was a desperation to return to normal. The president suggested reopening for Easter (April 11). This date came and passed. April into May and the pressure to reopen built. 

Number geeks put together a series of statistical benchmarks for reopening. Yay, thought the geeks. We can help fight this virus. Among these was a guideline that the local area should have a 5% or lower positivity rate. 

State governments looked at their numbers and freaked out. I have to tell this urban county they can reopen and not this rural one? Won't people just cross the county borders to go shopping? What if the number is 6%? Or 10%. Iowa's governor later put out a guideline that schools can request closing if the local numbers were over 20%. 

And so many states ignored the stop signals. With positivity rates of over 10%, Florida allowed the reopening of Disneyworld. The numbers rose. These are the median number of cases per week per million for the fifty states and the District of Columbia starting the week ending May 30th. The median number were derived by ranking the states each week and noting the number of the state in the middle spot: twenty-five states with more cases, twenty-five with fewer. I also included the rate of cases for the state that had the peak number. 

For the week ending June 6th, Maryland led the nation with 904.3 new cases per million population. In the past two weeks this number was well below the median. Having crunched a lot of these numbers, 1000 new cases per week per million was my line for dividing out those states with out-of-control infection rates. Now it is the norm. 

In the first days, a select number of states had high infection rates, while others were nearly virus-free. During July, as more and more states "reopened," the infections shifted to high-population states, most especially Florida and Texas. California had a moderately high rate and with its population added to the total. This gave a peak in total cases in new cases per week climbed over 500,000.

As the most populous states lowered their rates, the new cases per week fell to near 240,000. This week it passed 300,000.

The current rise in the median number of cases indicates that most states are experiencing high rates. This is especially true of a number of low-populated state. Before October, Florida set the record high in new cases per week with 3867.2 per million. This past week, North Dakota shattered that record, nearing 5000. (South Dakota also broke Florida's record.)

I have written about the Sturgis, South Dakota motorcycle rally being a super-spreader event. This past week, South Dakota and those states sharing a border ranked 1st, 2nd, 3rd, 6th, 9th, 13th and 17th in most new cases per million people. 

Here is a graphic for all fifty states and the District of Columbia for new cases per million for the week ending October 10th. Although Vermont had the fewest new cases, they have had a blip or possibly significant increase of four-fold over the past two weeks. Other states that have been doing well, such as New York, have also had a disturbing jump. 

Appendix: Texas Tweets. These three tweets were from March 4th Texas Department of Public Health Twitter feed.

First Texas COVID19 Case, Travel Related

Texas DSHS confirms a presumptive positive case in a person infected with COVID-19 when traveling abroad. This does not mean there is community spread of COVID-19 in Texas.

---

“Having a COVID-19 case in Texas is a significant development in this outbreak, but it doesn’t change the fact that the immediate risk to most Texans is low,” said Dr. John Hellerstedt, DSHS commissioner.

---

“Over the past month, the state of Texas has been preparing for this moment, and we are confident in the steps we have taken to safeguard our communities against the coronavirus,” said 

@GovAbbott

9:16 PM · Mar 4, 2020

By March 6th, Texas had identified 6 cases, all from travel. On March 13th, Texas Governor Abbott declared a state of disaster for all Texas counties. There would be over 2000 cases by March 28, 6000 cases by April 4th, 12500 cases by April 11th, and over 800000 cases by October 14th.

Martin Hill Ortiz is a Professor of Pharmacology at Ponce Health Sciences University and has researched HIV for over thirty years.

https://mdhillortiz.com/

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Discrepancies in Florida COVID-19 Data Reporting

One measure of COVID-19 virus infections is the positivity rate. This is the percent of tested samples reported positive for infection.

In one of almost a dozen tweets, Florida governor Ron DeSantis has crowed about his state's day-to-day positivity rate.

In one example, DeSantis wrote:"Yesterday yielded 187 new cases in Phase 1 counties with a positivity rate of 1.43%. The positivity rate has ranged between 1.43% and 4.2% over the past 2 weeks for our Phase 1 counties and has noticeably declined in the past week." Ron DeSantis, May 11, 2020.

This tweet was accompanied by the graph:

Concurrent with this "noticeable" decline, on May 5th, Rebekah Jones, the manager of the Florida State Department of Health COVID-19 database was removed from her position, saying it was for not complying with orders to delete data. A quote from the Tampa Bay Times:

In her [Jones] Friday email to subscribers of a COVID data listserv, Jones said she was reassigned on May 5 "[f]or reasons beyond my division’s control" and warned that whoever took over may be less straightforward.

The above graph can be compared to others that DeSantis tweeted. This graph represents the last days of Jones.

Ibid, 5/2/2020

Notably, the overlapping data points between the above two graphs (5/6 to 5/10) do not match.

Overlapping	Tweet 5/5	Tweet 5/11
Apr. 27	5.98	4.04
Apr. 28	4.57	3.46
Apr. 29	5.00	3.83
Apr. 30	5.11	3.91
May. 1	4.09	3.03
May. 2	4.81	4.20
May. 3	4.68	2.41
May. 4	2.61	1.67

The rates for each overlapping date was revised downward post-Jones.

DeSantis last tweeted a positivity graph on May 26.

So, what is going on? What I suspect.

The numbers changing in the positivity reports is too great for the normal adjustments that usually take place. It is likely that Florida is mixing antibody positives with COVID-19 confirmatory tests (PCR). Antibody positives run about half the rate of PCR rates. One explanation for the numbers dropping between reports is that the tests were added to old data, retroactively.

On May 5th, 2020, Governor De Santis declared:

"Antibody testing is finally here."

He said that 200,000 antibody tests were already in Florida and more were on their way.

Combining antibody tests with PCR tests is a form of data manipulation. According to the prestigious COVID Tracking Project:

"As antibody tests become more widely available across the United States, we call on all states and territories to preserve the integrity and usefulness of their COVID-19 testing data by maintaining separate viral testing and antibody testing counts."

Furthermore, Florida counts multiple negative results from the same individual, rather than reporting the number of individuals who tested negative. "People tested on multiple days will be included for each day a new result was received." as quoted by The COVID Tracking Project.

Florida does not support data integrity.

Ten nurses and ten National Guard members for 500 tests a day?

On May 6, the Florida Department of Health announced a mobile testing lab testing up to 500 individuals a day. The mobile testing unit will be staffed by 10 members of the National Guard and 10 nurses, DeSantis said.

Breaking news: (6/18) Florida reports record-breaking 3207 new cases.

Martin Hill Ortiz is a Professor of Pharmacology at Ponce Health Sciences University and has researched HIV for over thirty years.

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Undercounting the COVID-19 Deaths

The excess number of deaths that are not explicitly being attributed to SARS-CoV-2 (coronavirus) has become mainstream news recently. The New York Times recently put out a series of graphs that look at localities that provide their COVID-19 death statistics in comparison to the average number of deaths in the same time period over the previous five years. Those five years include the late winter-early spring of 2018, when a particularly lethal flu virus dominated.

The U.S. deaths for flu for the 2017-18 season was initially calculated at 79,400 and then reduced to 61,000. The former number would have made it the worst flu season since modern tracking techniques in the mid-1970s and even the adjusted numbers made it one of the worst. Due to the 2017-18 bad flu season, in the initial parts of 2020 the number of deaths showed a slight decline when averaged out over previous years.

The United Kingdom provides mortality statistics, including those deaths due to coronavirus weekly, with about a two week delay. These numbers are gathered separately for England and Wales (combined), Scotland, and Northern Ireland. I present these below as a peek into both the number of increased deaths attributed to COVID-19 and the number not attributed.

I updated these tables using the figures most recently available as of 4/29/2020.

England and Wales.

First, England and Wales which have a combined population of 59,115,800 (2018). The raw numbers came from the UK Office of National Statistics, England and Wales .

*The initial period of deaths are presented as average deaths per week. The determination of excess deaths not classified as COV-19 (1 - (column 2/(column 4 - column 3)) as percentage) is performed the two most recent weeks when total deaths rise above noise. An excess death figure of 100% means that the increased deaths over the week were twice what was attributed to COVID-19.

England and Wales are having a considerable degree worse time with COVID-19 than Scotland or Northern Ireland, below.

Scotland

Here are the numbers for Scotland which has a population of 5,438,100 (2018). Here the raw numbers are from the UK official site for Scotland. Note: Scotland does their counting using Week Beginning rather than Week Ending and start on a different weekday.

Northern Ireland.

Northern Ireland has a population of 1,881,600 (2018). The raw numbers came from the UK official site for Northern Ireland.

The Scotland and the Northern Ireland figures are not included in the New York Times article cited above. I used the figures for only the most recent weeks in estimating the undercounting of COV-19 deaths. In each instance, the undercounting occurred to a much lesser degree over subsequent weeks and, in the most recent weeks, there was even overcounting.

Previously:
SARS-CoV-2 Infection and Mortality Rates
The Coronavirus: Potential Treatments and Drugs to Potentially Avoid

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SARS-CoV-2 Infection and Mortality Rates

COVID-19 is the name given to the disease caused by the SARS-CoV-2 virus (commonly called coronavirus). SARS-CoV-2 is listed in a recent article by LiveScience.com on the viruses most deadly to humans, not because it has the highest rate of mortality, but because it rapidly becomes widespread. The mortality rate given in the article is 2.3%, but open to conjecture.

Worldwide numbers for infections by SARS-CoV-2 have topped 2 million but are likely to be a gross underestimation. The politics of 200 different countries, the rates in which test for infections take place, how countries they define their positive cases, and how they define deaths by COVID-19 are not only variable, they are confounding. For example, Chile counts those who have died due to SARS-CoV-2 virus as being recovered. They are no longer infectious.

This leads to two important issues are: how many people have SARS-CoV-2 but are either untested or asymptomatic; and, how many people die of SARS-CoV-2 but are not listed among the total deaths.

How Many Total Infections?

In regards to the first question, an interesting observation was reported in the New England Journal of Medicine. One New York City hospital tested all of the women (215) admitted for childbirth and found an infection rate of 15.4%. Of these, 87.9% were asymptomatic. Several factors suggest that late-term pregnant women may not be representative of infection rate in the population as a whole, but nevertheless, this is an intriguing number comparing infections to those asymptomatic.

This report states the United States is detecting only 9% of the coronavirus infections.

Such reports are political fodder and it is difficult to be sure if the input is unbiased. One model generated by Chicago economists says that 1.5 to 14% of the infections have been detected depending on lag time involved in detecting the infections.

Why political fodder? If the risk from SARS-CoV-2 is much smaller than reported, then the number infected (and perhaps immunity) is much higher. In such a case the risk of opening the economy is lessened. Some are gung-ho to lift safety measures in place.

The ultimate risk of SARS-CoV-2 is both from its morbidity and mortality rates and its degree of infection. A virus that causes a 0.5% death rate (low end) and saturates at 70% of people infected (high end estimates), would kill 25 million worldwide along with a million Americans. A similar number would come from a 1.5% mortality rate and 23% infection rate.

What We Can Learn from the Diamond Princess Cruise.

The Diamond Princess cruise ship is instructional when trying to determine unknowns regarding SARS-CoV-2 infection rates. I agree with this quote in the scientific journal, Nature. “Cruise ships are like an ideal experiment of a closed population. You know exactly who is there and at risk and you can measure everyone.” John Ioannidis, an epidemiologist at Stanford University in California.

According to the CDC's March 27, 2020 report, the ship set sail on January 20th from Yokohama with 3711 passengers and crew. When stopping in Hong Kong on January 25th, one passenger disembarked due to being symptomatic. This passenger was later confirmed to have SARS-CoV-2.

The crew averaged 36 years of age and the passengers 69 for a combined average age of 59.6. Due to concerns regarding SARS-CoV-2, those on the ship were not allowed to disembark when it docked in Japan on February 3rd. On February 5th passengers were quarantined in their cabins.

According to the Nature report, over 3,000 tests were run on those aboard the Diamond Princess, with some tested more than once. This says that the testing was not comprehensive. A total of 712 tested positive. Back to the CDC report: Of those testing positive, 46.5% had no symptoms at the time of testing. Furthermore, and more revealing, it was estimated that 17.9% never developed symptoms.

At the time of the CDC and Nature reports, 9 of those aboard the Diamond Princess had died. I have found more recent figures place the number of deaths at 12, these from Sydney Morning Herald and Wikipedia. A higher figure makes sense: the previously mentioned articles spoke of some of those from the Diamond Princess as being in critical condition. Using the figure of 712 testing positive this has a mortality rate of 1.3 to 1.7%. On the one hand, the cruise ship did skew toward elderly passengers. On the other hand, the attendant publicity likely ensured top quality care for those who were aboard.

There are other cases of cruise ship outbreaks with some continuing to be in quarantine.

Excess Deaths in Nembro, Italy (citation) The red line is the number of deaths in the time period in 2020. The green line is the number of official COVID-19 deaths (all 2020). The blue line is the average number of deaths in the same time period but from 2015-19.

Undercounting Mortality

To what degree are deaths due to COVID-19 undercounted? One way in which this can be addressed is by looking at the excess number of deaths taking place in a location where SARS-CoV-19 has become prominent in comparison to previous years. A number of studies have been made.

One is a look at the mortality statistics collected in England and Wales. This is not a small population sampling: together they have a population of 60 million. The following table lists the number of deaths attributed to COVID-19 and compares those to the increased number of deaths. England began its lockdown on March 23rd. The table below is my creation taken from the aforementioned dataset.

Weekly deaths in England and Wales

 The small decrease in the early part of 2020 may be due to a particular virulent strain of flu virus dominant in 2017-2018.

 For the week ending April 3rd, those deaths officially deemed to be due to COVID-19 accounted for only 57% of the increase in deaths (that is a total of 33.6% of the 59% increase).

Because the report notes that the final week's cause of death may be incomplete, it is worth noting that for the week ending March 27th, the official COVID-19 deaths account for only 53% of the increase (5.3% of the 10%). It might also be noted that a 59% increase in death does not correspond to a virus that was as lethal as the annual flu. The annual flu had been around in previous years.

Two factors may contribute to the total deaths figure. One is an increase in deaths due to other causes due to, for example, an overwhelmed health care system. The other could be an underestimation due to the decrease in certain deaths such as traffic fatalities due to the lockdown conditions.

 According to the UK Office for National Statistics, these data will be updated on April 21st. Considering the rapid rise in the number of weekly deaths, that update will be crucial to providing an even better picture.

This phenomenon is hardly limited to England and Wales. This report from Netherlands analyzes increases in deaths compared to previous years and find that the official COVID-19 numbers only account for half of the deaths.

Similarly, from Spain, a study described in El Pais, says that while the official number of COVID-19 deaths was 3439 during the time period of March 14th through March 31st, there was an increase in total deaths of 6613 when compared to the same time period in the previous year.

This news report describes several U.S. cities as having significant undercounting.

What's the takeaway from this? First of all, although there are a variety of models that come to different conclusions, there is some hard evidence out there about the undercounting of infections and deaths. The very fact of the spikes in deaths exist indicates that SARS-CoV-2 has a much higher lethality rate than a typical influenza virus. Deaths are probably double the official figures in places where deaths are meticulously counted. In other parts of the world, where the government either wishes to lowball the pandemic or else just doesn't count, the statistics on death are meaningless.

Previously: The Coronavirus: Potential Treatments and Drugs to Potentially Avoid
Next: Undercounting COVID-19 Deaths.

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The Coronavirus: Potential Treatments and Drugs to Potentially Avoid

Pharmacology and SARS-CoV-2

I have taught pharmacology, the science of drugs, going on thirty years. Several matters related to pharmacology have appeared regarding SARS-CoV-2. I will address two broad questions. First: do some drugs work against the virus? Second: do some drugs make the infection worse?



Let's start off with some perspective. All of this is new. Even a quick study rushed to publication takes months: and we are not many months into this infection. There is no definitive statement regarding any of these matters, just a handful of very recent publications along with too many anecdotal reports. In the early days of AIDS (of which I have some familiarity), a lot of the original information about treatment candidates proved to be born out of desperation rather than usefulness.

Coronaviruses, along with rhinoviruses and adenoviruses, are among those that cause the common cold. That's the bad news: common colds are common. They are readily transmissible and, as we all know, there is no cure for the common cold. Beyond that, SARS-CoV-2 is much more dangerous than a typical cold or flu.

On the other hand, treating the SARS-CoV-2 virus is not the same as curing the common cold. We are not targeting all of the potential "cold" viruses here: just one. That provides hope for vaccines, and perhaps, pharmaceutical agents. (Strictly speaking, vaccines are pharmaceutical agents, but for the sake of this piece, I'll only be talking about non-vaccine drugs.) Some of the drugs mentioned here were tested during previous SARS outbreak.

Potential Drugs to Treat Coronavirus

These are some of the drugs that have been put forward as to helping with COV-19 infection.

Oseltamivir (Tamiflu). This drug is taken orally to help curtail influenza disease course. It is useful only if the drug is taken within the first two days of symptoms. Even then, it will only briefly shorten the recovery time. Oseltamivir helps prevent newly-formed viral particles from escaping an infected cell and therefore infecting new cells. It does this by inhibiting the neuraminidase enzyme. It is available orally and that's probably why it is prescribed a lot: convenience. In contrast, zanamivir (Relenza) is an inhalant that also inhibits neuraminidase used for flu. It has less side effects than oseltamivir because it is an inhalant: less gets to the blood, more hangs around the lungs where it is needed. Perhaps the best thing about oseltamivir is that it can be used for prophylaxis of the flu, which is especially helpful in high intensity infection settings such as nursing homes.

I've never been a big fan of oseltamivir. Its window of use is brief, its maximum effect is limited, and its side effects are potentially problematic. When I was hospitalized for bacterial pneumonia I was started on oseltamivir -- six days after arrival. That made no sense to me unless there was a concern I was coming down with a secondary infection. I experienced hallucinations. I can't be sure it was the oseltamivir, but delirium is one of its side effects.

Oseltamivir has not been shown to be effective in the previous SARS outbreak, nor did it change long-term outcomes of previously infected SARS patients. It is unlikely that it will work for the current coronavirus.

Favipiravir (Avigan) is fascinating. It has been shown to have efficacy for a variety of RNA-viruses. It has been approved for use in China, Japan, and Italy and has made it through a pair of Phase 3 studies in the US for the treatment of influenza. (China and Italy approved it just this past week.) Its mechanism of action is similar to that of ribavirin and remdesivir (below): they all inhibit RNA virus RNA polymerase.

On March 17, China announced that they had completed clinical studies for favipiravir and that it was helpful in recovery from the disease. To quote:

"The Third People's Hospital of Shenzhen in Guangdong province conducted a clinical trial on 80 patients, with 35 receiving the drug. The results have shown patients treated with favipiravir took four days before being tested negative, whereas the control group took 11 days."

That's a pretty dramatic difference. It is said to not be helpful in severe disease. As I discussed in my pharmacology class, with severe viral diseases such as influenza, all the cells that are going to be infected are infected.

I am surprised by their description of "no obvious adverse effects," same source as above, however, Phase 2 trials in the US showed a low degree of side effects.

Phase 3 studies against influenza virus were finished in 2015. No results have been presented. That suggests the results were not good, at least against the flu virus. Good results get published and the drug is put in for approval.

Remdesivir is much like favipiravir, only earlier in being studied. It has the same mechanism of action. Studies are beginning now.

Lopinavir/ritonavir (Kaletra in combination). These are anti-HIV protease inhibitors. There is no reason to believe they should work on coronavirus and an initial study indicates that they don't.

Chloroquine (Araclen) and hydroxychloroquine are classical antimalarial drugs. For decades chloroquine was the drug of choice against malaria due to being effective while being safer than the others. Now chloroquine-resistant malaria dominates the world and, we have some newer choices that are more powerful, the artemisinins. Hydroxychloroquine is also an antiinflammatory and is used for rheumatoid arthritis.

When I said these are safer than other antimalarials, I didn't mean that they don't have any toxicities. Like quinine, chloroquine and hydroxychloroquine can affect blood sugar. It can cause headaches, diarrhea, and hemolytic anemia in patients with G-6-PD deficiency.

There has been one smallish study that found that azithromycin (an antibacterial protein synthesis inhibitor, Zithromax) and hydroxychloroquine helped to dramatically reduce the length the patient carried the virus and the amount of the virus. The drop out rate was high (6 out of 26) among those initially treated with three of those going to the ICU and one dying. All in all, the study is open for interpretation as either hopeful or problematic. As is usually the case, more studies are needed.

Another study from China found efficacy from chloroquine and remdesivir, in vitro. 

So how does chloroquine or hydroxychloroquine help? That's unknown. Perhaps it is the anti-inflammatory effect. The azithromycin might be preventing secondary bacterial pneumonia infection or it might be due antiviral properties that azithromycin is claimed to have. Furthermore, azithromycin is also an antiinflammatory. On the other hand, since chloroquine has been shown to be effective in vitro, that suggests its effect is more than the antiinflammatory actions.

Concerns about what drugs not to use.

ACE inhibitors / Angiotensin Receptor Blockers (ARBs)

These drugs are standard care for high blood pressure and are used as adjuncts in congestive heart failure. Do they make coronavirus symptoms worse? There are three reasons why this is suspected.

1) SARS-CoV-2 uses the angiotensin coverting enzyme type-2 as a cell receptor for infection.
2) ACE inhibitors, in particular, have been shown to upregulate angiotensin converting enzyme. 
3) Among the co-morbidities for death in Italy in one study, 74% of patients had high blood pressure. This might simply be because high blood pressure and age have a strong association. Age also presents a strong association with SARS-CoV-2 lethality.

In a recent commentary, it was strongly suggested that patients do not stop using these popular blood pressure medicines: the evidence for bad outcome with SARS-CoV-2 infection is not clear. The authors disclosed pharmaceutical ties. Nevertheless, the advice is generally sound.

Ibuprofen / NSAIDs / Acetaminophen.

Ibuprofen in particular was mentioned as something that might be avoided. The director of the National Institute of Allergy and Infectious Diseases, Anthony Fauci, suggests that this is an alarmist extrapolation from aspirin in viral infections causing Reyes' syndrome in children. Others have suggested that fever has a place in the body's fight against infections, and that NSAIDs and acetaminophen lower fever.

Let's take these one by one. The Reyes' concerns should not carry over to other NSAIDs and should not affect decisions in adults. For children, for pain and fever, it is generally recommended to avoid aspirin. Some physicians recommend acetaminophen. Acetaminophen overdose is so common, I would go with a non-aspirin NSAID.

Is lowering the fever in the case of a viral infection a bad strategy? Is the body fighting the infection with fever? In the case of bacterial infections this makes more sense to me. When culturing human pathogenic bacteria, the classic temperature of the heating device is 98.6 F (37 C). This concept to  doesn't pass over to viruses. Viruses in the blood are not going to affected by a fever. Viruses perform their main functions, including replication inside of cells, which I suspect are less susceptible to overall body temperature changes. That said, there is an argument that the induction of heat-shock proteins is protective. In the cited study, the temperature was raised to 40 C (104 F), which is a fairly heavy duty fever, the upper range below emergency.

Asthmatics are advised to avoid NSAIDs. This is because NSAIDs block the production of prostaglandins and the action of blocking the production of prostaglandins shunts the precursors over to leukotrienes, some of which mediate inflammation, and, in particular, mediate inflammation in asthma. If those leukotrienes are exacerbating symptoms in coronavirus patients with compromised respiration, this may be a concern. Of course, some asthma patients will have coronavirus. Perhaps using a leukotriene synthesis blocker such as zileuton could be helpful to overcome this.

The FDA is stating that there is not enough evidence to exclude the use of NSAIDS in coronavirus.

So, what's the bottom line? This is my take. If you have mild symptoms of fever and aches and you don't know if you have coronavirus, and you are over 12 years of age and don't have asthma, take an aspirin or other NSAID. The most significant exception to that rule is if you are allergic to aspirin. In the same situation if you're under 12, then try acetaminophen or ibuprofen. If you have coronavirus and you are not actively have problems breathing, then the NSAIDs are okay. For asthma, acetaminophen will not cause the problems with peripheral leukotrienes.

NSAIDs may be contraindicated if the infection is severe and with active respiratory problems. Even then, the evidence is out.

My primary sources in putting this together were (a) Anthony Fauci's March 18 podcast with the editor of the Journal of the American Medical Association, and (b) Derek Lowe's In the Pipeline blog as part of Science Translational Medicine, his March 6th and (c) March 19th entries.

(a) https://youtu.be/EXY76TKNy2Y
(b) https://blogs.sciencemag.org/pipeline/archives/2020/03/06/covid-19-small-molecule-therapies-reviewed
(c) https://blogs.sciencemag.org/pipeline/archives/2020/03/19/coronavirus-some-clinical-trial-data

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