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Herd Mentality – How We Strayed From the Truth on COVID-19 Herd Immunity (June 16, 2020)

by Buzz Hollander MD

“Lies, damn lies, and statistics.” Most people would attribute that quotation to Mark Twain, and they would be wrong. Now, if I said, “Herd immunity requires 60% of the population to have covid-19 before transmission will start to slow down on its own,” most people would consider that to be true, and they would also be wrong. In fact, it is the most dangerous kind of statistic – not a mean-spirited lie, but a reasonable sounding assumption repeated so often that we all assume it to be true. Believing the oft-repeated statistics of herd immunity has made it hard to understand what we have been seeing with our own eyes. Only when we understand herd immunity can we begin to make sense of this pandemic.

Now, I do not want to imply that epidemiologists been deliberately lying to us since they became the stars of the intellectual universe four months ago. Heavyweights like Marc Lipsitch and Joel Miller have unveiled some dense and illuminating twitter threads on the matter of herd immunity. However, perhaps because of the incredible complexity of the subject, the implications never really caught on with the media version of herd immunity that made it to the public.

Most of us got the condensed version already, in which the herd immunity threshold is related to the reproductive rate, R0 (“R-naught”) by the following equation: 1-1/R0. If an infected person passes the virus to 2.5 other people on average, R0 is 2.5 and the threshold for herd immunity is 60%. That’s fine and good, albeit simplistic, when discussing immunization plans, the primary use of herd immunity concepts when they gained popularity in the 1970s. However, it is a terrible model for understanding the dynamics of a pandemic!

The dynamics of a pandemic are messy and complex. However, one critically important point needs to be made, and you are more likely to see a jackalope hop by your house than find this concept in a media article on herd immunity: the simplified (1-1/R0) definition of herd immunity implies “homogenous” spread of a disease through a population. Everyone is assumed to randomly bump into other people, and everyone they bump into is equally susceptible to the virus. Sound logical to you? I didn’t think so. This assumption is what we might call a model killer. Virus spread in the real world is actually “heterogenous.” Now we can start to talk about this like proper armchair epidemiologists.

While there are scores of factors which disrupt homogenous spread and can scupper a herd immunity model, let’s focus on four of particular importance: contacts, exposures, infections, and immunity.

1. Herds of People Are Not Like Herds of Sheep

We can start with an example: Think of your diabetic Aunt Ramona in New York City, who volunteers for ten organizations and loves her book clubs. Then there’s your retired Uncle David, who is fit as a fiddle and prefers long walks alone. Aunt Ramona probably got COVID-19 in the first wave, and possibly spread a good bit of it, too. She is one of the 20-25% of New Yorkers who tested positive for antibodies; David probably is not. Assuming some degree of lasting immunity (or death, but we are going to keep this example upbeat), Ramona is now out of the picture for any second wave consideration. The first wave infects Ramonas, not Davids! The 75% of un-protected New Yorkers are going to be comprised disproportionately of Davids, which drives down the effective transmission rate in future waves. This is Mother Nature’s way of “flattening the curve.” Now, it does very little good at the start of an outbreak — the Ramonas of a population are able to do a lot of damage. However, as time passes, if the Davids of the world don’t change their behaviors and become more gregarious or less hygienic, we can expect the real world, or effective reproduction number (Re) to drop – and, with it, the threshold for herd immunity.

“How much?” is a fair question to ask. In early May, two papers appeared as pre-prints that addressed this question, one a paper from a group led by Tom Britton, and the other by Gabriela Gomes. The Britton paper projected the herd immunity threshold for COVID-19 to be 43%; the Gomes paper modeled the threshold to be as low as 10-20%. The implications of this are huge, of course, but the past four months have taught us to take all models with a grain of salt.

One reason to suspect that SARS-CoV-2 is indeed spread in very heterogenous fashion has been its well-documented tendency towards case clusters and superspreader events. One model suggested that 10% of infected people might cause 80% of all cases. In terms of actual data, a study based on contact tracing in Hong Kong found that 20% of cases led to 80% of all infections. Yes, this implies that most people infected with SARS-CoV-2 did not spread the disease to a single soul. If the 10-30% of highly effective spreaders are largely out of the susceptible population early in the course of the pandemic, the disease loses its best soldiers, and the threshold to reach herd immunity drops.

2. All Exposures Are Not Created Equal

Not every social contact carries the same risks from exposure. If someone with an active case of covid-19 coughs in my face while I am swabbing them without any PPE, I am more likely to be infected than if I share a menu with a previous diner with covid-19. No one knows for sure just how many particles of SARS-CoV-2 are needed to cause someone to be infected rather than simply exposed, but there is general consensus that larger viral exposures lead to more likely infections, and the larger the exposure, quite possibly the more severe the infection, too. Not clear is whether severe cases of COVID-19 lead to higher viral loads and to larger future exposures. However, it is likely that the type of exposure can affect the likelihood of transmission — another way that our models might get confounded!

A great example is household exposure. In a helpful compilation of infection rates within households posted by Dr Muge Cevik, household transmission rates from studies in China were 13.2% of 157 cases; 11.2%  of 391 cases; 19.3% of 349 cases; and 16.3% of 105 cases. This would imply the average COVID-19 patient would not infect a single person within a 4 or 5 member household. The home environment is a surprisingly unfriendly place for transmission of the novel coronavirus.

Contrast that to prisons, meat processing plants and cruise ships. There are a lot of problems with the type of exposure in these places. Density is high, so exposures tend to be closer range. The Davids of the world are not free to limit their interactions as they would in their home environments – everyone has a lot of social contacts. The number of daily interactions is extremely high. I will add one more possible critical factor. Whether it looks like this:

Or this:

Editorial credit: Gianluca Piccin /

People take their meals in cafeterias: poorly ventilated spaces where folks linger in the company of each other; loud enough that they sometimes have to shout to be heard; and passing condiments around the table before touching their food and putting it in their mouths. Cafeterias are an ideal venue for a superspreader event, and create environments which can blow past a normal herd immunity threshold.

The risk is not just theoretical, of course. A cruise to Antarctica which embarked in mid-March (after the COVID-19 pandemic had been declared) screened the entire ship with PCR testing 20 days into their cruise: 59% were positive! Prisons are even worse. Now that some prisons have began testing their entire populations, we are seeing some astounding numbers: Ohio’s Marion Correctional Institute found that 80% of their over 2000 inmates were PCR-positive for covid-19; and Marion Correctional Facility (OH) had 73% test positive.

The takeaway is that exposure type is another factor which can reduce real-world herd immunity thresholds; people who live or work in high intensity exposure settings are more likely to be the Ramonas of the first wave, and therefore not be vulnerable to a second wave. The caveat is that if our symbolic David takes a cruise, starts working for a meat processing plant, or becomes incarcerated, all bets are off.

3. Not Every Infection is a Problem Infection

By now, everyone is aware that older, sicker individuals are more likely to become seriously ill if infected with SARS-CoV-2. However, we do not hear much about the people testing positive who get only mild illness (“paucisymptomatic”), or even no symptoms at all (“asymptomatic”) despite a positive covid-19 test. Some asymptomatic people might only be “pre-symptomatic” (i.e., about to get sick) but a well-designed study comes back to check on these people a few weeks after their positive test. We assume a lot of asymptomatic positives to be younger, healthier individuals. In the Mission District of San Francisco testing, for instance, people with medical comorbidities were exactly half as likely (38% vs 76%) to have asymptomatic covid-19 than those without.

However, the very high prevalence aforementioned “cafeteria” environments reveal an interesting phenomenon when examined more closely:  a shockingly high asymptomatic rate, beyond what age alone would predict. Perhaps a cafeteria is a safer place for exposure than, say, a bar after an Atalanta-Valencia soccer match, or a choir practice in the Seattle area. The latter — granted, with an average age of 69 — had 87% of its attendees develop symptomatic illness.  In a Washington state nursing home, 94% of positive tests were eventually symptomatic. Having worked in a nursing home prior to starting medical school, I can attest to the fact that there is a LOT of shouting in the ears of heard-of-hearing residents while moving them in and out of their beds.

In contrast, in large community studies, about 50% of positives in Iceland were asymptomatic, as were 45% in large scale community testing in Indiana, and 43% in the town of Vo in northern Italy. Moving up the spectrum, that Antarctic cruise that tested everyone on board found an 81% rate of asymptomatic positives despite Antarctic cruises having an average age well above a typical population. At the extreme end of the spectrum, a little over 90% of the positives at the St Joseph, MO, meat processing plant were asymptomatic. In correctional facilities, multiple reports detail the same trend: a four state review found an asymptomatic rate among 3277 covid-19 positive inmates to be 96%; and in two facilities that followed prisoners for 2 weeks after PCR testing, Montgomery County (PA) prison posted a 95% asymptomatic figure; and 99% of positive inmates at the Bledsoe County (TN) Correctional Complex lacked symptoms.

These are eye-opening numbers that largely escape discussion by the press – except for comments like “asymptomatic transmission has caused particular challenges.” I get it — it is hard to find and isolate asymptomatic carriers. However, I might add, “asymptomatic patients don’t take up hospital beds or die of covid-19.”

A recent, hotly-contested study suggested that aerosolized spread, not the widely assumed droplet spread, was the primary driver of covid-19 infections. This may or may not end up being borne out by future studies. The implication is that poorly-ventilated indoor gathering spaces could be spreading infection by circulating fine particles with small amounts of virus that evade the immune responses in our mucous membranes and head straight into our respiratory tract. This might just explain the low percent of symptomatic cases in this exposure setting versus others of the “direct hit,” large droplet variety — like nursing homes and bars after sporting events.

The hope is that these mild cases produce lasting antibodies just as well as serious cases. We are a long way from knowing this with confidence, due to a lack of systematic follow-up testing. However, a recent Lancet article detailed 9 PCR-positive patients from the Diamond Princess cruise. Unsurprisingly, 6 were completely asymptomatic, and all of them tested positive for IgG antibodies to SARS-CoV-2. This is a tiny but encouraging report. On a larger but less scientifically rigorous  scale, two correctional facilities with a high proportion of asymptomatic covid-19 patients performed antibody testing on their entire populations: George W. Hill (DE) Correctional Facility found 43% of inmates to have antibodies, and Parnall Correctional Facility (MI) reported 92%!  What does an exposure that produces antibodies while only rarely causing symptoms remind me of? A vaccine. Unfortunately, these numbers cast doubt on the WHO’s recent assertion that asymptomatic patients rarely spread the virus.

In any case, as economies re-open and people return to large-scale work environments, if the exposure types favor asymptomatic disease, we might expect a smoother passage to herd immunity than first-wave, lockdown data might predict.

4) Having Immunity

An individual’s immune system is the other essential factor which determines whether an exposure leads to an illness, and how severe that illness becomes. The assumption behind our basic (1-1/R0) calculation for herd immunity is that everyone entered 2020 equally susceptible to covid-19. The closing line of a depressing May 29 New York Times article on herd immunity was that there were “…328 million Americans who were susceptible to this when this started.” It’s worth looking at that line of thought a little more closely.

Our immune system is mind-blowingly complicated. We humans are exposed to viral particles in every social situation. As a first line of immediate defense, we have an “innate” immune response – things like skin, mucous, a cough reflex, and, more glamorously, immune system agents like cytokines and “Natural Killer” cells, that recognize antigens like viral particles that are “not self” and rapidly act to limit their ability to gain traction in our bodies. The “adaptive” or “acquired” immune response, on the other hand, involves recognition of antigens from prior exposure and the production of antibodies to neutralize antigens, and requires days to take full effect. These two types of responses are deeply interconnected, but those are the basics. The rubber hits the road when the immune system is exposed to viral particles that pass through our physical defenses.

Some people are going to be more vulnerable to an exposure to SARS-CoV-2. Old age is associated with weakening of the innate immune response. So, too, is chronic disease. Certain comorbidities dominate covid-19 cases: high blood pressure, obesity, diabetes, and heart disease. These seemingly disparate health problems all share one common ground: the metabolic syndrome. Put simply, metabolic syndrome is a problem of insulin resistance. Insulin resistance, we are beginning to discover, is a disease process that affects every aspect of our health, including our innate immune response. The pro-inflammatory state found in people with metabolic syndrome is likely related to the excess inflammation thought to play a role in the “cytokine storm” and other severe inflammatory reactions seen in the worst covid-19 cases.

Put simply, a healthy 40 year old is less likely to turn an exposure to SARS-CoV-2 into a significant illness than an obese or diabetic 40 year old. The same goes for a healthy 75 year old versus an unhealthy peer. What’s more, psychological stress was shown in a decades-old study to inhibit the immune response. The same goes for sleep deprivation.  (The physician in me notes that healthier Americans would, in turn, be less vulnerable Americans in times of a pandemic.) Back to herd immunity, though — the most susceptible members of a population are most likely to turn an exposure to virus into an illness, and spread disease.  These same people are more likely to have antibodies (or have died) from the first wave of a pandemic, and this phenomenon further lowers the herd immunity threshold.

Another factor worthy of mention is the possibility that significant “partial immunity” might exist to covid-19. The notion that the known cold-type coronaviruses, especially if acquired recently, might convey some immune protection was presented early in the pandemic. Watching much of the developing world resist major covid-19 outbreaks, some have posited — controversially — that the common tuberculosis vaccine, BCG, might confer some resistance; and, similarly, the oral polio vaccine. Whatever the source of pre-existing immunity, a pre-print paper released last month from the La Jolla Institute for Immunology found that 50% of their pre2019 control blood samples had immune cells which reacted to SARS-CoV-2. Granted, the study was small (40 subjects); it had not been peer-reviewed; and all the action took place under a microscope and not in a human body; but, still, the notion is plausible. It is the old concept of  “immune imprinting.” We don’t doubt that prior flu exposures to different strains from past years provide some protection against new strains of flu. The upshot of the La Jolla study, which was primarily designed to investigate vaccine targets, largely escaped media notice. That is, until May 27, when the Conservative Review ran the following tantalizing headline: “Horowitz: Bombshell study: Could half the uninfected population already be partially immune?

The prison or cruise sub-populations which have reached 60-90% prevalence tell us that no, half our population does not appear to be immune to covid-19. However, any factor that contributes to a less-susceptible population will help lower the herd immunity threshold, although the durability of that effect is hard to predict.

5) Putting It All Together

The first question to ask would be: “Is what we are seeing happen in the real world in line with a 60% herd immunity threshold or more like 10-20%?”

To attempt to answer that, we in the Western world look to Sweden. While Sweden has taken a good many measures in the realm of social distancing, among them outlawing gatherings over 50 and closing secondary schools and universities, they have not approached the restrictive lockdowns seen elsewhere. As such, epidemiologists the world over warned that anything less than a total lockdown would doom Sweden to overwhelmed hospitals with tenfold ICU demand beyond capacity and a massive death toll.

What really happened was a more tempered outbreak. Here are screenshots of the actual ICU data, from the Swedish Intensive Care Registry; and below that, the actual total deaths per day, from Worldometer:


What began to push ICU and death rates down in late April over a month after restrictions were put in place? While the effective reproduction number was estimated to be 1.6 in Stockholm in early April modeling, why did it so quickly drop to <1, shrinking the outbreak, without any new restrictions?

If you answered, “summer backstop,” please try again. Not only do we not know why, or even if, a “summer backstop” exists, but the weather in Stockholm was equally dismal from late March onward; the high temperature in May did not even cross 60 degrees Fahrenheit until May 21! Something else was going on.

Recently released data suggests that only 5-10% in Stockholm would have had antibodies to SARS-CoV-2 back in mid-April. Low as this sounds, perhaps the the most likely explanation is that Sweden was already beginning to flirt with the 10-20% herd immunity threshold as described by Gomes. Otherwise, we are left with the rather flimsy theory that it took the Swedes 5 weeks to really get the hang of social distancing and hand washing.

This explanation sounds radical if you have only been reading media reports on herd immunity. That May 29 New York Times article on herd immunity reminds us no less than five times that herd immunity requires about 60% of the population to become infected, and concludes, “most places would have to see 10 or more times as many illnesses — and possibly, deaths — to reach the point where an outbreak would not be able to take off.” Is that really our future without a vaccine or strict social distancing?

Here in the US, most everyone in the medical community (myself included) predicted a sharp rise in covid-19 illnesses within weeks after states began the re-opening process in late April and early May. After all, if the effective reproduction number could only be controlled by social distancing restrictions, it stood to reason that relaxing those restrictions would lead to a substantial increase in disease burden. Using hospitalizations as our benchmark (due to the well-documented problems with relying on case numbers), what we have seen has told a different story. A screenshot of COVID-NET hospitalization data pooled from14 states shows a steadily slowing hospitalization rate:

US covid-19 death rates, again courtesy of Worldometer, echo this trend:

The news right now is filled with alarming reports about rising hospitalization rates in certain states. However, a June 6 ABCNews report revealed that only 8 states are seeing rising covid-19 hospitalizations, while 5 are about flat, and 37 are actually falling. We are seeing many more stories about the 8 states rising than the 37 states falling! If herd immunity is protecting the hardest hit states of the first wave, like New York, Michigan and Louisiana, we might expect the states struggling now to have largely escaped a broad first wave. Indeed, using deaths per capita due to covid-19 as a rough yardstick for disease prevalence, those 8 states — Arizona, Arkansas, Mississippi, North Carolina, South Carolina, Tennessee, Texas and Utah — rank 22, 42, 13, 33, 30, 40, 41, and 45, respectively. Of the only two in the top 30 of most deaths per capita, Arizona has been virtually flat in hospitalization levels since late March, and deaths have been flat-to-declining since mid-April; and Mississippi, which never started down from its first wave, has seen essentially stable ICU hospitalizations and deaths since mid-May.

Again, it’s hard to explain what we are seeing on the ground with a belief that only social distancing and mask-wearing can protect us from wide-spread outbreaks of covid-19. Once we allow for the possibility that herd immunity might already be limiting the transmission and severity of this virus, what we see starts to make sense.

To be clear, this is not an exercise in finger-pointing. Your perspective on lockdowns depends on how you value lives lost versus personal liberty and economic health. What’s more, a place like Sweden — or insert any lightly-affected region here — might stereotype as younger, healthier, more conforming, less dense, and less inter-connected than your home region. New York City serves as a warning – sprinkle in high density, multi-generational homes, tightly-packed public transit, and sub-populations with poor health, and you see a rise in prevalence to 20%, and double that in certain neighborhoods. Declaring the imminent arrival of herd immunity in New York City once prevalence hit 10% based on the above arguments would have been dangerously wrong.

The other X-factor is your optimism about a vaccine. Your openness to embrace the herd immunity threshold as a means to naturally check covid-19 transmission can vary greatly with your feelings about a safe, effective, available, and widely-accepted vaccine arriving in the months ahead. There are plenty of reasons for pessimism. However, if a public health policy maker has cause to believe their region could be largely vaccinated in January, then they might justify a policy of maintaining a low reproductive number via social distancing, combined with active testing/isolation/quarantine policies to minimize cases, hospitalizations and deaths, while waiting for a vaccine’s imminent arrival. On the other hand, if you don’t expect a vaccine for another year, that sort of aggressive program might seem socially untenable. Yes, letting go of social distancing and a “test and track” mentality will lead to more deaths from covid-19. In the context of influenza (some 50,000 deaths a year) and tobacco (closer to 500,000), however, our society seems to have been pretty comfortable with tolerating a substantial amount of suffering and death in the name of personal freedoms and economic growth.

Every region is unique in their likelihood to benefit from herd immunity at current low prevalence levels. I see four types of regions in this regard:

  1. Places like Hawaii, Alaska, New Zealand, Australia, and Japan, which have had very low prevalence to this point, possibly in the <1% range, and a minimal outbreak. They were able to harness island-type status to limit clusters and risk of superspreader events, so have almost no herd immunity protection at this point – but probably benefit from unique societal/geographic/climactic factors to help provide a ceiling to their transmission rates. They are probably more vulnerable to a Sweden-like experience than the nightmare of New York City.
  2. Some areas had explosive early outbreaks, suggesting a high reproduction number, that were rapidly tamped down by a strict lockdown, like Seattle and San Francisco. These places make me nervous if social distancing is abandoned.
  3. Other regions never seemed to heat up much, even with lackluster restrictions, like Georgia and south Florida; both states have seen covid-19 deaths stabilize or decline since mid-April highs, despite easing social distancing requirements, suggesting inherently low reproductive rates, and might already be able to benefit in terms of herd immunity dynamics from a moderate prevalence in the 5-10+% range.
  4. Then there are cities like New York, Detroit, and New Orleans, where per capita death rates many times that of flu season imply relatively high prevalence rates coupled with high reproduction numbers; on a broad scale, they are most likely to already be seeing substantial limiting of transmission from approaching their herd immunity threshold, but on the sub-population level, they carry high risk of explosive clusters in places largely spared by their first wave.

Policy should flow from these self-assessments, on a regional level. Public health decisions should not be cookie-cutter policies. A city, county or state’s decision making needs to incorporate their willingness to assume health risk relative to economic risk, their confidence in a vaccine, the vulnerability of their population, and the interplay of reproductive rate and herd immunity threshold in their region.

Regions that are high on the scale of trust in an impending vaccine and fears over an elderly or unhealthy population rationally could pursue a strategy of aggressive containment. They might allow only low-risk groups to gather — like school children and younger workers — and avoid large events, continue social distancing while stepping up protections for the elderly, and actively test/isolate/quarantine. Their hope would be that a vaccine comes along and swiftly takes them over the herd immunity threshold.

However, regions not bullish on an imminent vaccine, and with a less vulnerable population or early indications they are approaching a herd immunity threshold, might choose a more nuanced approach. Spread among the young and healthy might be deemed a positive, in that the sooner herd immunity dynamics kick in, the sooner there will be fewer cases of covid-19 to spread from the low-risk to the high-risk. After all, we have seen all too often how difficult it is to put a bubble around the elderly in places like nursing homes. This approach could tolerate low or moderate exposure settings among low risk populations: workplace cafeterias, movie theaters, concerts for the under 40 crowd, or even football games, for healthy non-seniors. The idea is to avoid pot-bellied, 75 year old Philadelphia Eagle fans screaming near each other, or 50 year old hypertensive Eagle fans yelling at each other in the bars afterward. Situations that congregate vulnerable populations in indoor settings for prolonged periods of time are the most concerning; for example, churches and casinos fall squarely in this category, and I pray for social distancing and good ventilation in places of worship and wagering, both. Nursing homes are one of the few places where I think at least weekly PCR testing should be required for visitors and staff.

Places that choose to embrace less restrictive approaches will require vigilance to minimize the risk of a New York-style outbreak. Periodic antibody testing of randomized samples of the local population will help reveal if spread is slowing in ways suggesting herd immunity. Close watch on hospitalization figures for signs of explosive growth of serious covid-19 cases could merit  the re-establishment of practices likely to limit large transmission events, like banning large group gatherings and indoor dining.

If regions do things right, this country as a whole should avoid a panic-inducing second wave. Outbreaks will be unavoidable, and some of them probably will be severe. However, if we keep our eyes on the prize — herd immunity — we might find the road to a vaccine to be less rocky than predicted.


UPDATE 8-22-2020: This piece has aged fairly well, given that I started writing it almost 3 months ago! I think the experiences in states like AZ, FL, and TX – not to mention Sweden, which has made the strongest case for herd immunity threshold being as low as 10% in a favorable population – argue strongly that herd immunity dynamics probably kick in well under 20% even in these “hotspot” regions, unless you believe that more restrictive rules (i.e., mask mandates) and changes in public behavior were the primary drivers in each of these different states, and had a surprisingly rapid effect that coincidentally mirrored Sweden’s experience.

What would I change now? Well, clearly Georgia and south Florida had a much longer way to go to benefit from herd immunity than I expected in June! Their slow case growth in May/early June despite lax restrictions was more a combination of good fortune and a low R0 relative to, say, NYC or Milan, than any real herd immunity phenomenon. In all but the highest R0 regions, we are seeing how covid-19 can simmer for weeks or months before reaching exponential growth, a la Oahu right now. I also think the section on asymptomatic spread in congregate settings was grossly over-simplified, so I expanded on those thoughts and wrote a new (also long) piece.

All in all, the contrarian notion that herd immunity might explain the unexpectedly short burns of the worst hotspots is gaining traction, as evidenced by this New York Times article last week, with the headline, “What if ‘Herd Immunity’ Is Closer Than Scientists Thought?”

One Hundred Eleven Good Reasons to Avoid Antibody Testing for COVID-19

by Buzz Hollander MD
Antibody testing for COVID-19 is the new darling of the media. It seems that everyone wants to know whether that little scratch in their throat they had in early February might just mean they have antibodies to SARS-CoV-2! As scientists are interviewed touting the impressive accuracy of these tests, interest continues to grow about antibody testing being the key to “re-opening the economy” as people are able to learn their immune status. But is this going to be as good as it sounds?
Let’s look at two examples to better understand; one hypothetical, the other real world:
Covania is a small town of 1000 people in the outskirts of a metropolitan area with a significant COVID-19 outbreak. 5 Covanians ended up needing to be hospitalized in the initial wave of the outbreak, two required a ventilator, and one died of COVID-19. Officially, 25 Covanians were tested and 10 were found to be positive, including the 5 hospitalized patients. However, in our hypothetical example, 50 Covanians actually had COVID-19, although 10 never exhibited symptoms. The very high test positive rate of 40%, and the rather high testing rate of 2.5% of the population, mirror the numbers for New York City rather well; as does the deaths per million (DPM) of 1000 DPM that Covania’s single death produces. Covania’s true prevalence of COVID-19 at the time of this study is 5%(50 cases/1000 citizens).
Now, let’s add antibody testing to the mix. Our Dr Deborah Birx expects antibody testing to be about 90% specific and sensitive to this SARS-CoV-2 virus: 10% of positives would be false positives (“90% specificity”); hence, these people do not have antibodies to the virus despite a positive test. Likewise, 10% of people actually with antibodies to the disease will be told they are negative (“90% sensitivity”). If we were to test everyone in Covania in a couple weeks (to allow antibodies to form), the test would produce results like this:
950 Covanians with no COVID-19 X 0.1 false positive rate = 95 false positives
50 Covanians with COVID-19 X 0.9 true positive rate = 45 true positives and 5 false negatives
2/3rds of our “positive” results would be inaccurate. 140 Covanians might decide they can go out in the world without fear of contracting or spreading COVID-19, but 95 of those 140 would have FALSE reassurance!
Switch gears to a real world example: the Big Island of Hawaii. Prior to last week’s outbreak with 30 cases related to McDonald’s employees, there were 31 known cases. The positive test rate is app. 2.5%; well under 1% of the population has been tested, and the vast majority of tests have been administered to people with symptoms concerning for COVID-19, and often contact with people with known disease or travel to high-prevalence areas, given the difficulties with access to testing. It is safe to assume that the 97.5% of people tested as negative represent a substantially higher risk group than the general population at large. Moreover, the lack of any hospitalized patients would suggest that the 31 known prior cases are a fairly accurate count; even 31 cases would be expected to produce 2-3 hospitalizations in an average population, so the probability that many more than 31 cases existed a week ago, which would have allowed time to develop symptoms severe enough to warrant hospitalization, is quite low. An assumption of 50 true cases (prior to the McDonald’s outbreak) would be generous. This would indicate a prevalence of 50/200,000, or 0.025%. This is a fairly solid number – and a remarkably low one, at that – which we now must revise upwards given this new outbreak. For the sake of the model, let’s be neither optimistic nor terribly pessimistic, and say these 29 new cases mushroom into 150, bringing our total number of cases up to 200; at 200/200,000, we have a new prevalence of 0.1%.
Now let’s see how useful antibody testing would be:
199, 800 Hawaii County residents with no COVID-19 X0.1 false positive rate = 19,980 false positives
200 Hawaii County residents with COVID-19 X0.9 true positive rate = 180 true positives and 20 false negatives
20,000 people with the wrong test result! Most importantly: nearly 10% of the entire population would be reassured that they are safe to go back to work, to care for their elderly parents, to see patients in their clinics, etc – AND THEY WOULD NOT BE SAFE!  Only 180 people would benefit from the entire island being given this test and most of them would already have already received a positive PCR (“antigen”) test, anyway. The average person would be 111X more likely to get a false result than true!
Why does the test fail us so spectacularly? Taking a fairly accurate test for any disease and applying it to a population with a low rate of  that disease will always lead to a preponderance of false positives – poorly as it does on the Big Island, it will perform better in Covania, and better still in Lombardy. Improving the false positive rate makes a huge difference, as well. Increase specificity from 90% to 99% (and some antibody tests will claim this) and the numbers improve markedly: a 99% specific test in Covania with its 5% prevalence yields 5 true positives for every false positive – now we are starting to talk about a test worth running (with some caution). However, that same 99% accurate test in our Hawaii County example with 0.1% prevalence: “only” 1998 false positives for our 180 true positives. You are still 11X more likely to get bad information than good information if you take this test. The Abbott testing getting a lot of attention in California this week claims 99.6% specificity, a rather bold claim and one that needs to be tested in the real world; even at that rate, the Big Island would have nearly 800 false positives to accompany its 200 true positives – a 4:1 rate of bogus results and false reassurance.
In summary: unless COVID-19 spreads much more broadly through the population of Hawaii County, or someone, somehow, develops a true 100% specificity test, you are far more likely to be given a test with a false positive result than an accurate result. Pass on taking an antibody test, unless either these numbers change dramatically; or you were at a very, very high risk of exposure to the disease.
UPDATED 8-22-2020: All these principles have held true over time. Many of the antibody tests have been shown to be quite accurate; but concerns have mostly been based on their lack of accuracy in low prevalence populations, as discussed. The main additions are that we now have reason to believe that many people recovering from covid-19 have lost detectable antibodies within 2-3 months of infection, further limiting their usefulness.

Uncertainty and COVID-19: Managing a Pandemic with Bad Data

by Buzz Hollander MD

When do we get to leave our house again?” This is a question we can expect to hear more and more in the days and weeks to come, along with its distant cousin: “Did we overreact to the threat of COVID-19?” Most of the media focus these days continues to involve mortality rates, overwhelmed hospitals, PPE, and ventilators, but as places like New York City and New Orleans begin to turn their respective corners, the “opening up” of the American economy will begin to take center stage. The problem is that predicting what will happen next is marred by uncertainty – the uncertainty begotten by bad data.

UNCERTAINTY #1: The severity of the first wave. 

As the world watched COVID-19 sweep through Wuhan, and then Lombardy, the “expert opinion” was: “look out – this is what your city will look like in 9-14 days!” This turned out to be eerily true in New York City and a handful of other American cities. However, even some of those places for which early modeling depicted scenes of horror in hospitals and morgues, like Seattle and San Francisco, emerged with one tenth the per capita suffering as New York. Why the difference? Many theories have evolved: the role of subways and intense population density; possible differences in viral strains; the prevalence of multi-generational housing; variations in climate; demographic and genetic/ethnic trends; timing and quality of the lock-down response. However, all of these theories have obvious flaws as primary explanations for the differences between regions, and none of these theories can be supported with great data. While it looks increasingly likely that Sweden will win its gamble with minimal government intervention by suffering only a modest increase in deaths compared to its locked-down neighbors; and that New York should have shut down more decisively and earlier, akin to California; and that the UK will fall somewhere in between despite its deliberately slow response; what is also clear is that there was really no way for the leadership of those different places to know what the best course of action would be. The risk of Lombardy hovered over everyone, and some places (New York) have endured that risk becoming reality; and others (San Francisco) have not.

UNCERTAINTY #2: The severity of future waves while awaiting a vaccine or effective treatment.

Some models have predicted that with relaxation of restrictions, the next waves will mirror the first. This does not make a great deal of common sense. We might reasonably expect that those most vulnerable to developing symptoms (and serious illness) to COVID-19 would have been disproportionately represented in the first wave statistics. In other words, assuming some people have advantages in fighting off this viral infection based on genetics or overall more vigorous health, these people would be less likely to have gotten ill from a mild exposure to COVID-19. People with less vigorous immune defenses would be more likely to fall ill with the same exposure. Hence, each successive wave of exposures leads to a lower rate of illness than the prior on a “per-exposure” basis. Future waves should be at least a little buffered from serious disease compared to the initial, on that basis alone. More importantly, there will also be a completely different set of obstacles to transmission for the virus to face than it did as it entered the first wave. Workplaces doing fever tests. A lot of people wearing masks. Handshakes, hugs and kisses, and nose-to-nose discussions, greatly reduced. Sporting events, large funerals, and choral practices banned for a spell. Barring a viral mutation to the worse, which virtually no one is predicting, it is hard to make the case that a second wave will be anything but gentler than the first. Whether it will be 10% gentler or 300% gentler, however, remains anybody’s guess.

UNCERTAINTY #3: The role of herd immunity in reducing the severity of the pandemic.

Some respected voices in the debate of how best to manage this pandemic have taken the side that the virus is already more common than we know, and that “herd immunity” is quietly building, and therefore we should relax restrictions and let it finish its natural course.

Herd immunity – the concept that enough of the population has antibodies to a given infectious agent that its transmission becomes so low as to eliminate it as a problem – is a popular concept to invoke amongst those who number themselves in the “business as usual” crowd. This is the sunny daydream of epidemiologists studying COVID19 with an optimistic attitude. The idea would run like this: a large proportion of people in an affected population get mild or no symptoms, never get tested or suspected of exposure, and when we have accurate antibody testing we will find that the majority of people after the first wave of illness will have already been exposed and have immunity to COVID19. If this number breaks over 60% or so, future spread of COVID19 will be tempered by the lack of receptive “COVID19” potential victims, and a population could see a slow, manageable ascent to herd immunity, when 95+% of a population has protective antibodies to a virus. Sounds great, doesn’t it? The problem is the lack of data to back up these suppositions. In places where entire populations have been tested, i.e. Vo, Italy, the rate of infection tends to be low, well under 5%; and even heavily-exposed populations like the beleaguered Diamond Princess cruise ship was under 20%. Unless the rate of false negative antigen tests is very much higher than we believe, there is almost no way that more than 10 or 20% of even the hardest hit regions, like northern Italy, have antibodies to this illness. If that is the case – imagine how bad Lombardy, Madrid or New York City would have looked had the authorities there not enforced social distancing!  Conservatively, double or triple the case rate in New York, and run that through your imagination. Barring the deus ex machina scenarios that mild disease already abounds and has avoided testing, we develop a highly effective treatment, or the virus mutates to be less lethal, there are two ways to achieve herd immunity to COVID19: let a potentially huge number of people die, many times over what we are seeing with social distancing requirements; or wait for a vaccine.

UNCERTAINTY #4: The cost of a government-imposed shut-down vs the disease itself.

This is a hard one to even talk about. You hear headlines like, “One unnecessary death from COVID-19 is one death too many”; and the governor of Hawaii expressing condolences to the family of each victim of COVID-19. The hypocrisy is obvious. No such announcements are made during flu season, despite the fact that Hawaii is likely to see only a fraction of its residents die of COVID-19 than the flu this year. Tobacco is still legal in the United States despite its excess mortality being far greater than any viral infection. No one is padding every tree on every roadway in America with thick cushions to reduce the incidence of traffic fatalities despite their causing 35,000 deaths annually in the US. Why not? Almost any intervention to reduce mortality comes at a cost; a cost to liberty, or a financial cost. The means to reduce the impact of COVID-19 have both these types of cost.

From a public health perspective, the ideal approach to re-introducing commerce would involve a lot of government restrictions: restricted travel from high-prevalence regions; limited socializing for the elderly; bans on large gatherings; possible continued school closures; and perhaps even requirements to show proof of prior infection, or of lacking high-risk co-morbitidies before allowances to travel freely throughout society. This would have an immediate cost to liberty; and perhaps a long-term price even higher, as the populace gets comfortable with being monitored in ways that seemed Orwellian a few months ago.

Then there is the economic cost. This has been well-documented. The deliberate shut-down of most sectors of the national economy has already had a disturbing effect on the unemployment rate; is triggering a recession, possibly a long and profound one; and has led to a massive government bail-out, one which will either lead to increased taxes, a devalued dollar, long-term limited growth, and/or all of the above. Such economic costs also come at a price to human health. People lose their health insurance. Technologies that can save lives get put on hold. Suicide rates climb. Nutrition gets compromised. Although in the short term, mortality in the western world tends to improve in a recession because people do fewer higher-risk activities, we lack numbers on what happens in the long term. Was there an alternative to government shut-downs?

 Letting COVID-19 “run its course” would have its own cost, too. Not just with a higher death rate, either. These are all very much “back-of-napkin” projections, but it seems reasonable to think the cases and deaths could easily have been many times what we have actually seen with strict lock-down responses. If you double the number of hypothetical New York ICU beds to, say, an additional 30,000, and calculate the expense of an average ICU stay to be $50,000 (a conservative estimate, to be sure), some astronomical numbers begin to appear: $1.5 BILLION in New York alone from additional hospital expenses. Then there is the loss to the work force of more people getting ill, and more people caring for ailing family members. Add in a paranoid populace not going out to eat  much or showing up for work of their accord, taking its own steep toll on the economy. Would a lot of tourists have showed up at Times Square during a hypothetical COVID-19 outbreak even worse than we have witnessed? You can make the case that an expensive recession was inevitable in those places getting badly hit by COVID-19, even without government-enforced lock-downs; and that the “savings” in terms of minimizing deaths and severe illnesses are well worth any additional cost. A contrarian, however, could make the case that on a national level the risk of “having a few New Yorks” being even worse than they were would have been a fair trade for not having the entire country suffer economically the way it has.

One thing is certain: we will never know with certainty who would be “right.” As a country, though, there are some hard decisions to make in the weeks and months to come, and they will have to made with bad data shedding its murky light. There is a growing chorus of how the country can be “re-opened”, however, and there is good reason for hope that this can be done without a repeat of the damage seen from COVID-19’s first wave. This is a certain topic for a future post!

What to do, what to think about and what to take – a few thoughts on health and Covid-19

by Michelle Suber, ND


We at Iris Integrative Health have received countless calls and emails over the past few weeks from patients, most with variations on the following questions:


How can I prevent coronavirus?

What should I or a family member have on hand if I do get coronavirus?

What supplements should I be taking to support my immune health?


My invitation is to expand our questions to include these:

How can I best prevent infectious disease?  While Covid-19 is unique in many ways, we will surely be faced with other viruses – and global health challenges – in the future.

How can I best prevent chronic degenerative disease?  We know that excellent health is an important predictor of outcome should one become infected.

What is health?  When we read that young healthy people are contracting Covid-19, we must wonder what is meant by “healthy.”  Typically this means that they don’t have a “problem list” or list of diagnoses.  This does not mean they are truly healthy.

What should I do to optimize immune function?  What should I do to be healthy?  How can I support my family and community, not only in this time, but in the future?

What changes am I being called to make?  What changes are we being called to pursue globally?  What is my role in this collective process?


These questions are both more productive and proactive than putting all of our focus on the effects of a single virus.  By no means do I intend to diminish the significance of this global pandemic, which seems to have turned our world upside down, at least temporarily.  I recognize the immense suffering.  My intention is to provide a set of guidelines and things to consider not only to protect yourself and your family, but also to harness this opportunity to live with more vitality and awareness.


For the past few weeks, I have been delving deeply into the most evidence-based strategies for the treatment and prevention of Covid-19.  I will focus here on prevention.  Interestingly, prevention of Covid-19 appears to be very much like prevention of other viral illnesses.   Should you fall ill, please do let us know; the strategies intensify and change.  We are here for you and prepared should this occur.  I have broken my suggestions down into three categories:  what to do, what to take and what to think about.  I expect that some of the more specific approaches will change as we learn more about Covid-19, but many are in place to help you be the healthiest you can be.


What to do

There are themes here that make these suggestions look a little different for everyone.


Get at least 8 hours of quality sleep every night.  At least 2-3 of those hours are ideally before midnight.

Exercise daily, preferably in the fresh air.  This can have a profound effect on all other health habits.  I recommend different types and intensities of exercise to each patient, but aim for 60 minutes/day, which a combination of aerobic and strength building movement.  Please talk with me for details if you want help with your exercise plan; we can make it very tailored to your current abilities and future goals.

Eat well.  This is a big one!  If you’re one of the several hundred people for whom I’ve done genotyping, you’ve got your blueprint for ideal nourishment.  Good for you!  If you don’t, and at least know your blood type, consider following those guidelines which are in place to optimize your immune response.  If neither of these apply to you, then at least be sure to include 5-7 servings of vegetables and 2-3 servings of fruit daily.  Avoid processed sugar and any junk foods.  Enjoy local, clean, organic, whole food as much as possible.  Take your time cooking and preparing food; then eat slowly and with awareness.  A few important foods to remember right now are in the allium family:  garlic, onions, shallots and leeks.  Green tea is also quite anti-viral.  If you have blood type A (and are therefore slightly more vulnerable to a poor outcome with Covid-19), incorporate silver dollar mushrooms, soy (real food, not powders or isolates), fava beans and Great Northern beans.

Stay warm with saunas, exercise, steamy showers.  Always end these hot exposures with cold immersion/cold shower.

Spend time in nature.  Slow down and listen.  Observe.  Relax.   If you’re in a place you can go outside, do so (with no device in hand!) for at least 30 minutes.  If you’re not, still turn off that phone, open your window and breathe.  To that end, limit time on social media and watching the news.

Stay connected with others.  Social distancing does not (and should not) mean isolation.

Find your purpose and find a way to express that every day.

Do things you love.

Feel and express gratitude.

Be of service to others.  (Opportunities abound.)

Don’t skip these last 6 things!  They sound soft and fluffy, but they all have solid scientific, peer reviewed evidence for their roles in the prevention of chronic disease and the promotion of longevity.  They also, along with exercise and sleep (and many other things like yoga and meditation), modulate stress; and this is key to optimal immune function.   If you need help with any of these concepts or want to brainstorm with us, let us know.  We also can suggest some good books to help get your wheels turning.


What to think about

Certainly life will never be the “same,” even after the threat of Covid-19 is in our rearview mirrors. How can we shift our thinking from being afraid to being proactive?    Consider the fact that this virus has brought movement all over the planet to a screeching halt.  We are asked to stay home, spend time with our families, stop traveling so much, and pay very close attention to everything we bring into our home.   We also need to be very creative about what really needs to be done in person and what can be done well remotely.  Our health has become a whole new priority.  Our teachers and farmers and nurses are now our heroes (they’ve always been, but we know it even more so now).   Many things suddenly seem insignificant; will it serve to let these things go?  The opportunity for personal and collective healing is significant.  I recommend that you focus your mental energy on these things instead of worst case scenarios.


What to take

I’ll bet some of you jumped right to this section, right?  I listed it as my third category because I feel that it is the least important.  If you’re my patient, we talk about this all the time:  in terms of importance, supplements comprise perhaps 5% of a treatment plan, and what you do and how you live is about 90%.  These numbers are my own and based on 22 years of practice.  That last 5%?  You did the math!  It is different for everyone and sometimes in the realm of the unexplainable.  I like to keep an open mind about what this might be for each patient.  But for now, back to supplements.  They are ideally prescribed personally and tailored to the unique needs of the individual.  But until we can do that one-on-one, here are some guidelines:

Vitamin C 200mg – 1500 mg 3x/day.  Dose will vary per individual bowel tolerance.    Choose a formula that is clean and made with integrity (this goes for anything you put in your body).  My personal favorite is Potent C Guard by Perque.

Melatonin 3-6 mg before bed.  If you’ve had untoward experiences with melatonin, do not take it (of course).

Curcumin. Dose will depend on preparation.  A good formula is Theracurmin HP by Integrative Therapeutics, dose here is 2 capsules/day for 1 week, then decrease to 1 capsule/day.

Zinc 15-30 mg/day as a lozenge; best with food.

A high quality multivitamin.  Compare yours to Multi-Nutrients III by Vital Nutrients.  3 capsules 2x/day with food.

Selenocystiene or selenomethionine 200 mcg/day *or 3 Brazil nuts/day.

Elderberry 1 teaspoon/day.  In our family, we expand this approach and enjoy Fruit Anthocyanins, which includes elderberry.

Vitamin D3 5000 IU/day with food.


Most of these supplements you can find online or at Iris.  Please let us know if you have any questions about dosing or reputable companies.

In conclusion, YES stay at home, YES wash your hands, YES clean everything. Do your utmost best to “flatten the curve.”  These things go without saying.  But remember that this is a chance for all of us take a broader view,  be healthier, live better and revolutionize the way life is lived on our precious planet.

Many NDs have been particularly eloquent and comprehensive about Covid-19.  One of them is here:

COVID19 By The Numbers- for people who like numbers!

by Buzz Hollander MD

***COVID19 disclaimer: I am not an epidemiologist nor an infectious disease specialist. I am a humble family doctor who likes to study numbers. This is for other people who like to study numbers. Take what follows with a grain of salt as many of the professionals would disagree with my conclusions.****

The number to ignore is… “confirmed cases”. 

Many people have raised our awareness that the number of known cases is grossly under-represented due to the lack of testing. Testing varies by country. It varies within a country by region. It varies by timing within a region, as most testing is limited in the early phases of an outbreak as a country “gears up” for the infection, and might be limited again later in an outbreak as a country “gives up” on aggressive testing. Here in Hawaii County we are still in the “gearing up” phase, with perhaps 200 test results reported as of March 28th. That’s 0.1% of the population with a known test result. While an accelerating number of deaths is always alarming, an accelerating number of “confirmed cases” might just be indicating an accelerating capacity to test.

The best number to watch is… deaths. 

This is not just because deaths are a fair surrogate marker for the suffering and loss a country experiences. It is because deaths are the hardest number to get wrong. Imperfect, yes – surely some people died of unrelated bacterial pneumonias or heart failure cases and were mis-ascribed to COVID19 deaths. However, this is our most solid number to track the progression of this disease. It is also a “lagging indicator”, meaning the by the time someone dies from COVID19, weeks have probably passed since they became sick. That means that the death toll better represents the severity of a growing infection 2-3 weeks ago rather than now. This is why it is such a hugely good sign when the death rate starts to drop, and so alarming when it is rising exponentially. That rapid growth is the signal that 2-3 weeks ago cases were exploding, and only the leading edge of the wave is hitting.

The numbers we want to know about our COVID19 test are… missing.

We have a fair sense that the many tests out there for COVID19 are fairly accurate. That’s about it. Every test needs a “gold standard” to evaluate it. If I invent a new stool test to screen for colon cancer, I compare my test results to what is found on colonoscopy, as colonoscopy can detect the vast majority of colon cancers and is considered our “gold standard” for the purpose. To the degree that the gold standard fails to be accurate, my new stool test becomes harder to evaluate. When it comes to COVID19, we have a test, but no gold standard with which to compare it. If someone took the time to follow a couple thousand people tested for COVID19, and observed them for 3 weeks, and made sure a CT was done on all the positives, and evidence of viral shedding was studied on all the negatives, we could have a good sense of how “sensitive” (able to avoid false negatives and miss people WITH the disease) and “specific” (able to avoid false positives and mis-label people WITHOUT the disease) the test is. No one has the time or resources to do this, yet. 

Why does this matter? Well, if we knew the test rarely had false positives, we could aggressively test low risk people without symptoms. If positive, we isolate them and reduce transmission. However, some Chinese researchers have suggested that the false positive rate might be rather high. That’s okay if you only test high-risk people, but if you start testing low-risk (asymptomatic) people your results get wonky. Think of using an accurate test, like tests for banned substances in athletes, and assume it is about 97% specific (ie few false positives). It works pretty well at finding a high rate of true positives in a collection of professional bicyclists who were not anticipating testing. But, if you tested 100 accountants who ride recreationally, you might expect to get 3 positives, all of them false positives. When we test asymptomatic people in households or cruise ships, we don’t know if we are getting mostly true positives or false positives, and it skews how we might view the contagiousness of this virus, and which measures of containment are needed. We also know there is a substantial false negative rate with these tests, often needing two or more tests to find a positive COVID19 case, and this makes triage of sick patients all the harder. My take-away point is this: when you hear that 600 out of 3000 tested people on a cruise ship of 3600  tested positive for COVID19, but only half had symptoms, think of professional bikers and accountants. Did 600 people on the cruise really have COVID19? Or was it closer to 300? We don’t really know until we understand our test accuracy better.

The mortality rate of COVID19 is going to end up being… low.

Not WHO 3.4% high, anyway. The numbers reported from Wuhan initially, and now Italy, are rather shocking, 4+% in the former and up to 8% in the latter . Since the percentage comes from the number of deaths in the numerator (which we trust) divided by number of cases in the denominator (which we don’t), we take the mortality rates with a grain of salt. One theory for the variance is that overwhelmed health care systems, like northern Italy and Hubei Province, lead to excess deaths. The very interesting articles from Tomas Pueyo (a fellow non-epidemiologist) that have widely circulated and are worth a read repeat this theory: when we do not “flatten the curve” and hospitals get overwhelmed by a large initial wave of CIOVDFI19 infections, the death rate goes radically higher due to reduced hospital capacity. I agree with most of his conclusions, but I doubt this theory. Data from both Italy and China suggest that about 50% of people admitted to the ICU with severe disease die. A small study from China showed that 80% of people who made it to a ventilator died anyway, and a colleague from the West Coast is suggesting that number might be closer to 90% from his experience. Increasing ICU beds and ventilators would not seem to be the intervention that led to a 4% mortality rate in Hubei and a 0.5% mortality rate in the rest of China, an 8-fold improvement. Fewer people getting sick would be the significant intervention that led to the 8-fold improvement! Why the high mortality rate in those settings early in the outbreak, then? Testing lagged behind deaths in the early going in both places, and the Italians are still not testing in anything like the numbers we see the South Koreans or Germans doing, for instance. The places that test broadly, report mortality rates around or under 1%. This is the number to expect when the dust settles, and more likely lower than higher.

So, when it comes to the mortality rate, the country to follow is… South Korea.

Of large countries with a major epidemic of COVID19, South Korea tested the best.  If you had a cold, you got tested. They might even be the one place where the mortality rate might be falsely low from over-testing and finding false positives! Still, their mortality rate has to be considered the most solid of anywhere, since we trust their denominator (cases) as well as their numerator (deaths), and they are seeing a mortality rate right under 1%. When commentators draw on the data from Iceland, which has almost no cases reported in those over 80 years of age, to make the case that the mortality rate might be lower than that of influenza, maybe even 10 times lower (!), you have to question whether Iceland is the useful place from which to be gathering data, given its stark contrast to other places that have tested thoroughly. Try telling an ICU physician in Milan or Madrid that the mortality rate of COVID19 is less than the flu!

The most useful contagious disease to compare COVID19 to is… the flu.

This comparison is getting widely panned in the media, for good reason. What COVID19 is doing to the hardest hit regions in the world is worse than the worst of flu epidemics in the past century. However, it is still a useful comparison given our lack of data on COVID19, and our abundance of data for influenza. While COVID19 is probably rather more contagious than the flu, and 10 times more lethal, we can project from flu data and make some rapid conclusions about COVID19. We can extrapolate that if we sit back and do nothing and let COVID19 spread like – well, the flu – we can guess that it will cause at least as many cases as the flu, if not many more; and kill 10X as many people that contract it. This is a 20 second, back-of-the-napkin calculation that was available to every world leader by mid-February.  Some world leaders would probably like those 20 seconds back.  

The other relevant aspect of the flu is that the capacity of our ERs and ICUs have been indirectly determined by it. Car accidents, heart attacks, cancer complications – these are fairly steady over the year in large populations. The flu drowns the ER and ICUs for a few weeks or months every year. If a hospital cannot handle the surge of flu cases in your community in a “bad” flu year, it is forced to revamp and increase capacity. It is a fairly safe estimate that if COVID19 starts turning in seriously ill patients at a rate 2-3X what the flu does in a given community, that hospital will be overwhelmed, a la Bergamo. 

A mortality rate of 1% applied globally if COVID19 transmits like the flu would be… catastrophic.

Thinking the mortality rate will be low does not mean I find COVID19 anything but alarming. The math is simple, and has been widely shared. If 10% of people get the flu each year, and the flu is really not as easily spread as COVID19, we might expect that more than 10% of people would get COVID19 in the world’s population. Let’s just use that 10% number because it’s easy. Couple it with the 1% mortality rate. That means if you want to see how many people will die in your country if we take a “business as usual” approach, it would be 0.01 X 0.1, or 0.001 of the population, or 0.1%. 350 million Americans X 0.1% = 350,000 deaths. That’s 7X a typical flu season. Double that number if the transmission is twice as high, a reasonable supposition. Go up to 30%, and now we have a million Americans dying. These are catastrophic numbers unless your biggest cause is controlling population growth.

The most useful to consider from a Public Health Policy perspective is… deaths per million (DPM).

This number does not have much traction in the media, but it is very useful. 3,000 deaths in China with its 1.4B population is remarkable compared to 10,000 deaths in Italy with its 60M population. China is sitting at 0.5 deaths per million inhabitants. Even in Hubei Province, with its population of 60M, the DPM is still only around 50. Flu season in the USA sees a DPM around 150. Reassuring, right?

The reason why COVID19 is causing mayhem in hospitals in some places, and hardly a ripple in others, is… uneven distribution.

The flu tends to spread through the country in a fairly orderly and predictable wave. COVID19 hits more like a cell of tornados, selectively smashing certain areas. Wuhan got smashed; the rest of China did not. Lombardy, Italy got smashed and still is; Rome is not. Seattle, New York and New Orleans are getting smashed; most other cities are not (yet). Italy still only had a DPM in the 80s with a death toll around 5,000- so what was the problem with Italy? The problem is that when the Italian DPM was 80 for the entire country, the DPM in Lombardy was around 300. “Only” double the death toll we see with the flu, and the system was overwhelmed and reports from hospitals in the North sounded straight out of dystopian novels. Their DPM has since risen to around 600. This is why Italy shut down the entire country, and not just the North, once the severity of its problem became apparent. When people talk about 60% of Americans getting COVID19 if we do not take preventative measures, it would lead to a DPM on the order of 6000.  Folks that think that all this “shelter at home” stuff is a huge over-reaction can mull over that number – while they are staying at home.

The rate of infection in the general population now is quite low… probably under 1%.

We hear about the case numbers in cruise ships and nursing homes that get publicized, and it’s easy to think that those people grabbing rolls of toilet paper out of our hands at the Costco are surely infected. Actually, they’re probably not. In this case, the denominator is the population with which you are concerned. Let’s take our country. The denominator is 350 million. The infection rate, which in epidemiological parlance is the “prevalence” – what percentage of people in a population have a given problem – is the number of cases divided by the total population. We know we cannot trust confirmed cases as our numerator. However, we can make educated guesses based on the number of deaths. Since we are trusting our mortality rate of 1%, it takes about 100 cases stewing out in the real world for 2-3 weeks to see one death. Here in Hawaii County, having not had our first death, or even publicly announced confirmed ICU case of COVID19, we can assume that the number of cases as of two or three weeks ago (the amount of time from infection to death) was probably under 100. If we really don’t even have a COVID19 case in the ICU, since people end up in the ICU earlier and more often than people who die of COVID19, we might argue that as of a week ago Hawaii County probably had fewer than 50 cases. 50/200,000 is a tiny prevalence. However, since our “confirmed cases” continue to rise, and those are only the tip of the iceberg, we can trust that number of actual cases to be far higher now – but still well under 1% of the population. That level would require 2,000 actual cases. When populations are fully tested, we get a better sense of the true prevalence. An Infectious Disease specialist friend in Seattle (who does not endorse my conclusions on prevalence!) shared that they tested an entire nursing home where a death was reported: 30 employees and 100 nursing home inhabitants, and 6 positive tests (counting the death). Prevalence:  5%. The infamous Princess Cruise line with 3000 passengers stranded at sea ended up with about 600 positive tests after quarantine was complete, a rate of around 20%. They tested every one of the 3000 citizens in the Lombardy town of Vo: 66 positives in the town that essentially started the Lombardy outbreak with its first death, or a prevalence of 2.2%. (This “experiment” in complete testing, by the way, resulted in a prevalence of zero after isolations were completed). The Kirkland, WA, nursing home: 300 residents and staff, 63 infections, for a prevalence of 21%. In a Dutch hospital system where health care workers were starting to fall ill, out of some 6000 workers, 1353 people with any cold symptoms were tested, and there were 86 cases, or 6.4%. These are some of the worst possible sub-populations – a Lombardy town, the worst of the cruise ships, two Seattle nursing homes, a hospital system in the Netherlands – and the prevalence ranges from 2-21%. Your neighbor probably does not have COVID19. Yet.

The “acceptable” prevalence rate for an entire population is… well under 1%.

South Korea had about 100 deaths after the first rush of their outbreak. Given that they are now on the back end of the bell curve, we would expect that we can use the death rate as a fair proxy for 1% of the total cases that have happened in that country. We would estimate 10,000 cases based on their death rate;  unsurprisingly, given the excellent testing in South Korea, at they point where they had 100 deaths, they had confirmed nearly… 9000 cases. About 52 million people live in South Korea. They kept their whole population prevalence rate closer to 0.01% than 1%! That is how you have only 100 deaths in a country nearly as populous as Hubei province and Italy! Our current “worst case scenario” which has completed its first wave of deaths – Wuhan – might be useful in determining an “acceptable” prevalence, based on a  flu-like impact. With 3000 deaths, we can assume there were about 100X as many cases, or 300,000. Within a population of 60M, that would be a prevalence of 0.5%. If Hubei had its nightmare with a prevalence of 0.5% – followed by a shut-down of all activity that could probably not be imitated in the western world – you can see why estimates of 60% prevalence or more lead to disturbing scenarios.

What we are seeing in the world right now suggests COVID19 deaths from the first wave of the pandemic will be… more like the flu.

Mercifully, death rates have not been anything like the above calculations. Projecting them forward is of great interest. Hubei province and Italy both have around 60 million inhabitants. A typical flu season might see 5,000-20,000 deaths from flu in a population that size (Italy seems to over-report flu-associated deaths, while China vastly under-reports them, but again – we choose to trust our mortality rate of around 0.1% with the flu).  Italy has passed that lower limit of 5000, but we hope will not close in on the upper boundary of flu deaths of 20,000. China has squelched community spread of COVID19 and ended up with perhaps half the deaths in Hubei one might expect from the flu. Even if the US ends up more like Italy than Hubei, and it is beginning to appear that Italy and Spain might be statistical outliers, we can probably multiply the death toll in Italy by six (given we have about 6 times as many citizens as Italy) to estimate the upper end of our death toll. 25,000-100,000 would seem a fair, broad guess. This is our flu season in a bad year. Why “only” as bad as a flu season? Only because we are locking our country down!

The country whose strategy we should not emulate is… the UK.

The British do some things their own way; they speak American with a funny accent, and they add a syllable to “aluminum.” They have also had a rather unique response to COVID19 that makes even ours seem “pro-active” by comparison. The reports from the UK are that “the plan” was to let COVID19 cases build up right to the point that the health care system can handle- and then lock things down! The problem is, relative to the start of their outbreak, they are waiting to lock things down until well after Wuhan got locked down, in terms of reported cases or DPM. This means they can expect a Wuhan-like experience in the weeks to come. And worse. Why did they deliberately wait before starting to shut things down? Their experts informed their policy makers that if they shut things down early, they would only delay the wave of deaths, but not the number of deaths, nor the chaos. I think this is a flawed theory. Acting early and aggressively – i.e., in the style of non-Hubei China, South Korea, or Hong Kong – has been very promising at limiting deaths per million to a fraction of what the late-responders experience. China has virtually eliminated new cases. South Korea has stabilized their death rate at a low level. Are they destined to have a second wave as bad as the first would have been without such restrictive measures? I would argue that they have some distinct advantages from having already faced the enemy and bought some time: more supplies to stock their hospitals with; more test kits; the ability to jump on top of regional outbreaks with testing and isolation techniques; and a seasoned populace who has had a chance to adjust to “work at home” where appropriate. The next flare will not be as bad as the first – megachurches will employ spacing; restaurants will open back up but with a mind towards lower seating densities; people will be smarter about how they greet each other; employees won’t dare come to work with a cough. While things might not be “business as usual” in Seoul come May, it will be a close enough approximation for its inhabitants to probably think: “this hardship was worth avoiding 20,000 deaths – and our economy probably shutting down, anyway.” Can they keep cases suppressed until a vaccine finally arrives in a year or two, maybe even sooner? Or an effective treatment surfaces? It seems plausible enough to say it was worth the risk of shutting down their economy. 

What about the UK? Barring some deus ex machina that British customs or lungs or genetics are somehow adequately different from the Spanish and Italians, the UK could well experience a Lombardy-like situation on a national level. What did they gain for it? An extra week or two of pub crawls and concerts. Their theory – that they would allow “herd immunity” to take effect in the younger, healthier population, blunting future problems with COVID19, was laughably naive if you consider the numbers, albeit crude numbers, we have been discussing. If “herd immunity” implies, as they stated, that 60% or more of UK citizens should get COVID19, this would be a public health catastrophe – and one that would destroy their economy more severely than any proposed austerity measures. Even if they somehow quarantined everyone over 60 (a real challenge given the need for most of the elderly to interact with those younger than themselves for their basic needs) – even if all of their COVID19 cases were younger people – even if their mortality rate was well under 0.5% – any manipulation of the numbers still yields DPM figures that would dwarf Lombardy. Is Lombardy, on the basis of going into a lock-down, due for a second wave that will then be worse than the UK’s experience, with residents burned out on quarantines and unwilling to comply for a second round? That seems to be the bet the UK was originally intent on making, before beginning to back down from this game of high-stakes chicken, and implanting its own, late, “shelter in place” measures. 

That gets us back to the South Korea analogy – can Lombardy, once this passes in a month or two, use the sort of containment they employed in Vo to prevent new clusters to develop, and while away their time in relative normalcy waiting for a vaccine to be developed? We shall see. It is the challenge awaiting the US later this spring. If there is to be no normalcy without incessant severe COVID19 spikes even after the first wave is done, the degree of psychic and economic suffering in the year to come before an effective vaccine arrives is going to make today’s angst in the US seem positively upbeat by comparison.

The Island of Hawaii should go into severe containment measures… yesterday.

If the best time to plant a tree is 10 years ago, our the Chinese proverb, then the best time to start a lockdown is before you have extensive community spread of COVID19. In a situation with precious little data, there is a plethora of data that the sooner you lock down and test extensively, the lower your DPMs end up in the first wave. Every day you wait, is an exponential increase in cases and deaths. Flying people in from Seattle, San Francisco, and Oahu is the best way to seed community spread. Shut it down and test, Hawaii! 

One last number… 500,000.

It’s not what you think. Most people have settled in to this “shelter at home” philosophy, figuring that the economic and societal suffering is worth it if it means a less chaotic first wave of deaths. I think the data speaks pretty clearly, despite all the uncertainty and need to project forward. What our eyes saw happen in Hubei, Lombardy, and Milan, can happen anywhere, if the prevalence is allowed to rise above a very low point for a highly infectious virus. The only way to suppress the prevalence to socially acceptable levels is with severe social distancing measures. The most viable strategy while we wait for a vaccine seems to be: Control the first wave though whatever it takes – and hope that mutations that calm the virus itself, breakthroughs in treatment, or reductions in transmission in “normal life” through lessons learned in the first wave, will lead to a “COVID19 Success Story.”

I have had many conversations in the past weeks with my college friends, most of whom exist not in medicine but in the world of business. Some are questioning whether the downside risk of COVID19 has been overstated, and if it has justified the certain dismantling of the economy we have undertaken for an uncertain reduction in deaths. They raise some fair points, although I disagree in general – the destruction wrought by COVID19 if left to progress mostly unabated is so severe on the level of both human and economic suffering, that I think standing on the sidelines would be a bad gamble. 

But back to that 500,000. That’s the number of deaths in America every year directly attributed to smoking. Every single year – not just one awful pandemic year! Sarcasm alert: If only we had the means to stop these 500,000 deaths, somehow, some way. But, no – outlawing tobacco products would be government straying way too far outside its lane in limiting personal liberties!

The hypocrisy is hard to deny. We are essentially put into house arrest on a massive scale, all in the name of not overburdening our health care system and to prevent a few hundred thousand unnecessary deaths in one year. God forbid we ban tobacco, though!

This tension, between government forcing us to follow their dictates for the common good, versus having the liberty to make our own poor decisions that lead to chaos and mass fatalities, is one with a rich history, especially in our country. When the dust clears from COVID19, yes, we will all use hand sanitizer more; yes, we might be more cautious in our style of greeting each other; no, we might not show up at work with a ripping cough; but will we be more, or less, open to the exchange of liberty for the public good? That will be one of many interesting story lines to follow in the year ahead. But for now – please have that conversation in the privacy of your own home.

Is Hydroxychloroquine the CURE for COVID19?

Examining the hype vs the data

by Buzz Hollander MD (updated April 14, 2020)


There has been a lot of excitement over the recent media reports of hydroxychloroquine (HCQ), the regularly-used cousin to chloroquine, and its potential efficacy against COVID-19. I am receiving regular questions about it, so I thought it was worth posting my thoughts.

First of all, let’s start simple: viruses are hard to kill. Maybe because they are not alive to start with. There are dozens of clinically important viruses that no one ever reads about in the media – respiratory syncytial virus, coxsackievirus, parainfluenza virus, etc., etc.. None of these have curative treatments. Only a handful of viruses do – and it took years or decades of research to come up with them. We now have effective treatments for Hepatitis C and HIV, but the struggles with finding those medications are well-known. We have fair-to-middling treatments for herpes viruses and influenza. That’s about it. All these medications took a lot of time to develop. What are the chances we stumble onto a highly effective treatment for a novel virus like COVID19 by just throwing an old antimalarial like HCQ at it? Low.

I don’t want to be “That Guy” in medicine who downplays every possible intervention that is not tried and true until the evidence finally becomes overwhelming and then finally admits “I guess the stuff works okay.” I am encouraged by the Gautret study from France (, and hopeful from the rather vague data coming from China per the Gao, Tiang, and Yand report ( However, if you actually look at the reports, and not the media buzz around them, they are not exactly “good science.” I started med school in 1998, and in the years since then I can’t count how many times there has been great excitement over the next cure for cancer, Alzheimers, heart disease, etc., based on laboratory research, high quality animal studies, or small scale human studies. They almost never pan out! In those 22 years, I can count on the fingers of one hand the genuine pharmaceutical advances that have been made that would really be considered “game-changers” like the Gautret article implies HCQ will be. That’s why I remain on the sidelines with this one: history suggests it will fail once exposed to more rigorous testing.

The Gautret study was small (42 patients); its data was corrupted (6 of the “treatment arm” patients left the study – 3 of them ICU-bound and 1 of them for the Next World – so 4 treatment failures were not included in the rosy summary); the treatment arm and control arm patients were not the slightest bit randomized (people unwilling to take a novel treatment were the “control” arm) nor were they equal (different patients were at different stages of disease, and the test group was twice as likely to be symptomatic and three times as likely to have pneumonia). Clearly the closer to disease peak you are in a study, the closer you are to either dying or clearing the disease – and since the study was evaluating the rate of disease clearance after 6 days on HCQ, treating more progressed people means you might have a bias towards finding cure (or death, which led to exclusion from the study results!). Even the treatments were different; some treated patients were given an antibiotic, azithromycin, leaving us wondering how much of a role this combination might have played. This is not to say there is no way HCQ was helping these patients; this is to say that when we have more data, I would bet my last dollar it will not be quite so positive.

On the bright side, HCQ is inexpensive and fairly well tolerated. I say “fairly” as I have had a good number of patients with autoimmune disease who were put on HCQ and did not stay on it for a variety of reasons – but rarely serious reactions and never for the retinal damage that is a well-documented but rare adverse effect of the medication. It is also difficult-to-impossible to order HCQ now, since there was a rush on it with the recent news. When supply lines are restored, would I treat someone with serious COVID-19 disease with it? Sure! Would I be optimistic it will be the “game-changer” that will save the patient? No.  Multiple studies are underway in the US right now; we can hope more positive news emerges from them, like it lowers infections rates in health care workers who are being regularly exposed (that would help the health care workers AND the health care system AND their patients, a lot!), or that it can be used early in the course of disease to prevent serious complications. We simply do not have this data yet. But here’s to hoping… just with a grain of salt sprinkled over my newspaper.


UPDATES as of April 14, 2020: A small study of 30 not seriously ill COVID-19 patients in China was published soon after I wrote this that was rather discouraging – the study group receiving HCQ did not fare better than the control group, although both received “standard therapies” which may have muddied the water: .

Also discouraging are recent reports of a Brazilian study of HCQ’s precursor medication, chloroquine, being stopped early due to an unacceptable increase in heart arrhythmias. While they are less common with HCQ, this remains a concern, especially when combined with another medication, azithromycin, that has been known to cause the same arrhythmias, sometimes fatal, on its own. 

On the other hand, on the auspicious day of April 1rst, another study from China was more positive: . In it, 62 hospitalized COVID-19 patients were randomized to receive HCQ for 5 days, or only standard treatment. In ten days after admission, 25/32 of the HCQ group was better vs 17/32 of the control group. The 4 patients who progressed to “serious disease” all were in the control group. Encouraging, yes; “game-changing”, maybe not. That of 62 patients sick enough to be hospitalized, only 4 progressed to serious disease might be a red flag that this was not a representative population; we might have expected this number to be closer to 20 in a representative sample based on China’s hospitalization rate being about triple its ICU rate.  I will also note that this study reports that none of their area 80 lupus patients on HCQ had been hospitalized with COVID-19; and that of their 178 hospitalized patients, none had lupus. While this sounds nice, it is important to remember that a case series of 80 patients for a disease that sickened a small proportion of the populace is very, very small; and that lupus affects only 1/10th of one percent of the Chinese population. While this sort of headline makes great news copy (“LUPUS PATIENTS ON PLAQUENIL DON’T GET COVID-19!”), it also reminds one of the old joke: “What are you doing?” “Hunting lions.” “But there are no lions here.” “See – it’s working!”

The bottom line: as of mid-April, despite certain well-publicized claims to the contrary, we lack reliable evidence that HCQ is a  useful tool against COVID-19; and that even if effective, it may only be marginally so.



Q: “Are you going to keep your clinic open through this?

A: Great question! The answer is YES. We know this is the sort of time when you really want to have a doctor available, and we will be available. 24/7. That said, we might be changing the way the clinic operates, especially as cases become more prevalent here on the Big Island. If you need to be seen in person – for example, if we need to check your home cuff because your blood pressures are alarmingly high, or you are having abdominal pain – we plan on keeping the clinic physically operational for visits like this. But we will increasingly plan on conducting visits via phone or video call for concerns not requiring a physical visit. We much prefer medicine face-to-face – but not when that increases the risk to ourselves and other patients and the community as a whole. 

Q: “What do I do if think I might have COVID19?

A: Call us. Right away. And stay home and self-quarantined – including and especially with your family, as most spread happens within the home – until you talk to us. Testing is now finally available at testing centers, which is the ideal way to be tested. We will stay abreast of their capacity. If we deem it necessary to have you come in and be seen, we definitely need to make a plan over the phone first, so we can come out and meet you in the parking lot before you might share your germs with our clinic staff and other patients!

Q: “There’s only one case on the Big Island – what’s all the fuss?

A: Sigh. OK, none of our patients have actually asked us this, but we hear it from others! It’s hard to know the amount of COVID19 on our island right now as there are no deaths, or confirmed ICU cases, at this point. We have just been alerted to the fact that we have one positive case on the island.  We all know by now that the testing has been grossly inadequate until now. Given the lack of confirmed community spread, it is a fair bet there may still be <50 cases circulating – but it is a better bet this will become a very high number soon! The data we have from other countries and localities is that the sooner a place shuts down public interaction, the better their chances of avoiding the vivid scenes of suffering we have witnessed in Bergamo and Wuhan.  Places that shut everything down, but were just a little slow in shutting it down, have not fared well. Stay home!

Q: “How likely am I to get this? Angela Merkel told me that I have a 60-70% chance of getting COVID19!

A: The important thing to remember is that there are a lot of “worst case scenarios” being floated around out there – and that’s just what they are. They are also avoidable if people take this threat very, very seriously. Once the rest of China got the memo from Wuhan to STAY HOME, their death rate tumbled almost by a factor of 10. Where people make uninformed decisions like, “I feel like going to a concert because COVID19 has got me down,” the infection rate stays high – probably not 70%, but perhaps 5-10%, and this is enough to cause hospital overwhelm, rationing of ventilators, and a death toll well beyond that of a bad flu season. Where people are asked/forced to stay home, the infection rate appears to drop down to more like 1% of the population. This results in mortality figures more like a typical flu season. If someone tries to point out to you that there are many places where the COVID19 death toll is lower than the influenza death toll, THAT IS BECAUSE EVERYONE STAYED HOME THERE! If Wuhan had never shut down, and tried to pretend it was “business as usual”, then perhaps Angela Merkel’s number could have come to fruition. If 70% of the population contracted a virus with a mortality rate of 1%, this would make indeed lead to many millions of deaths in America alone. However, if everyone is smart about this – keeping schools closed, avoiding unnecessary socialization, practicing good hygiene and social distancing – the first wave of this illness should end up being more like Beijing than Wuhan. To answer the question directly, the chances that you contract COVID19 are probably less than 1 in 20 if you (and everyone else!) stay home and Hawaii is smart about limiting all non-essential social gatherings. So – just stay home – and encourage others to do the same! 

Q: “Should I still go out to my favorite restaurant/take my trip to California/see my hairdresser?

A: Short answer: NO. While the odds as of mid-March that you will contract COVID19 are still quite low from any given trip out into our community, it’s best to look at it from a broader  perspective. What if you are the approximately 20% who might have the virus and don’t have symptoms yet? What if your hairdresser is? Every new case leads to exponential spread. From a personal health perspective, you can probably get away with a few extra forays into the community with the odds in your favor (for now); but from a public health perspective, the less everyone goes out and shares respiratory droplets, the more likely we are to not feel like northern Italy in a few weeks. Is that worth it to you? I hope so. And for goodness sake – don’t fly to California!!!

Q: “I heard that an HIV medicine cures COVID19 – can’t you order a bunch of it for me, just in case?

A: Negative. For a couple reasons. One, there is nothing with very convincing data yet, although it’s our job to follow this closely, and we do have people all over the country whose brains we are picking regularly about such things. Two, in case you have not tried to buy toilet paper or hand sanitizer lately, things are in short supply right now. Since our best guess is that, as long as Hawaii and our patients are smart about this, we will only have a handful of patients actually get COVID19, and fewer still get serious disease from it, it would be downright irresponsible to order potentially helpful meds for hundreds of patients when only a few might even possibly benefit from them. Trust us – we have ordered an adequate supply of readily available “promising” agents to treat our patients, and we will find a way to get them to you if you are the 1/10th of 1% that might actually benefit from them. But please don’t ask for them to put in your medicine cabinet! We have to take the larger view right now, all of us.

Q: “What natural supplements or herbs can I be taking now, or if I get sick, since you are telling me that pharmaceuticals might not help?

A: With regard to the novel coronavirus, Dr Suber is actively collaborating with her colleagues who are in the research realm to answer this as factually as possible. We can tell you that the usual caveats apply to keep your immune system strong: get eight hours of sleep every night, spend time outside, eat a wholesome diet, manage your stress as well as you can, and try to enjoy this time as an opportunity to do some of the things that really matter to you. Several natural products would appear to have potential benefit against coronavirus, but, of course, there is no randomized, controlled evidence to help guide our recommendations. Some that show signs of promise include: green tea and its EGCG components, garlic, stinging nettle, cinnamon, and elderberry.  There are many other botanicals with excellent science behind them for preventing viral illnesses in general.  Dr Suber will be highlighting some of these, as well as other recommendations for keeping yourself healthy, on our blog site shortly.

Q: “I called Tuesday about my cholesterol results and it’s Friday and still no call from the doctor – what’s going on?

A: It is our goal to be as prompt as possible in response to your queries, whether life-threatening or simply of concern. But, we imagine you can understand that the couple hours a day we are now spending researching COVID19, communicating with colleagues about it, and answering COVID19 questions from patients, were not built into our normal workflows! We will try to be as timely as possible in the realm of non-COVID19 issues, but things might run a bit more slowly than we all like.  Thank you in advance for your patience!

Q: “I just got laid off from my job because of all this – can I still be your patient if I can’t afford my fees?

A: YES – please talk to us so we can make a plan. Now is not the time to be looking for new doctors!

Q: “I don’t have any symptoms but I am just worried sick I might have COVID19 because I went out shopping 3 days ago – can you order me a test?

A: Negative – well, we could, but should not. The reason we are being told not to test asymptomatic people is not just to make testing more efficient for people with actual symptoms; but also because it appears the false positive test rate for people without symptoms might be very high. In other words – if we get that test on you, and it comes back positive, you might still be more likely to NOT have COVID19 than actually have it! Keep in mind that <1% of the Big Island probably has this right now; and perhaps 80% of people have symptoms when they test positive; so the odds we start down a public health rabbit hole of tracking contacts and a strict quarantine are greater than the odds that we do any real good with this test. If you have cold or flu-like symptoms – then let’s talk testing!

The Fountain of Youth – Part 2

In this segment, I will review some of the supplements and pharmaceutical agents that have generated the most excitement in the anti-aging community. Spoiler alert: some of these appear to work!

First up is resveretrol, that difficult-to-spell and awkward-to-pronounce supplement that has generated a huge amount of attention in the past two decades. Found in grape skins, red wine, and peanuts, some hypothesize that it might be behind the French Paradox – that the French manage to have excellent heart health far beyond what proponents of 1980s-era nutritional recommendations would expect for a people who tend to eat a diet high in animal products and saturated fats.  Could it be all that red wine? Personally, I think eating the sorts of delicious, handmade animal products I witnessed in Parisian and Provencal shops would help anyone live longer if only due to the joy they might bring into a non-vegan’s life, but I digress. Is there anything to this resveretrol craze?

Animal and “in vitro” studies (in which cells are studied under a microscope, rather than studying entire living beings) are plentiful. Resveretrol seems to activate an enzyme, sirtuin 1 (SIRT1), which plays a role in multiple pathways in cellular aging. (1)

In mice and simpler organisms, it does seem to extend longevity.  In primate studies, it improved some cardiovascular markers including arterial health on monkeys given a poor diet, and was associated with reduced weight gain among lemurs given resveretrol during sedentary periods. While encouraging, by no means were all findings positive.(2)

The list of medications and supplements that inspired a burst of optimism based on in vitro and animal studies is long indeed; the catch is whether high quality human studies will show the same thing.  The air began to come out of the resveretrol balloon in 2014, when a well designed study of an elderly population in the Italian Chianti region suggested that dietary resveratrol did not correlate with health or longevity. (3) A proper prospective clinical trial in humans is underway – a one year study on overweight adults checking cardiovascular health and fitness parameters at 75mg and 150mg twice daily -and should have results reported later in 2018. (4)  Will resveretrol ever be shown to be a dietary supplement to increase longevity? I suspect not. The recent study data on alcohol use, including red wine consumption specifically, was discouraging; those who drank even a glass a day fared worse in overall mortality than lighter drinkers, and the “two glasses of red wine a day is good for you” crowd (something I advocated until recently) took a major hit, as drinking more than a few drinks a week led to a direct increase in mortality as the drinks per week increased. (5) While it is possible that the concentrated doses of resveretrol found in supplements, or a similar compound like pterostilbene (which has far less human clinical trial evidence on its behalf than resveretrol [6]), might someday show evidence of real benefit in this regard, there is not much compelling science to take these supplements at this point.

For those losing hope that there might indeed be some magic element within a pill that could add years to their life, take heart. For starters, we have one of my very favorite pharmaceutical agents, metformin. It is an old, and effective, diabetes medication that affects cellular metabolism and quite possibly gut bacteria. Like so many of our most useful medications, it is borrowed from Mother Nature, as it was derived in the 1950s from French Lilac, aka Goat’s Rue (how could any plant with two names that good not be worth pursuing in a laboratory?).  Metformin binds the signaling protein, AMPK, which affects insulin sensitivity, and limits liver production of glucose. Lab studies have shown a significant survival benefit in worms – around 40%; and the worms not only lived longer, but they appeared more “youthful” – something that must have been fodder for late night talk show jokes (7). More and more studies are showing a decrease in cancer mortality amongst diabetics on metformin versus non-diabetics not taking metformin. The real shocker came in 2014, however, when a huge population-based study from the UK showed that health- and age-matched people without diabetes lived 16% shorter lives than their peers who had diabetes and took metformin (8).  Given that having diabetes on your diagnosis list is considered to drop at least 5-10 years off your life expectancy, these results caught the attention of the medical community in a big way!

What is lacking, of course, is a trial that pits age- and health-matched people without diabetes, going forward in time – not looking back through statistics.  A randomized controlled trial, the sanctified method by which most physicians prefer to obtain our data, is what’s really needed.  It’s expensive, though, to conduct these trials with thousands of volunteers over many years. The FDA has approved such a trial to take place to evaluate the claims for metformin – the “TAME” trial – but whether it will be funded remains to be seen (9).  It’s hard to raise tens of millions to study an off-patent drug that costs a few dollars a month.

So, right now, we are left with some promising data, and a few reasons to doubt. A study on non-diabetics with heart disease did not show improvement on their arterial plaques when given metformin (10).  Most of us practicing primary care prescribe metformin to scores if not hundreds of diabetic patients, and certainly I have never been struck by any sort of anecdotal “ah-hah” that my metformin patients are doing exceedingly well. So – I am not putting all my patients on metformin, at least not yet. About 10-20% get a persistent diarrhea from the medication, which is a deterrent. A small percentage of people on metformin develop a deficiency in vitamin B12. I also worry about the possible shift in gut bacteria producing unpredictable and untoward effects in my patients without diabetes whose gut bacteria may have been just fine before I started “improving” them. I hope the TAME trial runs; I hope by 2025 we have data from it; and I hope it is overwhelmingly positive.  For now, though, I limit metformin use to those with diabetes, but am easily talked into prescribing it for patients with above-normal sugars who are tempted by this tantalizing data.

Last, but hardly least, we come to a drug with the unusual name of Rapamycin. Those of us with some familiarity with Pacific Island geography might rightfully wonder about the “rapa” of the “rapamycin,” and, sure enough, the compound was derived from a bacterium found on Easter Island, known to most Polynesians as “Rapa Nui.” The backstory on the discovery of rapamycin, subsequent loss of interest, and then a great resurgence, is fascinating and outlined in many places. Originally it was thought to have its use as an antifungal agent. Then, researchers realized that it had major effects on cellular metabolism, including an immunosuppressive effect, which led to its approval as one of the medications to be used after kidney transplant under the generic name, Sirolimus. Anticancer properties were then noted, unusual in an immunosuppressive agent, and its cousin medications, such as Everolimus, have been approved for use with breast, kidney and thyroid cancers (11). As study of the substance intensified, it was found to play a critical role in the signaling processes which control a cell’s lifespan, and an entire cellular pathway was named after it – mTOR (mammalian target of rapamycin). You know you’ve made it to the big time when cellular pathways are named after you!

Will it help people live longer, though? It clearly extends mouse lifespans by some 25-30%, and is the first substance with compelling mammalian data in this realm (12). Some express concern that most lab mice die of cancer, due to their unfortunate selective breeding characteristics, so the primary benefit of rapamycin for this population might be its anti-cancer properties. This might not translate so well to us humans, who tend to die of heart disease. However, studies on other animals, such as dogs and monkeys, have suggested improvements in many realms: immunologic, metabolic, and neurologic (13,14). Akin to metformin, Alzheimers researchers are curious about possible preventive properties with rapamycin, given the preserved cognition seen in some of the studies.

What is holding back the adoption of rapamycin is the lack of long-term trials in healthy humans. Given its use as an immunosuppressant, there is concern that it might lead to severe infections. However, using a low dose or intermittent dosing regimens, human studies have shown an acceptably low rate of side effects and lack of issues with unhealthy blood counts (15). The current protocol recommended by those who espouse rapamycin for maximizing longevity, such as Dr Alan Green MD, is to take 6mg once weekly (compared to 5mg daily as a typical immunosuppressive regimen) (16). It still feels early to be writing prescriptions for this purpose.  The concerns for side effects gives pause, and the very high cost of an adequately large randomized controlled trial to prove its value as a longevity drug might make it unlikely to ever see such a study – potentially leaving this sort of protocol forever in the “highly experimental” realm. Rapamycin is also a good bit more expensive than metformin, currently in the area of $150/month for the weekly intermittent dosing protocol.

All in all, the world of longevity medicine has not given us anything we can shout  from the rooftops about. Good sleep, supportive relationships, healthy diet, regular movement, enjoying life and work – none of these things can be fit into a pill, and they are the cornerstones of a long and happy life, and have copious data to support that they will do more for you than any pill possibly could. The quest for that magic bullet will never end, however, and perhaps we will find that some things can indeed be packed into a pill that can substantially benefit our lives.  Stay tuned!


















The Fountain of Youth – Part 1


The notion of a Fountain of Youth – a magical source of a substance any one of us could drink of and slow or even reverse the aging process – has an obvious hold on the psyches of many of us with a few decades under our belt.  We might reasonably assume it is nothing more than myth.  In fact, even the myth of the Fountain of Youth as the object of explorer Ponce De Leon’s desire appears to be nothing more than a tall tale1!  That said, the less desirable aspects of life that often accompany aging – the aches and pains, the slow recovery from a work-out, the chronic diseases – not to mention death itself – ensure that the quest for a Fountain of Youth will never end in the world of medicine.

“Modern medicine” could claim that it is clearly on the right track in this regard.  The average American lived to age 47.3 in 1900; this leapt to 68.2 by 1950.  Much of this remarkable improvement can probably be ascribed to the improvements in infant mortality with better prenatal and obstetric care, immunizations, and public health improvements. Still, American lifespans continued to creep upwards in the ensuing decades, rising to 78.9 by 2010, likely related to improvements in managing cardiovascular events like heart attacks, among other things.  Any smugness we might feel that we are on an inexorable march towards all of us celebrating our 100th birthdays, however, is probably ill-placed.  The past five years have seen a virtual flat-lining of our lifespan.  Even if we go back to 1950, the number of additional years a 65 year old would live was 14 on average; now, 66 years later, that number has only risen five years2.  Given that tobacco use has plummeted since the 1965 Surgeon General’s announcement that, yes, tobacco was bad for us, we might well decide that much of that modest improvement was not due to modern medicine but simply smoking cessation.  The CDC estimates that smoking cuts approximately 10 years off an average lifespan; and the percentage of smoking Americans has dropped from 42% in 1965 to 17% today3; so we might estimate that nearly half of the mortality improvement in the last 50 years is due to the anti-smoking campaign!  Amazing as it seems, if you are a non-smoking 65 year old American, all of the wonderful advances of modern medicine in the past half-century — MRIs and CT scans, robotic surgeries, cardiac cath labs, cancer screening programs, and literally thousands of exciting new drugs — all of this has added maybe two or three years to your life.  That’s it.  It is easy to see why the thirst for a Fountain of Youth still exists.

When studies crop up suggesting that this or that supplement, lifestyle modification, or medication might have a significant effect on our lifespan (or “healthspan” – a new term for adding years before infirmity sets in rather than just counting years lived), the popular press is understandably enthused.  Sorting out just how promising these “breakthroughs” really are can be a challenge.  I will save the discussion of potentially exciting medications and supplements for my next post on the subject.  Let us begin with the most natural of options – changing what we eat.

Since I was in high school, I have been hearing: “the only way to live longer is to restrict calories.”  There is plenty of evidence to this effect, much as it is not nearly as attractive as a sip of magical water. 

Indeed, studies since the 1930s on mice and yeast have showed survival benefit with calorie restriction, sometimes remarkable – in the 40% range. It even has its own acronym in the scientific world – “CR.” That said, many a study has failed to translate from simple organisms, or even rodents, to humans.  Lab rodents are bred to die of cancers; about 80% do so (this fact still pains my mother, who found out the dark truth only as our beloved first, and only, pet rat was dying).  They are also different from humans in many complex and not-so-complex ways.  Therefore, there was great interest in primate studies on calorie restriction, but when finally published, the results have been mixed. The two largest studies, with a 15-30% calorie reduction, have yielded conflicting results. The most recent 23 year study on rhesus monkeys did not show survival benefit, only slight metabolic improvements in young-onset CR (those monkeys who were calorie limited from an early age). The prior study showing marked benefit allowed unlimited food access to controls, while the more recent limited the calorie consumption of its control monkeys to an “average amount” – so perhaps CR has benefit only when compared to unhealthy controls4,5

Finally, someone has tried a human model of this theory, in the “CALERIE” study, a 2 year randomized, controlled study that sought to find out if signs might point to longer life with CR; they had to limit themselves to signs like shifting metabolic rates, because it is hard to find backing for studies that require decades of cooperation, monitoring, and follow-up to really determine if people are living longer.  The study aimed for 25% calorie reduction in 160 normal or mildly overweight individuals (12% ended up being the actual average reduction); neither resting metabolic rate nor body temperature lowered as expected, but modest weight loss, improved blood pressure (only 4%), and better insulin sensitivity were seen. Of note, bone density worsened problematically, further lessening the appeal of the study6.

This would point towards the unattractive conclusion that, while there might be a “fountain of youth” readily accessible if you are a) a smoker; or b) have an unhealthy, over-consuming diet; you might see no remarkable longevity benefit from anything we have discussed if you are already a non-smoker who eats a reasonably healthy diet.

One potential caveat to this is the notion of methionine restriction (you guessed it: “MR”), a relatively new concept.  Methionone, an essential amino acid, meaning we must obtain it from our diet, seems linked to oxidative damage in the mitochondria. Many in the longevity business think that aging is roughly equivalent to the degree of oxidative damage in our cells (rust on metal is a typical oxidative process). Fly, mouse, and rat studies have shown that a 4-5-fold decrease in methionine in diets cause the same benefits as CR; and improve insulin sensitivity beyond just what the fat loss would predict7,8.  Since diabetes – the ultimate end point of poor insulin sensitivity – drops our lifespan by some 6-7 years9, this is doubly of interest.  How do we limit methionine?  Eat less animal muscle10.  All of those healthy proteins some of us have been exhorting our patients to eat to avoid carbs and trans-fats – poultry, fish, lamb, grass-fed beef – are loaded with methionine.  Some in the medical community have responded that eating the WHOLE animal, which is richer in glycine, which gets depleted by high-methionine meals, might limit the apparent damage.  There is also an inherent problem that limiting methionine, also well represented in dairy and eggs, makes it harder to avoid carbs and the inherent risks of insulin resistance from them.  So… the jury is still out.  Moderation is probably wise when it comes to meat muscle; and the now-chic “bone broths” are probably the smartest way to get your meat. 

At this point, I do not see enough evidence to advocate strongly for CR, MR, or any other acronym, when it comes to food restriction, until we learn more.  An individualized diet that stresses whole foods based on your own genetics and health conditions, and lots of vegetables, serves as common sense. And, yes – if you have not quit smoking yet, now is the time!

*Part 2 will address the most promising supplements and pharmaceuticals in the Fountain of Youth realm.*









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The Statin Conundrum


One of the most frequently asked questions I get from patients about their medications is:  “Do I really need to be on this statin?”

The answer varies by the patient.  The statin drugs, which are the class of cholesterol lowering medications that end their name with “statin” (i.e., “lovastatin,” “atorvastatin,” etc), are among the most heavily prescribed medications in the world. Once upon a time, in the not so distant past, we in the conventional medical community said things like, “Statins should be in the water supply!”  After all, they reduced cholesterol, overall inflammation, heart attack and stroke risk, and were thought to do nearly no harm — some reversible liver inflammation at times, muscle aches at a rate perhaps no higher than placebo, and not much else.  That perception of statins has changed remarkably in the last five years.  Now, the question is more like: “Do we need them at all?”

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