2020-04-22 - The COVID-19 numbers are not what you think
Given the seriousness of the COVID-19 pandemic, it's amazing how
bad our metrics are. We really don't know much about the
epidemiology of this disease.
Following is a laundry list of problems with the various
metrics that are bandied about in the press...
Chinese numbers are just propaganda. The Chinese claim to have
about 85,000 cases and 4,600 deaths.
This is the recently increased set of figures, where they increased
the number of reported Wuhan fatalities by 50% in the hopes that
people (at least Chinese citizens) will believe the new lies, because
nobody believed the old lies.
The figures don't make any sense:
- Does anyone really believe that Chinese figures are
so much better than in the US, given dense living
conditions and 4x the population?
- The number of funerary urns recently delivered to
cremation facilities in Wuhan alone suggests that the
incremental deaths there (above and beyond what is normal
for such a large city) were between 20,000 and 80,000.
As an order of magnitude guess, it's reasonable to
estimate that COVID-19 deaths in China are 4 times that,
or about 200,000 -- at least 40 times higher than reported.
- UPDATE: the first recorded death due to COVID-19 in the
US was on February
6. This was due to community spread. Given typical
21 days from infection to death, this means that the virus arrived
in the Bay Area by mid-January. An infected individual
presumably traveled from Wuhan to the region at that time.
Given the relatively small amount of such traffic (three
direct flights weekly from Wuhan to SFO - so probably under 1000
people/week coming over), the fact that at least one
infected individual came over mid-January suggests a fairly
widespread infected population in Wuhan by early January.
I'd guess that at least 0.1% of the Wuhan population, or over
10,000 people, were infected in Wuhan by January 10. The
Wuhan lockdown started January 23, so with a doubling
rate of about 2.5 days, Wuhan would have had over 300,000
infections by then. That's just Wuhan -- never mind
the hundreds of other clusters across China due to 5
million people traveling out of Wuhan for Chinese New
Year just before lockdown.
Confirmed cases are not the same as community cases. Every
jurisdiction is struggling with testing capacity, and prioritizes
tests for symptomatic people, and often those who have had contact
with a known infected individual or recent travel. That means that
lots of people who are positive are not tested and do not count towards
to the total reported number of cases. Moreover, it seems that lots
of people are asymptomatic or pre-symptomatic.
Depending on the
test capacity of a given region, there is some multiplier to go
from confirmed cases to actual community cases. A recent
antibody study with a somewhat random sample
in Santa Clara placed this multiplier in that
jurisdiction at somewhere between 50 and 85 (MedRxiv.org).
- UPDATE: I just ran across This
study from USC.edu where another random sample was done
to see who has antibodies. It estimates that 2.8% to 5.6%
of the population of LA county has already been infected.
- This means 221,000 to 442,000 infections. They have recorded
over 650 deaths, so their implied mortality rate is between
0.14% and 0.29%. Worst case: 3x worse than an average
seasonal flu (which has 0.10% mortality).
In regions where a lot of testing has been done, per-capita, this
multiplier might be lower. Say 10x or 20x. In regions with
essentially no test capacity, such as developing countries (India, Egypt, etc.), the
multiplier will be much higher -- say 1000x.
World-wide, there have been almost 3 million confirmed tests as
I write this. Much of the world is low income, so the average
multiplier will be high. Assume 50x as a very conservative
multiplier. That means that there are already over 150,000,000
COVID-19 infections world-wide. There is no way that we can ever
put this genie back into the bottle.
The tests themselves are not that reliable. There are two categories
of tests: (a) are you currently shedding virus? and (b) are there
antibodies for the virus in your body? There are multiple versions
of each of these. None of them is super reliable. Someone might
test negative for the virus now and positive in an hour, for example.
The mortality rates are not what you think.
- First, There is the obvious problem (above) of not knowing
how many people are actually infected. We can see who
dies in hospital of the disease (at least in countries whose
health system has not been overwhelmed and whose political
class are not pathological liars) -- that's the numerator.
Unfortunately, the denominator is people who were infected 2
to 4 weeks earlier, and we have no idea what that denominator
was or is.
- To give a sense of this - lets use the above estimate
of 150 million infections world-wide today.
- Assume a doubling rate of 7 days (with all the
recent control measures, pretty much everywhere) and
time-to-mortality of 3 weeks (21 days). That means
that world-wide infections totaled about 19 million
cases 3 weeks ago. There is huge uncertainty in this
- Reported world-wide fatalities are currently about
183,000. Given the inability of some countries to
report and the proclivity of others to lie, lets
assume the real number is 300,000. You should
get a sense for the uncertainties by this point...
- Using these estimates, the COVID-19 mortality rate is
1.6%. That's much worse than seasonal flu. But adjust
any of the huge assumptions above and this number shoots
up or down -- a lot!
- Second, people who die of the disease are not the only
variable. There are also these other variables:
- People who get into accidents, are sick, etc. and
who delay or avoid medical treatment because they are
afraid of being infected while visiting a hospital
(where all the scary COVID-19 victims are hiding out,
waiting to infect you!). This mechanism is killing at
least as many people as COVID-19. My friend is an ER
doctor and reports seeing conditions that have never
been seen in her career - like appendicitis patients
presenting with sepsis because they delay coming to the
hospital until too late.
- A lower rate of trauma (accidents) due to reduced car
traffic, closed schools / playgrounds and outdoor
- Economic hardship and extended social isolation
lead to mental illness, which is often accompanied
by violence and death.
- In places where hospitals are overwhelmed, higher
morbidity from COVID-19 due to people not being
- Also in places where hospitals are overwhelmed, higher
morbidity from other causes due to hospital congestion.
Even if we knew the actual morbidity rates of COVID-19
(i.e., percent of infections that lead to death), we still
wouldn't have a handle on the actual impact in terms of
increased deaths in the population as compared to a normal
Note that in a year we'll know. We can measure total
mortality rates in a population and compare to the
same time the previous year.
Not knowing is dangerous. Policy makers are making
monumental decisions that will impact billions of people
for decades, and they are flying blind. Is COVID-19 worse
than season flu? Yes, certainly. How much worse? Maybe 2x.
Maybe 10x. Maybe 100x. Maybe it depends on isolation measures
and healthcare capacity. Nobody really knows. Are different
control measures working? Some of them are supported by evidence
(closing schools, restricting travel, wearing face
masks, contact tracing) and some are only supported by
what seems like common sense, rather than hard data (stay at
We need to gather more and better data.
Are control measures effective? Are they causing more
harm than good?
- We should test random population samples to gauge
the extent of infection currently in the community,
rather than just focusing on symptomatic people.
- We should repeat this over time to get real trends.
- We should test individuals for antibodies to gauge
how far the disease has already passed through the
- We should measure increased and decreased morbidity
due to deferred hospital admissions and reduced trauma,
- Data from police and distress centres should be
incorporated too, because of the elevated mental stress
in the population.
All of this takes work and will require much larger testing
capacity. That has to be a top priority. Surely we can
afford it, given the billions already allocated to economic