Hello, and welcome to Medicine with Dr.
Moran.
i'm Dr. Keith Moran. I have been asked a
number of questions about The Odds of
Dying with Coronavirus video that I made
and how this changes with different
patient age groups.
My patients have asked specific
questions about their odds at their
age with their specific medical problems.
We do have new evidence from a recent
meta-analysis.
This was published recently. The link to
this paper is down below in the
description.
This was a meta-analysis looking at
age-specific
infection fatality rates derived from
three large recent antibody studies.
These antibody studies give us a good
idea of all the coronas virus infections
not just the people that have presented
and have had a positive nasopharyngeal
swab.
To review, the infection fatality rate is
the percentage of people who die of all
people who develop
infection with coronavirus. This is the
statistic that my patients really want
to know.
This of course is significantly less
than the case fatality rate
which is the percentage of people who
die out of all the cases that come to
medical attention.
These two important things are defined
on this slide for you.
With this illness the case fatality rate
is typically about five to ten times
higher than what the infection fatality
rate is.
As an introduction this slide shows the
Covid-19 cases in New York city.
Out of 8 million residents antibodies
studies showed that the estimated number
of infections was 1.6 million
of which 1.1 were symptomatic .There were
220,000
reported cases which led to 55,000
hospitalizations
and 23,000 deaths. So you can see that
the reported cases were 12%
of all infections and fatalities were
only 1% of all
infections. The authors in this study
took a look at
all studies that they could see about 50
different ones in total but a number of
studies were excluded because a large
number were not suitable for estimating
an age specific infection fatality rate.
Others did not have a good
representative sample of the general
population. They
used six studies as their benchmark. This
slide shows the location of the six
recent large-scale antibody studies
they were done in Geneva Switzerland,
Belgium,
Indiana, New York, Spain,
as well as Sweden. This slide shows the
estimated infection fatality rates which
I will refer to as the IFR
for the different age groups based on
these six studies.
As you can see the IFR is close to zero
for younger adults but rises to 0.3
percent for ages 50 to 59.
1.3 percent for ages 60 to 69
4.6 for ages 70 to 79
and 25 for people who were 80 or above.
They then went on to compare this
particular graph to the antibody studies
of nine other U.S
geographical regions. I covered these
nine
particular regions in my video Odds of
Dying from Coronavirus
an Update. Here is the graph for those
additional studies.
You can see that the vast majority of
the data is within the prediction
intervals.
In addition they compared it to data for
three countries and three small scale
locations
that had engaged in comprehensive
tracking and tracing
of Covid-19 infections. the three
countries were New Zealand,
South Korea, and Iceland. They also
included data from Castiglione in Italy,
the Diamond Princess cruise ship, as well
as the town of Gangelt
in Germany. On this slide you can see
again that the data is within the
prediction interval
with the exception of the data from
Castiglione in Italy
which was affected early on and severely
and their medical resources
unfortunately were overwhelmed
leading to rationing of health care and
thus slightly higher death rates than
would normally have been.
They went on to take these
age-specific IFR numbers
and to compare it against accidental
injuries.
This chart shows that if you're in the
55 to 64 age group your IFR is 0.7%.
Meaning if you catch the virus the
chance of dying
in that age group is 0.7%
but if you look at your yearly
automobile accident fatality rate being
0.01%
that's much lower. So the likelihood of
dying from covid19
is 50 times higher than the annual
fatality risk
of driving an automobile. In addition the
antibody study data
indicates by the last week in June 20
million Americans have become infected
which is 6.4 percent of the U.S.
population.
Based on IFR rates at different ages
they then went on to pose three
different scenarios which are outlined
on this slide.
The three scenarios assume that the
infection rate continues rising to a
plateau of around 20%
which was what was seen in New York city.
The first scenario assumes that the
frequency of infections in each age
group will remain
similar to the pattern so far .Scenario
two looks at a situation where disease
occurs in equal fashion
across age groups. Scenario three
is if there's significant protection of
the vulnerable age groups which is the
elderly.
Based on this they can predict the total
number of deaths as you see on the slide.
It's of course difficult to know whether
the virus will truly plateau around 20%.
There have not been any good studies
looking at the role of comorbidities or
demographic or socioeconomic factors to
give IFR rates by
age. These will of course be done.
Often I will get asked the question what
is the likelihood of dying with the
virus if i'm in my 50s and have diabetes
or if I'm in my 70s and have obesity and
high blood pressure.
There's no question based on a recent U.K.
study in hospitalized patients
that mortality rates are strongly linked
to things such as diabetes
obesity and chronic lung disease.
In this U.K. study there is no question
that patient age was the most
important risk factor and much more
important than any other specific
comorbidity
in determining whether you're going to
die or not.
The U.K. study showed that an obese 40
year old patient
in the hospital was at a slightly higher
mortality rate than a non-obese
individual of the same age,
but that 40 year old patient who was
obese
had only a one tenth chance
of death compared to a non-obese 75 year
old patient.
So this is the most important thing is
that age seems to be the biggest risk
factor by far.
Thank you for joining me today on
medicine with Dr. Moran.
I'm Dr. Keith Moran. Get healthy and stay
healthy.
