In this session, we're going to
talk about the common numbers
that you will have seen to
describe and predict the behavior
of the COVID-19 pandemic caused
by the SARS-Coronavirus II.
The most familiar number probably
is the basic reproduction number,
known as the “R naught.”
This is the average number of secondary
infections produced by an index case
or a typical first case of
an infection in a population,
where everyone is susceptible.
It is used to measure the
transmission potential of the disease,
in this case of COVID-19.
If R naught, is greater than 1,
then the number of infected people
will likely increase exponentially
and an epidemic or pandemic can ensue.
If the R naught is less than one, then
the number of those secondary cases
from the index case, will not be
sufficient to sustain an outbreak
and it will likely recede on its own.
The problem of course as
with any of these indices,
is that the R naught, is not sufficiently valid,
to definitively forecast an outbreak.
It certainly can be affected by other factors,
but it is very important as an
early warning system, sort of,
giving the indication of the possibility,
of an epidemic or a pandemic.
The R naught then can be used
even to compare and contrast,
different types of epidemics or pandemics,
even such as we see here, comparing
the current COVID-19 pandemic,
with an annual influenza epidemic.
So, on the left COVID-19 pandemic, R
naught values have been from 2 to 2.5,
certainly, in the early days of the pandemic,
compared to a typical year with an influenza,
where the on R naught has ranged
anywhere from 0.9 up to 2.1.
Those years where the R
naught was 0.9 for influenza,
were largely fizzles, that there were not
significant numbers of secondary cases
and the epidemic was not extreme.
Versus those years of influenza
where the R naught was 2.1,
where there was a rip-roaring
epidemic with tons of secondary cases.
So, the R naught, can vary widely
and in fact, those ranges you see
both for COVID-19 and for influenza,
the R naught varies widely because
there are other host and viral factors,
which can affect it.
Certainly, if you think about it are not
can be affected by interventions, right,
so, as we have seen with COVID-19
and as we hope to see every year with influenza
intervening with public
health interventions such as,
wearing masks, social distancing,
physical distancing, closing the schools,
avoiding social gatherings, all
those can have a major impact,
on the exposures for the virus,
both for SARS-Coronavirus II
and for influenza and therefore
on the numbers of secondary cases.
After those public health measures are initiated,
then we can look and see what
happens and that number is called,
the “Effective reproductive number.”
As you would hope this is typically
much lower than the R naught,
meaning that we've had an
effective cluster of interventions.
So, the effective reproductive
number, if it's greater than 1,
means that we were not very
good at our interventions
and that the outbreak is likely going to
overwhelm further healthcare resources,
to overwhelm the healthcare system.
In if for example you can see this playing
out in lifetime in February of 2021,
the R naught for COVID-19 in the United
Kingdom was 0.6 to 0.9, so less than 1,
meaning that there was going to be a successful
or predicted successful diminishing of
the outbreak numbers in the United Kingdom
and that in fact was what
was seen after a very strict
lockdown measures were implemented.
So again, diminishing spread with the R naught.
Unfortunately, things change and variance
and in this case, we're talking
about virus factors now.
Variants of the SARS-Coronavirus II,
have shown increasing,
differing levels of infectivity
and are of major concern.
So, despite the United Kingdom
having an initial response,
it's both R naught and its effective
reproductive numbers below 1,
unfortunately, the delta variant the B.1.617.2,
first reported in India in late 2020,
entered into the United Kingdom and
changed its epidemic picture completely.
The R naught and the effective
reproductive number both rose,
to be above 1.
This is played out in other
parts of the world as well.
So, here's where viral
factors can negatively affect,
the R naught and the effective reproductive number
and how does that happen?
Well, it likely has to do
with variants or mutations,
which occur in the SARS-Coronavirus II itself.
This virus itself has shown itself
quite able to undergo mutations,
especially in the spike protein,
which will increase its infectivity
or its transmissibility.
Of course, it's very difficult to know
exactly what effect a single mutation
or a cluster of mutations might have,
in the transmissibility of the virus.
But, by using the R naught and
the effective reproductive number,
then we can at least follow
the small changes and predict,
that there's going to be a change
in the behavior of the pandemic.
Another number, which you you'll
hear, another estimate I should say,
is the “Case fatality rate,” which
actually should be, “Case fatality ratio.”
This this estimates the mortality ratio,
among documented cases and it's
calculated by taking the number of deaths,
divided by the number of documented cases.
As noted, we should not
really consider that a rate,
but unfortunately, rate, is the usage or the term,
which most individuals in the social and
common media and literature have used
and so, you'll hear us use rate.
Ratio of course, is the more
accurate statistical number.
This number the “CFR” is not a constant
and it's also a very poor measure,
during an epidemic.
You could pause this this session right now,
just think about reasons for that.
But of course, what you're coming to come up with,
is that, the CFR will typically
overestimate the true death rate,
why is that?
Because our denominator the total number of cases,
we don't know the number of asymptomatic cases,
we don't know the number of
true cases that were not tested
and not confirmed and so our “n” our denominator,
is likely far larger than what
we are using to calculate the CFR
and again, as we say here most death by infection
are also noted going to be noted
because they may not be diagnosed
or they may be attributed to something else
or they may be wrongly attributed to
infection with SARS-Coronavirus II,
So again, perhaps a more accurate
estimate of the mortality rate,
is the infection fatality rate the “IFR.”
And this is the number of
deaths due to infections,
divided by the total number of infected people.
So, inserting here, is going
to be a better attempt,
to confirm that deaths and
infections are specifically due,
to the disease of interest, in this case COVID-19.
So, the IFR, should be a better measurement,
it will almost always be lower than the CFR,
just due to the imperfections
in calculating the CFR.
The IFR, will include both documented and
undocumented or asymptomatic cases
and it's going to be typically
estimated at the end of a pandemic.
Although of course estimates will
occur throughout the epidemic,
but it is largely looking in retrospect,
that one can accurately calculate the IFR.
Why is it more accurate?
Because it requires
documentation of the infection,
typically, through antibody studies,
the IFR is going to vary with the
distribution of other factors,
comorbidities, so age, health
issues, pre-existing health issues,
other qualities of the infected individuals,
as well as qualities of the
medical care they receive
or have access to.
So, you can imagine then that that for COVID-19,
that the, true mortality rates
have and will vary greatly,
across different countries and age groups.
The CFR currently is being
estimated at 2.2% with COVID-19,
the IFR the infection fatality rate is estimated
at being somewhere less than 0.5%,
but neither of these is going to account
for the full burden of the COVID-19,
because they're not going to include mortality,
which is caused by other things, such as,
delayed care of other medical conditions,
certainly, the individual with
chronic lung disease or even asthma,
who may have an exacerbation,
due to something other than COVID-19,
may still have prevention of care,
because they can't get into
the emergency department.
Perhaps the health system itself is overburdened,
certainly, we're seeing this
in many parts of the world,
were, the sheer vast numbers of COVID-19 patients,
has overwhelmed the medical
setting, clinics, hospitals,
emergency departments and there
is insufficient medication,
or healthcare personnel, ventilators, IV fluids
and thus, those who do make
it into the healthcare system,
encounter an overburden system,
which has a very decreased quality of care.
Social determinants of health,
this is a very difficult
and yet a very important factor which
will impact on both CFR and IFR.
So those individuals who lost their
jobs because of all the social closures.
Decreased social interactions,
causing perhaps mental health variabilities,
maintenance of education,
maintenance and mental health et cetera.
All these have the ability to intervene or impact
on the CFR or the IFR.
So, as an example, again in real time,
these are still estimates, but the fatality rates,
in individuals with COVID-19
who also have comorbidities
and you see them listed here.
Cardiovascular disease, the
mortality rate, the fatality rate,
over 10%, those with diabetes,
especially those with insulin
dependent diabetes, 7.3%,
those individuals with chronic
respiratory disease, 6.3%,
death rate from COVID-19,
pre-existing hypertension or other
cardiovascular disease, 6.0%,
those with cancer immunodeficiencies, almost 6.0%,
those who had no pre-existing conditions,
so zero comorbidities, age, obesity,
any other medical conditions,
that the estimate of the fatality
rate with COVID-19 is just 0.9,
while that is still much higher,
than it is for influenza,
where the estimate is 0.1%, yet that
is far less significantly horrible,
than as we see with cardiovascular disease.
So, it is through using these
statistical predictive numbers,
that we can both follow as well
as predict areas of the world,
which are going to be negatively
affected by the COVID-19 pandemic
and it is certainly the wish and the concern,
to continue to use these successfully
to drive resources and to do a
better job of impacting on COVID-19.