if you follow the news you've probably heard the words "Wuhan" and "Coronavirus" a lot lately.
In December 2019 a cluster of patients was found in Wuhan, China, with
pneumonia of unknown cause. The virus has since spread rapidly over the last
month there have been over 20,000 confirmed cases according to the World
Health Organization. While the majority of the cases remain in China there have
been confirmed cases in countries around the world including several in the
United States. The interim named of the new virus is 2019-rCoV.
Coronaviruses derive their name from the crown likespikes that adorn their surface
resembling the Sun's corona. Coronaviruses are zoonotic which means they're
transmitted between animals and people. It remains unclear with the host animal
of the new coronaviruses though bats are a prime suspect.
Experts think another animal may serve as an intermediate host but they have not
identified it yet. During the course of the outbreak a number that you may never
have heard of shown up again and again. It's called the R0 and it's been a
critical part of the scientific effort to understand just how transmissible the
new virus is. Understanding what it is can tell us some useful things about all
disease outbreaks. The R0 is also known inside epidemiology as the basic
reproduction number. It's a measure of how potentially infectious that disease
is. What that boils down to essentially is the are not predicts how many
additional people one infected person could get sick in a population with no
immunity to the disease.
In general the higher the R0 the more infectious the disease.
And the value of one is important when it comes to the R0. An R0 less than
one means the outbreak will peter out, whereas an R0 greater than one
means the infection will continue to spread.
Here are some R0s from past outbreaks.
Measles's R0 is an estimated 12 to 18.
SARS or Sudden Acute Respiratory Syndrome has an R0 of 2
to 4. it is also a coronavirus virus. Early genetic analysis suggests that the new
coronavirus emerged from a virus related to SARS.
So what is the R0 of 2019-n-CoV?
An early scientific consensus is forming around than R0 of 2 to 3.
But the R0 can be thought of as some silver bullet metric
for the reality of this outbreak or any other.
Infectious disease expert David Fishman of the University of Toronto explains
If you didn't know that an infectious disease and you let it just run through
a totally immune population early on in the epidemic
how many secondary cases would you get for each primary case that's what they
R0 is it's right at baseline and the reason people distinguish R0
from the reproduction number later in an epidemic and sometimes called RE which
is R effective is that reproduction numbers change for a few
different reasons one of them is that people become immune and that deprives
the disease of new susceptible people to infect and that slows epidemics down the
second thing that changes reproduction numbers pretty predictably and without
vaccines or antibiotics or public health intervention is that people's behavior
often changes in the context of epidemics people react to them sometimes
in ways that are helpful in terms of reproduction numbers and sometimes in
ways that are unhelpful. If the outbreak was tailing off and everybody looks
around and says I can come out of hiding now because the outbreak is going away
you can have multiple waves of outbreaks so that's one example behavior changing
affecting reproduction number. How do we calculate R0? Well there are a
couple of different components to R0. One is how many contacts does the
case have per unit time. One is how likely are they if they're infected to
infect each of those contacts so probability of transmission conditional
on contact and then the third component of R0 is duration of infectivity.
So the longer your infectious the more people you can potentially infect and
that drives the reproduction number up. It's a unitless quantity so you need to
rescale the epidemic into into bug time rather than people time and we call that
the serial interval, which is you can you can use our knot to map out what an
epidemic is likely to do if you know what the serial interval is. And that's the
average interval between a becoming infectious and that case's
average secondary case becoming infectious. That's how we talk about
generations and infectious diseases. So you use R0 in combination with
serial intervals to figure out how diseases are going to grow. One of the
frustrating things about a situation like this where everyone's sort of on
edge and wants it to stop and go away is the time steps in this epidemic are
seven or eight days so people look at change in case numbers day to day that
has nothing to do with the underlying epidemic that has to do with how many
people are getting tested. So we really don't see the contour of the epidemic
play out at one to two day time steps. It's week to week to week so patience is
the watchword and I feel like you make predictions on this stuff at your peril.
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