Name: COVID-19更新：如何判斷是否可能發生大流行-R0和序列間隔。 (COVID-19 Update: How to tell if a pandemic is likely to occur or not–R0 and the serial interval.)
Uploaded: 2021-01-14T08:48:48.000Z
Duration: 7 min 57 s
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Welcome to today's Medmastery coronavirus update.

I'm an internist, trained in epidemiology and public health at Johns Hopkins and the

Today we're going to learn how to predict if an epidemic is going to spread fast and

The new coronavirus called SARS-CoV-2 might very well become a pandemic.

There are a couple of things you need to know.

Let's first talk about the basic reproductive ratio called R naught.

It applies to a situation where everyone in the population is susceptible and no

So we're talking about a population that has no immunity to the pathogen.

They're seeing the virus or bacteria for the very first time.

R naught, gives you the number of new cases that an existing case can generate

So let's take an arbitrary population and say that this guy has the disease and

So on average, one case gives the disease to one other person.

In the scenario where R naught is equal to one, the population of infected

Now let's look at another fictitious population where one infected person

infects three other individuals on average.

So this guy gives it to these three people, and these three people give it to

I think you can already tell that what we're looking at here is an exponential

growth curve that looks something like this.

So the number of infected patients increases.

So as we've seen, when R naught is equal to one, the group size will stay constant.

When R naught is greater than one, the group of infected individuals will grow.

And what will happen if R naught is below one?

If that happens, the population of infected individuals will get smaller and

Let's now look at the variables that influence R naught.

So R naught will vary depending if the route of transmission is fecal-oral or if

For example, both modes of transmission have been described for the new

Another factor that influences the value of R naught is the epidemiological system

So R naught will be slightly different in various geographic regions with different

social and cultural behaviors, for example.

Here's a quick formula - how you can think of R naught.

It basically depends on the susceptible population that an infected person is

going to encounter per time unit, let's say per days, times the average duration

of infectiousness in days, times the average probability that transmission will

So each time an infectious individual interacts with another susceptible person.

Which is largely a measure of pathogen virulence - the ability of a pathogen to

It has been estimated by various authors that R naught for COVID-19 is somewhere

Let's compare that to the values of R naught seen during flu pandemics.

During the 1918 influenza pandemic, R naught was 1.8.

So when it comes to R naught, SARS-CoV-2 is quite a bit more scary than influenza,

So what else do we need to know in order to tell if an epidemic is going to spread

Well, we need to know what is called the serial interval.

Well, let's say this guy, Bob, infected this girl, Pam, with the new coronavirus.

The serial interval would correspond to the time it takes between symptom onset in

Essentially the serial interval is a measure of how fast the disease spreads

Let's take the example of a fictitious population of 1000 uninfected individuals

who have never been exposed to the coronavirus, let's say.

Let's assume that this guy enters the population because he has just returned

Now I will make up some numbers for demonstration purposes.

Let's say R naught was five and the serial interval was 10 days.

So in the first 10 days, this guy infects five people, they develop disease.

After 10 more days, each of these individuals infects five more people in

So we have now 25 people, and after 10 more days, each one of those 25 people

So we end up with 125 new infected individuals in the last 10 day period.

So overall, we end up with 156 infected individuals in this population of a

That's 156 per 1000 per 30 days, or 5.2 per 1000 per day.

Let's take a different serial interval and see what happens.

Let's now say that the serial interval is 30 days instead of 10.

Now that initial case, infects five people over the entire month, so we end up with

Six cases per 1000 per 30 days corresponds to 0.2 per 1000 per day.

So you see, changing the serial interval really makes a big difference.

So what's the serial interval for the novel coronavirus?

Well, different authors describe different numbers.

It's generally thought to be somewhere around 7.5 days, maybe even shorter.