Adam Kucharski on what should (and shouldn't) worry us about the coronavirus

Hello, I'm Chris Anderson.
Welcome to The TED Interview.

We're gearing up for season four
with some extraordinary guests,

but I don't want to wait for that
for today's episode,

because we're in the middle of a pandemic,

and there's a guest
I really wanted to talk to now.

He is Adam Kucharski,

an infectious diseases scientist

who focuses on the mathematical
modeling of pandemics.

He's an associate professor

at the London School of Hygiene
and Tropical Medicine

and a TED Fellow.

(Music)

(TED Talk) Adam Kucharski:
So what kind of behavior

is actually important for epidemics?

Conversations, close physical contacts?

What sort of data should we be collecting

before an outbreak

if we want to predict
how infection might spread?

To find out, our team
built a mathematical model ...

Chris Anderson: When it comes
to figuring out what to make of

this pandemic,
known technically as COVID-19,

and informally as just the coronavirus,

I find his thinking unbelievably helpful.

And I'm excited to dive into it with you.

A special callout to my friends on Twitter

who offered up many
suggestions for questions.

I know this topic
is on everyone's mind right now.

And what I hope this episode does

is give us all a more nuanced way

of thinking about how this pandemic
has unfolded so far,

what might be to come

and what we all collectively
can do about it.

Let's dive in.

(Music)

Adam, welcome to the TED Interview.

Adam Kucharski: Thank you.

CA: So let's just start
with a couple of basics.

A lot of skeptical people's response --

certainly over the last few weeks,
maybe less so now --

has been, "Oh, come on,
this isn't such a big deal,

there's a relatively tiny number of cases.

Compare it to the flu,
compare it to anything else.

There are much bigger
problems in the world.

Why are we making such a fuss about this?"

And I guess the answer to that fuss
is that it comes down to the mathematics.

We're talking about the mathematics
of exponential growth,

fundamentally, right?

AK: Exactly.

And there's a number that we use
to get a sense of how easy things spread

and the level of transmission
we're dealing with.

We call that the reproduction number,

and conceptually, it's just,

for each case you have, on average,

how many others are they infecting?

And that gives you a sense
of how much is this scaling,

how much this growth
is going to look like.

For coronavirus, we're now seeing,
across multiple countries,

we're seeing each person on average
giving it to two or three more.

CA: So that reproduction number,

the first thing to understand
is that any number above one

means that this thing is going to grow.

Any number below one
means it's going to diminish.

AK: Exactly -- if you have it above one,

then each group of people infected

are going to be generating more infection
than there was before.

And you will see the exponential effect,

so if it's two, you will be doubling
every round of infection,

and if it's below one,

you're going to get something
that's going to decline, on average.

CA: So that number two or higher,

I think everyone here is maybe familiar
with the famous story

of the chessboard and the grains of rice,

and if you double the number of grains
for every square of the chessboard,

for the first 10 or 15 squares
nothing much happens,

but by the time you've got
to the 64th square,

you suddenly have tons of rice
for every individual on the planet.

(Laughs)

Exponential growth is an incredible thing.

And the small numbers now

are really not what you
should be paying attention to --

you should be paying attention
to the models of what could be to come.

AK: Exactly.

Obviously, if you continue
the exponential growth,

you do sometimes get
these incredibly large,

maybe implausibly large numbers.

But even looking at a timescale
of say, a month,

if the reproduction number is three,

each person is infecting three on average.

The gap between these rounds
of infection is about five days.

So if you imagine
that you've got one case now,

that's, kind of, six of these
five-day steps in a month.

So by the end of that month,

that one person could have generated,

I think it works out at about 729 cases.

So even in a month,

just the scale of this thing
can really shoot up

if it's not controlled.

CA: And so certainly,

that seems to be happening
on most numbers that you look at now,

certainly where the virus
is in the early stages

of entering a country.

You've given a model

whereby we can much more clearly
understand this reproduction number,

because it seems to me this is almost
like the core to how we think of the virus

and how we respond to it
and how much we should fear it, almost.

And in your thinking,

you sort of break it down
into four components,

which you call DOTS:

Duration, Opportunities,

Transmission probability

and Susceptibility.

And I think it would be
really helpful, Adam,

for you to just explain each of these,

because it's quite a simple equation

that links those four things
to the actual reproduction number.

So talk about them in turn.

Duration, what does that mean?

AK: Duration measures
how long someone is infectious for.

If, for example,

intuitively, if someone is infectious
for a longer period of time,

say, twice as long as someone else,

then that's twice the length

that they've got
to be spreading infection.

CA: And what is the duration
number for this virus,

compared with, say, flu
or with other pathogens?

AK: It depends a little bit

on what happens
when people are infectious,

if they're being isolated very quickly,
that shortens that period of time,

but potentially, we're looking
at around a week

people are effectively infectious
before they might be isolated in hospital.

CA: And during that week,
they may not even be showing symptoms

for that full week either, right?

So someone gets infected,
there's an incubation period.

There's a period some way
into that incubation period

where they start being infectious,

and there may be a period after that,
where they start to show symptoms,

and it's not clear, quite,
how those dates align.

Is that right?

AK: No, we're getting more information.

One of the signals we see in data

that suggest that you may have
that early transmission going on

is when you have this delay
from one infection to the next.

So that seems to be around five days.

That incubation period,
the time for symptoms to appear,

is also about five days.

So if you imagine that most people

are only infecting others
when they're symptomatic,

you'd have that incubation period

and then you'd have some more time
when they're infecting others.

So the fact that those values
seem to be similar,

suggesting that some people
are transmitting

either very early on or potentially
before they're showing clear symptoms.

CA: So almost implies that on average,

people are infecting others

as much before
they show symptoms as after.

AK: Potentially.

Obviously these are early data sets,

but I think there's good evidence
that a fair number of people,

either before they're
showing clear symptoms

or maybe they're not showing the kind of
very distinctive fever and cough

but they're feeling unwell
and they're shedding virus

during that period.

CA: And does that make it
quite different from the flu, for example?

AK: It makes it actually
similar to flu in that regard.

One of the reasons pandemic flu
is so hard to control

and so feared as a threat

is because so much transmission happens
before people are severely ill.

And that means that by the time
you identify these cases,

they've probably actually spread it
to a number of other people.

CA: Yeah, so this is
the trickery of the thing,

and why it's so hard
to do anything about it.

It is ahead of us all the time,

and you can't just pay attention
to how someone feels

or what they're doing.

I mean, how does that happen, by the way?

How does someone infect someone else

before they're even showing
symptoms themselves,

because classically, we think of,
you know, the person sneezing

and droplets go through the air
and someone else breathes them in

and that's how infection happens.

What is actually going on
for infection pre-symptoms?

AK: So the level of transmission
we see with this virus

isn't what we see,
for example, with measles,

where someone sneezes
and a lot of virus gets out

and potentially lots of susceptible
people can get exposed.

So potentially, it could be quite early on

that even if someone
has quite mild symptoms,

maybe a bit of a cough,

that's enough for some virus
to be getting out

and particularly,

some of the work that we've done

trying to look at sort of
close gatherings,

so very tight-knit meals,

there was an example in a ski chalet --

and even in those situations,
you might have someone mildly ill,

but enough virus is getting out
and somehow exposing others,

we're still trying
to work out exactly how,

but there's enough there
to cause some infection.

CA: But if someone's mildly ill,
don't they still have symptoms?

Isn't there evidence that even before
they know that they're ill,

something is going on?

There was a German paper
published this week

that seemed to suggest
that even really early on,

you take a swab from the back
of someone's throat

and they have hundreds
of thousands of these viruses

already reproducing there.

Like, can someone just
literally just be breathing normally

and there is some transmission
of virus out into the air

that they don't even know about

and is either infecting people directly

or settling on surfaces, is that possible?

AK: I think that's what
we're trying to pin down,

how much that [unclear].

As you said,

there's evidence that you can have
people without symptoms

and you can get virus out their throats.

And so certainly there's potential
that it can be breathed out,

but is that a fairly rare event
for that actual transmission to happen,

or are we potentially seeing more
infections occur through that route?

So it's really early data,

and I think it's a piece of the puzzle,

but we're trying to work out
where that fits in

with what we know about the kind of
other transmission events we've seen.

CA: Alright, so, duration is the duration
of the period of infectiousness.

We think is five to six days,
is that what I heard you say?

AK: Potentially around a week,

depending on exactly what happens
to people when they're infectious.

CA: And there are cases
of people testing positive

way, way later,
after they've got infected.

That may be true, but they are probably
not as infectious then.

Is that basically right,
that's the way to think of this?

AK: I think that's our working theory,

that a lot of that infection
is happening early on.

And we see that for a number
of respiratory infections,

that when people obviously
become severely ill,

their behavior is very different

to when they may be walking around
and going about their normal day.

CA: And so again, comparing
that D number to other cases,

like the flu,

is flu similar?

What's the D number for flu?

AK: So for flu,
it's probably slightly shorter

in terms of the period
that people are actively infectious.

I mean, for flu,
it's a very quick turnover

from one case to the next, actually.

Even a matter of
about three days, potentially,

from one infection
to the person that they infect.

And then at the other end of the scale,
you get things like STDs,

where that duration could be
several months, potentially.

CA: Right.

OK, really nothing that unusual so far,
in terms of this particular virus.

Let's look at the O, opportunity.

What is that?

AK: So opportunity is a measure
of how many chances

the virus has to spread
through interactions

while someone is infectious.

So typically, it's a measure
of social behavior.

On average, how many
social contacts do people make

that create opportunities for transmission
while they're infectious.

CA: So it's how many people
have you got close enough to

during a day, during a given day,

to have a chance of infecting them.

And that number could be,

if people aren't taking precautions
in a normal, sort of, urban setting,

I mean, that could run
into the hundreds, presumably?

AK: Potentially, for some people.

We've done a number of studies
looking at that in recent years,

and the average,
in terms of physical contacts,

is about five people per day.

Most people will have
conversation or contacts

generally with about 10, 15,

but obviously,

between cultures,
we see quite a lot of variation

in the level of physical greetings
that might happen.

CA: And presumably, that number
again is no different for this virus

than for any other.

I mean, that's just a feature
of the lives that we live.

AK: I think for this one,

if it's driven through
these kind of interactions,

and we've seen for flu,
for other respiratory infections,

those kinds of fairly close contacts
and everyday physical interactions

seem to be the ones
that are important for transmission.

CA: Perhaps there is one difference.

The fact that if you're
infectious pre-symptoms,

perhaps that means that actually,
there are more opportunities here.

This is part of the virus's
genius, as it were,

that by not letting on
that it's inside someone,

people continue to interact and go to work

and take the subway and so forth,

not even knowing that they're sick.

AK: Exactly.

And for something like flu,

you see when people get ill, clearly,
their social contacts drop off.

So to have a virus that can be infectious

while people are going around
their everyday lives,

really gives it an advantage
in terms of transmission.

CA: In your modeling,

do you actually have this
opportunities number higher than for flu?

AK: So for the moment,
we're kind of using similar values,

so we're trying to look at, for example,

physical contacts
within different populations.

But what we are doing is scaling the risk.

So that's coming on to the T term.

So that between each contact,

what's the risk that a transmission
event will occur.

CA: Alright, so let's go on
to this next number,

the T, transmission probability.

How do you define that?

AK: So this measures the chance

that, essentially,
the virus will get across

during a particular opportunity
or a particular interaction.

So you may well have
a conversation with somebody,

but actually, you don't cough
or you don't sneeze

or for some reason,
the virus doesn't actually get across

and expose the other person.

And so, for this virus, as I mentioned,

say people are having
10 conversations a day,

but we're not seeing infected people
infect 10 others a day.

So it suggests that not all
of those opportunities

are actually resulting
in the virus getting across.

CA: But people say
that this is an infectious virus.

Like, what is that transmission
probability number,

again, compared with, say, the flu?

AK: So, we did some analysis
looking at these very close gatherings.

We looked at about 10
different case studies,

and we found that about a third
of the contacts in those settings

subsequently got infected

in these early stages,
when people weren't aware.

So if you had these, kind of,
big group meals,

potentially, each contact
had about, a kind of, one in three chance

of getting exposed.

For seasonal flu,
that tends to be slightly lower,

even within households
and close settings,

you don't necessarily
get values that high.

And even for something like SARS,
those values have, kind of --

the risk per interaction you had

was lower than what we seem
to be getting for coronavirus.

Which intuitively makes sense,

there must be a higher risk
per interaction

if this thing is spreading so easily.

CA: Hm.

OK, and then the fourth letter of DOTS

is S for susceptibility.

What's that?

AK: So that is a measure of the proportion
of the population who are susceptible.

If you imagine you have
this interaction with someone,

the virus gets across, it exposes them,

but some people may have been vaccinated

or otherwise have some immunity

and not develop infection themselves

and not be infectious to others.

So we've got to account for this
potential proportion of people

who are not actually
going to turn into cases themselves.

CA: And obviously, there's no vaccine yet
for this coronavirus,

nor is anyone, at least initially,
immune, as far as we know.

So are you modeling that
susceptibility number pretty high,

is that part of the issue here?

AK: Yeah, I think the evidence

is that this is going to fully
susceptible populations,

and even in areas,
for example, like China,

where there's been a lot of transmission

but there's been very strong
control measures,

we estimated that up to
the end of January,

probably about 95 percent of Wuhan
are still susceptible.

So there's been a lot of infection,

but it hasn't really taken much
of that component,

of the DOTS, of those four things
that drive transmission.

CA: And so the way the mathematics works,

I have to confess, amidst the stress
of this whole situation,

the nerd in me kind of loves
the elegance of the mathematics here,

because I'd never really
thought about it this way,

but you basically just multiply
those numbers together

to get the reproduction number.

Is that right?

AK: Exactly, yeah,

you almost take the path
of the infection during transmission

as you multiply those together,

and that gives you
the number for that virus.

CA: And so there's just
a total logic to that.

It's the number of days,
duration that you're infectious,

it's the number of people
you're seeing on average

during those days
that you have a chance to infect.

Then you multiply that
by the transmission probability,

is virus getting into them, essentially,

that's what you mean by crossing over.

And then by the susceptibility number.

By the way, what do you think
the susceptibility probability is

for this case?

AK: I think we have to assume
that it's near 100 percent

in terms of spread, yeah.

CA: Alright, you multiply
those numbers together,

and right now, it looks like,
for this coronavirus,

that you say two to three
is the most plausible current number,

which implies very rapid growth.

AK: Exactly.

In these uncontrolled outbreaks,

we're seeing now a number
of countries in this stage --

you are going to get
this really rapid growth occurring.

CA: And so how does
that two to three compare with flu?

And I guess, there's seasonal flu,

in the winter, when it's spreading,

and at other times during the year
drops well below one

as a reproduction number, right?

But what is it during seasonal flu time?

AK: During the early stage
when it's taking off

at the start of the flu season,

it's probably, we reckon,
somewhere between about maybe 1.2, 1.4.

So it's not incredibly transmissible,

if you imagine you do have some immunity
in your population from vaccination

and from other things.

So it can spread, it's above one,

but it's not taking off, necessarily,
as quickly as the coronavirus is.

CA: So I want to come back
to two of those elements,

specifically opportunity
and transmission probability,

because those seem to have the most
chance to actually do something

about this infection rate.

Before we go there,

let's talk about another
key number on this,

which is the fatality rate.

First of all, could you define --

I think there's two different versions
of the fatality rate

that maybe confuse people.

Could you define them?

AK: So the one that we often talk about
is what's known as the case fatality rate,

and that's of the proportion who show up
with symptoms as cases,

what proportion of those
will subsequently be fatal.

And we also sometimes talk
about what's known

as the infection fatality rate,

which is, of everyone who gets infected,

regardless of symptoms,

how many of those infections
will subsequently be fatal.

But most of the values
we see kicking around

are the case fatality rate, or the CFR,
as it's sometimes known.

CA: And so what is
that fatality rate for this virus,

and again, how does that compare
with other pathogens?

AK: So there's a few numbers
that have been bouncing around.

One of the challenges in real time
is you often don't see all of your cases,

you have people symptomatic
not being reported.

You also have a delay.

If you imagine, for example,

100 people turn up to a hospital
with coronavirus

and none have died yet,

that doesn't imply
that the fatality rate is zero,

because you've got to wait to see
what might happen to them.

So when you adjust for that
underreporting and delays,

best estimate for the case fatality
is about one percent.

So about one percent
of people with symptoms,

on average,

those outcomes are fatal.

And that's probably about 10 times
worse than seasonal flu.

CA: Yeah, so that's a scary
comparison right there,

given how many people die of flu.

So when the World Health Organization
mentioned a higher number,

a little while back, of 3.4 percent,

they were criticized a bit for that.

Explain why that
might have been misleading

and how to think about it
and adjust for that.

AK: It's incredibly common that people
look at these raw numbers,

they say, "How many deaths
are there so far, how many cases,"

and they look at that ratio,

and even a couple of weeks ago,
that number produced a two percent value.

But if you imagine
you have this delay effect,

then even if you stop all your cases,

you will still have these kind of
fatal outcomes over time,

so that number will creep up.

This has occurred in every epidemic
from pandemic flu to Ebola,

we see this again and again.

And I made the point to a number of people
that this number is going to go up,

because as China's cases slow,

it will look like it's increasing,

and that's just kind of
a statistical quirk.

There's nothing really
kind of, behind the change,

there's no mutations or anything going on.

CA: If I have this right,
there are two effects going on.

One is that the number of fatalities

from the existing caseload will rise,

which actually would boost
that 3.4 even higher.

But then you have to offset that
against the fact that apparently,

huge numbers of cases
have just gone undetected

and that we haven't,

due to bad testing,

that the number of fatalities don't --

They probably reflect
a much larger number of early cases.

Is that it?

AK: Exactly.

So you have one thing
pulling the number up,

and one thing pulling it down.

And it means that on these
kind of early values,

if you actually just adjust for the delay,

and don't think
about these unreported cases,

you start getting really
very scary numbers indeed.

You get up to 20, 30 percent potentially,

which really doesn't align

with what we know
about this virus in general.

CA: Alright.

There's a lot more data in now.

From your point of view,
you think the likely fatality rate,

at least in the earlier stage
of an infection,

is about two percent?

AK: I think overall,

I think we can put something probably
in the 0.5 to two percent range,

and that's on a number
of different data sets.

And that's for people who are symptomatic.

I think on average, one percent
is a good number to work with.

CA: OK, one percent,

So flu is often quoted
as a tenth of a percent,

so it's five to ten times or more
more dangerous than flu.

And that danger is not symmetric
across age groups,

as is well known.

It primarily affects the elderly.

AK: Yeah, we've seen
that one percent on average,

but once you start getting
into the over 60s, over 70s,

that number really starts to shoot up.

I mean, we're estimating
potentially in these older groups,

you're looking at maybe five,
ten percent fatality.

And then of course, on top of that,

you've got to add what
are going to be the severe cases

and people are going to require
hospitalization.

And those risks get very large
in the older groups indeed.

CA: Adam, put these numbers
together for us.

In your models,

if you put together
a reproduction rate of two to three

and a fatality rate
of 0.5 percent to one percent,

and you run the simulation,

what does it look like?

AK: So if you have
this uncontrolled transmission,

and you have this reproduction
number of two or three

and you don't do anything about it,

the only way the outbreak ends

is enough people get it
and immunity builds up

and the outbreak kind of ends on its own.

And in that case,

you would expect very large numbers
of the population to be infected.

It's what we see, for example,

with many other uncontained outbreaks,

that it essentially burns
through the population,

you get large numbers infected

and with this kind of fatality rate
and hospitalization rate,

that would really be hugely damaging
if that were to occur.

Certainly at the country level,
we're seeing --

Italy is a good example at the moment,

that if you have that early
transmission is undetected,

that rapid growth,

you very quickly get to a situation
where your health systems are overwhelmed.

I think one of the nastiest
aspects of this virus

is that because you have the delay
between infection and symptoms

and people showing up in health care,

if your health system is overwhelmed,

even on that day,

if you completely stop transmission,

you've got all of these people
who have already been exposed,

so you're still going to have cases
and severe cases appearing

for maybe another couple of weeks.

So it's really this huge
accumulation of infection and burden

that's coming through the system
on your population.

CA: So there's another
key number, actually,

is how does the total case number

compare to the capacity
of a country's health system

to process that number of cases.

Presumably that issue
makes a huge difference

to the fatality rate,

the difference between people
coming in with severe illness

and a health system that's able
to respond and one that's overwhelmed.

The fatality rate is going to be
very different at that point.

AK: If someone requires an ICU bed,

that's a couple of weeks
they're going to require it for

and you've got more cases
coming through the system,

so it very quickly gets very tough.

CA: So talk about the difference
between containment

and mitigation.

These are different terms
that we're hearing a lot about.

In the early stages of the virus,
governments are focused on containment.

What does that mean?

AK: Containment is this idea
that you can focus your effort on control

very much on the cases and their contacts.

So you're not causing disruption
to the wider population,

you have a case that comes in,
you isolate them,

you work out who they've come
into contact with,

who's potentially these
opportunities for exposure,

and then you can follow up those people,

maybe quarantine them to make sure
that no further transmission happens.

So it's a very focused, targeted method,

and for SARS, it worked remarkably well.

But I think for this infection,

because some cases are going to be missed,
they're going to be undetected,

you've really got to be capturing
a large chunk of people at risk.

If a few slip through the net,

potentially, you're going
to get an outbreak.

CA: Are there any countries

that have been able
to employ this strategy

and effectively contain the virus?

AK: So Singapore have been doing
a really remarkable job of this

for the last six weeks or so.

So as well as some wider measures,

they've been working incredibly hard

to trace people
who have come into contact.

Looking at CCTV,

going through to find out
which taxi someone might have gotten,

who might be at risk --

really, really thorough follow up.

And for about six weeks,
that has kept a lid on transmission.

CA: So that's amazing.

So someone comes into the country,

they test positive --

they go to work, and with a massive team,

and trace everything,

to the level of actually saying,

"Oh, you don't know what taxi you went in?

Let us find that out for you."

And presumably,
when they find the taxi driver,

they then have to try and figure out
everyone else who was in that taxi?

AK: So they will focus on
close contacts of people most at risk,

but they're really minimizing the chance
that anyone slips through the net.

CA: But even in Singapore,
if I'm not mistaken,

numbers started to trend
back down to zero,

but I think recently,
they've picked up again a bit.

It's still unclear

whether they will actually
be able to sustain containment.

AK: Exactly.

If we talk in terms
of the reproduction number,

we saw it dipped to maybe 0.8, 0.9,

so under that crucial value of one.

But in the last week or two,

it does seem to be taking up
and they're getting more cases appearing.

I think a lot of it is,

even if they are containing it,

the world is experiencing outbreaks

and just keeps throwing
sparks of infection,

and it becomes harder and harder

with that level of intensive effort
to stamp them all out.

(Music)

CA: In the case of this virus,

you know, there was warning
to most countries in the world

that this thing was happening.

The news out of China
very quickly became very bleak

and people had time to prepare.

I mean, what would an ideal
preparation look like

if you know that something
like this is coming

and you know that there's
a lot on the line

if you can successfully contain it
before it really escapes?

AK: I think two things
would make a really big difference.

One is having as thorough follow up
and detection as possible.

We've done some modeling analyses,

looking at how effective
that kind of early containment is.

And it can be, if you're identifying
maybe 70 or 80 percent

of the people who might have
come into contact.

But if you're not detecting
those cases coming in,

if you're not detecting their contacts --

and a lot of the early focus, for example,
was on travel history to China,

and then it became clear
that the situation was changing,

but because you were relying on that
as your definition of a case,

it meant a lot of maybe other cases
that matched the definition

weren't being tested

because they didn't seem
to be potentially at risk.

CA: So I mean, if you know
that early detection is key to this,

an essential early measure, I guess,

would be to rapidly ensure
that you had enough tests available,

and where needed,

so that you could respond,

be ready to swing into action
as soon as someone was detected,

you then have to very quickly,
I guess, test their contacts and so forth,

to have a chance
of keeping this under control.

AK: Exactly.

In my line of work, we say
there's value in a negative test,

because it shows that you're looking
for something and it's not there.

And so I think having
small numbers of people tested

doesn't give you confidence
that you're not missing infections,

whereas if you are doing
really thorough follow up on contacts,

we've seen countries even like Korea now,

huge numbers of people tested.

So although there are still
cases appearing,

it gives them more confidence

that they have some sense
of where those infections are.

CA: I mean, you're in the UK right now,

I'm in the US.

How likely is it that the UK
is going to be able to contain,

how likely is it that the US
is going to be able to contain this?

AK: I think it's pretty
unlikely in both cases.

I think the UK is going to have
to introduce some additional measures.

I think when that happens
obviously depends a bit

on the current situation,

but we've tested almost 30,000 people now.

Frankly, I think the US
may well be moving beyond that point,

given how much evidence
of extensive transmission that has,

and I think without clear ideas
of how much infection there is

and that level of testing,

it's quite hard to actually see
what the picture currently is in the US.

CA: I mean, I definitely don't want to get
too political about this,

but I mean, does this strike you as --

you just said that the UK
has tested 30,000 people --

the US is five or six times bigger

and I think the total number
of tests here is five or six thousand,

or it was a few days ago.

Does that strike you as bizarre?

I don't understand, honestly,
how that happened in an educated country

that has so much knowledge
about infectious diseases.

AK: It does,

and I think there's obviously
a number of factors playing in there,

logistics and so on,

but there has been that period of warning

that this is a threat
and this is coming in.

And I think countries need to make sure
that they've got the capacity

to really do as much detection as they can
in those early stages,

because that's where
you're going to catch it

and that's where you're going to have
a better chance of containing it.

CA: OK, so if you fail to contain,

then you have to move
to some kind of mitigation strategy.

So what comes into play there?

And I think I almost want
to bring that back

to two of your DOTS factors,

opportunity and transmission probability,

because it seems like
the virus is what it is,

the actual duration when someone
is potentially infectious,

we can't do much about.

The susceptibility side,

we can't do much about
until there's a vaccine.

We could maybe talk about that in a bit.

But the middle two of opportunity
and transmission probability,

we can do something about.

Do you want to maybe talk
about those in turn,

of what that looks like,

how would you build a mitigation strategy?

I mean, first of all,
thinking about opportunity,

how do you reduce
the number of opportunities

to pass on the bug?

AK: And so I think in that respect,

it would be about massive changes
in our social interactions.

And if you think in terms
of the reproduction number

of being about two or three,

to get that number below one,

you've really got to cut
some aspect of that transmission

in half or in two thirds,

to get that below one.

And so that would require,

of the opportunities
that could spread the virus

are these kind of close contacts.

Everybody in the population, on average,

will be needing to reduce
those interactions

potentially by two thirds
to bring it under control.

That might be through working from home,

from changing lifestyle

and kind of where you go
in crowded places and dinners.

And of course, these measures,
things like school closures,

and other things
that just attempt to reduce

the social mixing of a population.

CA: Well, actually, talk to me more
about school closures,

because that, if I remember,

often in past pandemics has been cited
as an absolutely key measure,

that schools represent this sort of
coming together of people,

children are often --

certainly when it comes to flu and colds,

they're carriers.

But on this case,

children don't seem to be getting sick
from this particular virus,

or at least very few of them are.

Do we know whether they
can still be infectious?

They can be the unintended carriers of it.

Or actually, is there evidence
that school closures

may not be as important
in this instance as it is in others?

AK: So that point
on what role children play

is a crucial one,

and there's still not
a good evidence base there.

From following up of contacts of cases,

there's now evidence
that children are getting infected,

so when you're testing,
they are getting exposed,

it's not that somehow they're just
not getting the infection at all,

but as you said, they're not showing
symptoms in the same way,

and particularly for flu,

when we see the implications
of school closures,

even in the UK in 2009 during swine flu,

there was a dip in the outbreak
during the school holidays,

you could see it on the epidemic curve,

it kind of comes back down in the summer
and goes back up in the autumn.

But of course, in 2009,
there was some immunity in older groups.

That kind of shifted more the transmission
onto the younger ones.

So I think it's really something
we're trying to work to understand.

Obviously, it will reduce interactions,
with school closures,

but then there's knock-on social effects,

there's potential
knock-on changes in mixing,

maybe grandparents and their role
in terms of alternative carers

if parents have to work.

So I think there's a lot of pieces
that need to be considered.

CA: I mean, based on all of the different
pieces of evidence you've seen,

if it were down to you,

would you be recommending
that most countries at this point

do look hard at extensive school closures
as a precautionary measure,

that it's just worth it to do that

as a sort of painful two,
three, four, five-month strategy?

What would you recommend?

AK: I think the key thing,

given the age distribution of risk
and the severity in older groups

is reduce interactions that bring
the infection into those groups.

And then amongst everyone else,
reduce interactions as much as possible.

I think the key thing is

we've got so much of the disease burden
in the kind of 60-plus group

that it's not just about
everyone trying to avoid

everyone's interactions,

but it's the kind of behaviors

that would drive infections
into those groups.

CA: Does that mean
that people should think twice

before, I don't know, visiting a loved one

in an old people's home
or in a residential facility?

Like that, we should just pay
super special attention to that,

should all these facilities
be taking great care

about who they admit,

taking temperature and checking
for symptoms or something like that?

AK: I think those measures
definitely need to be considered.

In the UK, we're getting plans

for potentially what's known
as a cocooning strategy

for these older groups

that we can really try
and seal off interactions

as much as possible

from people who might
be bringing infection in.

And ultimately, because as you said,

we can't target these other
aspects of transmission,

it is just reducing the risk
of exposure in these groups,

and so I think anything
at the individual level you can do

to get people reducing their risk,

if either they're elderly
or in other risk groups,

I think is crucial.

And I think more at the general level

those kind of more large-scale measures
can help reduce interactions overall,

but I think if those
reductions are happening,

and not reducing the risk

for people who are going
to get severe disease,

then you're still going to get
this really remarkably severe burden.

CA: I mean, do people have to almost
apply this double lens

as they think about this stuff?

There's the risk to you
as you go about your life,

of you catching this bug.

But there's also the risk
of you being, unintentionally, a carrier

to someone who would suffer
much more than you might.

And that both those things
have to be top of mind right now.

AK: Yeah, and it's not just
whose hand you shake,

it's whose hand that person
goes on to shake.

And I think we need to think
about these second-degree steps,

that you might think you have low risk,

and you're in a younger group,

but you're often going to be
a very short step away

from someone who is going to get hit
very hard by this.

And I think we really need
to be socially minded

and think this could be quite dramatic
in terms of change of behavior,

but it needs to be

to reduce the impact
that we're potentially facing.

CA: So the opportunity
number, we bring down

by just reducing the number
of physical contacts we have

with other people.

And I guess the transmission
probability number,

how do we bring that down?

That impacts how we interact.

You mentioned hand-shaking,

I'm guessing you're going to say
no handshaking.

AK: Yeah, so changes like that.

I mean, another one, I think,

handwashing operates in a way

that we might be still be doing
activities that we've previously done,

but handwashing reduces the chance
that from one interaction to another,

we might be spreading infection,

so it's all of these measures

that mean that even
if we're having these exposures,

we're taking additional steps
to avoid any transmission happening.

CA: I still think most people
don't fully understand

or don't have a clear model of the pathway

by which thins thing spreads.

So you think definitely people understand

that you don't breathe in

the water droplets of someone
who has just coughed or sneezed.

So how does it spread?

It gets onto surfaces. How?

Do people just breathe out
and it goes on from people who are sick,

they touch their mouth
or something like that,

and then touch a surface
and it gets on that way?

How does it actually get onto surfaces?

AK: I think a lot of it would be
that you cough in your hand

and it ends up on a surface.

But I think the challenge, obviously,
is untangling these questions

of how transmission happens.

You have transmission in a household,

and is it that someone coughed
and it got on a surface,

is it direct contact, is it a handshake,

and even for things like flu,

that's something that we work
quite hard to try and unpick,

how does social behavior correspond
to infection risk.

Because it's clearly important,
but pinning it down is really tough.

CA: It's almost like embracing the fact

that for a lot of these things,
we actually don't know

and that we're all
in this game of probabilities.

Which, in a way, is why I think
the math is so important here.

That you have to think of this
as these multiple numbers

working together on each other,

they all have their part to play.

And any of them that you can
take down by a percentage

is likely contributing,

not just to you, but to everyone.

And people don't actually know
in detail how the numbers go together,

but they know that they
probably all matter.

We almost need people to, somehow,
you know, embrace that uncertainty

and then try to get some satisfaction
by acting on every single part of it.

AK: I think it's this idea

that if on average,
you're infecting, say, three people,

what's driving that and how can you
chip away at that value?

If you're washing your hands,

how much might that chip away
in terms of the handshakes,

you know, you may have had virus
and you no longer do,

or if you are changing
your social behavior in a certain way,

is that taking away
a couple of interactions,

is that taking away half,

how can you really chip into that number
as much as you possibly can?

CA: Is there anything else to say
about how we could reduce

that transmission probability
in our interactions?

Like, what is the physical distance

that it's wise to stay away
from other people if we can?

AK: I think it's hard to pin down exactly,

but I think one thing to bear in mind
is that there's not so much evidence

that this is a kind of aerosol
and it goes really far --

it's reasonably short distances.

I don't think it's the case

that you're sitting a few meters
away from someone

and the virus is somehow
going to get across.

It's in closer interactions,

and it's why we're seeing
so many transmission events

occur in things like meals
and really tight-knit groups.

Because if you imagine

that's where you can get
a virus out and onto surfaces

and onto hands and onto faces,

and it's really situations like that
we've got to think more about.

CA: So in a way,

some of the fears that people have
may actually be overstated,

like, if you're in the middle
of an airplane

and someone at the front sneezes,

I mean, that's annoying,

but it's actually not the thing
you should be most freaked out about.

There are much smarter ways
to pay attention to your well-being.

AK: Yeah, if it was measles
and the plane is susceptible people,

you would see a lot
of infections after that.

I think it is, bear in mind,
that this is, on average,

people infecting two or three others,

so it's not the case of your
maybe 50 interactions over a week,

all of those people are at risk.

But it's going to be some of them,

particularly those close contacts,

that are going to be
where transmission's occurring.

CA: So talk about,

from a sort of national
strategy point of view.

There's a lot of talk about the need
to "flatten the curve."

What does that mean?

AK: I think it refers to this idea
that for your health systems,

you don't want all your cases
to appear at the same time.

So if we sat back and did nothing,

and just let the epidemic grow,

and you had this growth rate
that, at the moment,

in some places is looking like maybe

three to four days,
you're getting doubling.

So every three or four days,
the epidemic is doubling.

It will skyrocket and you'll end up

with a whole bunch
of really severely ill people

needing hospital care
all at the same time,

and you just won't have capacity for it.

So the idea of flattening the curve
is if we can slow transmission,

if we can get that
reproduction number down,

then there may still be an outbreak,

but it will be much flatter,

it will be longer,

and there will be fewer
severe cases showing up,

which means that they can get
the health care they need.

CA: Does it imply that there will be
fewer cases overall, or ---

When you look at the actual images
of people showing

what flattening the curve looks like,

it almost looks as if you've got
the same area still under the graph,

i.e. that the same number of people,
ultimately, are infected,

but over a longer period.

Is that typically what happens,

and even if you adopt
all these strategies of social distancing

and washing hands and etc.

that the best you can hope for
is that you slow the thing down,

you actually will get
as many people infected in the end?

AK: Not necessarily --
it depends on the measures that go in.

There are some measures like,
shutting down travel,

which typically delay the spread
rather than reduce it.

So you're still going to get
the same outbreaks,

but you're stretching out the outbreaks.

But there are other measures.

If we talk about reducing interactions,

if your reproduction number's lower,

you would expect fewer cases overall.

And eventually, in your population,

you will get some buildup of immunity,

which would help you out
if you think about the components,

reducing susceptibility,

alongside what's going on elsewhere.

So the hope is that the two things
will work together.

CA: So help me understand
what the endgame is here.

So, take China, for example.

Whatever you make
of the early suppression of data

and so forth,

that seems pretty troubling there.

The intensity of the response
come January time or whatever,

with the shutdown
of this huge area of the country,

seems to have actually been effective.

The number of cases there are falling
at a shockingly high rate in some ways.

Falling to almost nothing.

And I can't understand that.

You are talking about a country
of, whatever, 1.4 billion people.

There have been a huge
number of cases there,

but it was a tiny fraction
of the population have actually got sick.

And yet, they've got the number way down.

It's not like every other person in China
has somehow developed immunity.

Is it that they have been
absolutely disciplined

about shutting down travel
from the infected regions

and somehow really dialed up,
massively dialed up

testing at any sign of any problem,

so that literally, they are back
in containment mode

in most parts of China?

I can't get my head around it,
help me understand it.

AK: So we estimated,
in the last two weeks of January,

when these measures went in,

the reproduction number
went from about 2.4 to 1.1.

So about 60 percent decline
in transmission

in the space of a week or two.

Which is remarkable and really,

a lot of it is likely to be driven
by just fundamental change

in social behavior,

huge social distancing,

really intensive follow up,
intensive testing.

And it got to the point

where it took enough
off the reproduction number

to cause the decline,

and of course,
we're seeing, in many areas,

a transition back to more
of this kind of containment,

because there's few cases,
it's more manageable.

But we're also seeing them
face a challenge,

because a lot of these cities
have basically been locked down

for six weeks

and there's a limit to how long
you can do that for.

And so some of these measures
are gradually starting to be lifted,

which of course creates the risk

that cases that are appearing
from other countries

may subsequently go in
and reintroduce transmission.

CA: But given how infectious the bug is,

and how many theoretical pathways
and connection points there are

between people in Wuhan, even in shutdown,

or relatively shut down,

or the other places
where there's been some infection

and the rest of the country,

does it surprise you how quickly
that curve has gone down to nearly zero?

AK: Yes.

Early on when we saw
that flattening off in cases

in those first few days,

we did wonder whether it was just
they hit a limit in testing capacity

and they were reporting 1,000 a day,

because that's all the kits they had.

But it continued, thankfully,

and it shows that it is possible
to turn this over

with that level of intervention.

I think the key thing now
is seeing how it works in other settings.

Italy now are putting in
really dramatic interventions.

But of course,
because of this delay effect,

if you put them in today,

you won't necessarily see
the effects on cases

for another week or two.

So I think working out
what impact that's had

is going to be key for helping
other countries

work on how to contain this.

CA: To have a picture, Adam,

of how this is likely to play out
over the next month or two,

give us a couple of scenarios
that are in your head.

AK: I think the optimistic scenario

is that we're going to learn a lot
from places like Italy

that have unfortunately
been hit very hard,

and that countries are going to take
this very seriously

and that we're not going to get
this continued growth

that's going to overwhelm totally,

that we're going to be able
to sufficiently slow it down,

that we are going to get
large numbers of cases,

we're probably going to get
a lot of severe cases,

but that will be more manageable,

that's the kind of optimistic scenario.

I think if we have a point

where countries either
don't take this seriously

or populations don't respond well
to control measures

or it's not detected,

we could get situations --

I think Iran is probably
the closest one at the moment --

where there's been extensive
widespread transmission,

and by the time it's being responded to,

those infections are already in the system

and they are going to turn up
as cases and severe illness.

So I'm hoping we're not at that point,

but we've certainly got, at the moment,

potentially about 10 countries
on that trajectory

to have the same outlook as Italy.

So it's really crucial what happens
in the next couple of weeks.

CA: Is there a real chance
that quite a few countries

end up having, this year,

substantially more deaths from this virus
than from seasonal flu?

AK: I think for some countries
that is likely, yeah.

I think if control is not possible,

and we've seen it happen in China,

but that was really just an unprecedented
level of intervention.

It was really just changing
the social fabric.

I think people, many of us,
don't really appreciate, at a glance,

just what that means,

to reduce your interactions
to that extent.

I think many countries just simply
won't be able to manage that.

CA: It's almost a challenge
to democracies, isn't it --

"OK, show us what you can do
without that kind of draconian control."

If you don't like the thought of that,

come on, citizens, step up,
show us what you're capable of,

show that you can be wise about this

and smart and self-disciplined,

and get ahead of the damn bug.

AK: Yeah.

CA: I mean, I'm not personally
superoptimistic about that,

because there's such conflicting messaging
coming out in so many different places,

and people don't like
to short-term sacrifice.

I mean, is there almost a case that --

I mean, what's your view

on whether the media has played
a helpful role here

or an unhelpful role?

Is it actually, in some ways, helpful

to, if anything, overstate
the concern, the fear,

and actually make people
panic a little bit?

AK: I think it's a really
tough balance to strike,

because of course, early on,
if you don't have cases,

if you don't have any evidence
of potential pressure,

it's very hard to get that message
and convince people to take it seriously

if you're over hyping it.

But equally, if you're waiting too long,

and saying it's not a concern yet,
we're OK for the moment,

a lot of people think it's just flu.

By the time it hits hard, as I've said,

you're going to have weeks
of an overburdened health system,

because even if you take interventions,

it's too late to control the infections
that have happened.

So I think it's a fine line

and my hope is there is
this ramp-up in messaging,

now people have these
tangible examples like Italy,

where they can see what's going to happen
if they don't take it seriously.

But certainly, of all
the diseases I've seen,

I think many of my colleagues
who are much older than me

and have memories of other outbreaks,

it's the scariest thing we've seen
in terms of the impact it could have,

and I think we need to respond to that.

CA: It's the scariest disease you've seen.

Wow.

I've got some questions for you
from my friends on Twitter.

Everyone is obviously
superexercised about this topic.

Hypothetically,

if everyone stayed home for three weeks,

would that effectively wipe this out?

Is there a way to socially
distance ourselves out of this?

AK: Yeah, I think in certain countries
with reasonably small household sizes,

I think average in the UK, US
is about two and a half,

so even if you had a round of infection
within the household,

that would probably stamp it out.

As a secondary benefit,

you may well stamp out
a few other infections too.

Measles only circulates in humans,

so you may have some knock-on effect,

if, of course, that were
ever to be possible.

CA: I mean, obviously that would be
a huge dent to the economy,

and this is in a way almost, like,
one of the underlying challenges here

is that you can't optimize public policy

for both economic health
and fighting a virus.

Like, those two things are,
to some extent, in conflict,

or at least, short-term
economic health and fighting a virus.

Those two things are in conflict, right?

And societies need to pick one.

AK: It is tough to convince
people of that balance,

the thing we always say
of pandemic planning

is it's cheap to put
this stuff in place now --

otherwise, you've got to pay for it later.

But unfortunately,
as we've seen with this,

that a lot of early money
for response wasn't there.

And it's only when it has an impact
and when it's going to get expensive

that people are happy to take
that cost on board, it seems.

CA: OK, some more Twitter questions.

Will the rising temperature
in coming weeks and months

slow down the COVID-19 spread?

AK: I haven't seen any convincing evidence

that there's that strong pattern
with temperature,

and we've seen it for other infections
that there is this seasonal pattern,

but I think the fact
we're getting widespread outbreaks

makes it hard to identify, and of course,

there's other things going on.

So even if one country doesn't have
as big an outbreak as another,

that's going to be influenced
by control measures,

by social behavior, by opportunities
and these things as well.

So it would be really reassuring
if this was the case,

but I don't think
we can say that just yet.

CA: Continuing from Twitter,

I mean, is there a standardized
global recommendation

for all countries

on how to do this?

And if not, why not?

AK: I think that's what
people are trying to piece together,

first in terms of what works.

It's only really in the last
sort of few weeks

we've got a sense that this thing
can be controllable

with this extent of interventions,

but of course, not all countries
can do what China have done,

some of these measures

incur a huge social, economic,
psychological burden

on populations.

And of course, there's the time limit.

In China, they've had six weeks,

it's tough to maintain that,

so we need to think of these tradeoffs

of all the things we can ask people to do,

what's going to have the most impact
on actually reducing the burden.

CA: Another question:

How did this happen
and is it likely to happen again?

AK: So it's likely that this originated
with the virus that was circling in bats

and then probably made its way
through another species

into humans somehow,

there's a lot of bits
of evidence around this,

there's not kind of single, clear story,

but even for SARS, it took several years

for genomics to piece together
the exact route that it happened.

But certainly, I think it's plausible
that it could happen again.

Nature is throwing out
these viruses constantly.

Many of them aren't
well-adapted to humans,

don't pick up,

you know, there may well have been
a virus like this a few years ago

that just happened to infect someone

who just didn't have any contacts
and didn't go any further.

I think we are going to face these things

and we need to think
about how can we get in early,

at the stage where we're talking
small numbers of cases,

and even something like this
is containable,

rather than the situation we've got now.

CA: It seems like
this isn't the first time

that a virus seems to have emerged
from, like, a wild meat market.

That's certainly how
it happens in the movies. (Laughs)

And I think China has already taken
some steps this time

to try to crack down on that.

I think that's potentially
quite a big deal for the future

if that can be properly maintained.

AK: It is, and we saw, for example,

the H7N9 avian flu,

over the last few years, in 2013,
it was a big emerging concern

and China made a very extensive response

in terms of changing
how they operate their markets

and vaccination of birds

and that seems
to have removed that threat.

So I think these measures can be effective
if they're identified early on.

CA: So talk about vaccinations.

That's the key measure, I guess,

to change that susceptibility
factor in your equation.

There's obviously a race on
to get these vaccinations out there,

there are some candidate
vaccinations there.

How do you see that playing out?

AK: I think there's certainly some
promising development happening,

but I think the timescales of these things

are really on the order
of maybe a year, 18 months

before these things be widely available.

Obviously, a vaccine has to go
through these stages of trials,

that takes time,
so even if by the end of the year,

we have something
which is viable and works,

we're still going to see a delay
before everyone can get ahold of it.

CA: So this really puzzles me, actually,

and I'd love to ask you
as a mathematician about this as well.

There are already several companies

believing that they have
plausible candidate vaccines.

As you say, the process
of testing takes forever.

Is there a case that we're not
thinking about this right

when we're looking at the way
that testing is done

and that the safety calculations are made?

Because it's one thing
if you're going to introduce

a brand new drug or something --

yes, you want to test to make sure
that there are no side effects,

and that can take a long time

by the time you've done all
the control trials and all the rest of it.

If there's a global emergency,

isn't there a case,

both mathematically and ethically,

that there should just be
a different calculation,

the question shouldn't be

"Is there any possible case
where this vaccine can do harm,"

the question surely should be,

"On the net probabilities,

isn't there a case
to roll this out at scale

to have a shot at nipping
this thing in the bud?"

I mean, what am I missing
in thinking that way?

AK: I mean, we do see that
in other situations,

for example, the Ebola vaccine in 2015

showed, within a few months,
very promising evidence

and interim results of the trial in humans

showed what seemed very high efficacy.

And even though
it hadn't been licensed fully,

it was employed for what is known
as compassionate use

in subsequent other outbreaks.

So there are these mechanisms

where vaccines can be
fast-tracked in this way.

But of course, we're currently
in a situation where we have no idea

if these things will do anything at all.

So I think we need
to accrue enough evidence

that it could have an impact,

but obviously, fast-track that
as much as possible.

CA: But the skeptic in me
still doesn't fully get this.

I don't understand

why there isn't more energy
behind bolder thinking on this.

Everyone seems, despite the overall risk,

incredibly risk-averse
about how to build the response to it.

AK: So with the caveat that,

yeah, there's a lot
of good questions on this,

and some of them are slightly
outside my warehouse,

but I agree that we need to do more
to get timescales out.

The example I always quote

is it takes us six months
to choose a seasonal flu strain

and get the vaccines out there to people.

We always have to try and predict ahead
which strains are going to be circulating.

And that's for something
we know how to make

and has been manufactured for a long time.

So there is definitely more
that needs to be done

to get these timescales shorter.

But I think we do have to balance that,

especially if we're exposing
large numbers of people to something

to make sure that we're confident and safe

and that it's going to have
some benefit, potentially.

CA: And so, finally,

Adam, I guess going into this --

There's another set of infectious things
happening around the world

at the same time,

which is ideas and the communication
around this thing.

They really are two very dynamic
interactive systems of infectiousness --

there's some very damaging
information out there.

Is it fair to think of this as battle
of credible knowledge and measures

against the bug,

and just bad information --

You know, part of what
we have to think about here

is how to suppress one set of things
and boost the other, actually,

turbocharge the other.

How should we think of this?

AK: I think we can definitely think of it
almost as competition for our attention,

and we see similarly, with diseases,

you have viruses competing
to infect susceptible hosts.

And I think we're now seeing,

I guess over the last few years
with fake news and misinformation

and the emergence of awareness,

more of a transition

to thinking about how do we
reduce that susceptibility

if we have people that can be
in these different states,

how can we try and preempt
better with information.

I think the challenge
for an outbreak is obviously,

early on, we have
very little good information,

and it's very easy for certainty
and confidence to fill that vacuum.

And so I think that is something --

I know platforms are working
on how can we get people exposed

to good information earlier,

so hopefully protect them
against other stuff.

CA: One of the big unknowns to me
in the year ahead --

let's say that the year ahead includes
many, many more weeks,

for many people,

of actually self-isolating.

Those of us who are lucky enough
to have jobs where you can do that.

You know, staying home.

By the way, the whole injustice
of this situation,

where so many people can't do that
and continue to make a living,

is, I'm sure, going to be
a huge deal in the year ahead

and if it turns out that death rates
are much higher in the latter group

than in the former group,

and especially in a country like the US,

where the latter group
doesn't even have proper health insurance

and so forth.

That feels like right there,
that could just become a huge debate,

hopefully a huge source
of change at some level.

AK: I think that's an incredibly
important point,

because it's very easy --

I similarly have a job
where remote working is fairly easy,

and it's very easy to say
we should just stop social interactions,

but of course, that could have
an enormous impact on people

and the choices and the routine
that they can have.

And I think those do need
to be accounted for,

both now and what the effect
is going to look like

a few months down the line.

CA: When all's said and done,

is it fair to say that the world has
faced, actually, much graver problems

in the past,

that on any scenario,

it's highly likely that at some point
in the next 18 months, let's say,

a vaccine is there and starts
to get wide distribution,

that we will have learned
lots of other ways to manage this problem?

But at some point, next year probably,

the world will feel like
it's got on top of this

and can move on.

Is that likely to be it,

or is this more likely to be,
you know, it escapes,

it's now an endemic nightmare
that every year picks off far more people

than are picked off by the flu currently.

What are the likely ways forward,

just taking a slightly longer-term view?

AK: I think there's plausible ways
you could see all of those

potentially playing out.

I think the most plausible is probably
that we'll see very rapid growth this year

and lots of large outbreaks
that don't recur, necessarily.

But there is a potential
sequence of events

that could end up with these kind of
multiyear outbreaks in different places

and reemerging.

But I think it's likely we'll see

most transmission concentrated
in the next year or so.

And then, obviously,
if there's a vaccine available,

we can move past this,
and hopefully, learn from this.

I think a lot of the countries
that responded very strongly to this

were hit very hard by SARS.

Singapore, Hong Kong,
that really did leave an impact,

and I think that's something
they've drawn on very heavily

in their response to this.

CA: Alright.

So let's wrap up maybe by just
encouraging people

to channel their inner mathematician

and especially think
about the opportunities,

and the transmission probabilities
that they can help shift.

Just remind us of the top
three or four or five or six things

that you would love to see people doing.

AK: I think at the individual level,
just thinking a lot more

about your interactions
and your risk of infection

and obviously, what gets onto your hands

and once that gets onto your face,

and how do you potentially
create that risk for others.

I think also, in terms of interactions,

with things like handshakes
and maybe contacts you don't need to have.

You know, how can we get those down
as much as possible.

If each person's giving it
to two or three others,

how do we get that number
down to one, through our behavior.

And then it's likely that we'll need
some larger-scale interventions

in terms of gatherings, conferences,

other things where
there's a lot of opportunities

for transmission.

And really, I think that combination
of that individual level,

you know, if you're ill
or potentially you're going to get ill,

reducing that risk,

but then also us working together

to prevent it getting
into those groups who,

if it continues to be uncontrolled,

could really hit some people
very, very hard.

CA: Yeah, there's a lot of things

that we may need
to gently let go of for a bit.

And maybe try to reinvent
the best aspects of them.

Thank you so much.

If people want to keep up with you,

first of all, they can follow you
on Twitter, for example.

What's your Twitter handle?

AK: So AdamJKucharski, all one word.

CA: Adam, thank you so much
for your time, stay well.

AK: Thank you.

(Music)

CA: Associate professor
and TED Fellow Adam Kucharski.

We'd love to hear what you think
of this bonus episode.

Please tell us by rating
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or your favorite podcast app.

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We certainly read every one,

and truly appreciate your feedback.

(Music)

This week's show was produced
by Dan O'Donnell at Transmitter Media.

Our production manager
is Roxanne Hai Lash,

our fact-checker, Nicole Bode.

This episode was mixed by Sam Baer.

Our theme music
is by Allison Layton-Brown.

Special thanks to my colleague
Michelle Quint.

Thanks for listening to the TED Interview.

We'll be back later this spring

with a whole new season's worth
of deep dives with great minds.

I hope you'll enjoy them
whether or not life is back to normal.

I'm Chris Anderson,

thanks for listening and stay well.