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

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

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

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because we're in the middle of a pandemic,

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

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He is Adam Kucharski,

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an infectious diseases scientist

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who focuses on the mathematical
modeling of pandemics.

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He's an associate professor

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at the London School of Hygiene
and Tropical Medicine

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and a TED Fellow.

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(Music)

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

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is actually important for epidemics?

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Conversations, close physical contacts?

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What sort of data should we be collecting

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before an outbreak

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if we want to predict
how infection might spread?

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

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

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this pandemic, 
known technically as COVID-19,

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and informally as just the coronavirus,

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I find his thinking unbelievably helpful.

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

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A special callout to my friends on Twitter

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who offered up many
suggestions for questions.

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

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And what I hope this episode does

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is give us all a more nuanced way

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of thinking about how this pandemic
has unfolded so far,

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what might be to come

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and what we all collectively
can do about it.

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Let's dive in.

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(Music)

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Adam, welcome to the TED Interview.

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Adam Kucharski: Thank you.

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

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A lot of skeptical people's response --

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

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

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there's a relatively tiny number of cases.

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

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There are much bigger
problems in the world.

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Why are we making such a fuss about this?"

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

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We're talking about the mathematics
of exponential growth,

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fundamentally, right?

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AK: Exactly.

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

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and the level of transmission
we're dealing with.

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We call that the reproduction number,

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and conceptually, it's just,

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for each case you have, on average,

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how many others are they infecting?

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

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how much this growth
is going to look like.

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

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

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CA: So that reproduction number,

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the first thing to understand
is that any number above one

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means that this thing is going to grow.

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

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

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then each group of people infected

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

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And you will see the exponential effect,

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

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and if it's below one,

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

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CA: So that number two or higher,

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I think everyone here is maybe familiar
with the famous story

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of the chessboard and the grains of rice,

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

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for the first 10 or 15 squares
nothing much happens,

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

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

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(Laughs)

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Exponential growth is an incredible thing.

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And the small numbers now

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

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

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AK: Exactly.

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Obviously, if you continue
the exponential growth,

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you do sometimes get
these incredibly large,

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maybe implausibly large numbers.

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

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if the reproduction number is three,

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each person is infecting three on average.

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

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

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

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So by the end of that month,

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that one person could have generated,

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I think it works out at about 729 cases.

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So even in a month,

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just the scale of this thing
can really shoot up

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if it's not controlled.

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CA: And so certainly,

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

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certainly where the virus
is in the early stages

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of entering a country.

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You've given a model

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whereby we can much more clearly
understand this reproduction number,

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

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

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And in your thinking,

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you sort of break it down
into four components,

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which you call DOTS:

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Duration, Opportunities,

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Transmission probability

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and Susceptibility.

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And I think it would be
really helpful, Adam,

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for you to just explain each of these,

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because it's quite a simple equation

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that links those four things
to the actual reproduction number.

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So talk about them in turn.

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Duration, what does that mean?

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AK: Duration measures
how long someone is infectious for.

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If, for example,

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

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say, twice as long as someone else,

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then that's twice the length

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that they've got
to be spreading infection.

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

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compared with, say, flu
or with other pathogens?

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AK: It depends a little bit

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on what happens
when people are infectious,

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

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but potentially, we're looking
at around a week

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

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

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for that full week either, right?

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

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There's a period some way
into that incubation period

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where they start being infectious,

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

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

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Is that right?

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AK: No, we're getting more information.

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One of the signals we see in data

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that suggest that you may have
that early transmission going on

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

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So that seems to be around five days.

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That incubation period,
the time for symptoms to appear,

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is also about five days.

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So if you imagine that most people

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are only infecting others
when they're symptomatic,

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you'd have that incubation period

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

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So the fact that those values
seem to be similar,

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suggesting that some people
are transmitting

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

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CA: So almost implies that on average,

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people are infecting others

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as much before
they show symptoms as after.

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AK: Potentially.

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Obviously these are early data sets,

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

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either before they're
showing clear symptoms

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

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

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during that period.

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

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

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One of the reasons pandemic flu
is so hard to control

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and so feared as a threat

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

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

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

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

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

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It is ahead of us all the time,

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

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or what they're doing.

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

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How does someone infect someone else

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before they're even showing
symptoms themselves,

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

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

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and that's how infection happens.

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What is actually going on
for infection pre-symptoms?

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

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

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where someone sneezes
and a lot of virus gets out

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and potentially lots of susceptible
people can get exposed.

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So potentially, it could be quite early on

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that even if someone
has quite mild symptoms,

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maybe a bit of a cough,

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that's enough for some virus
to be getting out

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and particularly,

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some of the work that we've done

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trying to look at sort of
close gatherings,

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so very tight-knit meals,

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there was an example in a ski chalet --

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

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but enough virus is getting out
and somehow exposing others,

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we're still trying
to work out exactly how,

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but there's enough there
to cause some infection.

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

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

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something is going on?

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There was a German paper
published this week

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that seemed to suggest
that even really early on,

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

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and they have hundreds
of thousands of these viruses

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already reproducing there.

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Like, can someone just
literally just be breathing normally

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and there is some transmission
of virus out into the air

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that they don't even know about

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and is either infecting people directly

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or settling on surfaces, is that possible?

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

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how much that [unclear].

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As you said,

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there's evidence that you can have
people without symptoms

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and you can get virus out their throats.

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

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

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

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So it's really early data,

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

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

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

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

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

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AK: Potentially around a week,

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

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CA: And there are cases
of people testing positive

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

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

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

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AK: I think that's our working theory,

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that a lot of that infection
is happening early on.

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And we see that for a number
of respiratory infections,

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that when people obviously
become severely ill,

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their behavior is very different

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

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

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like the flu,

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is flu similar?

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What's the D number for flu?

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

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in terms of the period
that people are actively infectious.

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

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from one case to the next, actually.

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00:11:09,078 --> 00:11:11,514
Even a matter of
about three days, potentially,

247
00:11:11,538 --> 00:11:13,995
from one infection
to the person that they infect.

248
00:11:14,852 --> 00:11:17,958
And then at the other end of the scale,
you get things like STDs,

249
00:11:17,982 --> 00:11:20,678
where that duration could be
several months, potentially.

250
00:11:21,228 --> 00:11:22,379
CA: Right.

251
00:11:22,403 --> 00:11:26,958
OK, really nothing that unusual so far,
in terms of this particular virus.

252
00:11:26,982 --> 00:11:29,791
Let's look at the O, opportunity.

253
00:11:29,815 --> 00:11:30,973
What is that?

254
00:11:30,997 --> 00:11:34,437
AK: So opportunity is a measure
of how many chances

255
00:11:34,461 --> 00:11:37,217
the virus has to spread
through interactions

256
00:11:37,241 --> 00:11:38,709
while someone is infectious.

257
00:11:38,733 --> 00:11:41,058
So typically, it's a measure
of social behavior.

258
00:11:41,646 --> 00:11:45,014
On average, how many
social contacts do people make

259
00:11:45,038 --> 00:11:48,529
that create opportunities for transmission
while they're infectious.

260
00:11:48,553 --> 00:11:53,696
CA: So it's how many people
have you got close enough to

261
00:11:53,720 --> 00:11:56,095
during a day, during a given day,

262
00:11:56,119 --> 00:11:58,063
to have a chance of infecting them.

263
00:11:58,087 --> 00:12:00,990
And that number could be,

264
00:12:01,014 --> 00:12:04,611
if people aren't taking precautions
in a normal, sort of, urban setting,

265
00:12:04,635 --> 00:12:07,155
I mean, that could run
into the hundreds, presumably?

266
00:12:07,179 --> 00:12:08,751
AK: Potentially, for some people.

267
00:12:08,775 --> 00:12:11,734
We've done a number of studies
looking at that in recent years,

268
00:12:11,758 --> 00:12:13,992
and the average,
in terms of physical contacts,

269
00:12:14,016 --> 00:12:15,452
is about five people per day.

270
00:12:15,476 --> 00:12:17,633
Most people will have
conversation or contacts

271
00:12:17,657 --> 00:12:19,007
generally with about 10, 15,

272
00:12:19,031 --> 00:12:20,195
but obviously,

273
00:12:20,219 --> 00:12:22,518
between cultures,
we see quite a lot of variation

274
00:12:22,542 --> 00:12:25,101
in the level of physical greetings
that might happen.

275
00:12:25,125 --> 00:12:29,710
CA: And presumably, that number
again is no different for this virus

276
00:12:29,734 --> 00:12:30,900
than for any other.

277
00:12:30,924 --> 00:12:34,367
I mean, that's just a feature
of the lives that we live.

278
00:12:35,280 --> 00:12:37,049
AK: I think for this one,

279
00:12:37,073 --> 00:12:39,438
if it's driven through
these kind of interactions,

280
00:12:39,462 --> 00:12:42,367
and we've seen for flu,
for other respiratory infections,

281
00:12:42,391 --> 00:12:46,316
those kinds of fairly close contacts
and everyday physical interactions

282
00:12:46,340 --> 00:12:49,435
seem to be the ones
that are important for transmission.

283
00:12:49,459 --> 00:12:51,650
CA: Perhaps there is one difference.

284
00:12:51,674 --> 00:12:56,400
The fact that if you're
infectious pre-symptoms,

285
00:12:56,424 --> 00:12:59,790
perhaps that means that actually,
there are more opportunities here.

286
00:12:59,814 --> 00:13:02,784
This is part of the virus's
genius, as it were,

287
00:13:02,808 --> 00:13:06,609
that by not letting on
that it's inside someone,

288
00:13:06,633 --> 00:13:09,976
people continue to interact and go to work

289
00:13:10,000 --> 00:13:11,777
and take the subway and so forth,

290
00:13:11,801 --> 00:13:13,729
not even knowing that they're sick.

291
00:13:13,753 --> 00:13:14,916
AK: Exactly.

292
00:13:14,940 --> 00:13:16,293
And for something like flu,

293
00:13:16,317 --> 00:13:20,276
you see when people get ill, clearly,
their social contacts drop off.

294
00:13:20,300 --> 00:13:23,283
So to have a virus that can be infectious

295
00:13:23,307 --> 00:13:26,149
while people are going around
their everyday lives,

296
00:13:26,173 --> 00:13:28,712
really gives it an advantage
in terms of transmission.

297
00:13:28,736 --> 00:13:29,903
CA: In your modeling,

298
00:13:29,927 --> 00:13:34,755
do you actually have this
opportunities number higher than for flu?

299
00:13:35,406 --> 00:13:39,940
AK: So for the moment,
we're kind of using similar values,

300
00:13:39,964 --> 00:13:43,023
so we're trying to look at, for example,

301
00:13:43,047 --> 00:13:45,450
physical contacts
within different populations.

302
00:13:45,474 --> 00:13:47,879
But what we are doing is scaling the risk.

303
00:13:47,903 --> 00:13:50,212
So that's coming on to the T term.

304
00:13:50,236 --> 00:13:52,474
So that between each contact,

305
00:13:52,498 --> 00:13:55,347
what's the risk that a transmission
event will occur.

306
00:13:55,371 --> 00:13:57,620
CA: Alright, so let's go on
to this next number,

307
00:13:57,644 --> 00:14:00,299
the T, transmission probability.

308
00:14:00,323 --> 00:14:01,982
How do you define that?

309
00:14:02,006 --> 00:14:04,609
AK: So this measures the chance

310
00:14:04,633 --> 00:14:07,212
that, essentially,
the virus will get across

311
00:14:07,236 --> 00:14:10,110
during a particular opportunity
or a particular interaction.

312
00:14:10,134 --> 00:14:13,120
So you may well have
a conversation with somebody,

313
00:14:13,144 --> 00:14:16,573
but actually, you don't cough
or you don't sneeze

314
00:14:16,597 --> 00:14:19,295
or for some reason,
the virus doesn't actually get across

315
00:14:19,319 --> 00:14:20,969
and expose the other person.

316
00:14:20,993 --> 00:14:23,794
And so, for this virus, as I mentioned,

317
00:14:23,818 --> 00:14:25,929
say people are having
10 conversations a day,

318
00:14:25,953 --> 00:14:28,810
but we're not seeing infected people
infect 10 others a day.

319
00:14:28,834 --> 00:14:31,254
So it suggests that not all
of those opportunities

320
00:14:31,278 --> 00:14:33,710
are actually resulting
in the virus getting across.

321
00:14:34,540 --> 00:14:38,921
CA: But people say
that this is an infectious virus.

322
00:14:38,945 --> 00:14:42,452
Like, what is that transmission
probability number,

323
00:14:42,476 --> 00:14:44,407
again, compared with, say, the flu?

324
00:14:44,858 --> 00:14:48,617
AK: So, we did some analysis
looking at these very close gatherings.

325
00:14:48,641 --> 00:14:51,061
We looked at about 10
different case studies,

326
00:14:51,085 --> 00:14:54,889
and we found that about a third
of the contacts in those settings

327
00:14:54,913 --> 00:14:56,764
subsequently got infected

328
00:14:56,788 --> 00:14:59,145
in these early stages,
when people weren't aware.

329
00:14:59,169 --> 00:15:01,440
So if you had these, kind of,
big group meals,

330
00:15:01,464 --> 00:15:05,177
potentially, each contact
had about, a kind of, one in three chance

331
00:15:05,201 --> 00:15:06,558
of getting exposed.

332
00:15:06,582 --> 00:15:10,189
For seasonal flu,
that tends to be slightly lower,

333
00:15:10,213 --> 00:15:12,323
even within households
and close settings,

334
00:15:12,347 --> 00:15:14,482
you don't necessarily
get values that high.

335
00:15:14,506 --> 00:15:18,366
And even for something like SARS,
those values have, kind of --

336
00:15:18,390 --> 00:15:21,700
the risk per interaction you had

337
00:15:21,724 --> 00:15:24,466
was lower than what we seem
to be getting for coronavirus.

338
00:15:24,490 --> 00:15:25,934
Which intuitively makes sense,

339
00:15:25,958 --> 00:15:28,120
there must be a higher risk
per interaction

340
00:15:28,144 --> 00:15:30,096
if this thing is spreading so easily.

341
00:15:30,120 --> 00:15:31,270
CA: Hm.

342
00:15:32,350 --> 00:15:35,904
OK, and then the fourth letter of DOTS

343
00:15:35,928 --> 00:15:38,482
is S for susceptibility.

344
00:15:39,873 --> 00:15:41,045
What's that?

345
00:15:41,069 --> 00:15:45,591
AK: So that is a measure of the proportion
of the population who are susceptible.

346
00:15:45,615 --> 00:15:48,170
If you imagine you have
this interaction with someone,

347
00:15:48,194 --> 00:15:50,381
the virus gets across, it exposes them,

348
00:15:50,405 --> 00:15:52,350
but some people may have been vaccinated

349
00:15:52,374 --> 00:15:54,175
or otherwise have some immunity

350
00:15:54,199 --> 00:15:55,992
and not develop infection themselves

351
00:15:56,016 --> 00:15:57,776
and not be infectious to others.

352
00:15:57,800 --> 00:16:01,291
So we've got to account for this
potential proportion of people

353
00:16:01,315 --> 00:16:04,382
who are not actually
going to turn into cases themselves.

354
00:16:06,371 --> 00:16:11,701
CA: And obviously, there's no vaccine yet
for this coronavirus,

355
00:16:11,725 --> 00:16:16,312
nor is anyone, at least initially,
immune, as far as we know.

356
00:16:16,336 --> 00:16:20,360
So are you modeling that
susceptibility number pretty high,

357
00:16:20,384 --> 00:16:22,097
is that part of the issue here?

358
00:16:22,121 --> 00:16:23,728
AK: Yeah, I think the evidence

359
00:16:23,752 --> 00:16:26,577
is that this is going to fully
susceptible populations,

360
00:16:26,601 --> 00:16:29,141
and even in areas,
for example, like China,

361
00:16:29,165 --> 00:16:31,093
where there's been a lot of transmission

362
00:16:31,117 --> 00:16:33,268
but there's been very strong
control measures,

363
00:16:33,292 --> 00:16:35,339
we estimated that up to
the end of January,

364
00:16:35,363 --> 00:16:38,115
probably about 95 percent of Wuhan
are still susceptible.

365
00:16:38,139 --> 00:16:39,816
So there's been a lot of infection,

366
00:16:39,840 --> 00:16:43,056
but it hasn't really taken much
of that component,

367
00:16:43,080 --> 00:16:46,096
of the DOTS, of those four things
that drive transmission.

368
00:16:47,359 --> 00:16:49,371
CA: And so the way the mathematics works,

369
00:16:49,395 --> 00:16:55,219
I have to confess, amidst the stress
of this whole situation,

370
00:16:55,243 --> 00:16:58,387
the nerd in me kind of loves
the elegance of the mathematics here,

371
00:16:58,411 --> 00:17:00,822
because I'd never really
thought about it this way,

372
00:17:00,846 --> 00:17:03,546
but you basically just multiply
those numbers together

373
00:17:03,570 --> 00:17:05,509
to get the reproduction number.

374
00:17:05,533 --> 00:17:06,684
Is that right?

375
00:17:06,708 --> 00:17:07,890
AK: Exactly, yeah,

376
00:17:07,914 --> 00:17:10,843
you almost take the path
of the infection during transmission

377
00:17:10,867 --> 00:17:12,374
as you multiply those together,

378
00:17:12,398 --> 00:17:14,541
and that gives you
the number for that virus.

379
00:17:14,565 --> 00:17:17,781
CA: And so there's just
a total logic to that.

380
00:17:17,805 --> 00:17:20,567
It's the number of days,
duration that you're infectious,

381
00:17:20,591 --> 00:17:23,432
it's the number of people
you're seeing on average

382
00:17:23,456 --> 00:17:26,058
during those days
that you have a chance to infect.

383
00:17:27,188 --> 00:17:32,180
Then you multiply that
by the transmission probability,

384
00:17:32,204 --> 00:17:34,880
is virus getting into them, essentially,

385
00:17:34,904 --> 00:17:36,752
that's what you mean by crossing over.

386
00:17:36,776 --> 00:17:38,863
And then by the susceptibility number.

387
00:17:38,887 --> 00:17:41,948
By the way, what do you think
the susceptibility probability is

388
00:17:41,972 --> 00:17:43,312
for this case?

389
00:17:43,796 --> 00:17:47,050
AK: I think we have to assume
that it's near 100 percent

390
00:17:47,074 --> 00:17:49,110
in terms of spread, yeah.

391
00:17:50,133 --> 00:17:52,434
CA: Alright, you multiply
those numbers together,

392
00:17:52,458 --> 00:17:57,454
and right now, it looks like,
for this coronavirus,

393
00:17:57,478 --> 00:18:02,228
that you say two to three
is the most plausible current number,

394
00:18:02,530 --> 00:18:04,663
which implies very rapid growth.

395
00:18:05,141 --> 00:18:06,308
AK: Exactly.

396
00:18:06,332 --> 00:18:07,878
In these uncontrolled outbreaks,

397
00:18:07,902 --> 00:18:10,488
we're seeing now a number
of countries in this stage --

398
00:18:10,522 --> 00:18:13,533
you are going to get
this really rapid growth occurring.

399
00:18:13,804 --> 00:18:18,638
CA: And so how does
that two to three compare with flu?

400
00:18:18,662 --> 00:18:22,217
And I guess, there's seasonal flu,

401
00:18:22,241 --> 00:18:23,942
in the winter, when it's spreading,

402
00:18:23,966 --> 00:18:28,244
and at other times during the year
drops well below one

403
00:18:28,268 --> 00:18:30,403
as a reproduction number, right?

404
00:18:30,427 --> 00:18:33,093
But what is it during seasonal flu time?

405
00:18:33,831 --> 00:18:36,045
AK: During the early stage
when it's taking off

406
00:18:36,069 --> 00:18:37,596
at the start of the flu season,

407
00:18:37,620 --> 00:18:41,736
it's probably, we reckon,
somewhere between about maybe 1.2, 1.4.

408
00:18:41,760 --> 00:18:43,706
So it's not incredibly transmissible,

409
00:18:43,730 --> 00:18:47,735
if you imagine you do have some immunity
in your population from vaccination

410
00:18:47,759 --> 00:18:48,949
and from other things.

411
00:18:48,973 --> 00:18:50,560
So it can spread, it's above one,

412
00:18:50,584 --> 00:18:54,139
but it's not taking off, necessarily,
as quickly as the coronavirus is.

413
00:18:55,020 --> 00:18:58,268
CA: So I want to come back
to two of those elements,

414
00:18:58,292 --> 00:19:00,856
specifically opportunity
and transmission probability,

415
00:19:00,880 --> 00:19:05,553
because those seem to have the most
chance to actually do something

416
00:19:05,577 --> 00:19:07,387
about this infection rate.

417
00:19:07,411 --> 00:19:08,561
Before we go there,

418
00:19:08,585 --> 00:19:10,927
let's talk about another
key number on this,

419
00:19:10,951 --> 00:19:13,910
which is the fatality rate.

420
00:19:13,934 --> 00:19:15,609
First of all, could you define --

421
00:19:15,633 --> 00:19:18,410
I think there's two different versions
of the fatality rate

422
00:19:18,434 --> 00:19:20,442
that maybe confuse people.

423
00:19:20,466 --> 00:19:22,466
Could you define them?

424
00:19:22,490 --> 00:19:26,584
AK: So the one that we often talk about
is what's known as the case fatality rate,

425
00:19:26,608 --> 00:19:30,482
and that's of the proportion who show up
with symptoms as cases,

426
00:19:30,506 --> 00:19:33,559
what proportion of those
will subsequently be fatal.

427
00:19:34,177 --> 00:19:36,313
And we also sometimes talk
about what's known

428
00:19:36,337 --> 00:19:37,829
as the infection fatality rate,

429
00:19:37,853 --> 00:19:39,789
which is, of everyone who gets infected,

430
00:19:39,813 --> 00:19:41,027
regardless of symptoms,

431
00:19:41,051 --> 00:19:43,736
how many of those infections
will subsequently be fatal.

432
00:19:43,760 --> 00:19:45,866
But most of the values
we see kicking around

433
00:19:45,890 --> 00:19:49,032
are the case fatality rate, or the CFR,
as it's sometimes known.

434
00:19:49,963 --> 00:19:54,032
CA: And so what is
that fatality rate for this virus,

435
00:19:54,056 --> 00:19:57,264
and again, how does that compare
with other pathogens?

436
00:19:57,668 --> 00:20:00,482
AK: So there's a few numbers
that have been bouncing around.

437
00:20:00,506 --> 00:20:04,189
One of the challenges in real time
is you often don't see all of your cases,

438
00:20:04,213 --> 00:20:06,688
you have people symptomatic
not being reported.

439
00:20:06,712 --> 00:20:07,871
You also have a delay.

440
00:20:07,895 --> 00:20:09,236
If you imagine, for example,

441
00:20:09,260 --> 00:20:11,815
100 people turn up to a hospital
with coronavirus

442
00:20:11,839 --> 00:20:13,307
and none have died yet,

443
00:20:13,331 --> 00:20:15,680
that doesn't imply
that the fatality rate is zero,

444
00:20:15,704 --> 00:20:18,569
because you've got to wait to see
what might happen to them.

445
00:20:18,593 --> 00:20:21,482
So when you adjust for that
underreporting and delays,

446
00:20:21,506 --> 00:20:24,601
best estimate for the case fatality
is about one percent.

447
00:20:24,625 --> 00:20:26,729
So about one percent
of people with symptoms,

448
00:20:26,753 --> 00:20:28,133
on average,

449
00:20:28,157 --> 00:20:29,403
those outcomes are fatal.

450
00:20:29,427 --> 00:20:32,282
And that's probably about 10 times
worse than seasonal flu.

451
00:20:33,514 --> 00:20:37,174
CA: Yeah, so that's a scary
comparison right there,

452
00:20:37,198 --> 00:20:40,351
given how many people die of flu.

453
00:20:40,375 --> 00:20:44,844
So when the World Health Organization
mentioned a higher number,

454
00:20:44,868 --> 00:20:47,608
a little while back, of 3.4 percent,

455
00:20:47,632 --> 00:20:50,331
they were criticized a bit for that.

456
00:20:50,355 --> 00:20:54,102
Explain why that
might have been misleading

457
00:20:54,126 --> 00:20:57,173
and how to think about it
and adjust for that.

458
00:20:57,197 --> 00:21:00,300
AK: It's incredibly common that people
look at these raw numbers,

459
00:21:00,324 --> 00:21:03,238
they say, "How many deaths
are there so far, how many cases,"

460
00:21:03,262 --> 00:21:04,633
and they look at that ratio,

461
00:21:04,657 --> 00:21:08,141
and even a couple of weeks ago,
that number produced a two percent value.

462
00:21:08,165 --> 00:21:10,791
But if you imagine
you have this delay effect,

463
00:21:10,815 --> 00:21:13,061
then even if you stop all your cases,

464
00:21:13,085 --> 00:21:15,918
you will still have these kind of
fatal outcomes over time,

465
00:21:15,942 --> 00:21:17,688
so that number will creep up.

466
00:21:17,712 --> 00:21:21,617
This has occurred in every epidemic
from pandemic flu to Ebola,

467
00:21:21,641 --> 00:21:23,228
we see this again and again.

468
00:21:23,252 --> 00:21:26,982
And I made the point to a number of people
that this number is going to go up,

469
00:21:27,006 --> 00:21:28,536
because as China's cases slow,

470
00:21:28,560 --> 00:21:30,220
it will look like it's increasing,

471
00:21:30,244 --> 00:21:32,694
and that's just kind of
a statistical quirk.

472
00:21:32,718 --> 00:21:35,131
There's nothing really
kind of, behind the change,

473
00:21:35,155 --> 00:21:37,638
there's no mutations or anything going on.

474
00:21:38,972 --> 00:21:41,940
CA: If I have this right,
there are two effects going on.

475
00:21:41,964 --> 00:21:45,056
One is that the number of fatalities

476
00:21:45,080 --> 00:21:47,618
from the existing caseload will rise,

477
00:21:47,642 --> 00:21:51,634
which actually would boost
that 3.4 even higher.

478
00:21:51,658 --> 00:21:55,482
But then you have to offset that
against the fact that apparently,

479
00:21:55,506 --> 00:21:58,093
huge numbers of cases
have just gone undetected

480
00:21:58,117 --> 00:21:59,579
and that we haven't,

481
00:21:59,603 --> 00:22:02,025
due to bad testing,

482
00:22:02,049 --> 00:22:04,589
that the number of fatalities don't --

483
00:22:04,613 --> 00:22:07,956
They probably reflect
a much larger number of early cases.

484
00:22:07,980 --> 00:22:09,151
Is that it?

485
00:22:09,175 --> 00:22:10,349
AK: Exactly.

486
00:22:10,373 --> 00:22:12,445
So you have one thing
pulling the number up,

487
00:22:12,469 --> 00:22:13,926
and one thing pulling it down.

488
00:22:13,950 --> 00:22:16,243
And it means that on these
kind of early values,

489
00:22:16,267 --> 00:22:18,284
if you actually just adjust for the delay,

490
00:22:18,308 --> 00:22:20,411
and don't think
about these unreported cases,

491
00:22:20,435 --> 00:22:22,873
you start getting really
very scary numbers indeed.

492
00:22:22,897 --> 00:22:24,882
You get up to 20, 30 percent potentially,

493
00:22:24,906 --> 00:22:26,206
which really doesn't align

494
00:22:26,230 --> 00:22:29,191
with what we know
about this virus in general.

495
00:22:29,542 --> 00:22:30,874
CA: Alright.

496
00:22:31,621 --> 00:22:33,137
There's a lot more data in now.

497
00:22:33,161 --> 00:22:36,781
From your point of view,
you think the likely fatality rate,

498
00:22:36,805 --> 00:22:41,503
at least in the earlier stage
of an infection,

499
00:22:41,527 --> 00:22:43,687
is about two percent?

500
00:22:44,330 --> 00:22:45,481
AK: I think overall,

501
00:22:45,505 --> 00:22:48,806
I think we can put something probably
in the 0.5 to two percent range,

502
00:22:48,830 --> 00:22:51,644
and that's on a number
of different data sets.

503
00:22:51,668 --> 00:22:53,668
And that's for people who are symptomatic.

504
00:22:53,692 --> 00:22:56,736
I think on average, one percent
is a good number to work with.

505
00:22:56,760 --> 00:22:58,301
CA: OK, one percent,

506
00:22:58,325 --> 00:23:01,370
So flu is often quoted
as a tenth of a percent,

507
00:23:01,394 --> 00:23:06,513
so it's five to ten times or more
more dangerous than flu.

508
00:23:06,537 --> 00:23:10,006
And that danger is not symmetric
across age groups,

509
00:23:10,030 --> 00:23:11,395
as is well known.

510
00:23:11,419 --> 00:23:14,466
It primarily affects the elderly.

511
00:23:14,490 --> 00:23:16,815
AK: Yeah, we've seen
that one percent on average,

512
00:23:16,839 --> 00:23:19,458
but once you start getting
into the over 60s, over 70s,

513
00:23:19,482 --> 00:23:21,323
that number really starts to shoot up.

514
00:23:21,347 --> 00:23:24,109
I mean, we're estimating
potentially in these older groups,

515
00:23:24,133 --> 00:23:28,879
you're looking at maybe five,
ten percent fatality.

516
00:23:29,243 --> 00:23:31,013
And then of course, on top of that,

517
00:23:31,037 --> 00:23:33,656
you've got to add what
are going to be the severe cases

518
00:23:33,680 --> 00:23:35,950
and people are going to require
hospitalization.

519
00:23:35,974 --> 00:23:38,853
And those risks get very large
in the older groups indeed.

520
00:23:41,193 --> 00:23:43,296
CA: Adam, put these numbers
together for us.

521
00:23:43,320 --> 00:23:44,470
In your models,

522
00:23:44,494 --> 00:23:49,407
if you put together
a reproduction rate of two to three

523
00:23:49,431 --> 00:23:53,548
and a fatality rate
of 0.5 percent to one percent,

524
00:23:53,572 --> 00:23:56,062
and you run the simulation,

525
00:23:56,086 --> 00:23:57,620
what does it look like?

526
00:23:58,699 --> 00:24:01,517
AK: So if you have
this uncontrolled transmission,

527
00:24:01,541 --> 00:24:04,030
and you have this reproduction
number of two or three

528
00:24:04,054 --> 00:24:05,783
and you don't do anything about it,

529
00:24:05,807 --> 00:24:07,480
the only way the outbreak ends

530
00:24:07,504 --> 00:24:11,289
is enough people get it
and immunity builds up

531
00:24:11,313 --> 00:24:15,400
and the outbreak kind of ends on its own.

532
00:24:15,424 --> 00:24:16,587
And in that case,

533
00:24:16,611 --> 00:24:19,861
you would expect very large numbers
of the population to be infected.

534
00:24:19,885 --> 00:24:21,449
It's what we see, for example,

535
00:24:21,473 --> 00:24:24,019
with many other uncontained outbreaks,

536
00:24:24,043 --> 00:24:26,355
that it essentially burns
through the population,

537
00:24:26,379 --> 00:24:27,856
you get large numbers infected

538
00:24:27,880 --> 00:24:30,869
and with this kind of fatality rate
and hospitalization rate,

539
00:24:30,893 --> 00:24:35,022
that would really be hugely damaging
if that were to occur.

540
00:24:35,046 --> 00:24:37,252
Certainly at the country level,
we're seeing --

541
00:24:37,276 --> 00:24:39,133
Italy is a good example at the moment,

542
00:24:39,157 --> 00:24:41,768
that if you have that early
transmission is undetected,

543
00:24:41,792 --> 00:24:43,045
that rapid growth,

544
00:24:43,069 --> 00:24:47,260
you very quickly get to a situation
where your health systems are overwhelmed.

545
00:24:47,284 --> 00:24:50,895
I think one of the nastiest
aspects of this virus

546
00:24:50,919 --> 00:24:55,002
is that because you have the delay
between infection and symptoms

547
00:24:55,026 --> 00:24:57,279
and people showing up in health care,

548
00:24:57,303 --> 00:24:59,145
if your health system is overwhelmed,

549
00:24:59,169 --> 00:25:00,382
even on that day,

550
00:25:00,406 --> 00:25:02,430
if you completely stop transmission,

551
00:25:02,454 --> 00:25:05,328
you've got all of these people
who have already been exposed,

552
00:25:05,352 --> 00:25:08,260
so you're still going to have cases
and severe cases appearing

553
00:25:08,284 --> 00:25:10,180
for maybe another couple of weeks.

554
00:25:10,204 --> 00:25:13,149
So it's really this huge
accumulation of infection and burden

555
00:25:13,173 --> 00:25:16,144
that's coming through the system
on your population.

556
00:25:17,497 --> 00:25:19,561
CA: So there's another
key number, actually,

557
00:25:19,585 --> 00:25:24,098
is how does the total case number

558
00:25:24,122 --> 00:25:27,791
compare to the capacity
of a country's health system

559
00:25:27,815 --> 00:25:30,219
to process that number of cases.

560
00:25:30,846 --> 00:25:33,014
Presumably that issue
makes a huge difference

561
00:25:33,038 --> 00:25:34,235
to the fatality rate,

562
00:25:34,259 --> 00:25:37,037
the difference between people
coming in with severe illness

563
00:25:37,061 --> 00:25:40,410
and a health system that's able
to respond and one that's overwhelmed.

564
00:25:40,434 --> 00:25:43,363
The fatality rate is going to be
very different at that point.

565
00:25:43,387 --> 00:25:45,141
AK: If someone requires an ICU bed,

566
00:25:45,165 --> 00:25:47,816
that's a couple of weeks
they're going to require it for

567
00:25:47,840 --> 00:25:50,331
and you've got more cases
coming through the system,

568
00:25:50,355 --> 00:25:52,045
so it very quickly gets very tough.

569
00:25:52,069 --> 00:25:54,942
CA: So talk about the difference
between containment

570
00:25:54,966 --> 00:25:56,529
and mitigation.

571
00:25:56,553 --> 00:25:59,895
These are different terms
that we're hearing a lot about.

572
00:25:59,919 --> 00:26:06,110
In the early stages of the virus,
governments are focused on containment.

573
00:26:06,134 --> 00:26:07,737
What does that mean?

574
00:26:07,761 --> 00:26:11,467
AK: Containment is this idea
that you can focus your effort on control

575
00:26:11,491 --> 00:26:13,737
very much on the cases and their contacts.

576
00:26:13,761 --> 00:26:16,467
So you're not causing disruption
to the wider population,

577
00:26:16,491 --> 00:26:19,167
you have a case that comes in,
you isolate them,

578
00:26:19,191 --> 00:26:21,459
you work out who they've come
into contact with,

579
00:26:21,483 --> 00:26:24,550
who's potentially these
opportunities for exposure,

580
00:26:24,574 --> 00:26:26,537
and then you can follow up those people,

581
00:26:26,561 --> 00:26:30,133
maybe quarantine them to make sure
that no further transmission happens.

582
00:26:30,157 --> 00:26:32,680
So it's a very focused, targeted method,

583
00:26:32,704 --> 00:26:35,304
and for SARS, it worked remarkably well.

584
00:26:35,982 --> 00:26:37,823
But I think for this infection,

585
00:26:37,847 --> 00:26:41,397
because some cases are going to be missed,
they're going to be undetected,

586
00:26:41,421 --> 00:26:44,627
you've really got to be capturing
a large chunk of people at risk.

587
00:26:44,651 --> 00:26:46,153
If a few slip through the net,

588
00:26:46,177 --> 00:26:48,356
potentially, you're going
to get an outbreak.

589
00:26:48,380 --> 00:26:49,749
CA: Are there any countries

590
00:26:49,773 --> 00:26:51,855
that have been able
to employ this strategy

591
00:26:51,879 --> 00:26:55,188
and effectively contain the virus?

592
00:26:55,212 --> 00:26:58,760
AK: So Singapore have been doing
a really remarkable job of this

593
00:26:58,784 --> 00:27:00,324
for the last six weeks or so.

594
00:27:00,744 --> 00:27:03,157
So as well as some wider measures,

595
00:27:03,181 --> 00:27:04,903
they've been working incredibly hard

596
00:27:04,927 --> 00:27:07,482
to trace people
who have come into contact.

597
00:27:08,117 --> 00:27:09,585
Looking at CCTV,

598
00:27:09,609 --> 00:27:12,569
going through to find out
which taxi someone might have gotten,

599
00:27:12,593 --> 00:27:13,767
who might be at risk --

600
00:27:13,791 --> 00:27:15,450
really, really thorough follow up.

601
00:27:15,474 --> 00:27:18,656
And for about six weeks,
that has kept a lid on transmission.

602
00:27:19,355 --> 00:27:20,529
CA: So that's amazing.

603
00:27:20,553 --> 00:27:22,974
So someone comes into the country,

604
00:27:22,998 --> 00:27:24,553
they test positive --

605
00:27:24,577 --> 00:27:27,133
they go to work, and with a massive team,

606
00:27:27,157 --> 00:27:29,268
and trace everything,

607
00:27:29,292 --> 00:27:31,133
to the level of actually saying,

608
00:27:31,157 --> 00:27:33,157
"Oh, you don't know what taxi you went in?

609
00:27:33,181 --> 00:27:34,664
Let us find that out for you."

610
00:27:34,688 --> 00:27:36,926
And presumably,
when they find the taxi driver,

611
00:27:36,950 --> 00:27:40,344
they then have to try and figure out
everyone else who was in that taxi?

612
00:27:40,368 --> 00:27:43,463
AK: So they will focus on
close contacts of people most at risk,

613
00:27:43,487 --> 00:27:47,327
but they're really minimizing the chance
that anyone slips through the net.

614
00:27:47,925 --> 00:27:51,680
CA: But even in Singapore,
if I'm not mistaken,

615
00:27:51,704 --> 00:27:54,054
numbers started to trend
back down to zero,

616
00:27:54,078 --> 00:27:56,522
but I think recently,
they've picked up again a bit.

617
00:27:56,546 --> 00:27:58,435
It's still unclear

618
00:27:58,459 --> 00:28:01,617
whether they will actually
be able to sustain containment.

619
00:28:01,641 --> 00:28:02,801
AK: Exactly.

620
00:28:02,825 --> 00:28:05,029
If we talk in terms
of the reproduction number,

621
00:28:05,053 --> 00:28:07,443
we saw it dipped to maybe 0.8, 0.9,

622
00:28:07,467 --> 00:28:09,402
so under that crucial value of one.

623
00:28:10,201 --> 00:28:11,550
But in the last week or two,

624
00:28:11,574 --> 00:28:14,876
it does seem to be taking up
and they're getting more cases appearing.

625
00:28:14,900 --> 00:28:16,138
I think a lot of it is,

626
00:28:16,162 --> 00:28:18,130
even if they are containing it,

627
00:28:18,154 --> 00:28:20,065
the world is experiencing outbreaks

628
00:28:20,089 --> 00:28:22,157
and just keeps throwing
sparks of infection,

629
00:28:22,181 --> 00:28:23,760
and it becomes harder and harder

630
00:28:23,784 --> 00:28:26,522
with that level of intensive effort
to stamp them all out.

631
00:28:26,546 --> 00:28:32,349
(Music)

632
00:28:47,712 --> 00:28:49,578
CA: In the case of this virus,

633
00:28:49,602 --> 00:28:52,688
you know, there was warning
to most countries in the world

634
00:28:52,712 --> 00:28:54,172
that this thing was happening.

635
00:28:54,196 --> 00:28:58,380
The news out of China
very quickly became very bleak

636
00:28:58,404 --> 00:29:01,118
and people had time to prepare.

637
00:29:01,142 --> 00:29:05,630
I mean, what would an ideal
preparation look like

638
00:29:05,654 --> 00:29:07,805
if you know that something
like this is coming

639
00:29:07,829 --> 00:29:09,832
and you know that there's
a lot on the line

640
00:29:09,856 --> 00:29:12,807
if you can successfully contain it
before it really escapes?

641
00:29:13,291 --> 00:29:16,022
AK: I think two things
would make a really big difference.

642
00:29:16,046 --> 00:29:20,767
One is having as thorough follow up
and detection as possible.

643
00:29:20,791 --> 00:29:22,416
We've done some modeling analyses,

644
00:29:22,440 --> 00:29:25,529
looking at how effective
that kind of early containment is.

645
00:29:25,553 --> 00:29:29,671
And it can be, if you're identifying
maybe 70 or 80 percent

646
00:29:29,695 --> 00:29:32,799
of the people who might have
come into contact.

647
00:29:32,823 --> 00:29:36,348
But if you're not detecting
those cases coming in,

648
00:29:36,372 --> 00:29:38,368
if you're not detecting their contacts --

649
00:29:38,392 --> 00:29:41,948
and a lot of the early focus, for example,
was on travel history to China,

650
00:29:41,972 --> 00:29:44,669
and then it became clear
that the situation was changing,

651
00:29:44,693 --> 00:29:47,852
but because you were relying on that
as your definition of a case,

652
00:29:47,876 --> 00:29:50,860
it meant a lot of maybe other cases
that matched the definition

653
00:29:50,884 --> 00:29:52,051
weren't being tested

654
00:29:52,075 --> 00:29:54,617
because they didn't seem
to be potentially at risk.

655
00:29:54,641 --> 00:29:59,227
CA: So I mean, if you know
that early detection is key to this,

656
00:29:59,251 --> 00:30:01,131
an essential early measure, I guess,

657
00:30:01,155 --> 00:30:06,268
would be to rapidly ensure
that you had enough tests available,

658
00:30:06,292 --> 00:30:07,990
and where needed,

659
00:30:08,014 --> 00:30:09,783
so that you could respond,

660
00:30:09,807 --> 00:30:13,720
be ready to swing into action
as soon as someone was detected,

661
00:30:13,744 --> 00:30:19,029
you then have to very quickly,
I guess, test their contacts and so forth,

662
00:30:19,053 --> 00:30:21,910
to have a chance
of keeping this under control.

663
00:30:21,934 --> 00:30:23,220
AK: Exactly.

664
00:30:23,244 --> 00:30:26,410
In my line of work, we say
there's value in a negative test,

665
00:30:26,434 --> 00:30:29,760
because it shows that you're looking
for something and it's not there.

666
00:30:29,784 --> 00:30:33,283
And so I think having
small numbers of people tested

667
00:30:33,307 --> 00:30:36,315
doesn't give you confidence
that you're not missing infections,

668
00:30:36,339 --> 00:30:39,308
whereas if you are doing
really thorough follow up on contacts,

669
00:30:39,332 --> 00:30:41,316
we've seen countries even like Korea now,

670
00:30:41,340 --> 00:30:42,901
huge numbers of people tested.

671
00:30:42,925 --> 00:30:45,013
So although there are still
cases appearing,

672
00:30:45,037 --> 00:30:46,426
it gives them more confidence

673
00:30:46,450 --> 00:30:49,241
that they have some sense
of where those infections are.

674
00:30:49,265 --> 00:30:51,963
CA: I mean, you're in the UK right now,

675
00:30:51,987 --> 00:30:54,767
I'm in the US.

676
00:30:54,791 --> 00:30:58,368
How likely is it that the UK
is going to be able to contain,

677
00:30:58,392 --> 00:31:02,194
how likely is it that the US
is going to be able to contain this?

678
00:31:03,162 --> 00:31:06,625
AK: I think it's pretty
unlikely in both cases.

679
00:31:06,649 --> 00:31:10,051
I think the UK is going to have
to introduce some additional measures.

680
00:31:10,075 --> 00:31:12,410
I think when that happens
obviously depends a bit

681
00:31:12,434 --> 00:31:13,656
on the current situation,

682
00:31:13,680 --> 00:31:16,013
but we've tested almost 30,000 people now.

683
00:31:17,403 --> 00:31:21,735
Frankly, I think the US
may well be moving beyond that point,

684
00:31:21,759 --> 00:31:24,688
given how much evidence
of extensive transmission that has,

685
00:31:24,712 --> 00:31:27,808
and I think without clear ideas
of how much infection there is

686
00:31:27,832 --> 00:31:30,103
and that level of testing,

687
00:31:30,127 --> 00:31:33,516
it's quite hard to actually see
what the picture currently is in the US.

688
00:31:35,308 --> 00:31:39,028
CA: I mean, I definitely don't want to get
too political about this,

689
00:31:39,052 --> 00:31:40,894
but I mean, does this strike you as --

690
00:31:40,918 --> 00:31:43,441
you just said that the UK
has tested 30,000 people --

691
00:31:43,465 --> 00:31:45,964
the US is five or six times bigger

692
00:31:45,988 --> 00:31:49,181
and I think the total number
of tests here is five or six thousand,

693
00:31:49,205 --> 00:31:50,458
or it was a few days ago.

694
00:31:50,482 --> 00:31:52,673
Does that strike you as bizarre?

695
00:31:52,697 --> 00:31:56,644
I don't understand, honestly,
how that happened in an educated country

696
00:31:56,668 --> 00:31:59,460
that has so much knowledge
about infectious diseases.

697
00:32:00,173 --> 00:32:01,340
AK: It does,

698
00:32:01,364 --> 00:32:04,542
and I think there's obviously
a number of factors playing in there,

699
00:32:04,566 --> 00:32:05,891
logistics and so on,

700
00:32:05,915 --> 00:32:08,109
but there has been that period of warning

701
00:32:08,133 --> 00:32:10,212
that this is a threat
and this is coming in.

702
00:32:10,236 --> 00:32:13,561
And I think countries need to make sure
that they've got the capacity

703
00:32:13,585 --> 00:32:16,697
to really do as much detection as they can
in those early stages,

704
00:32:16,721 --> 00:32:18,871
because that's where
you're going to catch it

705
00:32:18,895 --> 00:32:22,450
and that's where you're going to have
a better chance of containing it.

706
00:32:22,474 --> 00:32:24,752
CA: OK, so if you fail to contain,

707
00:32:24,776 --> 00:32:28,090
then you have to move
to some kind of mitigation strategy.

708
00:32:28,114 --> 00:32:31,495
So what comes into play there?

709
00:32:31,519 --> 00:32:34,574
And I think I almost want
to bring that back

710
00:32:34,598 --> 00:32:38,419
to two of your DOTS factors,

711
00:32:38,443 --> 00:32:41,443
opportunity and transmission probability,

712
00:32:41,467 --> 00:32:43,720
because it seems like
the virus is what it is,

713
00:32:43,744 --> 00:32:46,506
the actual duration when someone
is potentially infectious,

714
00:32:46,530 --> 00:32:47,764
we can't do much about.

715
00:32:47,788 --> 00:32:49,879
The susceptibility side,

716
00:32:49,903 --> 00:32:52,505
we can't do much about
until there's a vaccine.

717
00:32:52,529 --> 00:32:54,760
We could maybe talk about that in a bit.

718
00:32:54,784 --> 00:32:58,451
But the middle two of opportunity
and transmission probability,

719
00:32:58,475 --> 00:32:59,871
we can do something about.

720
00:32:59,895 --> 00:33:03,418
Do you want to maybe talk
about those in turn,

721
00:33:03,442 --> 00:33:04,665
of what that looks like,

722
00:33:04,689 --> 00:33:09,273
how would you build a mitigation strategy?

723
00:33:09,297 --> 00:33:11,623
I mean, first of all,
thinking about opportunity,

724
00:33:11,647 --> 00:33:13,781
how do you reduce
the number of opportunities

725
00:33:13,805 --> 00:33:15,072
to pass on the bug?

726
00:33:15,885 --> 00:33:17,643
AK: And so I think in that respect,

727
00:33:17,667 --> 00:33:21,328
it would be about massive changes
in our social interactions.

728
00:33:21,352 --> 00:33:23,877
And if you think in terms
of the reproduction number

729
00:33:23,901 --> 00:33:26,068
of being about two or three,

730
00:33:26,092 --> 00:33:27,473
to get that number below one,

731
00:33:27,497 --> 00:33:30,763
you've really got to cut
some aspect of that transmission

732
00:33:30,787 --> 00:33:32,192
in half or in two thirds,

733
00:33:32,216 --> 00:33:33,620
to get that below one.

734
00:33:34,017 --> 00:33:35,747
And so that would require,

735
00:33:35,771 --> 00:33:38,128
of the opportunities
that could spread the virus

736
00:33:38,152 --> 00:33:40,101
are these kind of close contacts.

737
00:33:40,125 --> 00:33:42,379
Everybody in the population, on average,

738
00:33:42,403 --> 00:33:45,323
will be needing to reduce
those interactions

739
00:33:45,347 --> 00:33:47,966
potentially by two thirds
to bring it under control.

740
00:33:47,990 --> 00:33:50,704
That might be through working from home,

741
00:33:50,728 --> 00:33:52,735
from changing lifestyle

742
00:33:52,759 --> 00:33:56,102
and kind of where you go
in crowded places and dinners.

743
00:33:56,653 --> 00:33:59,490
And of course, these measures,
things like school closures,

744
00:33:59,514 --> 00:34:01,577
and other things
that just attempt to reduce

745
00:34:01,601 --> 00:34:03,386
the social mixing of a population.

746
00:34:03,712 --> 00:34:06,513
CA: Well, actually, talk to me more
about school closures,

747
00:34:06,537 --> 00:34:08,934
because that, if I remember,

748
00:34:08,958 --> 00:34:15,307
often in past pandemics has been cited
as an absolutely key measure,

749
00:34:15,331 --> 00:34:18,597
that schools represent this sort of
coming together of people,

750
00:34:18,621 --> 00:34:21,454
children are often --

751
00:34:21,478 --> 00:34:23,451
certainly when it comes to flu and colds,

752
00:34:23,475 --> 00:34:25,545
they're carriers.

753
00:34:25,569 --> 00:34:27,188
But on this case,

754
00:34:27,212 --> 00:34:31,093
children don't seem to be getting sick
from this particular virus,

755
00:34:31,117 --> 00:34:33,958
or at least very few of them are.

756
00:34:34,371 --> 00:34:39,301
Do we know whether they
can still be infectious?

757
00:34:39,325 --> 00:34:41,896
They can be the unintended carriers of it.

758
00:34:41,920 --> 00:34:45,342
Or actually, is there evidence
that school closures

759
00:34:45,366 --> 00:34:48,659
may not be as important
in this instance as it is in others?

760
00:34:49,093 --> 00:34:51,156
AK: So that point
on what role children play

761
00:34:51,180 --> 00:34:52,339
is a crucial one,

762
00:34:52,363 --> 00:34:54,680
and there's still not
a good evidence base there.

763
00:34:54,704 --> 00:34:56,942
From following up of contacts of cases,

764
00:34:56,966 --> 00:34:59,617
there's now evidence
that children are getting infected,

765
00:34:59,641 --> 00:35:01,974
so when you're testing,
they are getting exposed,

766
00:35:01,998 --> 00:35:05,629
it's not that somehow they're just
not getting the infection at all,

767
00:35:05,653 --> 00:35:09,117
but as you said, they're not showing
symptoms in the same way,

768
00:35:09,141 --> 00:35:11,445
and particularly for flu,

769
00:35:11,469 --> 00:35:14,201
when we see the implications
of school closures,

770
00:35:14,225 --> 00:35:17,120
even in the UK in 2009 during swine flu,

771
00:35:17,144 --> 00:35:19,954
there was a dip in the outbreak
during the school holidays,

772
00:35:19,978 --> 00:35:21,883
you could see it on the epidemic curve,

773
00:35:21,907 --> 00:35:25,319
it kind of comes back down in the summer
and goes back up in the autumn.

774
00:35:25,343 --> 00:35:28,403
But of course, in 2009,
there was some immunity in older groups.

775
00:35:28,427 --> 00:35:31,537
That kind of shifted more the transmission
onto the younger ones.

776
00:35:31,561 --> 00:35:34,832
So I think it's really something
we're trying to work to understand.

777
00:35:34,856 --> 00:35:37,733
Obviously, it will reduce interactions,
with school closures,

778
00:35:37,757 --> 00:35:39,749
but then there's knock-on social effects,

779
00:35:39,773 --> 00:35:41,876
there's potential
knock-on changes in mixing,

780
00:35:41,900 --> 00:35:45,743
maybe grandparents and their role
in terms of alternative carers

781
00:35:45,767 --> 00:35:47,109
if parents have to work.

782
00:35:47,133 --> 00:35:50,720
So I think there's a lot of pieces
that need to be considered.

783
00:35:52,101 --> 00:35:56,865
CA: I mean, based on all of the different
pieces of evidence you've seen,

784
00:35:56,889 --> 00:35:58,166
if it were down to you,

785
00:35:58,190 --> 00:36:01,579
would you be recommending
that most countries at this point

786
00:36:01,603 --> 00:36:05,878
do look hard at extensive school closures
as a precautionary measure,

787
00:36:05,902 --> 00:36:09,458
that it's just worth it to do that

788
00:36:09,482 --> 00:36:14,504
as a sort of painful two,
three, four, five-month strategy?

789
00:36:14,528 --> 00:36:16,163
What would you recommend?

790
00:36:16,187 --> 00:36:17,505
AK: I think the key thing,

791
00:36:17,529 --> 00:36:20,684
given the age distribution of risk
and the severity in older groups

792
00:36:20,708 --> 00:36:25,489
is reduce interactions that bring
the infection into those groups.

793
00:36:25,513 --> 00:36:28,975
And then amongst everyone else,
reduce interactions as much as possible.

794
00:36:28,999 --> 00:36:30,602
I think the key thing is

795
00:36:30,626 --> 00:36:34,473
we've got so much of the disease burden
in the kind of 60-plus group

796
00:36:34,497 --> 00:36:37,990
that it's not just about
everyone trying to avoid

797
00:36:38,014 --> 00:36:39,180
everyone's interactions,

798
00:36:39,204 --> 00:36:40,680
but it's the kind of behaviors

799
00:36:40,704 --> 00:36:43,147
that would drive infections
into those groups.

800
00:36:44,448 --> 00:36:47,264
CA: Does that mean
that people should think twice

801
00:36:47,288 --> 00:36:50,464
before, I don't know, visiting a loved one

802
00:36:50,488 --> 00:36:55,454
in an old people's home
or in a residential facility?

803
00:36:55,478 --> 00:36:59,281
Like that, we should just pay
super special attention to that,

804
00:36:59,305 --> 00:37:02,155
should all these facilities
be taking great care

805
00:37:02,179 --> 00:37:03,630
about who they admit,

806
00:37:03,654 --> 00:37:06,910
taking temperature and checking
for symptoms or something like that?

807
00:37:06,934 --> 00:37:09,832
AK: I think those measures
definitely need to be considered.

808
00:37:09,856 --> 00:37:11,387
In the UK, we're getting plans

809
00:37:11,411 --> 00:37:13,863
for potentially what's known
as a cocooning strategy

810
00:37:13,887 --> 00:37:15,172
for these older groups

811
00:37:15,196 --> 00:37:17,810
that we can really try
and seal off interactions

812
00:37:17,834 --> 00:37:19,212
as much as possible

813
00:37:19,236 --> 00:37:21,847
from people who might
be bringing infection in.

814
00:37:22,202 --> 00:37:24,879
And ultimately, because as you said,

815
00:37:24,903 --> 00:37:27,371
we can't target these other
aspects of transmission,

816
00:37:27,395 --> 00:37:30,331
it is just reducing the risk
of exposure in these groups,

817
00:37:30,355 --> 00:37:34,099
and so I think anything
at the individual level you can do

818
00:37:34,123 --> 00:37:36,321
to get people reducing their risk,

819
00:37:36,345 --> 00:37:39,385
if either they're elderly
or in other risk groups,

820
00:37:39,409 --> 00:37:40,561
I think is crucial.

821
00:37:40,585 --> 00:37:43,020
And I think more at the general level

822
00:37:43,044 --> 00:37:47,077
those kind of more large-scale measures
can help reduce interactions overall,

823
00:37:47,101 --> 00:37:49,696
but I think if those
reductions are happening,

824
00:37:49,720 --> 00:37:50,955
and not reducing the risk

825
00:37:50,979 --> 00:37:53,244
for people who are going
to get severe disease,

826
00:37:53,268 --> 00:37:56,912
then you're still going to get
this really remarkably severe burden.

827
00:37:58,107 --> 00:38:03,361
CA: I mean, do people have to almost
apply this double lens

828
00:38:03,385 --> 00:38:04,901
as they think about this stuff?

829
00:38:04,925 --> 00:38:07,292
There's the risk to you
as you go about your life,

830
00:38:07,316 --> 00:38:09,348
of you catching this bug.

831
00:38:09,657 --> 00:38:12,839
But there's also the risk
of you being, unintentionally, a carrier

832
00:38:12,863 --> 00:38:15,897
to someone who would suffer
much more than you might.

833
00:38:15,921 --> 00:38:19,569
And that both those things
have to be top of mind right now.

834
00:38:19,593 --> 00:38:22,204
AK: Yeah, and it's not just
whose hand you shake,

835
00:38:22,228 --> 00:38:24,434
it's whose hand that person
goes on to shake.

836
00:38:24,458 --> 00:38:27,323
And I think we need to think
about these second-degree steps,

837
00:38:27,347 --> 00:38:29,529
that you might think you have low risk,

838
00:38:29,553 --> 00:38:31,331
and you're in a younger group,

839
00:38:31,355 --> 00:38:34,450
but you're often going to be
a very short step away

840
00:38:34,474 --> 00:38:37,077
from someone who is going to get hit
very hard by this.

841
00:38:37,101 --> 00:38:39,744
And I think we really need
to be socially minded

842
00:38:39,768 --> 00:38:43,082
and think this could be quite dramatic
in terms of change of behavior,

843
00:38:43,106 --> 00:38:44,765
but it needs to be

844
00:38:44,789 --> 00:38:47,238
to reduce the impact
that we're potentially facing.

845
00:38:48,556 --> 00:38:51,135
CA: So the opportunity
number, we bring down

846
00:38:51,159 --> 00:38:53,805
by just reducing the number
of physical contacts we have

847
00:38:53,829 --> 00:38:55,532
with other people.

848
00:38:55,556 --> 00:38:58,810
And I guess the transmission
probability number,

849
00:38:58,834 --> 00:39:01,334
how do we bring that down?

850
00:39:01,358 --> 00:39:03,188
That impacts how we interact.

851
00:39:03,212 --> 00:39:04,558
You mentioned hand-shaking,

852
00:39:04,582 --> 00:39:06,876
I'm guessing you're going to say
no handshaking.

853
00:39:06,900 --> 00:39:08,910
AK: Yeah, so changes like that.

854
00:39:08,934 --> 00:39:10,341
I mean, another one, I think,

855
00:39:10,365 --> 00:39:12,026
handwashing operates in a way

856
00:39:12,050 --> 00:39:16,363
that we might be still be doing
activities that we've previously done,

857
00:39:16,387 --> 00:39:20,601
but handwashing reduces the chance
that from one interaction to another,

858
00:39:20,625 --> 00:39:22,172
we might be spreading infection,

859
00:39:22,196 --> 00:39:23,633
so it's all of these measures

860
00:39:23,657 --> 00:39:26,338
that mean that even
if we're having these exposures,

861
00:39:26,362 --> 00:39:29,655
we're taking additional steps
to avoid any transmission happening.

862
00:39:30,346 --> 00:39:32,822
CA: I still think most people
don't fully understand

863
00:39:32,846 --> 00:39:34,886
or don't have a clear model of the pathway

864
00:39:34,910 --> 00:39:38,886
by which thins thing spreads.

865
00:39:38,910 --> 00:39:40,879
So you think definitely people understand

866
00:39:40,903 --> 00:39:42,664
that you don't breathe in

867
00:39:42,688 --> 00:39:46,941
the water droplets of someone
who has just coughed or sneezed.

868
00:39:46,965 --> 00:39:49,117
So how does it spread?

869
00:39:49,141 --> 00:39:51,403
It gets onto surfaces. How?

870
00:39:51,427 --> 00:39:54,586
Do people just breathe out
and it goes on from people who are sick,

871
00:39:54,610 --> 00:39:56,784
they touch their mouth
or something like that,

872
00:39:56,808 --> 00:39:59,110
and then touch a surface
and it gets on that way?

873
00:39:59,134 --> 00:40:01,022
How does it actually get onto surfaces?

874
00:40:01,046 --> 00:40:03,864
AK: I think a lot of it would be
that you cough in your hand

875
00:40:03,888 --> 00:40:05,497
and it ends up on a surface.

876
00:40:05,871 --> 00:40:09,565
But I think the challenge, obviously,
is untangling these questions

877
00:40:09,589 --> 00:40:10,947
of how transmission happens.

878
00:40:10,971 --> 00:40:12,789
You have transmission in a household,

879
00:40:12,813 --> 00:40:15,403
and is it that someone coughed
and it got on a surface,

880
00:40:15,427 --> 00:40:17,332
is it direct contact, is it a handshake,

881
00:40:17,356 --> 00:40:18,779
and even for things like flu,

882
00:40:18,803 --> 00:40:22,014
that's something that we work
quite hard to try and unpick,

883
00:40:22,038 --> 00:40:25,250
how does social behavior correspond
to infection risk.

884
00:40:25,274 --> 00:40:28,537
Because it's clearly important,
but pinning it down is really tough.

885
00:40:29,228 --> 00:40:32,442
CA: It's almost like embracing the fact

886
00:40:32,466 --> 00:40:34,990
that for a lot of these things,
we actually don't know

887
00:40:35,014 --> 00:40:38,855
and that we're all
in this game of probabilities.

888
00:40:39,156 --> 00:40:42,117
Which, in a way, is why I think
the math is so important here.

889
00:40:42,141 --> 00:40:48,148
That you have to think of this
as these multiple numbers

890
00:40:48,172 --> 00:40:49,887
working together on each other,

891
00:40:49,911 --> 00:40:51,545
they all have their part to play.

892
00:40:51,569 --> 00:40:56,562
And any of them that you can
take down by a percentage

893
00:40:56,586 --> 00:40:58,062
is likely contributing,

894
00:40:58,086 --> 00:41:00,807
not just to you, but to everyone.

895
00:41:00,831 --> 00:41:04,609
And people don't actually know
in detail how the numbers go together,

896
00:41:04,633 --> 00:41:06,728
but they know that they
probably all matter.

897
00:41:06,752 --> 00:41:11,664
We almost need people to, somehow,
you know, embrace that uncertainty

898
00:41:11,688 --> 00:41:16,799
and then try to get some satisfaction
by acting on every single part of it.

899
00:41:16,823 --> 00:41:18,085
AK: I think it's this idea

900
00:41:18,109 --> 00:41:21,797
that if on average,
you're infecting, say, three people,

901
00:41:21,821 --> 00:41:24,695
what's driving that and how can you
chip away at that value?

902
00:41:24,719 --> 00:41:26,123
If you're washing your hands,

903
00:41:26,147 --> 00:41:29,403
how much might that chip away
in terms of the handshakes,

904
00:41:29,427 --> 00:41:32,006
you know, you may have had virus
and you no longer do,

905
00:41:32,030 --> 00:41:35,744
or if you are changing
your social behavior in a certain way,

906
00:41:35,768 --> 00:41:37,903
is that taking away
a couple of interactions,

907
00:41:37,927 --> 00:41:39,131
is that taking away half,

908
00:41:39,155 --> 00:41:42,584
how can you really chip into that number
as much as you possibly can?

909
00:41:43,698 --> 00:41:47,203
CA: Is there anything else to say
about how we could reduce

910
00:41:47,227 --> 00:41:51,693
that transmission probability
in our interactions?

911
00:41:51,717 --> 00:41:54,525
Like, what is the physical distance

912
00:41:54,549 --> 00:42:00,140
that it's wise to stay away
from other people if we can?

913
00:42:00,665 --> 00:42:02,680
AK: I think it's hard to pin down exactly,

914
00:42:02,704 --> 00:42:06,216
but I think one thing to bear in mind
is that there's not so much evidence

915
00:42:06,240 --> 00:42:08,871
that this is a kind of aerosol
and it goes really far --

916
00:42:08,895 --> 00:42:10,428
it's reasonably short distances.

917
00:42:10,452 --> 00:42:11,759
I don't think it's the case

918
00:42:11,783 --> 00:42:14,846
that you're sitting a few meters
away from someone

919
00:42:14,870 --> 00:42:17,028
and the virus is somehow
going to get across.

920
00:42:17,735 --> 00:42:19,085
It's in closer interactions,

921
00:42:19,109 --> 00:42:22,096
and it's why we're seeing
so many transmission events

922
00:42:22,120 --> 00:42:25,906
occur in things like meals
and really tight-knit groups.

923
00:42:25,930 --> 00:42:27,271
Because if you imagine

924
00:42:27,295 --> 00:42:30,310
that's where you can get
a virus out and onto surfaces

925
00:42:30,334 --> 00:42:31,882
and onto hands and onto faces,

926
00:42:31,906 --> 00:42:36,031
and it's really situations like that
we've got to think more about.

927
00:42:37,818 --> 00:42:39,024
CA: So in a way,

928
00:42:39,048 --> 00:42:41,993
some of the fears that people have
may actually be overstated,

929
00:42:42,017 --> 00:42:44,720
like, if you're in the middle
of an airplane

930
00:42:44,744 --> 00:42:47,268
and someone at the front sneezes,

931
00:42:47,292 --> 00:42:49,077
I mean, that's annoying,

932
00:42:49,101 --> 00:42:53,458
but it's actually not the thing
you should be most freaked out about.

933
00:42:53,482 --> 00:42:57,220
There are much smarter ways
to pay attention to your well-being.

934
00:42:57,244 --> 00:43:00,697
AK: Yeah, if it was measles
and the plane is susceptible people,

935
00:43:00,721 --> 00:43:02,847
you would see a lot
of infections after that.

936
00:43:02,871 --> 00:43:05,395
I think it is, bear in mind,
that this is, on average,

937
00:43:05,419 --> 00:43:07,184
people infecting two or three others,

938
00:43:07,208 --> 00:43:11,029
so it's not the case of your
maybe 50 interactions over a week,

939
00:43:11,053 --> 00:43:12,982
all of those people are at risk.

940
00:43:13,006 --> 00:43:14,633
But it's going to be some of them,

941
00:43:14,657 --> 00:43:16,625
particularly those close contacts,

942
00:43:16,649 --> 00:43:19,331
that are going to be
where transmission's occurring.

943
00:43:19,355 --> 00:43:21,498
CA: So talk about,

944
00:43:21,522 --> 00:43:25,632
from a sort of national
strategy point of view.

945
00:43:25,656 --> 00:43:29,863
There's a lot of talk about the need
to "flatten the curve."

946
00:43:29,887 --> 00:43:31,212
What does that mean?

947
00:43:31,236 --> 00:43:35,946
AK: I think it refers to this idea
that for your health systems,

948
00:43:35,970 --> 00:43:38,641
you don't want all your cases
to appear at the same time.

949
00:43:38,665 --> 00:43:40,712
So if we sat back and did nothing,

950
00:43:40,736 --> 00:43:42,260
and just let the epidemic grow,

951
00:43:42,284 --> 00:43:44,625
and you had this growth rate
that, at the moment,

952
00:43:44,649 --> 00:43:46,380
in some places is looking like maybe

953
00:43:46,404 --> 00:43:48,550
three to four days,
you're getting doubling.

954
00:43:48,574 --> 00:43:51,098
So every three or four days,
the epidemic is doubling.

955
00:43:51,122 --> 00:43:52,804
It will skyrocket and you'll end up

956
00:43:52,828 --> 00:43:55,982
with a whole bunch
of really severely ill people

957
00:43:56,006 --> 00:43:58,042
needing hospital care
all at the same time,

958
00:43:58,066 --> 00:44:00,029
and you just won't have capacity for it.

959
00:44:00,053 --> 00:44:03,204
So the idea of flattening the curve
is if we can slow transmission,

960
00:44:03,228 --> 00:44:05,276
if we can get that
reproduction number down,

961
00:44:05,300 --> 00:44:07,164
then there may still be an outbreak,

962
00:44:07,188 --> 00:44:08,545
but it will be much flatter,

963
00:44:08,569 --> 00:44:09,736
it will be longer,

964
00:44:09,760 --> 00:44:12,054
and there will be fewer
severe cases showing up,

965
00:44:12,078 --> 00:44:14,759
which means that they can get
the health care they need.

966
00:44:16,220 --> 00:44:23,220
CA: Does it imply that there will be
fewer cases overall, or ---

967
00:44:24,323 --> 00:44:26,776
When you look at the actual images
of people showing

968
00:44:26,800 --> 00:44:28,577
what flattening the curve looks like,

969
00:44:28,601 --> 00:44:31,879
it almost looks as if you've got
the same area still under the graph,

970
00:44:31,903 --> 00:44:34,855
i.e. that the same number of people,
ultimately, are infected,

971
00:44:34,879 --> 00:44:37,672
but over a longer period.

972
00:44:37,696 --> 00:44:40,264
Is that typically what happens,

973
00:44:40,288 --> 00:44:45,247
and even if you adopt
all these strategies of social distancing

974
00:44:45,271 --> 00:44:49,006
and washing hands and etc.

975
00:44:49,030 --> 00:44:52,149
that the best you can hope for
is that you slow the thing down,

976
00:44:52,173 --> 00:44:54,910
you actually will get
as many people infected in the end?

977
00:44:54,934 --> 00:44:57,792
AK: Not necessarily --
it depends on the measures that go in.

978
00:44:57,816 --> 00:45:00,212
There are some measures like,
shutting down travel,

979
00:45:00,236 --> 00:45:03,418
which typically delay the spread
rather than reduce it.

980
00:45:03,442 --> 00:45:05,719
So you're still going to get
the same outbreaks,

981
00:45:05,743 --> 00:45:07,845
but you're stretching out the outbreaks.

982
00:45:08,338 --> 00:45:09,783
But there are other measures.

983
00:45:09,807 --> 00:45:11,675
If we talk about reducing interactions,

984
00:45:11,699 --> 00:45:13,568
if your reproduction number's lower,

985
00:45:13,592 --> 00:45:15,849
you would expect fewer cases overall.

986
00:45:16,384 --> 00:45:18,183
And eventually, in your population,

987
00:45:18,207 --> 00:45:20,111
you will get some buildup of immunity,

988
00:45:20,135 --> 00:45:22,964
which would help you out
if you think about the components,

989
00:45:22,988 --> 00:45:24,243
reducing susceptibility,

990
00:45:24,267 --> 00:45:26,553
alongside what's going on elsewhere.

991
00:45:26,577 --> 00:45:29,164
So the hope is that the two things
will work together.

992
00:45:29,848 --> 00:45:33,727
CA: So help me understand
what the endgame is here.

993
00:45:34,904 --> 00:45:37,117
So, take China, for example.

994
00:45:38,967 --> 00:45:42,570
Whatever you make
of the early suppression of data

995
00:45:42,594 --> 00:45:43,759
and so forth,

996
00:45:43,783 --> 00:45:47,713
that seems pretty troubling there.

997
00:45:47,737 --> 00:45:53,426
The intensity of the response
come January time or whatever,

998
00:45:53,450 --> 00:45:57,449
with the shutdown
of this huge area of the country,

999
00:45:57,473 --> 00:45:59,356
seems to have actually been effective.

1000
00:45:59,380 --> 00:46:04,879
The number of cases there are falling
at a shockingly high rate in some ways.

1001
00:46:04,903 --> 00:46:06,791
Falling to almost nothing.

1002
00:46:06,815 --> 00:46:09,966
And I can't understand that.

1003
00:46:09,990 --> 00:46:14,115
You are talking about a country
of, whatever, 1.4 billion people.

1004
00:46:14,139 --> 00:46:16,242
There have been a huge
number of cases there,

1005
00:46:16,266 --> 00:46:19,718
but it was a tiny fraction
of the population have actually got sick.

1006
00:46:19,742 --> 00:46:24,613
And yet, they've got the number way down.

1007
00:46:24,637 --> 00:46:29,458
It's not like every other person in China
has somehow developed immunity.

1008
00:46:29,482 --> 00:46:33,396
Is it that they have been
absolutely disciplined

1009
00:46:33,420 --> 00:46:37,507
about shutting down travel
from the infected regions

1010
00:46:37,531 --> 00:46:43,335
and somehow really dialed up,
massively dialed up

1011
00:46:43,359 --> 00:46:46,363
testing at any sign of any problem,

1012
00:46:46,387 --> 00:46:50,065
so that literally, they are back
in containment mode

1013
00:46:50,089 --> 00:46:52,272
in most parts of China?

1014
00:46:52,296 --> 00:46:55,623
I can't get my head around it,
help me understand it.

1015
00:46:55,647 --> 00:46:58,197
AK: So we estimated,
in the last two weeks of January,

1016
00:46:58,221 --> 00:46:59,585
when these measures went in,

1017
00:46:59,609 --> 00:47:02,014
the reproduction number
went from about 2.4 to 1.1.

1018
00:47:02,038 --> 00:47:04,403
So about 60 percent decline
in transmission

1019
00:47:04,427 --> 00:47:06,418
in the space of a week or two.

1020
00:47:06,442 --> 00:47:08,919
Which is remarkable and really,

1021
00:47:08,943 --> 00:47:13,490
a lot of it is likely to be driven
by just fundamental change

1022
00:47:13,514 --> 00:47:14,801
in social behavior,

1023
00:47:14,825 --> 00:47:16,262
huge social distancing,

1024
00:47:16,286 --> 00:47:19,055
really intensive follow up,
intensive testing.

1025
00:47:20,166 --> 00:47:21,540
And it got to the point

1026
00:47:21,564 --> 00:47:23,825
where it took enough
off the reproduction number

1027
00:47:23,849 --> 00:47:25,053
to cause the decline,

1028
00:47:25,077 --> 00:47:28,166
and of course,
we're seeing, in many areas,

1029
00:47:28,190 --> 00:47:30,863
a transition back to more
of this kind of containment,

1030
00:47:30,887 --> 00:47:33,257
because there's few cases,
it's more manageable.

1031
00:47:34,320 --> 00:47:36,493
But we're also seeing them
face a challenge,

1032
00:47:36,517 --> 00:47:40,312
because a lot of these cities
have basically been locked down

1033
00:47:40,336 --> 00:47:41,507
for six weeks

1034
00:47:41,531 --> 00:47:43,974
and there's a limit to how long
you can do that for.

1035
00:47:43,998 --> 00:47:47,164
And so some of these measures
are gradually starting to be lifted,

1036
00:47:47,188 --> 00:47:48,806
which of course creates the risk

1037
00:47:48,830 --> 00:47:51,570
that cases that are appearing
from other countries

1038
00:47:51,594 --> 00:47:54,708
may subsequently go in
and reintroduce transmission.

1039
00:47:57,610 --> 00:48:00,847
CA: But given how infectious the bug is,

1040
00:48:00,871 --> 00:48:05,371
and how many theoretical pathways
and connection points there are

1041
00:48:05,395 --> 00:48:09,053
between people in Wuhan, even in shutdown,

1042
00:48:09,077 --> 00:48:10,371
or relatively shut down,

1043
00:48:10,395 --> 00:48:13,323
or the other places
where there's been some infection

1044
00:48:13,347 --> 00:48:14,736
and the rest of the country,

1045
00:48:14,760 --> 00:48:21,009
does it surprise you how quickly
that curve has gone down to nearly zero?

1046
00:48:21,865 --> 00:48:23,016
AK: Yes.

1047
00:48:23,040 --> 00:48:26,863
Early on when we saw
that flattening off in cases

1048
00:48:26,887 --> 00:48:28,696
in those first few days,

1049
00:48:28,720 --> 00:48:32,268
we did wonder whether it was just
they hit a limit in testing capacity

1050
00:48:32,292 --> 00:48:34,053
and they were reporting 1,000 a day,

1051
00:48:34,077 --> 00:48:36,109
because that's all the kits they had.

1052
00:48:36,133 --> 00:48:38,371
But it continued, thankfully,

1053
00:48:38,395 --> 00:48:41,490
and it shows that it is possible
to turn this over

1054
00:48:41,514 --> 00:48:43,276
with that level of intervention.

1055
00:48:43,300 --> 00:48:46,529
I think the key thing now
is seeing how it works in other settings.

1056
00:48:46,553 --> 00:48:51,221
Italy now are putting in
really dramatic interventions.

1057
00:48:51,245 --> 00:48:53,293
But of course,
because of this delay effect,

1058
00:48:53,317 --> 00:48:54,896
if you put them in today,

1059
00:48:54,920 --> 00:48:57,094
you won't necessarily see
the effects on cases

1060
00:48:57,118 --> 00:48:58,277
for another week or two.

1061
00:48:58,301 --> 00:49:00,418
So I think working out
what impact that's had

1062
00:49:00,442 --> 00:49:02,649
is going to be key for helping
other countries

1063
00:49:02,673 --> 00:49:04,140
work on how to contain this.

1064
00:49:04,711 --> 00:49:06,045
CA: To have a picture, Adam,

1065
00:49:06,069 --> 00:49:09,990
of how this is likely to play out
over the next month or two,

1066
00:49:10,014 --> 00:49:13,585
give us a couple of scenarios
that are in your head.

1067
00:49:14,560 --> 00:49:17,315
AK: I think the optimistic scenario

1068
00:49:17,339 --> 00:49:20,465
is that we're going to learn a lot
from places like Italy

1069
00:49:20,489 --> 00:49:22,532
that have unfortunately
been hit very hard,

1070
00:49:22,556 --> 00:49:25,176
and that countries are going to take
this very seriously

1071
00:49:25,200 --> 00:49:27,688
and that we're not going to get
this continued growth

1072
00:49:27,712 --> 00:49:29,337
that's going to overwhelm totally,

1073
00:49:29,361 --> 00:49:33,138
that we're going to be able
to sufficiently slow it down,

1074
00:49:33,162 --> 00:49:35,409
that we are going to get
large numbers of cases,

1075
00:49:35,433 --> 00:49:38,210
we're probably going to get
a lot of severe cases,

1076
00:49:38,234 --> 00:49:40,035
but that will be more manageable,

1077
00:49:40,059 --> 00:49:41,951
that's the kind of optimistic scenario.

1078
00:49:41,975 --> 00:49:43,260
I think if we have a point

1079
00:49:43,284 --> 00:49:45,674
where countries either
don't take this seriously

1080
00:49:45,698 --> 00:49:49,721
or populations don't respond well
to control measures

1081
00:49:49,745 --> 00:49:51,389
or it's not detected,

1082
00:49:51,413 --> 00:49:52,696
we could get situations --

1083
00:49:52,720 --> 00:49:55,387
I think Iran is probably
the closest one at the moment --

1084
00:49:55,411 --> 00:49:58,495
where there's been extensive
widespread transmission,

1085
00:49:58,519 --> 00:50:01,480
and by the time it's being responded to,

1086
00:50:01,504 --> 00:50:03,536
those infections are already in the system

1087
00:50:03,560 --> 00:50:06,313
and they are going to turn up
as cases and severe illness.

1088
00:50:06,337 --> 00:50:08,202
So I'm hoping we're not at that point,

1089
00:50:08,226 --> 00:50:10,209
but we've certainly got, at the moment,

1090
00:50:10,233 --> 00:50:13,547
potentially about 10 countries
on that trajectory

1091
00:50:13,571 --> 00:50:15,799
to have the same outlook as Italy.

1092
00:50:15,823 --> 00:50:18,918
So it's really crucial what happens
in the next couple of weeks.

1093
00:50:19,811 --> 00:50:22,302
CA: Is there a real chance
that quite a few countries

1094
00:50:22,326 --> 00:50:25,087
end up having, this year,

1095
00:50:25,111 --> 00:50:30,774
substantially more deaths from this virus
than from seasonal flu?

1096
00:50:31,942 --> 00:50:34,609
AK: I think for some countries
that is likely, yeah.

1097
00:50:34,633 --> 00:50:36,817
I think if control is not possible,

1098
00:50:36,841 --> 00:50:38,759
and we've seen it happen in China,

1099
00:50:38,783 --> 00:50:43,116
but that was really just an unprecedented
level of intervention.

1100
00:50:43,140 --> 00:50:45,632
It was really just changing
the social fabric.

1101
00:50:45,656 --> 00:50:51,767
I think people, many of us,
don't really appreciate, at a glance,

1102
00:50:51,791 --> 00:50:53,022
just what that means,

1103
00:50:53,046 --> 00:50:55,780
to reduce your interactions
to that extent.

1104
00:50:55,804 --> 00:50:58,968
I think many countries just simply
won't be able to manage that.

1105
00:51:00,769 --> 00:51:03,410
CA: It's almost a challenge
to democracies, isn't it --

1106
00:51:03,434 --> 00:51:07,936
"OK, show us what you can do
without that kind of draconian control."

1107
00:51:07,960 --> 00:51:10,065
If you don't like the thought of that,

1108
00:51:10,089 --> 00:51:12,862
come on, citizens, step up,
show us what you're capable of,

1109
00:51:12,886 --> 00:51:14,859
show that you can be wise about this

1110
00:51:14,883 --> 00:51:17,450
and smart and self-disciplined,

1111
00:51:17,474 --> 00:51:19,863
and get ahead of the damn bug.

1112
00:51:19,887 --> 00:51:21,291
AK: Yeah.

1113
00:51:21,315 --> 00:51:25,117
CA: I mean, I'm not personally
superoptimistic about that,

1114
00:51:25,141 --> 00:51:29,805
because there's such conflicting messaging
coming out in so many different places,

1115
00:51:29,829 --> 00:51:35,753
and people don't like
to short-term sacrifice.

1116
00:51:35,777 --> 00:51:38,177
I mean, is there almost a case that --

1117
00:51:38,673 --> 00:51:40,580
I mean, what's your view

1118
00:51:40,604 --> 00:51:43,568
on whether the media has played
a helpful role here

1119
00:51:43,592 --> 00:51:44,763
or an unhelpful role?

1120
00:51:44,787 --> 00:51:46,575
Is it actually, in some ways, helpful

1121
00:51:46,599 --> 00:51:50,529
to, if anything, overstate
the concern, the fear,

1122
00:51:50,553 --> 00:51:53,212
and actually make people
panic a little bit?

1123
00:51:53,236 --> 00:51:55,617
AK: I think it's a really
tough balance to strike,

1124
00:51:55,641 --> 00:51:58,133
because of course, early on,
if you don't have cases,

1125
00:51:58,157 --> 00:52:01,464
if you don't have any evidence
of potential pressure,

1126
00:52:01,488 --> 00:52:05,029
it's very hard to get that message
and convince people to take it seriously

1127
00:52:05,053 --> 00:52:06,260
if you're over hyping it.

1128
00:52:06,284 --> 00:52:08,728
But equally, if you're waiting too long,

1129
00:52:08,752 --> 00:52:11,783
and saying it's not a concern yet,
we're OK for the moment,

1130
00:52:11,807 --> 00:52:14,207
a lot of people think it's just flu.

1131
00:52:14,553 --> 00:52:17,711
By the time it hits hard, as I've said,

1132
00:52:17,735 --> 00:52:20,855
you're going to have weeks
of an overburdened health system,

1133
00:52:20,879 --> 00:52:23,671
because even if you take interventions,

1134
00:52:23,695 --> 00:52:26,531
it's too late to control the infections
that have happened.

1135
00:52:26,555 --> 00:52:28,087
So I think it's a fine line

1136
00:52:28,111 --> 00:52:30,516
and my hope is there is
this ramp-up in messaging,

1137
00:52:30,540 --> 00:52:33,015
now people have these
tangible examples like Italy,

1138
00:52:33,039 --> 00:52:36,555
where they can see what's going to happen
if they don't take it seriously.

1139
00:52:37,038 --> 00:52:39,799
But certainly, of all
the diseases I've seen,

1140
00:52:39,823 --> 00:52:42,465
I think many of my colleagues
who are much older than me

1141
00:52:42,489 --> 00:52:44,276
and have memories of other outbreaks,

1142
00:52:44,300 --> 00:52:47,752
it's the scariest thing we've seen
in terms of the impact it could have,

1143
00:52:47,776 --> 00:52:49,656
and I think we need to respond to that.

1144
00:52:49,680 --> 00:52:52,311
CA: It's the scariest disease you've seen.

1145
00:52:53,042 --> 00:52:54,192
Wow.

1146
00:52:54,216 --> 00:52:58,732
I've got some questions for you
from my friends on Twitter.

1147
00:52:58,756 --> 00:53:04,973
Everyone is obviously
superexercised about this topic.

1148
00:53:04,997 --> 00:53:06,536
Hypothetically,

1149
00:53:06,560 --> 00:53:09,052
if everyone stayed home for three weeks,

1150
00:53:09,076 --> 00:53:11,791
would that effectively wipe this out?

1151
00:53:11,815 --> 00:53:14,661
Is there a way to socially
distance ourselves out of this?

1152
00:53:15,352 --> 00:53:20,296
AK: Yeah, I think in certain countries
with reasonably small household sizes,

1153
00:53:20,320 --> 00:53:22,863
I think average in the UK, US
is about two and a half,

1154
00:53:22,887 --> 00:53:26,331
so even if you had a round of infection
within the household,

1155
00:53:26,355 --> 00:53:28,019
that would probably stamp it out.

1156
00:53:28,043 --> 00:53:29,270
As a secondary benefit,

1157
00:53:29,294 --> 00:53:31,643
you may well stamp out
a few other infections too.

1158
00:53:31,667 --> 00:53:33,348
Measles only circulates in humans,

1159
00:53:33,372 --> 00:53:35,149
so you may have some knock-on effect,

1160
00:53:35,173 --> 00:53:37,529
if, of course, that were
ever to be possible.

1161
00:53:37,553 --> 00:53:41,743
CA: I mean, obviously that would be
a huge dent to the economy,

1162
00:53:41,767 --> 00:53:46,043
and this is in a way almost, like,
one of the underlying challenges here

1163
00:53:46,067 --> 00:53:49,561
is that you can't optimize public policy

1164
00:53:49,585 --> 00:53:54,946
for both economic health
and fighting a virus.

1165
00:53:54,970 --> 00:53:57,628
Like, those two things are,
to some extent, in conflict,

1166
00:53:57,652 --> 00:54:01,565
or at least, short-term
economic health and fighting a virus.

1167
00:54:01,589 --> 00:54:03,565
Those two things are in conflict, right?

1168
00:54:03,589 --> 00:54:06,503
And societies need to pick one.

1169
00:54:06,988 --> 00:54:10,686
AK: It is tough to convince
people of that balance,

1170
00:54:10,710 --> 00:54:12,910
the thing we always say
of pandemic planning

1171
00:54:12,934 --> 00:54:15,193
is it's cheap to put
this stuff in place now --

1172
00:54:15,217 --> 00:54:17,218
otherwise, you've got to pay for it later.

1173
00:54:18,207 --> 00:54:20,287
But unfortunately,
as we've seen with this,

1174
00:54:20,311 --> 00:54:22,849
that a lot of early money
for response wasn't there.

1175
00:54:23,341 --> 00:54:26,746
And it's only when it has an impact
and when it's going to get expensive

1176
00:54:26,770 --> 00:54:30,725
that people are happy to take
that cost on board, it seems.

1177
00:54:31,612 --> 00:54:33,652
CA: OK, some more Twitter questions.

1178
00:54:33,676 --> 00:54:36,438
Will the rising temperature
in coming weeks and months

1179
00:54:36,462 --> 00:54:39,215
slow down the COVID-19 spread?

1180
00:54:39,784 --> 00:54:42,109
AK: I haven't seen any convincing evidence

1181
00:54:42,133 --> 00:54:44,490
that there's that strong pattern
with temperature,

1182
00:54:44,514 --> 00:54:48,768
and we've seen it for other infections
that there is this seasonal pattern,

1183
00:54:48,792 --> 00:54:51,403
but I think the fact
we're getting widespread outbreaks

1184
00:54:51,427 --> 00:54:53,895
makes it hard to identify, and of course,

1185
00:54:53,919 --> 00:54:55,355
there's other things going on.

1186
00:54:55,379 --> 00:54:58,506
So even if one country doesn't have
as big an outbreak as another,

1187
00:54:58,530 --> 00:55:00,887
that's going to be influenced
by control measures,

1188
00:55:00,911 --> 00:55:04,100
by social behavior, by opportunities
and these things as well.

1189
00:55:04,124 --> 00:55:07,045
So it would be really reassuring
if this was the case,

1190
00:55:07,069 --> 00:55:09,323
but I don't think
we can say that just yet.

1191
00:55:10,038 --> 00:55:11,760
CA: Continuing from Twitter,

1192
00:55:11,784 --> 00:55:15,366
I mean, is there a standardized
global recommendation

1193
00:55:15,390 --> 00:55:16,571
for all countries

1194
00:55:16,595 --> 00:55:18,365
on how to do this?

1195
00:55:18,389 --> 00:55:19,723
And if not, why not?

1196
00:55:20,628 --> 00:55:23,454
AK: I think that's what
people are trying to piece together,

1197
00:55:23,478 --> 00:55:25,039
first in terms of what works.

1198
00:55:25,345 --> 00:55:28,490
It's only really in the last
sort of few weeks

1199
00:55:28,514 --> 00:55:31,330
we've got a sense that this thing
can be controllable

1200
00:55:31,354 --> 00:55:32,981
with this extent of interventions,

1201
00:55:33,005 --> 00:55:35,864
but of course, not all countries
can do what China have done,

1202
00:55:35,888 --> 00:55:37,314
some of these measures

1203
00:55:37,338 --> 00:55:41,077
incur a huge social, economic,
psychological burden

1204
00:55:41,101 --> 00:55:42,547
on populations.

1205
00:55:42,925 --> 00:55:44,784
And of course, there's the time limit.

1206
00:55:44,808 --> 00:55:46,490
In China, they've had six weeks,

1207
00:55:46,514 --> 00:55:48,078
it's tough to maintain that,

1208
00:55:48,102 --> 00:55:49,942
so we need to think of these tradeoffs

1209
00:55:49,966 --> 00:55:52,799
of all the things we can ask people to do,

1210
00:55:52,823 --> 00:55:56,696
what's going to have the most impact
on actually reducing the burden.

1211
00:55:57,807 --> 00:55:59,006
CA: Another question:

1212
00:55:59,030 --> 00:56:02,008
How did this happen
and is it likely to happen again?

1213
00:56:03,295 --> 00:56:07,544
AK: So it's likely that this originated
with the virus that was circling in bats

1214
00:56:07,568 --> 00:56:10,807
and then probably made its way
through another species

1215
00:56:10,831 --> 00:56:12,045
into humans somehow,

1216
00:56:12,069 --> 00:56:14,934
there's a lot of bits
of evidence around this,

1217
00:56:14,958 --> 00:56:16,910
there's not kind of single, clear story,

1218
00:56:16,934 --> 00:56:18,925
but even for SARS, it took several years

1219
00:56:18,949 --> 00:56:22,253
for genomics to piece together
the exact route that it happened.

1220
00:56:22,277 --> 00:56:25,331
But certainly, I think it's plausible
that it could happen again.

1221
00:56:25,355 --> 00:56:27,876
Nature is throwing out
these viruses constantly.

1222
00:56:28,419 --> 00:56:31,005
Many of them aren't
well-adapted to humans,

1223
00:56:31,029 --> 00:56:32,207
don't pick up,

1224
00:56:32,231 --> 00:56:35,437
you know, there may well have been
a virus like this a few years ago

1225
00:56:35,461 --> 00:56:37,207
that just happened to infect someone

1226
00:56:37,231 --> 00:56:40,054
who just didn't have any contacts
and didn't go any further.

1227
00:56:40,078 --> 00:56:42,046
I think we are going to face these things

1228
00:56:42,070 --> 00:56:44,474
and we need to think
about how can we get in early,

1229
00:56:44,498 --> 00:56:47,291
at the stage where we're talking
small numbers of cases,

1230
00:56:47,315 --> 00:56:49,363
and even something like this
is containable,

1231
00:56:49,387 --> 00:56:51,339
rather than the situation we've got now.

1232
00:56:51,363 --> 00:56:53,379
CA: It seems like
this isn't the first time

1233
00:56:53,403 --> 00:56:56,709
that a virus seems to have emerged
from, like, a wild meat market.

1234
00:56:57,664 --> 00:57:00,346
That's certainly how
it happens in the movies. (Laughs)

1235
00:57:00,370 --> 00:57:03,029
And I think China has already taken
some steps this time

1236
00:57:03,053 --> 00:57:05,696
to try to crack down on that.

1237
00:57:05,720 --> 00:57:08,505
I think that's potentially
quite a big deal for the future

1238
00:57:08,529 --> 00:57:11,656
if that can be properly maintained.

1239
00:57:11,680 --> 00:57:13,569
AK: It is, and we saw, for example,

1240
00:57:13,593 --> 00:57:15,633
the H7N9 avian flu,

1241
00:57:15,657 --> 00:57:19,759
over the last few years, in 2013,
it was a big emerging concern

1242
00:57:19,783 --> 00:57:21,803
and China made a very extensive response

1243
00:57:21,827 --> 00:57:24,489
in terms of changing
how they operate their markets

1244
00:57:24,513 --> 00:57:26,217
and vaccination of birds

1245
00:57:26,241 --> 00:57:29,791
and that seems
to have removed that threat.

1246
00:57:29,815 --> 00:57:33,585
So I think these measures can be effective
if they're identified early on.

1247
00:57:34,323 --> 00:57:35,847
CA: So talk about vaccinations.

1248
00:57:35,871 --> 00:57:37,744
That's the key measure, I guess,

1249
00:57:37,768 --> 00:57:41,170
to change that susceptibility
factor in your equation.

1250
00:57:44,720 --> 00:57:49,053
There's obviously a race on
to get these vaccinations out there,

1251
00:57:49,077 --> 00:57:51,687
there are some candidate
vaccinations there.

1252
00:57:51,711 --> 00:57:54,047
How do you see that playing out?

1253
00:57:55,099 --> 00:57:58,647
AK: I think there's certainly some
promising development happening,

1254
00:57:58,671 --> 00:58:00,686
but I think the timescales of these things

1255
00:58:00,710 --> 00:58:03,797
are really on the order
of maybe a year, 18 months

1256
00:58:03,821 --> 00:58:05,728
before these things be widely available.

1257
00:58:05,752 --> 00:58:08,666
Obviously, a vaccine has to go
through these stages of trials,

1258
00:58:08,690 --> 00:58:11,125
that takes time,
so even if by the end of the year,

1259
00:58:11,149 --> 00:58:13,491
we have something
which is viable and works,

1260
00:58:13,515 --> 00:58:16,831
we're still going to see a delay
before everyone can get ahold of it.

1261
00:58:16,855 --> 00:58:18,784
CA: So this really puzzles me, actually,

1262
00:58:18,808 --> 00:58:21,760
and I'd love to ask you
as a mathematician about this as well.

1263
00:58:21,784 --> 00:58:23,717
There are already several companies

1264
00:58:23,741 --> 00:58:27,745
believing that they have
plausible candidate vaccines.

1265
00:58:28,061 --> 00:58:31,839
As you say, the process
of testing takes forever.

1266
00:58:32,909 --> 00:58:37,552
Is there a case that we're not
thinking about this right

1267
00:58:37,576 --> 00:58:42,553
when we're looking at the way
that testing is done

1268
00:58:42,577 --> 00:58:45,279
and that the safety calculations are made?

1269
00:58:45,303 --> 00:58:47,879
Because it's one thing
if you're going to introduce

1270
00:58:47,903 --> 00:58:49,471
a brand new drug or something --

1271
00:58:49,495 --> 00:58:53,681
yes, you want to test to make sure
that there are no side effects,

1272
00:58:53,705 --> 00:58:55,125
and that can take a long time

1273
00:58:55,149 --> 00:58:58,482
by the time you've done all
the control trials and all the rest of it.

1274
00:58:58,506 --> 00:59:00,482
If there's a global emergency,

1275
00:59:00,506 --> 00:59:02,994
isn't there a case,

1276
00:59:03,018 --> 00:59:04,903
both mathematically and ethically,

1277
00:59:04,927 --> 00:59:07,276
that there should just be
a different calculation,

1278
00:59:07,300 --> 00:59:08,744
the question shouldn't be

1279
00:59:08,768 --> 00:59:13,807
"Is there any possible case
where this vaccine can do harm,"

1280
00:59:13,831 --> 00:59:15,855
the question surely should be,

1281
00:59:15,879 --> 00:59:18,291
"On the net probabilities,

1282
00:59:18,315 --> 00:59:22,188
isn't there a case
to roll this out at scale

1283
00:59:22,212 --> 00:59:27,250
to have a shot at nipping
this thing in the bud?"

1284
00:59:27,274 --> 00:59:30,170
I mean, what am I missing
in thinking that way?

1285
00:59:30,654 --> 00:59:32,885
AK: I mean, we do see that
in other situations,

1286
00:59:32,909 --> 00:59:36,751
for example, the Ebola vaccine in 2015

1287
00:59:36,775 --> 00:59:39,720
showed, within a few months,
very promising evidence

1288
00:59:39,744 --> 00:59:44,601
and interim results of the trial in humans

1289
00:59:44,625 --> 00:59:47,180
showed what seemed very high efficacy.

1290
00:59:47,204 --> 00:59:50,434
And even though
it hadn't been licensed fully,

1291
00:59:50,458 --> 00:59:53,141
it was employed for what is known
as compassionate use

1292
00:59:53,165 --> 00:59:54,680
in subsequent other outbreaks.

1293
00:59:54,704 --> 00:59:56,605
So there are these mechanisms

1294
00:59:56,629 --> 00:59:59,469
where vaccines can be
fast-tracked in this way.

1295
00:59:59,934 --> 01:00:03,221
But of course, we're currently
in a situation where we have no idea

1296
01:00:03,245 --> 01:00:05,172
if these things will do anything at all.

1297
01:00:05,196 --> 01:00:08,021
So I think we need
to accrue enough evidence

1298
01:00:08,045 --> 01:00:10,141
that it could have an impact,

1299
01:00:10,165 --> 01:00:12,566
but obviously, fast-track that
as much as possible.

1300
01:00:13,780 --> 01:00:16,946
CA: But the skeptic in me
still doesn't fully get this.

1301
01:00:17,439 --> 01:00:19,439
I don't understand

1302
01:00:19,463 --> 01:00:24,786
why there isn't more energy
behind bolder thinking on this.

1303
01:00:24,810 --> 01:00:28,252
Everyone seems, despite the overall risk,

1304
01:00:28,276 --> 01:00:31,212
incredibly risk-averse
about how to build the response to it.

1305
01:00:31,759 --> 01:00:33,164
AK: So with the caveat that,

1306
01:00:33,188 --> 01:00:35,371
yeah, there's a lot
of good questions on this,

1307
01:00:35,395 --> 01:00:37,981
and some of them are slightly
outside my warehouse,

1308
01:00:38,005 --> 01:00:40,822
but I agree that we need to do more
to get timescales out.

1309
01:00:40,846 --> 01:00:42,276
The example I always quote

1310
01:00:42,300 --> 01:00:45,047
is it takes us six months
to choose a seasonal flu strain

1311
01:00:45,071 --> 01:00:47,039
and get the vaccines out there to people.

1312
01:00:47,063 --> 01:00:51,085
We always have to try and predict ahead
which strains are going to be circulating.

1313
01:00:51,109 --> 01:00:53,228
And that's for something
we know how to make

1314
01:00:53,252 --> 01:00:55,367
and has been manufactured for a long time.

1315
01:00:56,212 --> 01:00:58,537
So there is definitely more
that needs to be done

1316
01:00:58,561 --> 01:01:00,514
to get these timescales shorter.

1317
01:01:00,538 --> 01:01:02,620
But I think we do have to balance that,

1318
01:01:02,644 --> 01:01:05,788
especially if we're exposing
large numbers of people to something

1319
01:01:05,812 --> 01:01:08,081
to make sure that we're confident and safe

1320
01:01:08,105 --> 01:01:10,930
and that it's going to have
some benefit, potentially.

1321
01:01:12,546 --> 01:01:14,903
CA: And so, finally,

1322
01:01:14,927 --> 01:01:18,019
Adam, I guess going into this --

1323
01:01:18,942 --> 01:01:23,172
There's another set of infectious things
happening around the world

1324
01:01:23,196 --> 01:01:24,362
at the same time,

1325
01:01:24,386 --> 01:01:28,124
which is ideas and the communication
around this thing.

1326
01:01:28,148 --> 01:01:33,800
They really are two very dynamic
interactive systems of infectiousness --

1327
01:01:33,824 --> 01:01:36,998
there's some very damaging
information out there.

1328
01:01:37,022 --> 01:01:41,829
Is it fair to think of this as battle
of credible knowledge and measures

1329
01:01:41,853 --> 01:01:44,045
against the bug,

1330
01:01:44,069 --> 01:01:47,735
and just bad information --

1331
01:01:47,759 --> 01:01:50,149
You know, part of what
we have to think about here

1332
01:01:50,173 --> 01:01:55,022
is how to suppress one set of things
and boost the other, actually,

1333
01:01:55,046 --> 01:01:56,705
turbocharge the other.

1334
01:01:56,729 --> 01:01:58,109
How should we think of this?

1335
01:01:58,133 --> 01:02:02,074
AK: I think we can definitely think of it
almost as competition for our attention,

1336
01:02:02,098 --> 01:02:03,813
and we see similarly, with diseases,

1337
01:02:03,837 --> 01:02:06,416
you have viruses competing
to infect susceptible hosts.

1338
01:02:06,440 --> 01:02:08,227
And I think we're now seeing,

1339
01:02:08,251 --> 01:02:11,331
I guess over the last few years
with fake news and misinformation

1340
01:02:11,355 --> 01:02:12,904
and the emergence of awareness,

1341
01:02:12,928 --> 01:02:14,101
more of a transition

1342
01:02:14,125 --> 01:02:16,733
to thinking about how do we
reduce that susceptibility

1343
01:02:16,757 --> 01:02:19,391
if we have people that can be
in these different states,

1344
01:02:19,415 --> 01:02:21,876
how can we try and preempt
better with information.

1345
01:02:21,900 --> 01:02:24,292
I think the challenge
for an outbreak is obviously,

1346
01:02:24,316 --> 01:02:26,569
early on, we have
very little good information,

1347
01:02:26,593 --> 01:02:30,844
and it's very easy for certainty
and confidence to fill that vacuum.

1348
01:02:30,868 --> 01:02:32,971
And so I think that is something --

1349
01:02:33,320 --> 01:02:36,583
I know platforms are working
on how can we get people exposed

1350
01:02:36,607 --> 01:02:38,106
to good information earlier,

1351
01:02:38,130 --> 01:02:40,867
so hopefully protect them
against other stuff.

1352
01:02:41,830 --> 01:02:44,410
CA: One of the big unknowns to me
in the year ahead --

1353
01:02:44,434 --> 01:02:47,925
let's say that the year ahead includes
many, many more weeks,

1354
01:02:47,949 --> 01:02:49,291
for many people,

1355
01:02:49,315 --> 01:02:52,657
of actually self-isolating.

1356
01:02:52,681 --> 01:02:57,728
Those of us who are lucky enough
to have jobs where you can do that.

1357
01:02:57,752 --> 01:02:59,434
You know, staying home.

1358
01:02:59,458 --> 01:03:01,807
By the way, the whole injustice
of this situation,

1359
01:03:01,831 --> 01:03:06,291
where so many people can't do that
and continue to make a living,

1360
01:03:06,315 --> 01:03:10,331
is, I'm sure, going to be
a huge deal in the year ahead

1361
01:03:10,355 --> 01:03:16,122
and if it turns out that death rates
are much higher in the latter group

1362
01:03:16,146 --> 01:03:17,502
than in the former group,

1363
01:03:17,526 --> 01:03:19,493
and especially in a country like the US,

1364
01:03:19,517 --> 01:03:22,577
where the latter group
doesn't even have proper health insurance

1365
01:03:22,601 --> 01:03:24,326
and so forth.

1366
01:03:25,342 --> 01:03:30,610
That feels like right there,
that could just become a huge debate,

1367
01:03:30,634 --> 01:03:33,754
hopefully a huge source
of change at some level.

1368
01:03:33,778 --> 01:03:36,084
AK: I think that's an incredibly
important point,

1369
01:03:36,108 --> 01:03:37,730
because it's very easy --

1370
01:03:37,754 --> 01:03:41,164
I similarly have a job
where remote working is fairly easy,

1371
01:03:41,188 --> 01:03:44,987
and it's very easy to say
we should just stop social interactions,

1372
01:03:45,011 --> 01:03:48,276
but of course, that could have
an enormous impact on people

1373
01:03:48,300 --> 01:03:51,100
and the choices and the routine
that they can have.

1374
01:03:51,124 --> 01:03:53,299
And I think those do need
to be accounted for,

1375
01:03:53,323 --> 01:03:55,705
both now and what the effect
is going to look like

1376
01:03:55,729 --> 01:03:57,259
a few months down the line.

1377
01:03:57,283 --> 01:03:58,701
CA: When all's said and done,

1378
01:03:58,725 --> 01:04:03,783
is it fair to say that the world has
faced, actually, much graver problems

1379
01:04:03,807 --> 01:04:04,958
in the past,

1380
01:04:04,982 --> 01:04:08,069
that on any scenario,

1381
01:04:08,093 --> 01:04:11,762
it's highly likely that at some point
in the next 18 months, let's say,

1382
01:04:11,786 --> 01:04:16,095
a vaccine is there and starts
to get wide distribution,

1383
01:04:16,119 --> 01:04:22,101
that we will have learned
lots of other ways to manage this problem?

1384
01:04:22,125 --> 01:04:24,257
But at some point, next year probably,

1385
01:04:24,281 --> 01:04:30,412
the world will feel like
it's got on top of this

1386
01:04:30,436 --> 01:04:31,839
and can move on.

1387
01:04:31,863 --> 01:04:33,602
Is that likely to be it,

1388
01:04:33,626 --> 01:04:36,990
or is this more likely to be,
you know, it escapes,

1389
01:04:37,014 --> 01:04:42,061
it's now an endemic nightmare
that every year picks off far more people

1390
01:04:42,085 --> 01:04:44,634
than are picked off by the flu currently.

1391
01:04:44,658 --> 01:04:47,481
What are the likely ways forward,

1392
01:04:47,505 --> 01:04:49,550
just taking a slightly longer-term view?

1393
01:04:49,574 --> 01:04:52,589
AK: I think there's plausible ways
you could see all of those

1394
01:04:52,613 --> 01:04:54,204
potentially playing out.

1395
01:04:54,228 --> 01:04:58,838
I think the most plausible is probably
that we'll see very rapid growth this year

1396
01:04:58,862 --> 01:05:03,464
and lots of large outbreaks
that don't recur, necessarily.

1397
01:05:03,488 --> 01:05:05,638
But there is a potential
sequence of events

1398
01:05:05,662 --> 01:05:09,743
that could end up with these kind of
multiyear outbreaks in different places

1399
01:05:09,767 --> 01:05:10,925
and reemerging.

1400
01:05:10,949 --> 01:05:12,826
But I think it's likely we'll see

1401
01:05:12,850 --> 01:05:15,701
most transmission concentrated
in the next year or so.

1402
01:05:15,725 --> 01:05:18,761
And then, obviously,
if there's a vaccine available,

1403
01:05:18,785 --> 01:05:21,338
we can move past this,
and hopefully, learn from this.

1404
01:05:21,362 --> 01:05:24,554
I think a lot of the countries
that responded very strongly to this

1405
01:05:24,578 --> 01:05:26,006
were hit very hard by SARS.

1406
01:05:26,030 --> 01:05:29,156
Singapore, Hong Kong,
that really did leave an impact,

1407
01:05:29,180 --> 01:05:31,910
and I think that's something
they've drawn on very heavily

1408
01:05:31,934 --> 01:05:33,276
in their response to this.

1409
01:05:33,300 --> 01:05:34,458
CA: Alright.

1410
01:05:34,482 --> 01:05:37,157
So let's wrap up maybe by just
encouraging people

1411
01:05:37,181 --> 01:05:39,101
to channel their inner mathematician

1412
01:05:39,125 --> 01:05:44,414
and especially think
about the opportunities,

1413
01:05:44,438 --> 01:05:48,358
and the transmission probabilities
that they can help shift.

1414
01:05:48,382 --> 01:05:52,760
Just remind us of the top
three or four or five or six things

1415
01:05:52,784 --> 01:05:54,719
that you would love to see people doing.

1416
01:05:54,743 --> 01:05:57,615
AK: I think at the individual level,
just thinking a lot more

1417
01:05:57,639 --> 01:06:00,020
about your interactions
and your risk of infection

1418
01:06:00,044 --> 01:06:02,012
and obviously, what gets onto your hands

1419
01:06:02,036 --> 01:06:03,731
and once that gets onto your face,

1420
01:06:03,755 --> 01:06:06,340
and how do you potentially
create that risk for others.

1421
01:06:06,364 --> 01:06:09,037
I think also, in terms of interactions,

1422
01:06:09,061 --> 01:06:13,896
with things like handshakes
and maybe contacts you don't need to have.

1423
01:06:13,920 --> 01:06:16,697
You know, how can we get those down
as much as possible.

1424
01:06:16,721 --> 01:06:19,134
If each person's giving it
to two or three others,

1425
01:06:19,158 --> 01:06:22,371
how do we get that number
down to one, through our behavior.

1426
01:06:22,395 --> 01:06:26,204
And then it's likely that we'll need
some larger-scale interventions

1427
01:06:26,228 --> 01:06:29,169
in terms of gatherings, conferences,

1428
01:06:29,193 --> 01:06:31,827
other things where
there's a lot of opportunities

1429
01:06:31,851 --> 01:06:33,220
for transmission.

1430
01:06:33,244 --> 01:06:36,197
And really, I think that combination
of that individual level,

1431
01:06:36,221 --> 01:06:39,227
you know, if you're ill
or potentially you're going to get ill,

1432
01:06:39,251 --> 01:06:40,519
reducing that risk,

1433
01:06:40,543 --> 01:06:42,146
but then also us working together

1434
01:06:42,170 --> 01:06:44,274
to prevent it getting
into those groups who,

1435
01:06:44,298 --> 01:06:46,130
if it continues to be uncontrolled,

1436
01:06:46,154 --> 01:06:48,392
could really hit some people
very, very hard.

1437
01:06:49,434 --> 01:06:51,060
CA: Yeah, there's a lot of things

1438
01:06:51,084 --> 01:06:54,299
that we may need
to gently let go of for a bit.

1439
01:06:54,323 --> 01:06:58,553
And maybe try to reinvent
the best aspects of them.

1440
01:06:59,077 --> 01:07:00,418
Thank you so much.

1441
01:07:00,442 --> 01:07:03,235
If people want to keep up with you,

1442
01:07:03,259 --> 01:07:05,974
first of all, they can follow you
on Twitter, for example.

1443
01:07:05,998 --> 01:07:07,347
What's your Twitter handle?

1444
01:07:07,371 --> 01:07:09,990
AK: So AdamJKucharski, all one word.

1445
01:07:10,014 --> 01:07:12,524
CA: Adam, thank you so much
for your time, stay well.

1446
01:07:12,548 --> 01:07:13,928
AK: Thank you.

1447
01:07:13,952 --> 01:07:20,952
(Music)

1448
01:07:29,263 --> 01:07:32,533
CA: Associate professor
and TED Fellow Adam Kucharski.

1449
01:07:33,339 --> 01:07:35,934
We'd love to hear what you think
of this bonus episode.

1450
01:07:35,958 --> 01:07:38,799
Please tell us by rating
and reviewing us in Apple Podcasts

1451
01:07:38,823 --> 01:07:40,757
or your favorite podcast app.

1452
01:07:41,244 --> 01:07:43,217
Those reviews are influential, actually.

1453
01:07:43,241 --> 01:07:44,617
We certainly read every one,

1454
01:07:44,641 --> 01:07:46,791
and truly appreciate your feedback.

1455
01:07:46,815 --> 01:07:48,768
(Music)

1456
01:07:48,792 --> 01:07:52,592
This week's show was produced
by Dan O'Donnell at Transmitter Media.

1457
01:07:52,616 --> 01:07:54,647
Our production manager
is Roxanne Hai Lash,

1458
01:07:54,671 --> 01:07:56,988
our fact-checker, Nicole Bode.

1459
01:07:57,012 --> 01:07:59,290
This episode was mixed by Sam Baer.

1460
01:07:59,314 --> 01:08:01,355
Our theme music
is by Allison Layton-Brown.

1461
01:08:01,379 --> 01:08:03,926
Special thanks to my colleague
Michelle Quint.

1462
01:08:04,252 --> 01:08:06,473
Thanks for listening to the TED Interview.

1463
01:08:06,497 --> 01:08:07,998
We'll be back later this spring

1464
01:08:08,022 --> 01:08:11,370
with a whole new season's worth
of deep dives with great minds.

1465
01:08:11,759 --> 01:08:14,934
I hope you'll enjoy them
whether or not life is back to normal.

1466
01:08:15,634 --> 01:08:16,850
I'm Chris Anderson,

1467
01:08:16,874 --> 01:08:18,879
thanks for listening and stay well.