Talk Polymath: Evidence-based Conversations

Ep. 1 | COVID19: The same as – and different than – previous pandemics

February 02, 2021 Polyplexus.com Season 1 Episode 1
Talk Polymath: Evidence-based Conversations
Ep. 1 | COVID19: The same as – and different than – previous pandemics
Show Notes Transcript

The first Talk Polymath episode focuses on COVID-19 and how this pandemic mirrors and differs from previous ones. Our guests are William Warren, Ph.D., Vice President and head of FluNXT at Sanofi Pasteur; and José Ramón Fernández-Peña, MD, MPA, Director of Health Professions Advising at Northwestern University and President at American Public Health Association.

Talk Polymath is Polyplexus.com's monthly podcast series which features evidence-based conversations and invites global science leaders to converse about a topic in science, technology, engineering, the arts, and math. From public health topics such as vaccinations to changing models and trends in technology, this podcast engages in topics of current cultural interest across disciplines.

For more information visit www.polyplexus.com.

00:08

we're excited to have you join us

00:10

for the first edition of talk polymath

00:12

focusing on how coven 19 pandemic is

00:16

both

00:16

similar to yet different from previous

00:19

pandemics

00:20

i'm michael goldblatt one of the

00:22

co-founders of

00:23

polyplexus and it's my pleasure to be

00:25

able to introduce to you this evening's

00:27

guests

00:28

doctors william warren and jose ramon

00:31

fernandez pena

00:32

jose ramon has been in public health

00:34

since graduating medical school

00:36

most of his work focuses on workforce

00:39

diversity

00:40

and cross-cultural communications and

00:42

health

00:43

he has created programs to integrate

00:45

foreign educated health

00:47

care professionals into the us medical

00:49

system

00:50

and serves as an advisor to the white

00:52

house domestic policy council

00:54

on the economic integration of foreign

00:56

trained health care professionals

00:59

in addition to being a director of

01:01

health professions

01:02

advising in northwestern jose ramon is

01:05

also

01:05

president of the american public health

01:07

association

01:08

and is 25 000 members whose motto is

01:12

for science for action for health

01:16

bill warren's path has been less linear

01:19

starting professional life as a

01:20

mechanical engineer

01:22

and became one of if not the youngest

01:25

program manager

01:26

at the defense advanced research agency

01:29

he left darpa to become a biomedical

01:31

entrepreneur

01:32

building a company focused on the

01:34

real-time mass customization of body

01:37

parts on demand in vivo

01:40

ultimately his company focused on

01:42

constructing ex vivo fully human immune

01:45

systems

01:45

for the prediction of both vaccine

01:47

efficacy and adverse reactions

01:50

and as sometimes happens in the

01:52

entrepreneurial world

01:53

his success led to his company's

01:55

acquisition by sanofi pasteur

01:58

more than a decade later doctor

02:02

where he is vice president and

02:05

ex-biotech focusing on broadly

02:07

protective influenza vaccine

02:11

now polyplexus is all about

02:13

conversations intent of focused

02:14

discussion through the lens of what we

02:16

already know

02:17

in pursuit of what we might discover and

02:20

bill

02:20

and jose ramon are going to discuss the

02:23

evidence from prior pandemics

02:25

to shed light on what is different this

02:27

time and what is the same

02:30

please use the chat feature to ask any

02:32

questions you might have

02:33

i will be organizing the questions for

02:35

bill and jose ramon

02:37

to respond to during the last 10 to 15

02:40

minutes of their conversation

02:42

but before i disappear also let me add

02:45

that earlier today

02:46

barda the biomedical advanced research

02:49

and development authority

02:51

posted an incubator on polyplexus

02:53

focused on gaining

02:54

feedback from the community on the

02:56

clinical need for development of

02:58

and utility of infection severity tools

03:02

for future adoption and implementation

03:06

to put that question in the context of

03:08

tonight's discussion

03:09

consider that in the current pandemic

03:12

most individuals infected with sars cov2

03:15

have mild illness about twenty percent

03:17

of the infected patients experience

03:19

severe outcomes

03:20

and about six percent of those

03:22

individuals require critical care due to

03:24

complications

03:25

such as acute respiratory distress or

03:27

sepsis

03:28

hence the just potent just posted bar to

03:31

incubator

03:32

is interested in tools enabling

03:34

hospitals that are overwhelmed with

03:36

patients

03:36

and limited in resources to accurately

03:39

identify

03:40

patients who will require supervised

03:42

medical care versus those who are at low

03:44

risk for complications that can be sent

03:46

home

03:47

if interested in participating please

03:49

check out this incubator

03:51

and now i'll go on mute and turn the

03:53

control over to bill and jose ramon

04:02

thank you michael um and thank you jose

04:04

ramon for

04:05

uh agreeing to work with us today and

04:09

so why don't we start off with the very

04:10

first question

04:12

or the very first topic that michael had

04:14

raised about pandemics past and present

04:17

and then later we can segue into the

04:18

future and sort of discuss

04:21

really what has changed in what

04:24

what has anything changed and if it has

04:27

or has not what what are the things that

04:29

are similar what are some of the things

04:31

that are different than past pandemics

04:33

i think that's a great uh way to start

04:35

this conversation

04:37

and i also i'm very excited to hear what

04:39

you have to say

04:41

from your perspective from the vaccine

04:43

development side

04:44

versus my perspective as a prevention

04:47

and health education

04:48

perspective so from my side i would say

04:50

that

04:52

the messages are pretty consistent

04:54

across the centuries

04:55

the notion of maintaining distance

04:59

from people who may be infected the

05:01

notion of washing your hands often

05:04

the notion of wearing masks has been

05:06

clearly

05:08

a recommended since the 1917 flu

05:11

pandemic

05:12

and if we go further back in history the

05:14

notions of washing and distancing are

05:16

pretty consistent

05:20

yeah i i i completely agree in fact

05:24

one of the publications that was in

05:26

science

05:27

in 1919 which was following the 1918

05:31

pandemic

05:32

by uh professor george soper

05:35

i actually wrote this and i'm just going

05:36

to give a direct quote he said the

05:38

measures which were introduced for the

05:39

control the pandemic

05:41

were based upon the slenderous of

05:43

theories

05:44

respiratory diseases were not under

05:46

control

05:47

and then he went over and said what

05:49

stands in the way of prevention

05:51

and the first thing that he mentioned

05:52

jose ramon is actually in your court he

05:55

said the first thing that stands in the

05:56

way of prevention

05:57

is public indifference people do not

06:00

appreciate the risk they run

06:01

do you think anything's changed

06:06

no i mean it's it's uh it's sad to see

06:09

that especially in the environment where

06:12

we've been living for the last couple of

06:14

years

06:16

the notion of individualism seems to

06:18

prevail over the

06:20

feeling or an interest in the common

06:22

goodness or in the

06:23

common wellness so

06:26

because something is inconvenient for me

06:29

i'm not going to wear a mask or because

06:31

something i really want to get together

06:33

with my friends i'm going to have a

06:34

dinner party

06:35

or i really must go see my distant

06:37

relatives and i'm going to travel to

06:39

another location

06:41

and as we have not been able to speak

06:44

with one voice

06:45

as a nation we have not been able to

06:47

convey

06:48

one message of concern and clarity

06:51

regarding

06:52

this is serious this is how it doesn't

06:54

need to get any worse

06:56

has allowed for many different

06:57

conversations going in different

06:59

directions

07:00

and it's important to question

07:03

what we are told but to question

07:06

everything that comes

07:07

out from a so-called scientific basis

07:11

because i just want to question it has

07:13

led to a place that is

07:15

is not very good right now

07:18

yeah in fact jose roman one of the

07:20

things that we talked about

07:22

when getting prepared for this is that

07:24

the importance of the word and

07:27

and it seems like uh i won't even say

07:30

in the us i'd say globally it looks like

07:33

everybody's

07:34

about using the word or it is this way

07:36

or

07:37

that way is it pandemic real or is it

07:40

political

07:40

right and what we're talking about is

07:43

that the word and

07:45

where it's both just coming back to what

07:47

you were talking about

07:48

it is about public health and individual

07:51

health

07:52

and did you want to expand upon that

07:54

just a little bit because i think it is

07:56

about

07:57

there is an element of individual health

07:59

and public health

08:01

and it seems like we have two camps

08:03

absolutely unnecessarily so

08:06

and let me just go back to the first

08:09

pandemic of my lifetime the

08:11

hiv aids pandemic

08:14

where not unlike this time

08:19

it was a matter of choosing where to

08:20

allocate resources do we

08:22

focus on developing treatment and a

08:24

vaccine

08:25

versus do we focus on health education

08:27

and prevention

08:29

so the moment the conversation starts

08:31

with an ore

08:32

we lose half of the battle already

08:36

so the idea that we put

08:39

we we approach a public health crisis

08:41

from a uniquely medicalized

08:43

angle defeats the outcome immediately

08:47

so i think it's important to frame this

08:49

conversation and we need to do this and

08:51

we need to do that piece not one at the

08:53

expense of the other

08:55

yeah who do you agree i completely agree

08:58

in fact that one expanded

09:00

a little bit more so for certainly it is

09:02

about public health

09:03

and individual health because it's well

09:06

known that

09:07

during the pandemic some people's

09:09

individual health

09:11

actually began to suffer and depression

09:12

went up as an example and just sort of

09:14

preventative

09:16

diagnostics you know whether it be

09:18

mammograms or

09:20

as one example were really uh or cancer

09:23

screenings any cancer screenings were

09:25

down

09:26

but the other end in this is it is also

09:28

about micro

09:29

and macro economics at the same time

09:32

one of the things that i saw that sonic

09:35

kind of frightened me a little bit

09:37

is that according to the international

09:39

monetary fund

09:40

the debt is over 100 of the gdp globally

09:44

now

09:45

okay so it's over 11 trillion dollars

09:48

spent

09:48

on the pandemic so you know it seems as

09:52

though

09:52

we have to think about public health and

09:54

the economics so we don't

09:56

devastate economies globally at the same

09:59

time

10:00

and i i i think you know one of the

10:03

things we're talking about is we're

10:04

missing sort of

10:05

a real model that incorporates all of

10:07

these elements together

10:09

and so from a public health point of

10:12

view

10:12

do you see similarly absolutely i mean

10:15

right here in illinois where i live

10:18

we're just going to

10:19

reopen indoors dining because you know

10:22

when it's 10 degrees outside you cannot

10:24

have

10:24

outdoors dining anymore and the need to

10:27

have

10:28

some kind of economic engine moving

10:30

forward that allows people to stay

10:32

housed that allows people to buy food

10:34

that allows people to continue to send

10:36

their kids to school

10:38

is essential so what is the balance

10:40

between

10:41

we have to to allow for economic

10:44

activities to continue

10:47

and at the same time protect the

10:48

public's health

10:50

yeah and that's easier said than done if

10:53

we're going to be sitting at a

10:54

restaurant at a table and i'm going to

10:55

eat

10:56

i'm going to necessarily have to lift my

10:58

mask to eat and then put it down so

10:59

every

11:00

bite up and down and up and down it's

11:02

difficult it's complicated

11:04

so we need to be very careful on how we

11:06

craft our messages

11:08

to ensure that we take into account

11:10

people's fears concerns

11:12

but we're nonetheless firm and clear

11:15

about the importance to adhering to

11:17

certain behaviors

11:20

so i'm glad you mentioned the word that

11:24

uh we've got to keep it clear okay

11:27

so there's different quadrants uh that

11:30

a person could be located one would be

11:32

that your life is simple and easy

11:35

well wouldn't that be nice there's no

11:36

such thing but then there's the complex

11:38

and complicated and complicated means

11:40

that there's so many processes

11:42

right and complex simply means that

11:43

there's many unknowns

11:45

i think we've made ourselves in the

11:47

complex and

11:48

complicated and perhaps we should be in

11:50

the simple

11:51

clean messages even though the pandemic

11:54

is complex there's many unknowns

11:57

and i think from when i think about just

12:00

messaging from a public health point of

12:02

view and even from

12:03

many different from many researchers

12:06

i think they made it complex and

12:08

complicated and

12:09

that is when they lost the trust of the

12:11

public right i mean i mean you can

12:14

please talk about this but certainly in

12:16

the entire process of vaccine

12:18

development

12:19

and now they're rolling out the vaccines

12:23

what is the message that we're getting

12:24

at what how do we address the

12:27

fears and the concerns and the the

12:31

misinformation that prevails and that

12:33

gets disseminated perhaps even faster

12:36

than the actual science-based

12:38

evidence-based information

12:40

yeah yeah i i i

12:45

you know they they just did a um a study

12:48

using machine learning

12:49

using natural language processing of

12:52

social media

12:53

and how they want to deal with a vaccine

12:56

and roughly about

12:57

80 percent of the people were neutral

12:59

about 13

13:00

were negative and about 7 percent were

13:02

relatively positive

13:04

and the thing i find interesting is that

13:05

the megaphone of the 13

13:07

that are negative is the loudest right

13:10

and then they actually what it said is

13:12

that they're starting to affect the

13:14

neutrals

13:15

right and making them less uh you know

13:19

more of an anti-vaxxer as an example so

13:21

how do we address that

13:23

from the from the scientific and you

13:26

know heart science of science

13:27

the overall health

13:31

group how do we try to

13:33

[Music]

13:35

correct their incorrect information how

13:38

are we able to use those channels those

13:42

the media the social media to convey

13:45

information that is timely

13:47

easy to understand accurate and that

13:51

provides people with information they

13:52

need to make intelligent choices

13:55

yeah i'm going to come back to what we

13:57

talked about is that

13:58

instead of just focusing on just the

14:01

economy

14:02

and sort of denying the pandemic or just

14:05

instead of focusing on the pandemic and

14:07

scaring everybody

14:08

right that they won't even leave their

14:09

house and then they're not even

14:11

consuming

14:12

and they're not helping the economy

14:14

we're not

14:15

finding that middle ground in

14:18

in in in any conversation anymore we're

14:21

missing the and

14:23

right that i think it's easy to like i

14:25

can speak so i'm in florida right now

14:27

and in florida things are actually

14:28

pretty easy going

14:30

uh with respect to restrictions you know

14:32

we have to wear masks but

14:34

most uh companies are open most

14:36

restaurants are open

14:38

so i'm not in florida you're not seeing

14:40

the economic devastation

14:41

when people family members are visiting

14:44

from uh pennsylvania there it's much

14:48

uh this the state is more closed

14:51

and so really the cli it's probably

14:54

somewhere in between

14:55

florida and pennsylvania is where we

14:56

need to be as an example

14:58

right we don't need the whole economy we

15:01

don't need a lot of the economy closed

15:02

down but we don't need it

15:04

free willy-nilly where there's i mean

15:06

the outdoor malls here

15:08

were you wouldn't know it was any

15:10

different than uh from 2019

15:12

it was just so crowded i mean i didn't

15:14

go believe me i didn't go

15:16

but you could just see it from the car

15:18

on the highway right um

15:20

but it's just it's just amazing the two

15:22

extremes and where is the and

15:25

i think that's what we're missing

15:26

absolutely

15:28

and in that uh image that you present

15:30

between the

15:31

similarities or differences between

15:33

pennsylvania and florida or illinois in

15:35

this case

15:36

yeah i think we need to also acknowledge

15:39

that the the distribution of the

15:41

pandemic like in previous cases is an

15:44

uneven distribution of the burden of

15:46

disease right

15:48

there are certain communities that are

15:49

much more affected

15:51

both in their health in their economics

15:53

and their

15:54

ability to continue to be housed to feed

15:57

themselves etc

15:59

how do we go about it's not different

16:03

from previous pandemics we see it again

16:05

what is the bottom line why is this the

16:07

way it is

16:10

well you know i think that we were a

16:13

little bit too late

16:14

in identifying i think what we needed is

16:17

a common sense approach

16:18

by defining what are the hot spots

16:21

where you know this area is a hot spot

16:24

which would be probably more densely

16:27

populated cities and that's where you

16:29

have to take more severe measures

16:31

whereas more and more rural areas we

16:34

don't need

16:35

these uh you know strict uh measures on

16:38

how you know uh with respect to the

16:41

pandemic and i think it just depends

16:43

uh where because now they're using

16:45

machine learning to actually

16:47

predict and and actually apps on your

16:49

phone where they could predict where the

16:50

hot spots are well

16:52

if someone knew that there were hot

16:54

spots like for instance

16:55

in our community we actually knew where

16:57

there were some hot spots

16:59

and in fact they mapped it at various

17:01

different counties within the state of

17:03

florida so we

17:04

knew where there were problems and so

17:06

you just say okay i'm not going to go

17:08

near there or if you knew that there

17:09

were outbreaks at this particular

17:10

walmart or this target

17:12

right you wouldn't go there and i think

17:14

that it's just the information

17:16

access the information because everybody

17:18

has a mobile phone now

17:21

for better or worse yes for better for

17:24

work but that could be one way of

17:25

dealing with it it's just really

17:27

clear i think what you said is it's

17:28

clear information because

17:30

one of the things that you and i were

17:31

talking about before is in

17:33

epidemiology they have the sir model the

17:36

susceptible infectious recovery model

17:38

and this is basically where you can get

17:40

the r naught of the reproductive

17:44

oh my gosh i i'm having a hard time with

17:46

my words today

17:47

the the are not basically the reason how

17:50

fast the virus

17:51

actually um transmits from person to

17:53

person

17:55

and the thing that's interesting is they

17:57

found that

17:58

as an example r naught for justin bieber

18:00

is

18:01

24. okay the r naught for

18:04

sars cove 2 is about 2.4 so if justin

18:07

bieber

18:08

has a a an r naught of 10 times

18:12

and social media has taken both

18:15

information good information

18:16

and misinformation and misinformation

18:19

has

18:20

seems to have a very high r naught and

18:22

that's

18:23

you know we don't want a police language

18:26

because that's not

18:27

what we believe in but somehow we've got

18:30

to police

18:31

um somehow we've got to counter

18:34

misinformation

18:35

with truth absolutely

18:41

how do we make then the population of

18:44

uh a more educated

18:47

consumer or better able to discern

18:52

the truth from the rumor or the

18:54

speculation

18:56

yeah and to be honest i think

19:00

it it's at an individual level when you

19:03

actually have conversations

19:05

and i think sometimes people um

19:09

insult one group versus another group

19:12

and that's not the way of doing it

19:14

i think it's more of let's have the

19:15

discussion let's have an honest

19:17

discussion or an honest debate

19:19

and we should probably publicize these

19:21

types of things as well

19:22

so that there can so you know people can

19:25

hear both sides

19:26

here one with the evidence and hear one

19:29

with

19:30

well this is what i believe i believe

19:34

yeah i want to yeah it's a tough one

19:38

i wanna pick up on something that you

19:40

mentioned about the

19:42

the different areas that had higher

19:45

prevalence or whether it was

19:46

easier to acquire the the virus etc it

19:50

could be in larger urban areas or it

19:51

could be in meat packing factories in

19:53

iowa

19:54

so it was a density of the population

19:56

right it doesn't necessarily have to be

19:58

in the subway in new york city

20:00

so with that in mind now that we find

20:04

ourselves with a vaccine with a real

20:06

tool

20:07

and i'd like to equate that to a degree

20:09

with

20:10

back in the 80s if you had one less

20:12

condom

20:14

who did you give it to you gave it to

20:16

the person that was hiv positive

20:19

so if we have to decide on how to

20:22

allocate vaccines

20:24

who should we be prioritizing as we have

20:26

decided that we're prioritizing

20:29

frontline workers and then age groups

20:31

essential workers etc

20:33

is that from your perspective the best

20:36

way to go about it

20:40

um that is a loaded question and a very

20:43

good one okay

20:44

because it really gets into do we want

20:47

to follow

20:49

the math or do we want to follow or or

20:51

do we want to deal with the ethics of it

20:53

right

20:54

right and so if you follow the ethics of

20:57

it

20:58

you know you sort of the way that most

21:01

states have

21:03

enrolled the distribution of the vaccine

21:05

it's the healthcare workers first

21:06

because they're putting their lives in

21:08

line to help

21:08

and then it's the elderly because

21:10

they're the ones that truly

21:11

suffer from the pandemic have a greater

21:15

risk probability of suffering from the

21:18

pandemic more than the young

21:20

however if you there's a thing called

21:24

the prevention paradox

21:25

which basically says that you that the

21:28

people that you should work with

21:30

are the ones of low and moderate risk

21:32

not of high risk and you'll have the

21:34

biggest

21:34

impact on controlling the disease

21:37

epidemic

21:39

and that that probably falls within your

21:41

realm of public health

21:43

right but to control the pandemic it

21:46

mathematically i think it argues that

21:48

you want to deal with more of the people

21:50

that are spreading it

21:51

which are the ones that are low to

21:53

medium risk

21:54

of getting the disease as opposed to the

21:56

ones that are

21:57

high risk of actually of having

21:59

mortality

22:01

i think you're you're absolutely right

22:03

it's an it's an ethical question

22:05

and i don't think that anybody questions

22:07

the value of

22:08

uh vaccinating first the people that are

22:10

taking care and trying to control this

22:13

this pandemic but also we're dealing

22:16

with

22:17

a limited availability of vaccines right

22:20

now if we had

22:21

trillions of doses available right now

22:23

perhaps we would make different choices

22:26

i would like to think yeah

22:31

yeah because i was just looking at a few

22:33

numbers and i'm just going to go over

22:34

some right now because

22:36

the the challenge with this pandemic

22:39

you know from what you just talked about

22:40

is who should get the vaccine first

22:42

there's an ethical question and then

22:44

they're sort of like thinking about the

22:46

statistics of it

22:47

and who you should vaccinate which

22:49

they're not necessarily aligned

22:51

okay and the other thing that's not

22:53

aligned is that we have spreaders

22:55

and sufferers and the spreaders

22:58

are not the sufferers and that ends up

23:01

making this pandemic

23:03

kind of unique compared to the 1918

23:06

because in 1918 the um

23:09

the people that actually preferentially

23:11

died were the young people the

23:13

in their 20s in this case it's the older

23:16

people that died but

23:17

if you if you if you just look at the

23:18

numbers most of the people that spread

23:20

the disease

23:21

are between 15 and 54.

23:24

most of the people that suffer between

23:26

55

23:28

and over 85. wow and that's the

23:31

challenge of this one is between

23:33

the spreaders and the sufferers yeah and

23:36

this

23:36

is what is different from that pandemic

23:40

but yet the similarity remains on the

23:43

lack of the distribution in and of

23:48

itself was uneven people that lived

23:50

under

23:51

conditions in which they were more

23:53

clustered together perhaps were more

23:55

deeply affected that those who had

23:57

the ability of the the space available

24:00

to not be together at the same time

24:02

right among other things

24:07

yeah the other big difference between

24:09

previous pandemics and this one

24:11

is between asymptomatics and

24:13

symptomatics

24:15

uh the asymptomatics roughly are now

24:18

believed to comprise

24:19

of at least at least 20 percent of the

24:22

population

24:23

are believed to be asymptomatic so that

24:26

means that they have had the virus

24:28

and they probably spread it and didn't

24:30

even know

24:31

and that's that's a huge challenge

24:33

compared to other pandemics because

24:35

people are spreading it and they don't

24:37

even know

24:38

yes and yes this is also an airborne

24:41

transmission as opposed to others that

24:43

required vectors or intimate contact to

24:46

spread the

24:47

pandemics i think that what is common

24:51

as well is the

24:55

i think the fear and the misinformation

24:57

and back to this

24:58

not only disseminates faster but

25:02

sometimes trumps the adequate

25:03

information and people even people who

25:05

want to make the right choices are at a

25:08

loss as to what advice to follow

25:11

yeah and i'm still i mean in my head i'm

25:14

still

25:15

struggling with that when i say how do

25:16

we become

25:18

not only more aware but more proactive

25:23

about jumping faster

25:26

in order to not find ourselves in the

25:28

spot we

25:29

have found ourselves historically it's

25:31

like oops what happened

25:34

yeah yeah yeah you know

25:37

you mentioned the um aids pandemic

25:41

epidemic a few times and i just wanted

25:44

to go over

25:45

a few um different um

25:49

pandemics and with their death toll

25:53

and how long it took to develop a

25:55

vaccine

25:56

so if you think about the 1918 pandemic

25:59

the death toll was somewhere around 50

26:01

million people it took about 25 years

26:04

before they could actually deal with it

26:06

right

26:07

[Music]

26:08

sars which uh is the cousin to sarskov

26:13

um only about a thousand people have

26:15

died

26:16

and it's 17 years and ongoing without a

26:18

vaccine

26:19

right ebola about 11 000 people

26:23

um and it took 43 years to develop a

26:26

vaccine

26:27

aids it's around 25 to 35 million people

26:31

and no vaccine mostly because the virus

26:34

mutates so much

26:35

and then this covid19 we have somewhere

26:38

north

26:38

we're getting close to 2 million people

26:40

dying and we had a vaccine

26:42

in 11 months it's amazing and

26:46

so this so when even though we talked

26:49

that

26:50

nothing many things haven't changed from

26:52

social distancing to masks to

26:55

uh misinformation and public

26:57

indifference

26:58

one of the things that really changed

27:00

this time is

27:01

technology can you talk about that why

27:04

were we able

27:05

to get here so fast it's really like

27:07

light speed

27:09

it really is light speed and i think

27:12

it's due to a number of things right

27:14

um one is uh and

27:18

this sounds kind of silly but it's due

27:20

to money

27:21

uh you know uh operation warp speed in

27:24

the us provided a significant amount of

27:27

money

27:28

and that actually fueled a lot of things

27:30

and at the end it

27:31

fueled a lot of the advances so we even

27:33

have a vaccine now

27:34

how significant we're going to try to

27:36

interrupt you how significant is that

27:37

amount of money

27:40

i think it was extremely significant

27:42

because it took

27:43

what it did is the government bore the

27:45

risk

27:46

to develop the vaccine but more

27:48

importantly

27:49

even if people if certain companies

27:51

didn't take money to develop it

27:53

they could they they actually could

27:55

manufacture at risk

27:57

because the government was essentially

27:58

saying i will buy x you know

28:00

200 million doses from you at this price

28:03

so that was a huge incentive for the

28:06

pharmaceutical companies

28:07

and the biotech companies to actually

28:09

participate

28:10

and money fuels things so i think that's

28:12

one big difference

28:14

but that's not a technology the other

28:15

technology that really came in

28:17

were um basically sequencing technology

28:22

um so we can do deep level sequencing so

28:25

the

28:26

uh the sars code two uh

28:29

virus was sequenced within days if it

28:31

probably even faster

28:33

and sent out to the entire public and

28:34

then the the next thing that came

28:36

in is that we started bringing in

28:38

messenger

28:39

rna vaccines mrna vaccines and

28:42

they had never been tested before and or

28:45

approved before for a vaccine

28:47

but it ended up that they could uh there

28:50

were companies that went from

28:51

sequence to gmp material to start a

28:54

phase one

28:55

within 42 days was unprecedented

28:58

never been occurred before because of

29:00

technology so

29:01

there's a lot to be said that a lot of

29:03

people sort of poo poo poo

29:05

technology but it's because of

29:06

technology that we have a vaccine now

29:09

is there something to say for the

29:10

international cooperation behind this

29:15

you know um i i i'm

29:20

i'm i'm gonna say that the international

29:22

cooperation

29:24

was not very good okay

29:27

um i i can give multiple examples but i

29:30

probably won't

29:31

i i'll just give one right the us

29:34

dropped out of the whl

29:35

right but it wasn't largely countries

29:39

that were cooperating it was actually

29:41

multinational

29:42

companies because they're the only ones

29:45

that could actually move between various

29:48

countries

29:49

and they're profit driven i hate to say

29:52

it but again

29:52

money comes in and they were profit

29:55

driven and could move it through

29:57

now where some other things have come in

29:59

which have been really nice is there's

30:01

been things

30:02

uh the bill melinda gates foundation the

30:05

welcome trust

30:06

right um kovacs where they're trying to

30:08

say let's give

30:09

access to the vaccines to developing

30:12

countries as well

30:14

and that's where there's been more

30:15

international cooperation

30:17

but largely there hasn't been as much

30:20

international cooperation it's been a

30:22

little bit nationalistic and i think

30:24

we'll start to see that many

30:25

countries after this will say i want to

30:28

have vaccine manufacturing plants in my

30:30

country

30:31

right do you see similarly or

30:34

differently no i i agree with you

30:37

but i i recall in the beginning the big

30:40

talk about

30:41

the international corporation and this

30:43

german laboratory working with spicer

30:46

and then

30:47

the oxford astrazeneca piece and the

30:50

modern

30:51

and this international scientist but i

30:54

think you

30:54

you hit it in the head again it's it has

30:57

been

31:00

multinational industries that have been

31:03

the

31:04

the the catalysts to get this so fast

31:07

and

31:08

also i think we see it now that

31:11

there is again an uneven distribution of

31:14

resources

31:15

as to who's getting how much vaccine so

31:18

i think of my

31:19

native mexico where there's you know 130

31:22

million

31:23

people living and i think that the

31:25

supply of vaccine available is very

31:27

limited

31:28

and i imagine that in other parts of the

31:30

world the supply of vaccine is even

31:32

further limited and the

31:34

ability to distribute the

31:37

vials that we had to be at temperatures

31:41

of minus 60 degrees

31:42

is going to be very challenging yeah

31:47

i agree so just getting back to some of

31:50

the other things it wasn't just

31:51

technologies but as you mentioned it was

31:53

about partnerships

31:55

um it was also about health authorities

31:59

working with the companies and whether

32:02

it be

32:03

in europe or whether it be the fda in

32:05

the us

32:06

or other health authorities it's been a

32:09

about

32:10

global epidemiology which has been very

32:12

good um it's been about logistics

32:15

and we're going to talk about logistics

32:17

next because that's sort of the um

32:20

that's the that's the tall pull of the

32:23

tent

32:23

but i think it's been sort of a lot of

32:26

things from

32:27

technologies to partnerships to you know

32:32

to mrna to manufacturing

32:36

to funding to the science to health

32:38

authorities to epi i think

32:40

a lot of things have sort of come and

32:41

they've all converged at one time

32:43

which has been really comforting to see

32:46

that

32:47

globally we can pull together with

32:50

actually science and technology

32:51

sort of being the the uh the way to pull

32:54

it together

32:55

so are there no

32:58

things then because of

33:02

where we are in history

33:05

so none of these things would have been

33:08

possible

33:09

40 years ago because we didn't a have

33:12

the technology we didn't have the means

33:13

of communication we didn't have the

33:15

ability to create

33:16

so how much of the of the new of how we

33:20

deal with pademics is due to the

33:22

we are living in the 21st century the

33:24

second decade of the 21st

33:25

or third decade of the 21st century

33:28

versus we're better better human beings

33:31

we've learned from the past

33:34

is there a kumbaya moment that is not

33:36

happening here i'm

33:38

and i'm thinking towards the future how

33:41

we're gonna deal

33:42

with sars three

33:49

so it's interesting you mentioned that

33:51

because uh

33:52

just today or yesterday i got a

33:54

bipartisan

33:55

uh report uh called the apollo report

33:58

they talked about

33:59

what we could do in the future right and

34:02

one of the things that they which i

34:04

thought was really good and

34:07

but i'm just going to talk about one of

34:08

the things that they mentioned because i

34:10

think it's one of the more important

34:12

ones

34:12

is right now there's a difference

34:15

between a vaccine

34:16

and vaccination okay

34:20

so we understood before what i said is

34:22

how fast it took to develop

34:24

vaccines great we record speed now

34:28

because of technologies

34:30

the tall pole in the tent is vaccination

34:33

getting it to the people

34:34

right and so one of the things

34:37

so there's issues with cold chain uh

34:40

there's issues with two administrations

34:43

um you know there's just who gets it

34:45

first that we talked about before one of

34:48

the things that the apollo

34:50

committee came up with is that they

34:52

really want

34:54

a needle-free sort of oral

34:56

administration

34:58

and therefore it could be

34:59

self-administered

35:01

that would overcome a big bottleneck if

35:04

we start focusing on sort of mucosal

35:06

delivery

35:07

um and not needing a cold chain and i

35:11

think that's going to be

35:12

i think in the that that can help

35:16

the vaccination side of the equation if

35:19

that becomes real

35:20

so that's just one idea that i thought

35:22

was worth mentioning is that

35:24

that's such a big topic right now

35:27

is who's getting it um the long lines

35:30

and then there's all these charlatans

35:31

that have fake websites and they try to

35:33

get your information

35:34

and they're and so the idea is how do

35:37

you get it for the people well the

35:38

easiest way to get it to the people

35:40

is for them to administer it themselves

35:41

for an oral administration

35:43

like polio like polio exactly

35:48

um and uh so that would be one

35:51

i think that could be one way to help

35:53

with vaccination in the future

35:56

so if you were invited today to sit on a

35:59

panel

36:00

that is going to you know develop the

36:03

strategy

36:05

to prevent or to address the next

36:07

pandemic

36:09

what what would you bring from your

36:11

experience to date

36:13

in the area of vaccine development for

36:16

example and all the

36:17

conversations and all the operations

36:20

that happen behind the scenes what do

36:21

you

36:22

what would you want everybody to know

36:24

going forward

36:28

that um

36:32

the the the first thing i'd say is just

36:35

as

36:36

tesla has become an automobile company

36:39

because it

36:40

changed it into being a software company

36:43

right tesla at the end of it is a

36:45

software company

36:47

and we need to make this

36:50

make vaccine development and vaccination

36:53

more like software

36:55

where we can move at the speed of

36:56

electrons and not at the speed of humans

37:00

and i i would try to digitize everything

37:03

so sequencing is digitized now

37:06

then we have to think about how do we

37:08

synthesize

37:09

rapidly and so we can actually make

37:12

plasmid dna

37:13

um and then mrna is much is very fast

37:17

and then how do we actually think about

37:19

having

37:20

real having so much real world data that

37:23

we can actually have computer generated

37:25

clinical trials that are

37:26

just as predictive right so then you can

37:29

think about how do you digitize

37:31

everything and and and how do you

37:34

digitize a human

37:35

and predict how a human will respond

37:38

right

37:39

um all in all within computers all in

37:41

silicon and that's how you can do it in

37:43

rapid time

37:45

is and we're right at the precipice of i

37:48

think

37:49

really being able to engage upon that um

37:52

we're not there yet

37:53

but we're starting to get there i mean

37:55

there's been some really fascinating

37:57

um studies which have just come out

38:01

recently where they're

38:02

believe it or not it's kind of funny um

38:04

they're they're actually trying to

38:06

understand

38:07

uh the role of just repurposing drugs

38:10

and they're using machine learning to do

38:11

it

38:12

and they actually found that melatonin

38:14

of all things

38:15

has a probability of lower risk of covet

38:19

by like

38:20

20 to 30 percent than people who don't

38:22

take melatonin

38:23

it really gets into the importance of

38:25

sleep in fact when the pandemic came up

38:27

this is not a pr thing but i bought this

38:30

aurora ring

38:32

okay and this is basically a fully

38:35

uh uh it's a ring that actually has all

38:38

these electronics it measures your heart

38:39

rate variability it measures your core

38:42

temperature measure how many steps

38:43

right it measures your sleep patterns

38:45

whether you're in rem sleep

38:47

or uh deep sleep or light sleep and

38:50

this is an aside but my wife just got a

38:53

case of c

38:54

diff and when we knew that we had to do

38:57

something because this ring actually

38:59

gave out

39:00

warning signals about what's happening

39:02

with her heart rate variability

39:04

so we could actually take care of it

39:05

before it became really bad

39:07

we're taking care of it before it became

39:09

really bad so

39:11

i think you know just technologies

39:13

digitizing sensing

39:14

where you're you know all this

39:16

information starting to come in where we

39:18

can actually start to integrate all this

39:20

data together

39:21

and the idea of actually having you know

39:24

in silico humans right which we can

39:28

predict how how different subsets of the

39:30

population will

39:32

respond i think is uh is

39:35

within uh 10 10 to 15 year reach

39:39

that's one thought i don't know if you

39:40

agree or if you see a difference

39:42

i mean i'm a big fan of star trek and

39:44

have always been so i kind of envisioned

39:47

sickbay in star trek with a device to

39:50

scan a person and be able to tell these

39:51

things which

39:53

many of those things are becoming real

39:55

in my lifetime

39:56

yeah and it's it's it gives me hope for

40:00

the future because this is not

40:01

a pipe dream this is actually we're

40:04

almost there we're very close to those

40:06

kinds of things what i would add to this

40:08

is i would want to be invited to that

40:12

same group

40:12

and table and talk about the the

40:16

non-futuristic

40:17

still valid truths of today the

40:20

importance of a consistent message the

40:22

importance of trying to

40:23

alleviate the conditions that actually

40:25

create the basis for disparities and the

40:28

uneven distribution of disease

40:30

i would like to to ensure that there are

40:33

people that can come from different

40:35

angles and different perspectives and

40:36

can

40:37

offer why that would not work in this

40:40

particular community or that community

40:42

and that will be that awareness

40:44

in the development and distribution of

40:46

the out

40:47

of the prevention messages and of the

40:50

vaccine vials

40:52

so that kind of a more holistic approach

40:54

it's not the

40:55

or it would be really the end and have a

40:58

conversation that supports

41:00

both pieces so that we can have a real

41:03

positive outcome

41:07

so one of the things really important

41:10

about vaccination

41:12

is it's not just about protecting you

41:14

it's about protecting others

41:17

so the whole thing is it's about you and

41:20

me right again and thing

41:24

how do we get the message that

41:28

vaccination is about being others

41:30

focused

41:32

from a public health point of view right

41:34

because we're so

41:36

self-centered anymore and

41:39

i think we need to learn to be others

41:42

focused

41:42

and perhaps that's part of the challenge

41:45

absolutely

41:46

we've been working at apha on guidelines

41:50

with other partners to convey

41:54

messages that are vaccine positive

41:58

so rather than going what you said a

42:01

couple of minutes ago it's not about

42:02

punishing anybody

42:04

it's about helping people understand the

42:08

importance of this is something i do

42:10

for myself and for my community this is

42:13

something i do so that my neighbor can

42:15

return to

42:16

work this is something that i do so my

42:17

grandmother doesn't have to be

42:19

hospitalized this is something that

42:21

is not unprotected i'm good you figure

42:24

it out on your own

42:25

yeah it's really how are we a system

42:28

that is interdependent and that your

42:31

wellness is my wellness how can we make

42:34

it

42:35

a so that it's understood that way

42:38

is it's a task it's a task

42:42

yeah because if we're going to get hurt

42:45

immunity

42:46

you know the number depending on what

42:48

numbers you

42:49

listen to it's got to be somewhere

42:50

between 60 and 80 percent

42:52

of the people need to be vaccinated if

42:54

we don't get that hurt immunity then

42:56

these

42:57

mutants are going to start creeping up

42:59

more and more and then

43:01

you know the coronavirus could become

43:03

like a seasonal

43:04

uh vaccine that you have to take just

43:06

like influenza in which it mutates all

43:08

the time so

43:09

if if everyone's kind of participates in

43:11

this we could get the cured immunity

43:14

and actually try to stop the virus or at

43:17

least try to contain it a little bit

43:18

more than what we have that's what we

43:20

would hope for

43:20

right yeah yeah

43:24

yeah i'm just yeah i'm just i i guess

43:27

i'm just sort of

43:28

at a loss at uh

43:31

the idea of the misinformation

43:34

that not wanting to be others focused

43:37

and

43:38

what what have uh what are we turning

43:40

into

43:42

yeah i mean

43:46

i was speaking with some friends a

43:47

couple of months ago

43:49

and one of them was in charge of the

43:52

simulation disaster simulation

43:54

plans you know this tabletop exercises

43:57

where they

43:58

they envision crises and she was saying

44:01

that

44:02

in their exercises they have factored

44:04

everything for the outbreak and this and

44:06

you know where you go the hazmat suits

44:08

everything else

44:09

but one thing they had not factored into

44:12

that scenario was politics

44:16

politics was what sorry politics and

44:21

this has been a lesson this has been a

44:23

lesson because i think this is

44:25

new relatively new i mean you could

44:28

argue also that

44:29

i i would argue that during the eighth

44:31

span the mx politics had a lot to do

44:33

with the neglect

44:36

but it's certainly a factor that need i

44:39

don't know that it was a factor in in

44:40

1918

44:44

but certainly there's if we did a

44:46

regression analysis of all the variables

44:48

that have gotten us to the point where

44:49

we are i think that that variable

44:51

politics would account for

44:53

quite a degree of the variation of the

44:56

spread of the disease

45:01

i i agree i agree i think especially

45:05

initially

45:06

the first and then and then uh

45:09

and then things started to change slowly

45:11

but you're right and it

45:13

let it go but it's almost um this one

45:16

i think there was a little bit of

45:17

indifference uh you know i i have to

45:20

admit i'm in the vaccine world and i

45:22

heard about this in china and i

45:23

i actually sort of uh this is me

45:26

personally i sort of stuck my head in

45:27

the sand for a little bit and said well

45:29

you know

45:29

i just wonder if this is going to be

45:31

another uh

45:33

you know right zika right which

45:36

which uh sort of was really bad

45:39

because it caused microcephaly but at

45:40

the end it sort of just puffed away

45:43

and i was sort of half wondering you

45:45

know uh

45:46

is the sky falling is the sky falling

45:48

and is this going to be like another

45:50

zeke and do it i need to really think

45:51

about it

45:52

and uh i mean i was always watching it

45:55

but you know you never really pay

45:56

attention and

45:57

you you watch it and then all of a

45:59

sudden it hits and it's just like oh

46:01

i saw this coming why didn't i do

46:02

anything about it mr

46:04

in the vaccine world the rest of us mere

46:06

mortals

46:08

like what do we have to go with

46:11

right yeah i mean

46:14

it's uh i think we're going to be much

46:16

more aware and this gets into i see that

46:18

steven morris is asking a question about

46:20

surveillance

46:21

and some of this gets into surveillance

46:24

and

46:24

some of it is we need better

46:26

surveillance i completely agree

46:28

but some of it is we can't be too

46:32

lazy fair and we can't be too much of an

46:34

alarmist

46:36

and how to know which one is when to be

46:38

which one

46:40

uh can be kind of difficult and uh he

46:44

actually

46:44

his question was about the prevention

46:46

paradox you mentioned

46:48

um and would it require identifying the

46:51

spreaders first

46:52

without a good surveillance strategy you

46:55

can do that

46:56

period and that has been another problem

46:59

that there were so many surveillance

47:01

tools out there not consistent not

47:03

reliable

47:04

and everybody was doing whatever they

47:06

could be but there was not a loca uh

47:08

one repository of accurate information

47:12

yeah yeah if you can find the super

47:14

spreaders

47:15

those are the ones to get first

47:17

absolutely

47:18

and uh you know and i think some of the

47:21

surveillance that's out there

47:23

you know that at least that i'm aware of

47:25

g said

47:26

has been doing a really good job um and

47:29

they do it for flu

47:30

and for covet 19 but what would be

47:32

really nice is if we actually had

47:35

you know better surveillance for

47:36

respiratory diseases in general

47:39

and you know more holistically and not

47:42

but including rsv

47:44

um and just really monitoring these so

47:46

we can actually know but

47:48

but we still have to be careful of the

47:49

alarmist versus laissez-faire and to

47:51

know

47:52

when because if if we're too much of

47:55

alarmists all the time people are going

47:56

to get lacks and not believe

47:58

and uh and if we're too lazy fair

48:01

something's going to hit like it did

48:02

this time

48:03

and since you've gone to the questions

48:06

uh

48:06

in the time we have left there's some

48:08

really interesting questions here

48:10

uh one of which concerns clinical trials

48:12

and ways to

48:14

accelerate clinical trials you mentioned

48:16

earlier that in silico's where you want

48:19

to be

48:20

but is there a challenge studies both

48:24

ethically and technically

48:26

before we get to in silico

48:32

a good question so i'm gonna answer that

48:35

one in two parts if that's okay michael

48:36

so the first thing is to increase it

48:38

one of the things that they've done is

48:40

they've tried to find

48:42

what's known as predictive epidemiology

48:44

where they're using machine learning to

48:45

find

48:46

where the hot spots are and that's where

48:48

they would put up the clinical trial

48:50

site

48:50

and that's how you could really and so

48:53

some companies are actually using that

48:55

to

48:55

increase uh the phase three efficacy

48:58

trials and that's what's been

49:00

very unique about this pandemic is the

49:02

efficacy trials have been very fast

49:04

number one because it's a pandemic but

49:06

number two because they're trying to

49:08

put the clinical trial sites at hot

49:11

spots so they can get more cases

49:13

in the placebo group and hopefully less

49:15

cases in the vaccinated group to show

49:17

that there is atlaxian efficacy

49:19

now getting back to human challenge

49:21

models um

49:25

[Music]

49:26

yeah um that

49:30

human challenge models are typically

49:33

easier to do

49:34

when you have a therapy against it

49:38

okay so for instance there's human

49:41

efficacy trials against

49:42

influenza well it's because we have

49:44

antivirals against influenza that we

49:46

could have these

49:48

okay uh ethically we can have these

49:51

but for a pandemic when we didn't know

49:54

what if there was a therapy again now

49:56

there are some therapies but we didn't

49:58

know what the therapies were so it would

49:59

have been difficult to have a human

50:01

challenge model

50:02

if somebody got sick and you couldn't uh

50:05

first of all you didn't know if they

50:06

were gonna die or not which we don't

50:08

know

50:09

and then if we couldn't treat them so i

50:11

think if there

50:12

are for a pandemic if there is an

50:14

antiviral or therapeutic that could

50:16

reduce the disease severity after the

50:18

fact

50:19

um i think ethically you could do it but

50:21

otherwise i would

50:22

personally say there is

50:26

okay there is another question here

50:28

somebody's been doing their homework

50:30

because uh

50:31

in my rush to catch up with the the

50:33

seven minutes that we

50:34

had a late start i forgot to say that

50:36

that you were with sanofi

50:38

and in particular that you're in charge

50:40

of flu necks

50:41

and so somebody here has asked about a

50:44

broadly

50:44

uh protective influenza vaccine how do

50:46

you go about developing that

50:50

is there anything you can say

50:56

what would you look for in in any say

50:59

take

50:59

covet for example you now have mutations

51:02

coming about

51:03

you've indicated that you hope to slow

51:05

the rate of mutation with hurt immunity

51:07

but uh what would an approach be that a

51:10

technical community might be taking or

51:12

might consider taking

51:14

in order to create a broadly a broad

51:17

spectrum

51:18

anti-cova vaccine

51:22

so the first thing that they may want to

51:24

look at is

51:26

the antigen design and

51:29

which antigens are are conserved and

51:32

which ones are

51:33

more susceptible to mutations

51:38

the second thing is they may want to

51:40

look at the manufacturing platform

51:43

because just as an example if one was to

51:46

use mrna

51:48

you would get both t cell or

51:52

cellular mediated immunity as well as

51:55

antibody immunity

51:57

so you could actually get both arms of

51:59

the immune system versus a recombinant

52:01

which would largely be antibody based

52:03

now put in just to realize that most

52:06

vaccines that are out there are antibody

52:08

based

52:09

but covent as an example they believe

52:11

that the

52:13

protection comes from t cells and from

52:15

antibodies

52:16

so you could look at that you could look

52:18

at your clinical trial design

52:20

which by the way will become important

52:22

for covert in the future because for flu

52:24

as an example

52:25

most people are have already experienced

52:27

immunity to it

52:29

and so that will actually impact your

52:32

immune response if you've already had

52:34

uh immunity against it versus if you're

52:37

a naive host

52:39

so there's just a whole host there's a

52:40

lot of things from looking at

52:42

the role of the host looking at

52:44

effective mechanisms

52:45

looking at the antigen design or antigen

52:48

selection

52:49

to even thinking about how you want to

52:51

conduct your clinical trials

52:54

you know you mentioned about human

52:55

challenge models i think that's going to

52:58

become

52:58

very important for a broadly protected

53:00

because you want to see that

53:02

you know first of all you have to if

53:04

you're going to go to a regulatory

53:06

authority how are you going to define

53:08

universal how many strains which strains

53:11

are going to show

53:13

how how were these strains selected

53:15

right you have to show that they were

53:16

selected unbiased right

53:18

so there's a whole host of various

53:20

questions that

53:21

one has to grapple with you know which

53:24

host

53:25

uh you know in a immunocompromised host

53:28

an immunosuppressed host such as the

53:30

elderly

53:31

and a very naive host as in the

53:34

pediatrics or infants

53:36

so you have to when people use people

53:38

use the word

53:39

universal too loosely um

53:43

there's no such thing as a universal

53:45

anything really

53:46

i hate to say that but i mean

53:51

it's it's easy to use the word universal

53:53

it's hard to do it

53:54

so it's probably better to think about

53:56

something like a next generation

53:59

vaccine or a broadly protective but

54:02

universal

54:03

um if you i mean maybe that is possible

54:07

but

54:07

it's really hard to prove a universal

54:09

it's almost like trying to prove a

54:11

negative

54:11

point okay

54:15

um well we're we're sort of at the end

54:18

of time but uh we have a couple more

54:20

questions here if you don't mind hanging

54:21

around

54:22

we'll see what happens if the if if

54:25

riverside gives us back our seven

54:26

minutes or if they cut us off

54:28

but um uh there's a question here uh

54:32

richard garwin hypothesized that about

54:34

five to ten percent of the sars

54:36

kov2 infected individuals with the

54:39

highest viral loads

54:41

could be responsible for 90 to 95 of the

54:44

transmission

54:46

what do you think of that the hypothesis

54:52

do you want to take that word i think

54:55

i have that jose romano on the surface

54:58

it would seem like an easy yes

55:01

but i would want to know who those five

55:03

to ten percent

55:04

are and how much in contact with the

55:08

rest of the population they are

55:10

so if we were talking for example about

55:13

college students

55:14

that living in dorms then that could be

55:18

the super spreading opportunity is right

55:20

there

55:21

so depending on the context and

55:23

depending on the behaviors that these

55:25

[Music]

55:27

individuals are engaging in could be

55:30

easily responsible for that percentage

55:32

of the population

55:33

if they were a bus driver that was not

55:36

wearing protection correctly or the bus

55:39

was not well ventilated that could be

55:42

a different very different situation

55:44

from somebody that works from home

55:48

okay yeah just to follow up with that

55:52

question you know i i use the word

55:55

universal and i don't believe it but i

55:56

am gonna say that i

55:57

believe in one universal law which is

56:00

the 80 20 rule

56:01

you know some people say that 20 percent

56:03

giving 80

56:05

of the givings right but i've heard

56:08

that 20 of the population are giving

56:12

rise to 80

56:13

of the infections i think richard garwin

56:16

is sort of taking that sort of 10 to 90

56:18

percent

56:18

okay he's believing the 1090. um but i

56:21

think

56:21

i i think there's probably some truth to

56:23

it because that 80 20 rule seems to hold

56:26

all the time it really does and it's

56:28

really due to the role of these massive

56:30

super spreaders

56:31

uh so i think there could be some truth

56:33

to that okay

56:36

well thank you very much i think this

56:38

was absolutely awesome i could have

56:39

interrupted you

56:40

earlier but the conversation was so good

56:43

i felt we ought to let it go

56:45

and and we'll identify the rest of the

56:47

questions and uh

56:49

i'll try and figure out how to get

56:51

answers to those people who didn't get

56:53

their questions answered

56:54

um but in the interim uh thank you uh

56:57

this was our

56:58

first talk polly plexus i mean a

57:02

talk uh and and i am absolutely

57:04

delighted

57:05

uh i think it was wonderful the two were

57:07

marvelous guests

57:09

and uh i appreciate the time and the

57:11

energy and the thought that went into it

57:13

so so thank you very much