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to learn more. What would you.

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Like the power to do Bank

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of America any copyright. The

0:34

Economist. Hello

0:41

and welcome to The Intelligence from The

0:43

Economist. I'm Rosie Blore. And

0:45

I'm Jason Palmer. Every weekday we provide

0:48

a fresh perspective on the events shaping

0:50

your world. More

0:55

than 200 million people are infected

0:58

with malaria in Africa each year,

1:00

but progress in fighting the disease had

1:02

stalled. Now two

1:04

new vaccines and other clever innovations are

1:07

creating a buzz. And

1:10

there's a growing passion for a long

1:12

retired vision of 1950s domesticity in

1:16

which a woman's job really is no more

1:18

than making her home beautiful, her meals from

1:20

scratch, and her husband happy. We

1:23

meet the tradwives of TikTok. But

1:32

first... The

1:41

presidential campaigns of both Donald Trump and

1:44

Joe Biden are being run in the

1:46

shadow of America's justice system. Yesterday

1:49

Mr. Biden was the one to chalk

1:51

up an American first. His

1:53

son Hunter was convicted on three felony

1:55

charges, all related to the younger

1:57

Biden's drug use, lying on a federal ballot.

1:59

a background check and possessing a gun,

2:02

while, as the prosecutor put it, in

2:04

the throes of addiction. No

2:06

one in this country is above the law. Everyone

2:09

must be accountable for their

2:11

actions, even this defendant. However,

2:15

Hunter Biden should be no

2:17

more accountable than any other

2:19

citizen convicted of this same

2:21

conduct. Donald

2:23

Trump is being stalked by his own

2:25

Justice Department shadows and on

2:28

Monday had a crucial interview with his

2:30

probation officer. His hush money

2:32

felony convictions may yet get him a

2:34

prison sentence or probation or nothing at

2:36

all. To be blunt,

2:38

it's not a good look for either

2:40

candidate. And at this point, lots of

2:42

pollsters see these two men as neck

2:45

and neck, the election practically down to

2:47

a coin toss. Yet,

2:49

unlikely as it might once have seemed,

2:51

our data gurus think one candidate actually

2:53

has the edge here. Most

2:57

observers thought that the January 6th attack on

2:59

the Capitol and Donald Trump's second impeachment would

3:01

put an end to his political career. Dan

3:05

Rosenheck is the Economist's data editor. Now,

3:08

what once seemed unthinkable is starting

3:10

to look probable. The

3:12

Economist's new statistical forecast model gives Mr.

3:14

Trump a 60% chance of

3:16

returning to the White House. Okay,

3:19

how did you arrive at that number? How does this

3:21

model work? Our model

3:23

combines two main types of information,

3:25

polls and fundamentals. Fundamentals

3:27

are expectations based on historical precedence of

3:30

things like how the economy, presidential approval

3:32

ratings, and how long the president has

3:34

been in the White House tend to

3:36

affect election results. We combine

3:38

that with each state's track record of

3:40

voting in recent elections to come up

3:42

with a starting point estimate of how

3:44

each state is likely to vote and

3:46

thus determine the electoral college. We

3:49

then combine those expectations with all the

3:51

polls conducted of this campaign at both

3:53

the national and state level and

3:56

try to fit all of this information together into

3:58

a coherent picture. of

4:00

the electorate's true voting intentions. This

4:03

currently shows that although the national

4:05

popular vote is roughly a tie,

4:07

Trump has a narrow but clear lead in

4:10

all of the competitive states, particularly those in

4:12

the Sun Belt. And I

4:14

don't suppose that the model has any insights as

4:16

to how it is that Mr. Trump has has

4:18

risen to this level in the model after seeming

4:21

to be in the political wilderness a few years

4:23

ago. The model

4:25

looks at what people are telling pollsters,

4:27

not why. I

4:29

can offer some theories. Go on then, give

4:31

me some theories. The first thing is that

4:34

Joe Biden is extremely unpopular, and

4:36

historically, presidential elections have been referendums

4:38

on the incumbent, not the challenger.

4:41

There's lots of potential reasons for that,

4:43

but if we look outside the US,

4:45

the global bad of inflation in 2021

4:47

and 22, terrible for approval

4:49

ratings for incumbents all over the world, and

4:51

there's no reason to think that America would

4:53

be an exception. A

4:55

second factor is that Trump's biggest gains

4:57

in the polls have been with groups

5:00

who haven't voted in midterm elections or

5:02

off-year elections and don't tend to pay

5:04

a lot of attention to politics. Instead,

5:06

they're probably just looking at how things

5:09

are now, deciding they don't like Biden

5:11

and choosing to vote for the other

5:13

guy. One of the

5:15

most striking findings in recent polling is

5:17

that 17% of American

5:20

poll respondents blamed Joe Biden for

5:22

the end of the Roe v.

5:24

Wade decision that prevented states from

5:26

legalizing abortion, simply because he happened

5:28

to be in power when the

5:31

Supreme Court justices nominated by Mr.

5:33

Trump cast the necessary votes to

5:35

end Roe v. Wade. You

5:37

framed what you said there on the basis of

5:40

what Mr. Biden has done, or at least what's

5:42

happened during his tenure, not so much about what

5:44

Mr. Trump has done. So

5:46

voters have short memories. The Trump presidency was

5:49

four years ago, and particularly for young voters.

5:51

That's quite a long time. Trump

5:53

was recently convicted on 34 felony

5:55

counts in New York state, and

5:58

preliminary polling evidence suggests that

6:00

some wobbly voters in the middle may

6:02

be shifting either from Trump to Biden

6:04

or just from Trump to undecided in

6:06

response to that news. But

6:09

such effects tend to be small and short-lived.

6:11

For better or worse, the polls have barely

6:14

moved in the past six months and we

6:16

haven't yet seen any major surprises that would

6:18

inject more volatility into the race. Well

6:21

what kind of form might such surprises take?

6:23

What might change the stability the states is

6:25

here? I think it

6:28

would probably change the race substantially if

6:30

Trump were actually thrown in jail before

6:32

the election, but I think that's pretty

6:34

unlikely to happen based on the status

6:36

of all the court cases. Other

6:38

than that, I think the Fed cutting interest

6:41

rates could possibly give the economy a

6:43

tailwind that might help Biden, but

6:45

really, voters are mainly angry about the increase

6:47

in prices that happened in 2021 and 22,

6:51

not inflation now, and there's nothing anyone can

6:53

do to bring the price of eggs in

6:55

nominal dollar terms back to where it was.

6:59

So that's it then. You sound like you're

7:01

convinced that the spread that you see now

7:03

is likely to be the spread on Election

7:05

Day. I

7:07

think there's room for the polls to

7:09

move somewhat between now and Election Day,

7:11

but I wouldn't expect either candidate to

7:13

open an enormous lead. This

7:16

year's polls, like those in 2020,

7:18

have been remarkably stable. There

7:20

was a lot of up and down

7:22

volatility in 2016 and more significant

7:24

ups and downs in 2012, 8 and 4 as well.

7:28

I think part of the reason for

7:30

this stability is that the electorate has

7:32

become more polarized and in particular that

7:35

we're getting a rematch between two very

7:37

well-known candidates about whom opinions are pretty

7:39

firmly formed. And

7:41

let me ask you perhaps an uncomfortable question,

7:43

Dan. Why should we believe you? How reliable

7:46

is this model and why? All

7:48

statistical models like this extrapolate historical patterns

7:50

into the future, and they're only as

7:53

good as their training data. If

7:55

there's some fundamental shift in the way

7:57

American politics works, our model is... and

8:00

going to pick it up and its projections will

8:02

likely be very wrong. But we

8:04

are seeing a rematch between the same two candidates

8:06

that ran in 2020. So

8:08

at the very least, data from the most recent

8:10

cycle is probably going to give a decent indicator

8:13

of where things are likely to stand. In

8:16

2016, I think a lot of pundits

8:18

fell victim to what you might call

8:20

unthinkability bias, the idea that

8:22

just because something either hadn't happened before or

8:24

they thought it was so terrible that they

8:26

didn't want it to happen, they assumed that

8:29

it couldn't happen. Although

8:31

the 2016 election results relieved many

8:33

observers of those kinds of illusions,

8:35

I fear we're back in the

8:37

same place. It seems

8:39

unfathomable to a standard

8:43

observer of American politics

8:45

proceeding from conventional assumptions

8:47

and expectations that

8:50

a president who presided over the

8:52

January 6 attack on the Capitol

8:54

got impeached twice and has just

8:56

been convicted of 34 felonies

8:59

could ever be willingly returned to

9:01

office, not even just with an

9:03

electoral college majority, but it's

9:06

possible with an absolute majority of the

9:08

popular vote. Yet so far, this

9:10

year's polls are suggesting that there's a very

9:12

good chance that that might happen. Just

9:15

because you think something shouldn't happen doesn't mean

9:17

it won't. Dan, thanks very

9:19

much for joining us. My pleasure. Thanks for having

9:21

me. Thank you. You

10:12

probably recognize that sound. Though

10:16

I hate mosquitoes, they seem to love

10:18

me. But

10:20

in some parts of the world, these

10:22

insects aren't merely pests, they carry a

10:24

parasite that can kill. Studies

10:29

infected with malaria plague the ancient Romans,

10:32

and centuries later they infested the swamps

10:34

of Washington, D.C. Today,

10:37

the fight against the disease is

10:39

largely confined to a single continent.

10:43

97% of all deaths from malaria occur

10:45

in Africa. What's

10:47

astonishing about malaria is just how

10:50

many people it kills every year,

10:52

around And

10:55

mostly, this is children in sub-Saharan

10:57

Africa. Natasha

10:59

Loder is the health editor of The Economist.

11:03

From the year 2000, we made a

11:05

huge amount of progress in driving down

11:07

the number of cases and deaths from

11:09

malaria. But since

11:12

2015, progress has really stalled and

11:14

actually gone into reverse a little.

11:17

And this is not just a human

11:19

disaster, it's an economic one. These deaths,

11:21

these sicknesses are a huge drain on

11:23

household finances and on the

11:25

economy of these countries as well. And

11:29

we're now at quite a pivotal point

11:31

in the fight against malaria. Why

11:34

has this gone into reverse? Why is now such

11:36

a pivotal time? So funding

11:39

has plateaued. A significant portion

11:41

of the at-risk population in

11:43

Africa still lacks access to

11:45

basic interventions. And the other

11:47

thing that's happening is there

11:49

is a lot of concern

11:52

about emerging new threats. Mosquitoes

11:54

are developing resistance to insecticides

11:56

and also the malaria parasite

11:58

called Plasmodium felsoparium. the

12:00

worst form of malaria that you can get,

12:02

is actually becoming resistant to one of the

12:04

primary drugs used to treat it. And

12:07

so that's why we're just seeing

12:09

so many children continuing to die,

12:12

even when we do have quite a lot of tools that

12:14

could help. And what might some of

12:16

these other tools be? Are there other innovations that

12:18

are also giving us hope here? Yeah, well,

12:20

this is where it gets

12:22

really exciting, actually. First and

12:25

foremost, what we have today

12:27

for basic interventions would be

12:29

insecticide-treated bed nets, anti-malarial medicines.

12:31

There's quite a lot going on in

12:34

innovation as well. In the

12:36

vast majority of countries where malaria

12:38

is endemic, some mosquito

12:40

species have just become resistant to the

12:43

most common insecticide that is used to

12:45

treat these bed nets, the pyrethroids. And

12:48

so we now know that if you combine

12:50

this with another insecticide we have, that

12:53

that's going to be much better. It's going to

12:55

halve the chance of infection in children. There

12:57

are also tools like baits,

12:59

which lure mosquitoes with sugar and then

13:01

poison them. But one

13:04

of the most important is now

13:06

not one, but two groundbreaking new

13:08

vaccines. And we've had

13:10

the first one in really small quantities for

13:12

a couple of years, but it's

13:14

quite expensive. There's not much of it. But

13:16

what's happened now is a new

13:19

vaccine has started rolling out. It's

13:21

called R21. It's much cheaper. It's

13:23

been developed by Oxford University and

13:25

the Serum Institute in India. And

13:28

it can be made in huge quantities,

13:30

although there's only about 25 million doses

13:33

available so far. So

13:35

there's a lot of excitement about this new tool and

13:38

hope that this could represent

13:41

a turning point once

13:43

again in our efforts to drive

13:45

malaria out of Africa. Amazing

13:48

that we might be at a turning point. Why has

13:50

it taken so long to get this far? Well,

13:53

there's a short answer and a long one.

13:56

The short answer is firstly,

13:58

it was a really tricky scientific

14:00

problem to make a vaccine. And

14:02

also that it's

14:04

actually quite hard to make money

14:07

making vaccines for developing countries. And

14:09

so the first malaria vaccine that

14:12

we managed to make was by GSK,

14:14

the pharma firm. That was in 1987.

14:16

And it just wasn't a commercial product

14:19

for them. It hung around

14:21

for a long time. Eventually, people

14:23

like the Gates Foundation and other international

14:25

bodies supported it to

14:27

go through trials and eventually to

14:30

be manufactured. But GSK is

14:32

not particularly interested in making this vaccine

14:34

and has only ever committed

14:36

to making a small number of doses.

14:39

And so that's why this new vaccine R21

14:41

is so important. And it's

14:43

actually been down to the Serum Institute

14:45

in India and its

14:47

boss Adna Poonawala, which

14:49

saw this vaccine at an early stage

14:52

and said, we're going to fund trials.

14:54

We're going to manufacture this at risk.

14:56

We're going to build the plant to

14:58

make it in large quantities. And that

15:00

indeed is what's happened. So

15:03

it sounds like an incredible amount of progress,

15:05

but there's the risk that we might blow

15:07

the opportunity to do something

15:09

amazing because it's expensive. Yeah,

15:11

so the R21 vaccine is actually a

15:14

fraction of the price of the GSK

15:16

vaccine. But even so, it is expensive.

15:18

You need four doses. It's a little

15:20

over $3 a dose. And so the

15:23

money does need to be found. One

15:26

of the questions, of course, for developing

15:28

countries and also the international community is

15:30

how much money we're going to put

15:33

into these vaccines. What you really don't

15:35

want to happen is for countries

15:38

to say, oh, we've got a great new

15:40

vaccine. Let's stop funding bed nets. The

15:42

vaccines are not completely effective. And so

15:45

actually, if you want to save lives,

15:47

maximally, you're going to need bed nets

15:49

and vaccines. So until

15:51

we have even better vaccines that offer

15:53

even more protection, there's the question of

15:56

how much money are we going to

15:58

spend and how we're going to balance. spending

16:00

between vaccines and other tools that we

16:02

have to control malaria. Thank

16:05

you so much, Natasha. You're welcome. Tradwives

16:16

also believe that they should submit

16:18

to their husbands and serve their

16:20

husbands and family. And that triggers

16:22

people because the words

16:24

submit and serve. It makes women think

16:26

that we're saying that we're less than

16:28

a man. That's not what we're saying.

16:31

You're too smart just to be a housewife. Yes, I've had this

16:33

said to my face. Everyone wants to

16:35

make the world a better place, but for some odd

16:37

reason serving our families is not considered doing that. Putting

16:39

the needs of others in front of our own is

16:41

honorable. A question I ask myself often

16:44

is what legacy of servanthood am I modeling for

16:46

my family and my children? I'm

16:48

sorry if I'm a little out of breath and shaky.

16:50

I'm currently working out in

16:52

the home gym that my man provided

16:55

for me. I thought my life is so bad, guys. A

17:01

tradwife is a traditional homemaker, and we're

17:03

seeing lots of them on social media

17:05

telling other women how to look after

17:07

their homes and husbands. Caitlin

17:10

Talbot writes about culture for the Economist.

17:14

The hashtag tradwife has been viewed more than

17:16

600 million times on TikTok. So

17:20

who's making these videos? Why are they so

17:22

popular? So these videos

17:24

are being made by young women. I

17:27

see, I suppose, mid-20s. They

17:30

might already have a couple of children

17:32

or at least talk about wanting to

17:34

have children. They'll wear pretty floral dresses

17:36

usually, talk about frolicking and being a

17:39

homemaker. The idea of a housewife, it

17:41

comes from a history of idealizing parts

17:43

of domesticity. So cooking or

17:45

decorating have come to be seen as pastimes,

17:47

leisure activities that we do at the weekend.

17:49

There's also kind of a long history of

17:52

matrons who have offered advice. So

17:54

someone like Fanny Craddock in Britain. Everything

17:56

in life is so easy when you know the way. It's

17:59

just a question.