- So there's a new ritual that a lots of us share right now.

- 是以，現在有一個新的儀式，我們很多人都有。

Checking our temperature to see if we have a fever.

檢查我們的體溫，看我們是否有發燒。

And it's understandable.

這也是可以理解的。

Fever's are common symptoms of COVID-19.

發燒是COVID-19的常見症狀。

But if you're hoping your temperature is a nice 98.6 degrees

但是，如果你希望你的體溫是一個漂亮的98.6度

or 37 Celsius.

或37攝氏度。

You might learn something new about yourself.

你可能會學到一些關於你自己的新東西。

- 97.25.

- 97.25.

- 98.2.

- 98.2.

- 97.1.

- 97.1.

- Very low,

- 非常低。

Am I OK?

我還好嗎？

It turns out 98.6 degrees fahrenheit isn't really the

事實證明，華氏98.6度並不是真正的

ideal or normal body temperature.

理想或正常體溫。

There's really no such thing.

真的沒有這回事。

But temperature can still tell us a lot about our health.

但是溫度仍然可以告訴我們很多關於我們健康的資訊。

And about the spread of COVID-19.

還有關於COVID-19的傳播。

(temperature machines beeping)

(體溫機發出嗶嗶聲)

The number 98.6 mostly came from 19th century German

98.6這個數字主要來自19世紀的德國

researcher Carl Reinhold August Wunderlich.

研究員卡爾-萊因霍爾德-奧古斯特-吳德利希。

He claims to catch the numbers of more than a million

他聲稱抓住了超過一百萬的數字

in temperature readings to thousands of patients.

在溫度讀數中，有成千上萬的病人。

And he arrived at the number of 98.6.

而他得出的數字是98.6。

That number has stuck around ever since.

這個數字從那時起就一直存在。

But person to person

但人與人之間

it's kinda meaningless.

這有點毫無意義。

We asked our co workers to take their own readings

我們要求我們的同事們自己讀出他們的讀數

and this is what normal temperature looks like for us.

而這就是我們的正常溫度的樣子。

- 95.83.

- 95.83.

- 96.7 which seems low.

- 96.7，這似乎很低。

- I'm a cold,

- 我是個冷門。

cold man.

冷酷的人。

- Maybe [Inaudible]

- 也許[聽不清]。

I would have thought.

我本來以為。

- It's fine.

- 這很好。

I guess.

我猜。

- Wunderlich himself knew that body temperature varied.

- 吳德利希自己也知道，體溫是有變化的。

He recorded a healthy range from 97 and a quarter

他錄得的健康範圍為97和1/4

to 99 and a half in his subjects.

到99.5在他的科目。

Other studies have shown that temperature can differ

其他研究表明，溫度可能不同

noticeably across age, gender, size and race.

在年齡、性別、體型和種族方面有明顯的差異。

And modern research points to a much lower number.

而現代研究指出，這個數字要低得多。

Around 98.

98年左右。

That squares with our very informal staff average.

這與我們非常非正式的員工平均水平相吻合。

We're around 97.5.

我們在97.5左右。

- You let her write the thermometers broken.

- 你讓她把溫度計寫壞了。

I don't know.

我不知道。

- What's more, you yourself don't have one body temperature

- 更重要的是，你自己並沒有一個體溫

you have a range.

你有一個範圍。

Our team all took their ratings at 10am.

我們的團隊都在上午10點進行了評級。

But if you took yours a bunch over the course of a day,

但如果你在一天內拿了你的一堆。

you'll see it change.

你會看到它的變化。

Most people are coolest in the morning

大多數人在早上是最酷的

and warmest in the early evening.

並在早晚時分最溫暖。

It's a reflection of your bodies natural rhythms,

這是對你身體自然節奏的反映。

your digestion, hormone production and cognition and more.

你的消化、荷爾蒙分泌和認知等方面。

Here's what my temperature looks like

這是我的溫度看起來像什麼

throughout the day.

整天都是如此。

- Other bodily cycles like ovulation can cause small

- 其他身體週期，如排卵期，可引起小

swings in temperature too and different parts of you

溫度也有波動，你的不同部位也有波動。

are different temperatures.

是不同的溫度。

Under the tongue, armpit, forehead and rectal readings

舌下、腋下、額頭和直腸讀數

are all likely to be unique.

都可能是獨一無二的。

Point is there are tons of variables.

關鍵是有大量的變數。

We could be many temperatures all at once all the time

我們可以同時成為許多溫度，一直都是如此。

and still be perfectly healthy.

並且仍然非常健康。

- But being sick is another story.

- 但生病是另一回事。

(theme sound)

(主題音)

So, I spoke with a couple of people who are connecting

是以，我與幾個正在聯繫的人進行了交談

some interesting dots

一些有趣的圓點

between temperature variation

溫度變化之間的關係

and an illness like COVID-19.

和COVID-19這樣的疾病。

When you get sick,

當你生病的時候。

many of your bodies natural predictable rhythms

你身體的許多自然可預測的節奏

start to destabilize.

開始不穩定。

Your temperature might fluctuate more radically

你的體溫可能會有更劇烈的波動

and it might crank up above your natural range.

而且它可能超過你的自然範圍。

That's your body triggering a fever to make itself

這是你的身體引發了發燒，使自己

less hospitable to viruses or bacteria.

對病毒或細菌不太友好。

In other words

換句話說

your body temperature gets anomalous.

你的體溫變得不正常。

That's trouble for you,

這對你來說是個麻煩。

but for people tracking COVID,

但對於追蹤COVID的人來說。

it's crucial data.

這是很關鍵的數據。

One effort is Kinsa.

一項努力是金莎。

A company that tracks the spread of infectious disease

一家追蹤傳染病傳播的公司

using fevers.

使用發燒。

Kinsa sells a smart thermometer that sends your

Kinsa公司銷售一種智能溫度計，可以將你的

temperature back to the company every time you take it.

每次拿的時候都有溫度回饋給公司。

Kinsa says they have about a million thermometers

Kinsa說他們有大約一百萬個溫度計

in circulation.

流通中。

And with all that data,

而在所有這些數據中。

they've built a real time health weather map.

他們已經建立了一個實時的健康天氣圖。

It shows possible hot spots of COVID,

它顯示了COVID的可能熱點。

counties with more fever then flu season would explain.

有更多發燒的縣，那麼流感季節就可以解釋。

- Let's take our real time signal

- 讓我們來看看我們的實時信號

remove the expected value cold and flu.

刪除預期值感冒和流感。

What's left over is residual.

剩餘的是殘餘的。

That residual is a typical, in this particular

這種殘留物是一個典型的，在這個特定的

analysis a typical fever clusters.

分析一個典型的發燒群。

Things you would not expect.

你想不到的事情。

What we found since that point is that

從那時起，我們發現的是

there's a very high correlation between our hot spots

我們的熱點之間有一個非常高的相關性

and COVID-19 cases.

和COVID-19病例。

The work is not peer reviewed yet.

這項工作還沒有經過同行評審。

And some experts question how reliable it can be

而一些專家質疑它能有多大的可靠性

with only a million thermometers.

只用一百萬個溫度計。

Their user space could also be biased

他們的用戶空間也可能是有偏見的

by race or class or other factors.

按種族或階級或其他因素。

But Kinsa still thinks it can tease out

但Kinsa仍然認為它可以挑出

some interesting trends,

一些有趣的趨勢。

like the effect of social distancing.

像社會疏遠的影響。

Here's their look at Miami-Dade County

以下是他們對邁阿密-戴德縣的看法

in the middle of March.

在三月中旬。

In 9 days,

在9天內。

the percent of people with a fever

發燒的人的百分比

more than doubled.

增長了一倍多。

And around the 17th and 18th,

而在17日和18日左右。

they started implementing the closure bars.

他們開始實施封閉條。

So it starts going down.

所以它開始下降。

- Other researchers are taking a different attack.

- 其他研究人員正在採取不同的攻擊方式。

Looking for clues in body temperature that might

尋找體溫方面的線索，可能

predict a fever before it starts.

在發燒之前預測發燒。

- One study out of UCFS would collect temperature

- UCFS的一項研究將收集溫度

and other health data from participants by using a

和其他健康數據的參與者，通過使用一個

smart ring.

智能戒指。

The rings can measure small changes in body temperature

這些戒指可以測量體溫的微小變化

every minute.

每一分鐘。

The question is, can tiny temperature rhythms

問題是，微小的溫度節律能否

predict a brewing infections like COVID.

預測像COVID這樣的醞釀中的感染。

- And so we could pick up with great reliability

- 是以，我們可以非常可靠地拿起

those ultranium rhythms, those within a day rhythms,

那些Ultranium節奏，那些在一天之內的節奏。

that there are frequency that tend to tell us about

有一些頻率傾向於告訴我們關於

how stagily your hormones passing along, how synchronized

你的荷爾蒙如何錯落有致地傳遞，如何同步進行

are they inside of you.

他們是你的內心。

- It's early days for the study

- 該研究還處於早期階段

but once smart ring user

但一旦智能環的用戶

who tested positive for COVID has already shared

對COVID檢測呈陽性的人已經分享了

some interesting data.

一些有趣的數據。

- The temperature rhythms that I receive within the day

- 我在一天之內收到的溫度節律

start to sort of destabilize and amplify

開始有點不穩定和放大

before they have a fever

在他們發燒之前

right up to about 5 days beforehand.

直到約5天前。

The whole system would look like

整個系統將看起來像

it was sort of increasingly like a teeter totter

越來越像一個蹺蹺板了

before they have a fever,

在他們發燒之前。

before they felt sick.

在他們感到不適之前。

- Again that's just one patient.

- 同樣，這只是一個病人。

But with enough data,

但只要有足夠的數據。

the team hopes to build an algorithm

該團隊希望建立一種算法

that can sniff out COVID via rhythms like these.

可以通過像這樣的節奏嗅出COVID。

- We will be publishing the findings

- 我們將公佈研究結果

we will be putting out, you know,

我們將推出的，你知道。

competition or calls for [Inaudible]

競爭或呼籲[聽不清]

get everybody in the room

讓大家都到房間裡來

let's get this as good as we could possibly get it.

讓我們儘可能地把它弄好。

This is really just

這其實只是

how big of a defense can we make.

我們能做多大的防禦。

How quickly to get this into service.

如何快速將其投入使用。

- In the coming months while we take our temperatures

- 在未來的幾個月裡，當我們對我們的溫度

every minute like maniacs

每分鐘都像瘋子一樣

we're going to be hearing a lot more about the effort

我們將聽到更多關於這一努力的消息

to track and predict COVID-19.

來跟蹤和預測COVID-19。

Scientists will learn more about how the human body

科學家們將進一步瞭解人體如何

regulates itself and respond to disease.

自我調節並對疾病作出反應。

And along the way,

而在這一路上。

we might let go of some assumptions about what's normal

我們可能會放棄一些關於什麼是正常的假設

and healthy.

和健康。

- Obsessing about 98.6 is really false precision right?

- 執著於98.6確實是假的精確性吧？

Everybody should have a nice daily rhythm of their

每個人都應該有一個美好的日常節奏。

temperature.

溫度。

The only time your temperature is constant is when your dead

你的溫度唯一不變的時候就是你死的時候

and it's room temperature so

而且它是室溫的，所以

thinking about

思考

the patterns of change rather than the absolute number

變化的模式，而不是絕對數量

is much more important.

是更重要的。

- Psst cat, go on.

- Psst cat, go on.

Oh cat get outta there.

哦，貓離開那裡。

Cat [Inaudible]

貓 [聽不清]