The Vital Data You Flush Down the Toilet | Newsha Ghaeli | TED

譯者: Lilian Chiu 審譯者: Yanyan Hong

Has it ever occurred to you, as you walk down the street,

當你走在街上時，可曾想過，

just how much data is flowing beneath your feet?

有多少資料從你腳下流過？

A wealth of information on our health and our well-being

有大量關於我們健康和安康的 資訊流經我們城市的下水道，

is running through our city sewers,

and we're all contributing to it every single time we use the toilet.

而每次我們使用廁所時 都貢獻了一點資訊。

Think about it.

想想看。

Everybody pees and poops,

每個人都會尿尿和大便，

and we know that urine and stool contain a rich source of information

而我們知道尿液和糞便 含有豐富的資訊，

on our health and our well-being.

和我們的健康與安康有關。

Our doctors look at it all the time to analyze for a variety of things.

我們的醫生做許多分析時 都常會用到它們。

Now, every time you flush,

每當你沖馬桶時，

you're sending this valuable information down into our sewers,

就是將這些寶貴的資訊 送到下頭的下水道，

where it's mixing with waste from hundreds of thousands of other people.

在那裡，它們會混入 來成千上萬人的排泄物中。

Once collected, it looks something like this.

收集起來就會像這樣。

This tiny sample

這個小小的樣本

comes from a wastewater treatment plant

來自一個廢水處理廠， 代表超過一百萬人。

that represents more than one million people.

And from it, we can detect all sorts of things about that community:

我們可以從這個樣本檢測出 關於那個社區的各種狀況：

the infectious disease viruses that are circulating in our bodies,

在我們體內循環的感染性疾病病毒、

chemical markers for the drugs that are most commonly consumed.

最常被使用的藥物的化學標記。

And we can analyze for all the bacteria that live in our collective microbiomes.

我們可以分析存在於我們 集體微生物群中的所有細菌。

Now, if this sounds too close for comfort,

如果這聽起來不太舒服，

just consider all the personalized data that you're parting with every day

那就想一下你每天在用

智慧手機或智慧手錶時 分享出去的個人資料。

when you use gadgets like your smartphone or your smart watch.

What's amazing about sewage

汙水有個神奇的特色，

is that it's naturally aggregated and anonymized.

它很自然就會做到匯整和匿名化。

Once flushed,

你的排泄物被沖走之後就會 和成千上萬人的排泄物混在一起，

your waste is mixing with that of thousands and thousands of people,

so there's actually no way to tie any information from here

所以實際上不可能把這裡的任何資訊

back to a specific person.

連結到特定的人。

Put differently, it's the perfect data dump.

換句話說，它是完美的資料傾倒場。

(Laughter)

（笑聲）

The thoughtful collection and analysis of sewage

對汙水做考慮周全的收集和分析

has the potential to radically improve health outcomes

有可能可以大大改善 世界各地城市的健康結果，

in cities around the world,

and it's a growing field called "wastewater epidemiology."

這是個正在發展的領域， 叫「廢水流行病學」。

And wastewater epidemiology is but one example

現今我們會在我們的城市裡 產生各種大數據，

of all the big data that we're generating in our cities today.

廢水流行病學只不過是一個例子。

Consider all the data that you generate with every phone call, package delivered,

想想你每打一通電話、寄一個包裏、

開一英里路的車所產生的各種資料。

mile driven.

It's data from cameras, sensors, drones,

資料可能來自於相機、 感測器、無人機、

air quality, water quality monitoring,

空氣品質、水質監測，

and the vast amounts of information generated by our health care

以及我們的健康照護 及教育體系所產生的大量資訊。

and our educational systems.

All of this information, these digital breadcrumbs,

所有這些資訊，這些數位麵包屑，

tell us unique stories about our cities and the way that we live our lives.

講述的是關於我們城市 及我們生活方式的獨家故事。

The thoughtful collection and analysis of this information

考慮周全地收集和分析這些資訊

has the power to inform real-time improvements

就能提供訊息來做即時改善，

to things like social policy,

能協助如社會政策、 環境管理、健康平權等等。

environmental management, health equity and more.

As an architect, I believe that we need to harness

身為建築師，

我相信我們必須要利用 這數億 TB 的資料，

the hundreds of millions of terabytes of data

that we're generating in our cities each and every day.

我們每天在我們的城市中產生的資料。

And this is important now more than ever,

此時，這點特別重要，

because for the first time in human history,

因為這是人類史上第一次

more than half of all people live in cities.

全人類有一半以上的人住在城市裡。

By 2050,

到 2050 年，

this number will grow to nearly seven in 10 people.

會增加到有七成的人住在城市裡。

Now just think about what that means for a second.

想想看這背後的意涵。

It means our biggest crises,

那就是，我們最大的危機，

from climate change to pandemics to growing inequality,

從氣候變遷，到疫情， 到越來越嚴重的不平等，

are going to hit cities first and hardest.

最先衝擊到的就是城市， 且這衝擊會是最重的。

But the era of big data offers an opportunity

但大數據的時代提供了一個機會，

可以用有創意的新解決方案 來處理這些問題。

for new and creative solutions to tackle these problems.

所以，咱們來深入探討 廢水流行病學帶來的機會。

So let's dive into the opportunity presented by wastewater epidemiology.

Some of you may have heard of it as it gained a lot of popularity

有些人可能聽過它，

因為在新冠肺炎疫情期間 它得到相當的知名度及注意力。

and attention during the COVID-19 pandemic.

2020 年，世界各地的研究團隊

In 2020, research groups from around the world

began detecting SARS-CoV-2 RNA,

開始在汙水樣本中檢測造成

the virus that causes COVID-19, in sewage samples.

新冠肺炎的病毒， SARS-CoV-2 的 RNA。

I was on one of those teams.

我隸屬其中一個團隊。

We and others showed that you can actually use sewage

我們和其他人證明了 實際上可以用汙水

as an accurate representation of COVID activity in our communities.

準確地代表我們社區中的 新冠肺炎活動。

讓我說明我的意思。

Let me show you what I mean.

Here we're looking at a time series over the course of the pandemic.

圖上的是在疫情期間的時間序列。

So from March 2020 through just last week.

也就是從 2020 三月到上週。

The blue line represents COVID virus concentrations in sewage samples

藍色代表

美國各地汙水樣本中的 新冠肺炎病毒濃度，

from across the United States.

In yellow, we see COVID clinical case data.

黃色的是新冠肺炎臨床病例資料。

For the first two years of the pandemic, case data was very reliable.

在疫情的前兩年，病例資料非常可靠。

People were getting PCR-tested all the time.

大家隨時都在接受 PCR 檢測。

During those two years,

在這兩年中，這兩組資料集 都追蹤得非常好，那很棒。

the two data sets tracked very well.

That was great.

It meant that sewage was also reliable

這意味著汙水也是可靠的，

and an accurate representation of disease burden.

可以正確反應出這些疾病負擔。

However, over the past year and a half to two years,

然而，在過去一年半到兩年中，

we've seen a divergence in those data sets.

我們看到這兩組資料集出現分歧。

People just aren't getting COVID-tested nearly as often.

大家沒那麼常做新冠肺炎檢測了。

Sewage, on the other hand,

另一方面，汙水

doesn't require us to access health care services.

並不需要我們去使用 健康照護服務才能被記錄到。

We're all represented just by peeing and pooping.

樣本會代表所有有尿尿和大便的人。

Throughout the pandemic, we and others also showed that sewage is predictive

在整個疫情期間，我們和其他人 也證明了可以用汙水來做預測，

and a leading indicator of new COVID clinical cases.

且是預測新冠肺炎 臨床新病例的領先指標。

This is because infectious disease viruses incubate in our bodies

這是因為感染性疾病病毒 會在我們的體內醞釀，

before we develop symptoms or go get tested.

且在我們出現症狀或去做 檢測之前就開始醞釀了。

Meanwhile, we've been excreting the virus for days.

而這幾天我們也一直在排泄出病毒。

During COVID,

在新冠肺炎期間，已證明 在預測臨床病例方面汙水是

it was shown that sewage was anywhere between one to three weeks

leading indicator for clinical cases.

一到三週的領先指標。

Now I'm going to show you an example

接著我要舉個例子，有一回， 這促成了影響社區的重大決策。

of one time that this led to a big community-impacting decision.

Here, we're looking at data from the Boston area

現在看到的是來自波士頓地區的資料，

during the Omicron wave.

時間是 Omicron 流行期間。

In December 2021, towards the end of the month,

2021 年十二月的月底，

COVID cases began to skyrocket across the country

全國各地的新冠肺炎 病例數開始向上衝，

and didn't slow until the end of January.

到一月底才緩下來。

Boston Children's Hospital, though, was ready.

不過，波士頓兒童醫院 已經做好了準備。

They had been looking at Boston area sewage

他們一直在關注波士頓地區的汙水，

在幾週前就發現汙水病毒濃度上升，

and saw the sewage levels go up weeks earlier,

so they proactively postponed all non-emergency medical procedures.

因此他們主動延後了所有 非緊急的醫療程序。

They wanted to free up resources so that they could adequately respond

他們想要騰出資源，讓他們能妥善因應

to the incoming wave of hospitalizations.

接下來的住院潮。

Now wastewater epidemiology has been used

廢水流行病學也有被用來 處理其他迫切的健康議題。

to tackle other pressing health issues as well.

Before the pandemic,

在疫情之前，

the biggest public health crisis in the United States

美國最大的公共衛生危機

was our growing drug epidemic.

是日益嚴重的藥物氾濫。

用藥過量

Drug overdoses were growing year over year

一年比一年多，且已成為 五十歲以下的美國人

and had become the leading cause of accidental death

for Americans under the age of 50.

意外死亡的主因。

In 2018, a small town in North Carolina had seen overdoses go up,

2018 年，北卡羅萊納州的一個 小鎮發現用藥過量越來越多，

and they wanted better information,

他們想要有更好的資訊、

better data to know what to do about it,

更好的資料，以了解該怎麼做、

what was driving this trend and how to respond.

這個趨勢背後的推手 是什麼，以及如何因應。

So we turned to the sewers, and together with the mayor's office,

因此，我們把注意力轉向下水道， 和市長辦公室合作，

we began to analyze sewage samples from several sites across the city

開始分析來自城市中 數個地點的汙水樣本，

and were able to show that prescription opioids

得以證明處方鴉片類藥物

were the drug most commonly consumed, not injectable opioids.

是最常被使用的藥物， 而非注射型鴉片藥物。

Equipped with this data,

有了這些資料，

the city diverted resources from needle exchange sites

該城市把資源從針頭 交換站點轉移出來，

and put that money into medication takeback programs instead.

把那筆錢改投入藥物取回計畫。

They advertised and held dozens of town halls

他們打廣告，並舉辦了 數十場市政廳公眾會議來談論

where they talked about the adverse effects of prescription painkillers.

處方止痛藥的不良影響。

That year,

那一年，

the city saw a 40 percent reduction in overdoses,

該城市的用藥過量減少了四成，

and for the first time,

且頭一次，

they had engaged their community in a dialogue around drugs,

他們讓他們的社區 參與了對談，討論藥物、

addiction and overdose.

成癮，以及用藥過量。

Now imagine if every city around the world had access to this sort of information.

想像一下，如果全世界的每個城市

都能取得這類資訊，會如何？

Before the pandemic,

在疫情之前，廢水流行病學 只是個很小的領域，

wastewater epidemiology was a tiny field

with no more than a dozen experts worldwide.

全世界這方面的專家不超過十二位。

Today, 72 countries

現今，有七十二個國家

have used wastewater monitoring to understand COVID-19.

採用廢水監測來了解新冠肺炎的狀況。

And it's time that we leverage these investments

現在我們可以好好利用這些投資，

to monitor for all sorts of other things as well.

來做其他各式各樣的監測。

Imagine knowing when influenza and RSV are going to peak every year

想像一下，若知道每年何時流感 和呼吸道合胞病毒會達到高峰，

so that our hospitals can prepare.

醫院就可以做好準備。

Imagine mapping nutrition in our cities

想像一下，能夠繪出 我們城市的營養地圖，

so that we can identify food deserts

幫助我們辨識出食物沙漠，

and understand social determinants of health.

並了解決定健康的社會因子有哪些。

Imagine identifying superbugs and antibiotic resistant genes

想像一下，能辨識出超級細菌

及抗生素耐藥基因，當它們 出現在我們的社區時就能發現。

as they emerge in our communities.

Imagine preventing the next pandemic before it happens.

想像一下，能在下一次 疫情發生之前就預防它。

In the way that cholera prompted London to build modern-day sewer systems,

就如同霍亂促使倫敦建造 現代的下水道系統，

and poor health in the tenements of New York City

以及紐約市廉價公寓居民健康不佳

were one of the catalysts behind the building of Central Park,

是建立中央公園背後的催化劑之一，

this is how our cities can learn from COVID-19.

我們的城市以這種方式 從新冠肺炎疫情中學習。

And this is precisely how we can foster a new, intelligent kind of urbanization.

我們也能以這種方式， 促進新型且明智的都市化。

For years now, scientists, policymakers,

至今已經很多年，

科學家、政策制訂者、 建築師，以及都市規劃師

architects and urban planners

have been harnessing the power of technology and big data

都一直在利用科技和大數據的力量

to future-proof our cities.

讓我們的城市為未來做好準備。

Over the last decade,

在過去十年，

chief technology officers have been appointed in cities

世界各地的城市都安排了 技術長這個職務。

around the world.

Roles once reserved for the boardrooms

過去只為矽谷董事會 會議室和走廊保留的角色

and hallways of Silicon Valley

現在終於在市政廳中開放了。

are now finally open in city hall.

因此，當你下次刷信用卡、

So next time you swipe your credit card,

take a ride in a taxi or tap your MetroCard,

搭乘計程車，或感應捷運卡時，

just consider how you're contributing

想一下你正在如何為城市不斷 成長的數位基礎設施做出貢獻。

to your city's ever-growing digital infrastructure.

And next time you use the toilet,

當你下次上廁所時，

just remember, you're doing your civic duty.

別忘了，你是在履行你的公民職責。

(Laughter)

（笑聲）

Thank you.

謝謝。

(Applause)

（掌聲）