地平线系列：冠状病毒特别节目（2020）（2）

It goes to the surface of those cells
并被免疫系统的其它细胞所识别
which recognise by other cells of the immune system
这使得它们
and that triggers them
产生对抗COVID-19病毒的抗体
to make antibodies against the COVID-19 virus
全球约有二十五支团队正在使用这种方法
and around 25 groups around the world are using this approach.
尽管这些技术很了不起
These technologies are impressive
但无法保证这些方法能有效
but there is no guarantee that any of the approaches will work.
即使一种方法奏效了
And even if one does work
并且能安全地为民众进行大规模生产
and it can be safely mass produced for the general population,
这也仍然需要花费一年多的时间
it could still take well over a year.
目前 我们还必须要和病毒共存
For right now we're going to have to live with the virus
因为隔离措施并未能清除病毒
because the lockdown measures have not eradicated it.
随着国家开始复工复产
So as the country are starting to open up,
我们该如何在我们都想要的自♥由♥
how are we going to balance that great freedom
和第二波疫情的风险之间做出取舍
that we all want against the risks of a second peak?
我们该如何与病毒共存
如今 生活似乎开始有重回正轨的迹象
There are some signs of life beginning to return to normal.
但当隔离解除 我们走出家门时
But as we stepped our way out of lockdown
我们需要明白
we will need to understand
我们的行为会如何影响病毒的传播
how our behaviour affects the spread of the virus.
其中一种研究方法是使用数学模型
And one way of doing that is with mathematical models.
我们时常听到疾病爆发的模型
We keep hearing about the modelling of the outbreak
但这到底是什么意思
but what does that actually mean?
这是来自伦敦帝国学院的模型
This is the modeling from Imperial College London...
科学模型警告称
The scientific modelling warned that
英国正在遭受一场灾难性的大流行病
Britain was on course for a catastrophic epidemic...
在过去的两个月
Over the last two months,
我们的生活似乎被模型所掌控
our lives seem to have been controlled by models.
而它们将继续影响着对我们与病毒的共存
and they will continue to shape how we live with this virus.
数学模型能让你模拟出
Mathematical models allow you to simulate
病毒是如何在人群种传播的
how a virus spread through a population
但重要的是 它们也能让你可以测试出
but critically they also allow you to test
不同的措施会如何影响病毒传播
how different actions might affect that,
观察不同的情景
to look at different scenarios
并预测这些情景会如何发展
and predict how they will play out.
有很多不同的感染模型
There are many different models of infection,
但从本质上说 它们都是基于一个理念
but at their simplest they are all based on a single idea.
数学模型就像是模拟版的现实
Mathematical models are like a simulated version of reality.
你可以将其想作是电脑游戏一样的东西
You can think of them always as computer games.
如果我想模拟
If I want to simulate
一种病毒是如何在人群里传播
how a virus spread through a population,
首先我需要模拟一些人类
first I'm going to need some simulated people.
这里就是我的两百个模拟人
So here are my 200 individuals.
更复杂的模型不用屏幕上的这些圆点
The more complex models don't involve dots on a screen,
但与这个模型一样
but like this one
它们都会包含对人类行为的编程
they do involve programming in human behaviour.
在这个模型里 所有的人类都被编程
And in this version all my humans are programmed
以做出同样的行为
to behave in the same way.
下一步是将病毒引入这个人群
The next stage is to cede the virus into this population.
这个红点代表着一个被感染的人
This red dot right here represents an infected individual
而每位被感染的人都会继续感染其他人
and each infected individual can go on to infect others.
随着时间推移 感染者变成了蓝色
Over time infected individuals turn blue
这时他们要么已痊愈 要么没有
as they either recover or not,
但他们不会再去感染其他人了
but they stop infecting anyone else.
这里你有三组人群
You've got three groups of people,
有易感染 已痊愈 和已感染人群
you've got susceptible, recovered and infected,
去追踪人们是如何在这三个组里移♥动♥
and tracking how people move between those three groups
易感染
已痊愈
已感染
并计算这三个不同阶段的人数
and counting them at these different stages
就是你听说过的
is really at the very heart
所有流行病学模型的核心所在
of all of these epidemiological models that you have heard of.
正是这个原理让模型能去预测
It is this principle that allows models to predict
在任一时间点每个群组中会有多少人
how many people will be in each group at any one time.
当然 当你试图让这个模型
Of course, where it starts to become really tricky is
去模拟某一种特定的病毒时
when you try and get this model
情况就开始变得很棘手了
to be specific to a particular virus.
可以这样想这个过程
You kind of think of this in a way
你是在调整你的模型
that you are tuning your model,
你在努力地寻找某些特定的参数
you're trying to find the particular parameters that
能够让模型复♥制♥一种特定病毒的行为模式
let the model replicate how a particular virus behaves.
感染几率
感染持续时间
免疫持续时间
比如 你的编程可以针对
So, for example, you can programme in
你所知道的某人感染的持续时间
what you know about how long someone stays infected for,
或针对人们免疫的持续时间
or how long they are immune for,
这些参数将决定
and these parameters will determine
你模拟的流行病会如何发展
how your epidemic will play out.
而你对此病毒的了解越多
And the more you know about your virus,
你的模型对病毒会如何传播的预测就越精确
the more accurately your model will predict how it might spread.
然后你就可以测试像社交距离
You can then test the impact that interventions
这样的干预措施会有怎样的影响
like social distancing might have.
这些措施最终将改变再生数
Ultimately they change the reproduction number.
再生数是大家都在谈论的一个数字
The reproduction number is the number everyone talks about,
它是指一个人平均
It's how many individuals one person
会继续感染多少其他人
will go on to infect on average.
如果再生数大于一
If the reproduction number is greater than one,
疫情就在继续扩张
your epidemic is on the increase,
如果再生数小于一
and anything less than one
那么疫情就在缓和
then your epidemic is in decline.
我们现在担心 如果取消封锁措施
The worry now as we lift restrictions
感染人数会快速上升 导致第二次峰值
is that cases will quickly rise, causing a second peak.
科学家们估计 若不采取干预措施
Scientists estimate that with no measures in place
让学校开放 所有人都回去上班
so schools open, everyone back at work,
这次新冠病毒
this coronavirus has
将会出现大约为2.6的基本再生数
a basic reproduction number of around 2.6.
那我们怎么才能知道
So how will we know
哪些生活层面可以回归正常呢
what aspects of life can return to normal?
在伦敦卫生与热带医学院工作的
Based at the London School of Hygiene and Tropical Medicine,
罗莎琳德·埃戈医生是一个建模团队的成员
Dr. Rosalind Eggo is part of a team of modellers
他们团队为政♥府♥政策的制定提供信息
whose work informs government policy.
你好 很高兴见到你
Hi. Good to see you.
他们采用来自于
They've used data from
英国四万人的封锁前接触模式的数据
the pre-lockdown contact patterns of 40,000 people in the UK
来建造一个模型 其目的是测试
to produce a model that tests the impact
不同的干预措施会对再生数有何影响
that different measures might have on the reproduction number.
有些人会说 这很简单啊
Some people have just said, it is really simple,
你们针对整个人口做群体♥检♥测就好了
you do mass testing of the entire population
很容易啊 为什么你们做不了呢 罗丝
and you are done, right? Why can't you do that, Rose?
首先 测试量很大 而且有很多人
First of all, that's a lot of testing and a lot of people,
然后还要取决于人们在得到
and it depends on the behaviour of people
阳性检测结果后的行为
after they have a positive test,
取决于他们是否会减少接触机会
whether they decrease their contacts.
这个模型假设百分之十的人口
This model assumes that 10% of people
不会进行自我隔离
won't itself isolate
且是基于每天做四十六万次检测
and is based on 460,000 tests a day,
这比目前所进行的检测要多很多
many more than are currently being carried out.
我们认为人们只在很短一段时间内有感染性
We think that people are infectious for a fairly short time,
罗莎琳德·埃戈博士
伦敦卫生与热带医学院
所以只会在短时间内检测为阳性
so they will only test positive for a short time.
这不会像我们希望的那样
It doesn't have quite as much impact
会对再生数造成很大影响
on the reproduction number as we might hope.
群体♥检♥测
也许会从2.6降到2.5 差不多吧
Maybe change it from 2.6 to 2.5, something like that.
那基本没差别了
Almost nothing, then.
他们团队还研究了某数字化应用的使用
The group also looked at the use of a digital app
比如正在怀特岛上试用的那个
like the one being trialled on the Isle of Wight,
假设大概会有二分之一的人口会使用它
assuming roughly half of the population would use it.
这个应用可能会有用
The app might help
如果我们用它来做数字化接触追踪
if we use the app to do digital contact tracing,
如果那些警惕性高的人
if those people who are alerted decrease
能减少接触频率并执行居家隔离
their contacts and do quarantine at home,
这样可能会使再生数降到大约1.4