This is Scientific American's 60-second Science, I'm Steve Mirsky.
Here in New York the coronavirus cases are exploding—we're on the steep part of the curve. You've probably heard about the basic reproduction number, R0, or R-naught. And that's basically how many people an infected person goes on to infect themselves. The other night, I happened to see a tweet that showed just how big a difference there is over 10 cycles of transmission between a basic reproduction number of 1.3 and a basic reproduction number of 3. The different was astounding. The 1.3 after 10 cycles infected on average 14 other people total. The basic reproduction number of 3.0 led to 59,000.
Looking at those numbers was startling. So I got a calculator out. And I'm going to repeat this exercise that I did with the calculator. And you can do it, too. It's even a little bit fun. And it's kind of amazing. So I've got two calculators, because I'm going to do the two different basic reproduction numbers, the R-naughts, together.
Okay, so the calculator on my left—I'm going to assume 1.3 as the basic reproduction number. Each person infects 1.3 other people on average. The calculator on the right—I'm going to do 2.5—just to pick a number and because that looks like it may be fairly close to what the coronavirus number is.
So we'll start with one person (1) on each side. We multiply by 1.3 on the left to get 1.3, obviously. We multiply by 2.5 on the right to get, not surprisingly, 2.5. For cycle two, we multiply the one on the left by 1.3 again, and we get 1.69. On the right, we take 2.5, and we multiply it by 2.5, and we get 6.25. So that's two rounds.
Let's do it again. On the left, for the third round, multiplying by 1.3, we now have 2.197. On the right, multiplying by 2.5, we're up to 15.625.
So let's do the fourth round here. On the left, we multiply by 1.3, and we're up to 2.86 people. On the right, we multiply by 2.5—we're up to 39.1.
On the left, 1.3 is our number—we're up to 3.7. On the right, 2.5 is our number—we're up to 97.7.
Another round: 1.3, we multiply by, and we get 4.8 on the left. When we multiply our number on the right by 2.5, we're up to 244.
Let's do it again. We're going to multiply by 1.3, and we're now up to 6.3 people on the left. We multiply our right figure of 244.1 by 2.5, and now we're up to 610 people.
Let's do another round. Multiply by 1.3 on the left—we now have 8.2 people infected. Multiply the right number, 610.4, times 2.5—we're up to 1,525.9. But we're not done; we're going to go through this and take rounds.
One more on the left by 1.3—we're up to 10.6 people. On the right, multiply by 2.5: 3,814.7.
Let's do it again: 1.3 on the left—13.8. 2.5 on the right brings us up to 9,537.
That's why it's so important to cut the number of people each individual can infect with the policies of social distancing.
纽约这里的冠状病毒病例正在呈爆炸性增长，我们处于曲线的陡增部分 。你可能听说过“基本传染数”，即R0，或R-naught 。大意就是已感染者可继续感染的人数 。前几天晚上，我碰巧看到一条推特，展示了基本传染数为1.3的病毒和基本传染数为3的病毒之经10轮传播后的差异有多大 。差别令人震惊 。10轮传播后，基本传染数为1.3的病毒平均能感染14个人 。而基本传染数为3的病毒可导致5.9万人感染 。
看到这些数字令人无比震惊 。在此我拿出了计算器 。我打算重复之前用计算器运算的过程 。大家也可以一起算 。这还挺有趣的 。而且也很神奇 。我拿出了两个计算器，因为我要同时算两种不同基本传染数 。
好，我左边的计算器，我将假设基本传染数为1.3 。即每个已感染者平均传给1.3个人 。右边的计算器，我假设基本传染数为2.5，选这个数字是因为其似乎很接近冠状病毒的基本传染数 。
两边都从一个人（1）开始 。左边的计算器1乘以1.3，乘积显然是1.3 。右边的计算器1乘以2.5，毫无疑问乘积是2.5 。第二轮，左边1.3再乘以1.3，结果为1.69 。右边2.5乘以2.5，得到6.25 。这是两轮 。
我们再乘一次 。第三轮，左边数字乘以1.3，我们得到2.197 。右边乘以2.5，结果为15.625 。
我们再来做第四轮 。左边乘以1.3，传染人数为2.86人 。右边乘以2.5，结果为39.1 。
左边乘以1.3，得3.7 。右边乘以2.5，得97.7 。
再来一轮：乘数为1.3，左边结果为4.8 。当右边的数字乘以2.5时，我们得到244 。
我们再来算一轮 。左边要乘以1.3，现在传染人数为6.3人 。右边数字244.1乘以2.5，人数为610人 。
我们再来一轮 。左边乘以1.3，现在有8.2人被感染 。右边数字610.4乘以2.5后，我们得到1525.9 。但还没有结束，我们要完成计划，继续乘 。
左边再乘1.3，人数为10.6人 。右边乘以2.5，得到3814.7 。
再来一次：左边乘以1.3，得13.8 。右边乘以2.5，结果为9537 。
1. go on to do sth. 继续；持续；
If the gene is present, a human embryo will go on to develop as a male.
2. happen to do sth. 碰巧；凑巧；
If you happen to talk to him, have him call me
3. on average 平均起来；按平均值；
400 people a year die of this disease on average.
4. go through 完成；继续；
Let's go through the numbers together and see if a workable deal is possible.