具体你可以看这里：https://www.worldometers.info/coronavirus/country/germany/
不是中文的论调，而是全世界的论调。 比如说你的城市有一千万人，你被牛顶死，而且是全市唯一一个。那么被牛顶死的数据就是一千万分之一，但实际上只有在有牛的地方，而且牛发怒或者得了疯牛病的地方才有这个概率。而在一头疯牛旁边被顶死的概率可能超过50%
车祸也是同理，在某些地段因为某些因素出车祸的概率会比其他地方高很多。 特别是经常有飙车的地方。并不是说你在任何一条路上开车死亡概率都是平均值。  
如果你真的要考虑你自己的安全性，你需要做的更多。毕竟现实不是一个单纯的数字，从美国疫情数据研究。死的大部分都是每天需要上班的普通人，而有钱人的死亡概率相对非常小。 另外也要看省份，美国几个省死亡概率都不同。 这个原因有很多，比如感染的主要变种，比如温度，人口密集度，动物密集度，疫苗种类，病史，体质等很多其他因素。
不过分析的再多死了也就死了，当你病死了。哪怕病死的概率只有千万分之一，对你自己来说难道不是100%吗。。概率学在现实里的应用一般都取最低值。特别是做一些风投的时候一般不能考虑平均值。 但说实话在病毒这里意义不大，毕竟现实不是推演数据，你不可能一次一次反复来。正常人病死就一次。。 
你可以看看这个，是外国类似的东西。
来源：https://medium.com/trading-politics/theres-probability-theory-and-then-there-s-reality-b9edc5d6bc9e
Taking the Worse Deal
Some might argue that you’ll still want to select the choice with the greatest expected value and to never agree to a deal where the expected value is negative, as there would be a long run loss. For the most part, this idea holds. But the issue is that “long run behavior” does not apply in every case. Long run behavior requires being able to run as many trials as you want. So for instance, if there’s an extinction event, that’s it. For the same reason, people still get insurance, even though the expected value is negative.
Actuaries calculate risk of various payouts and your insurance premium is going to be higher than the expected value. However, without insurance, it may be impossible to pay, or it may bankrupt you, and so even though a mathematician might say that one should never take a deal with a negative expected value, odds are they’d still get insurance, or at least should, unless they’re really certain that they can save up enough money.
Getting it Right
The expected value is a powerful tool in risk-reward analysis, and it should not be ignored. For business operations with spare cash, it’s almost always best to go with the project with the highest expected value, and generally not a good idea to go with a project where the expected return, or expected earnings less cost, is negative. After all, if year after year we’re using available funds to generate more revenue, we’ll want the projects that will yield the best results, on average, and that’s generally determined by expected value.
However, in real life scenarios, we aren’t always guaranteed that we can keep playing the game over and over again, and so expected value has its limits. Taking on a risky project, or engaging in some activity that could be rewarding, but also potentially catastrophic, may not be the best option. Taking into account what each potential outcome really implies can be incredibly important, because we don’t always get a second chance.