Some people ask why the trend of the epidemic in Hong Kong is so stable. I just want to say that all mainstream views are one-sided.
Picture/Headline netizen
The real reason is: the infection shock wave follows the social phenomenon caused by various factors unique to Hong Kong, showing the long tail effect on the statistical model. Is
difficult to understand? Difficulty is right! Because most people don't have a concrete idea about it. When
used to go to school, the teacher would not teach you scientific knowledge, but would only make you memorize it by rote, and then do crazy questions. The two disciplines of statistics and probability can only be learned in universities and colleges after thousands of troops have passed the single-plank bridge of the college entrance examination. Even according to the majors, quite a few people can only take electives.
is far off.
In short, the public lacks enough understanding of this minimum common sense.
I think the lack of preparations for this liberalization is related to this common phenomenon, from decision-making officials to the grassroots and the masses.
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As shown in the picture above, the host said that Hong Kong has never experienced a medical run, and some people in the comment section later said that Hong Kong's "over-peak" is due to insufficient statistics, or they just slammed their heads and exaggerated, and then appealed to the mainland Followed suit.
Picture/Headline Netizen
is completely lying with his eyes open!
When the first wave of infections peaked in February, the number of new cases in Hong Kong doubled several times a day. How come there is no such thing as a medical run? The high fatality rate in Hong Kong is the best proof. Criticism that the data is not accurate is purely false, it is just that the statistical caliber is different.
As for those who call on the mainland to follow Hong Kong’s example, they are even more confused: Hong Kong was forced to open up, and although we were coerced by various factors, we had to let go, but if there is no "new policy" promulgated by the high-level Will we completely liberalize the ten-point policy?
In essence, we are voluntarily letting go. The high-level leaders were also very cautious, and many expert forums were held to discuss state affairs before the release. Since
is voluntarily liberalized, it is fundamentally different from Hong Kong's passive liberalization. When Hong Kong was initially liberalized, it was logical that medical resources ran out, vaccine vaccination rates were insufficient, and protection for the elderly, weak, sick and disabled was not enough.
In contrast to the mainland, you can experience it yourself.
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Instead of asking whether the mainland will be like Hong Kong, where only one wave of peaks is experienced and the remaining peaks are very small, would rather compare the differences in various social factors between the mainland and Hong Kong.
On the one hand, Hong Kong was once colonized by foreign powers, and people’s thinking has long been colored by Western culture such as carpe gratification.
Looking at the behavior of Western countries after the outbreak, we can also feel it, and Hong Kong citizens generally hold a liberal attitude in terms of epidemic prevention and control. Which is more important, life or freedom, already has an answer in their hearts. Soon after
was released, you can see that Central, Kowloon , New Territories , Sham Shui Po, Mong Kok, Tsuen Wan, and other places are overcrowded.
On the other hand, Hong Kong used to be the head of the Asian Tigers, a developed economic region, and it has enough strength to support citizens to go shopping and consume.
Just the year before last and last year, the SAR government distributed tens of thousands of Hong Kong dollars to citizens. This approach can not only drive consumption, but also connect with the US dollar over-issue cycle (the Hong Kong dollar adopts a pegged exchange rate system and anchors assets to the US dollar), He Le Why not?
Hong Kong’s overcrowded streets
But if you switch to the mainland, let alone whether you can learn from Hong Kong’s liberalization model, you can’t even learn from Taiwan’s liberalization model.
The reason is that the people in the mainland have adopted a more cautious attitude than the government towards the sudden release of epidemic prevention and control.
These days, some experts believe that as long as the liberalization is released, within a few weeks, our mainland will be overcrowded like Hong Kong, and the economy will shake off the impact of the epidemic and flourish.morning.
Seeing is believing, experiment is the only criterion to test the truth.
It's been three weeks since the "New Ten Rules" were promulgated. What about the people on the street? What about customers in physical stores? What about the express delivery?
Because the people in the mainland have adopted a cautious attitude, compared with the people in Taiwan, it is even worse than that, and even surpassed it!
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Jin Dongyan, a well-known professor at the School of Biomedical Sciences of the University of Hong Kong, said in an exclusive TV interview with Phoenix Satellite TV host Wu Xiaoli :
"I have some reservations about whether the first wave of infections in the mainland can be 60% (Opinion)."
"We can understand by talking about a few examples. First of all, let's look at Hong Kong. In fact, it did not take the initiative to let go, but passively broke the defense. In this case, the epidemic began to rise from early February to In early April (the number of infections) has fallen to the bottom, but its peak was in March, that is, one month after (the epidemic broke through), the whole cycle is about two months. Because the first wave affected enough people , From May to December, Hong Kong has been at a very low epidemic level."
"But if it is a region that is actively liberalized, like Taiwan, China, it has been liberalized since May, but until now In December, the epidemic basically never stopped, and there were two peaks of the epidemic, and these two peaks were the same height." People go to restaurants to eat, and few people take the subway. This is similar to the effect of 'closing the city'. You may not be able to achieve 60% (infection rate), but it becomes 30%. Then There may be another wave next time, another 30%."
"This has advantages and disadvantages. The advantage is that the impact of the two waves (infection peaks) on our medical system and society is relatively small, that is,' Staggered peak'. But the bad thing is that the epidemic lasted for a long time."
"I cite these examples to show that our China may not be a model in the end. It is a model from a (epidemic) pandemic to a regional epidemic. The ideal situation is that there is a big peak, and then (in terms of data presentation) there are all small peaks below, this is the ideal situation.”
Picture/Phoenix Satellite TV Douyin account
Professor Jin Dongyan’s words at least illustrate the following four points:
1. At the peak of the first wave of the epidemic, the infection rate of the mainland population may not reach 60%.
Here, let’s popularize science here. In order to form a sufficiently solid herd immunity barrier against the epidemic, the relatively unified academic conclusion of the domestic epidemiology is that the number of infected people must reach at least 60% of the total number of people, while major overseas countries The requirements are higher, such as the United Kingdom, which must reach more than 70%.
2. Referring to the Hong Kong region, after the passive liberalization, there was only one major peak of the epidemic this year, with a period of about two months, and the infection rate was extremely high, but there was no rebound in the following months, and the population had a high immune barrier .
3. Referring to the Taiwan region, after the voluntary liberalization, there have been two major epidemic peaks this year, and the epidemic has continued from May to December.
4. The ideal situation for an epidemic to go from a pandemic to a regional epidemic is that there will be a large peak followed by several small peaks.
At present, it seems that my country's model of releasing the epidemic is likely to learn from Hong Kong, but I have already said above that in reality, the attitude of the people in the mainland is more cautious than the people in Taiwan.
During the epidemic period, the physical stores were empty.
Of course, it is still too early to draw conclusions.
But we can now speculate according to Professor Jin Dongyan’s statement whether the final infection rate data at the peak of the first wave of the epidemic in my country can break through.60% broken.
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has now canceled large-scale nucleic acid testing , and the official specific confirmed case data is distorted and not useful for reference.
So how do we measure the number of infected people in each city?
For the United States, which wanted to let go of the epidemic at that time, this was also one of the difficulties that bothered her. However, they adopted the Hopkins University mathematical model to replace the nucleic acid testing data at the federal level.
Now we are also adopting the same method: A big data technology company from the private sector created a small program called "City Database" on WeChat , which contains the infected population of various cities in China after deduction by mathematical models Data, and a trend chart of the number of infected people.
There are more than 300 cities in the whole country. It is impossible for us to investigate one by one. We can only select representative cities for sampling analysis.
Since our country chooses to open up the initiative to boost the economy and people's livelihood, then we will select cities that have a greater impact on economic development and divide them into three levels to analyze their infection data.
First is the first gear, five megacities: Beijing, Shanghai, Guangzhou, Shenzhen, and Chongqing.
As shown in the picture, As of December 25, Beijing has passed the first wave of infection peaks, and the cumulative predicted population infection rate is 56.32%. If the cumulative infection rate on the day when the first wave of peaks ends is calculated at a ratio of 1.92%, the result is 76.24%.
By analogy, Calculated based on the infection rate of 3.17% on the day, the cumulative infection rate in Shanghai on the day when the first wave of peaks ended was 72.36%.
The cumulative infection rate of the first wave in Guangzhou was 74.53%.
Shenzhen is 83.6%.
Chongqing City is 73.66%.
It can be seen that the cumulative infection rates on the end day of the first wave of the five megacities in my country are generally above 70%.
Then comes the second tier, three megacities: Hangzhou, Wuhan, and Nanjing. Why did
list these three cities? Because they have absorbed enough labor and employment in recent years, the prospects for economic development are relatively clear, and the flow of people and goods is more important to their economic development.
The cumulative infection rate on the end day of the first wave peak in Hangzhou was 74.05%.
Wuhan City is 78.75%.
Nanjing is 81.46%.
In summary, The three cities that represent the "new front line" have generally reached more than 70%, among which Nanjing City is the strongest, with a cumulative infection rate of more than 80% at the end of the day.
is the third gear at the end, representing the manufacturing industry clusters that are the lifeline of my country's economy. One is Suzhou located in the Yangtze River Delta , and the other is Dongguan City located in the Pearl River Delta.
For the economic vitality of these two cities, letting go of the epidemic is a life-saving straw.
Suzhou City is 74.08%.
Dongguan City is 75.96%.
Like all other cities, the cumulative infection rate in these two cities also exceeded 70% on the end day of the first wave peak.
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However, the above data deductionDoes it mean that Professor Jin Dongyan's concern that the cumulative infection rate of the first wave peak is less than 60% will not come true?
The answer is not necessarily.
First, because these data are only the results of mechanical calculations based on my predicted infection rate on December 25th, the reference is a bit weak.
Because the downward trend after the peak of the epidemic is getting stronger every day, and the infection rate is relatively slow, the rough calculation of the urban infection rate is not accurate.
Second, the data setting of the statistical model can be shifted, and then the problem of weight preference will occur.
For example, in the Price Statistics Index (CPI) that everyone is more familiar with, pork and egg milk alone account for more than half of the weight, while real estate, which has the largest increase in the past, is not included in the statistics.
As for the big data system that predicts the peak of the epidemic infection, it also has its own weight preference problem that cannot be avoided. For example, it can only view the cities, but cannot specifically view the infection data in rural areas.
Although according to the division method of administrative regions in our country, most of the rural areas belong to the district or county level and are directly subordinate to the city, but this cannot be an excuse for the lack of data. The statistical bias of the forecasting system focuses on urban rather than rural areas.
In addition, due to the relative scarcity of medical resources and insufficient medical staff in rural areas, it is easy to be squeezed out, resulting in greater human and moral risks. Therefore, rural areas should not reach the peak too quickly. ignoring such issues.
Third, there is a concept in statistics called "excess rate". For example, for the statistics of the number of deaths in the epidemic, we will get data that is much larger than the actual situation.
Only in this way can we incorporate various risk parameters into it. And this system will also set the "excess infection rate" in the prediction model to ensure that its predictions are closer to the real data.
But here we need to discuss the facts, analyze rationally and objectively, in addition to taking various risk factors into consideration, what other factors affect the forecast data of this system. The "urban database" system
claims that the data of the prediction model comes from the search engines of major Internet companies such as Baidu, index, and giant computing. On today's Toutiao page, search for entries related to the epidemic, such as " new crown ", "fever", "fever reduction", "muscle pain", " pneumonia ", etc., are integrated through big data technology, and then Use it as a predictive model.
But after all, it is not the confirmed case data officially released by the country, and it has no advantages in terms of authority and reference.
In addition, we have to consider three questions:
First, will a considerable part of these data be found by Fuyang researchers?
Everyone knows that the definition of "Fuyang" is not secondary infection , but the original infection, then turned negative and did not get better, and then relapsed, which is essentially the first infection.
In the data of the current system prediction model, will there be such a part of the data, which will disturb the authenticity of the statistical results and increase the number of confirmed cases and the infection rate of the population in disguise?
Second, people who are not infected will instinctively search for relevant entries because everyone around them is positive, full of worry and anxiety, and get a vaccination in their hearts.
And this prediction model did not exclude these people, it also pushed up the infection rate of the crowd, making it deviate from the real situation.
Thirdly, the group of people who do not know how to use smartphones to search for terms online has become the "silent majority" in this prediction model. For example, the elderly and underage children also pose a big challenge to the authenticity of the data.
After the above analysis, I, like Professor Jin Dongyan, have reservations about whether the infection rate of the people hit by the first wave of the epidemic can reach 60%.
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