Virus propagation simulation experiment 2- clear or coexist?

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Two years ago. , I used to use it. python I have written a simulator for virus transmission , Use a simplified mathematical model to demonstrate the spread of the virus , It also explains why personal protection should be done well with simulation experiments 、 Reducing travel and centralized isolation of infected people can effectively block the spread of the virus .

See... For detailed analog logic and parameter descriptions ：

【 Experimental simulation 】 Yes , Can we relax our vigilance ？

Now simulate a virus that is more transmissible but less pathogenic 2 Number , See what results different epidemic prevention models will bring .

See video for details ：

Viruses 2 No. 1 has stronger propagation , But the pathogenicity is greatly reduced .

In addition to this 2 An important change ：

1. Suppose our simulated area is an open city , There will be new input cases
2. People who recover from infection , It is also possible to be infected again

Simulate after adjustment ：（ The red curve shows the number of infected cases , Green is the number of people who have recovered ）

Number of infections 56297 Number of deaths 13

Same strategy as before , When the number of cases reaches a certain level, comprehensive prevention and control will be carried out , Reset and then cancel . But because of the new input , So the epidemic situation will be repeated . Compared with the previous virus , Under the same strategy , The number of infected people is much higher , But the number of deaths from illness has been greatly reduced .

If we do not take preventive and control measures ？

Number of infections 89975 Number of deaths 1313

Because the possibility of repeated infection is set . Even if everyone is infected once , The epidemic will not end . Because there are too many people infected , And repeated infection , Even if the death rate is small , The absolute number of deaths caused by the disease is also large . And this is only the result of our limited time period .

From the comparison of the above experiments , For this virus 2 Number , The effect of comprehensive prevention and control is still far better than letting it go .

therefore , Is zero clearing better than coexistence ？

Need to know , Good epidemic prevention measures need to invest human and material resources . And for many people , Not going out to work means no income , The output of the whole society also decreases .

Add the above settings to the simulation experiment , Abstract out such a value as the total amount of resources ：

1. Everyone travels every day , Can produce 1 Some resources
2. Everyone consumes... Every day 0.5 Some resources , If you enter the onset stage , More consumption 0.1 spot , Severe multi consumption 0.5 spot
3. Additional consumption per day when entering the shelter 0.1 Some resources , Admission costs 0.3 spot
4. in addition , Because prevention, control and detection cost , So from entering the state of prevention and control , Consumption per person per day 0.1 Some resources

then , Then compare the above two modes .（ The light green light red bar graph indicates “ Total resources ” The change of ）

In normal times, the total amount of resources continues to rise , In the state of prevention and control , The total amount of resources in the model will continue to decrease . Outbreaks occur repeatedly , The curve goes down repeatedly .

If you give up control restrictions , Those who can go out to work go out as usual , Unless you are seriously ill or in hospital . Indeed, it can greatly reduce the impact on resource growth . However, the growth rate can not be compared with that in the absence of an epidemic , And as I said before , The impact of this approach will last for a long time .

Although economic development cannot be compared with human life , But if we don't have enough economic strength as a backup , High standards of prevention and control are also difficult to sustain . Besides, , The resources mentioned here , It's not just the economy , It also includes medical resources 、 Livelihood resources, etc , Excessive consumption may also cause secondary damage .

Therefore, comprehensive prevention and control cannot be said to be without problems .

Is there a better way to prevent epidemic disease ？ There are . It is the way that many cities are using now ： Precise prevention and control .

In the previous simulation , Once the epidemic reaches a certain scale , Restrict everyone's travel . Now I optimize it , Only close contact people who have been exposed to the case shall be isolated .

In reality , This operation is called streaming . It is inevitable that there will be omissions in flow reconciliation detection , So here's a probability parameter , Flow regulation accuracy .

Number of infections 13015 Number of deaths 3

Under the new mechanism , The simulation results are much better , Not only has the epidemic been brought under control , The consumption of resources has also been greatly reduced . Even if the input case occurs repeatedly, it is within the controllable range .

however , But again …… The premise of this operation is , The accuracy of flow regulation is high enough , And fast enough .

Number of infections 81078 Number of deaths 30

Here, the flow regulation accuracy is reduced a little , Once the infected people cannot be isolated in time , The loopholes will get bigger and bigger , The epidemic is getting worse .

Now? , Can you tell me , In such a pure simulated experimental environment , What kind of strategy is the optimal solution ？

I don't know what you think , At least I can't give a perfect conclusion .

And if put in reality , This problem is even more complicated . We need to face more 、 More complex parameters . What indicators do you choose , What kind of data should be accepted , Determines what conclusions you will draw . Even my experimental model , If you fine tune several parameters , It is also possible to get very different results .

under these circumstances , I don't quite understand why some keyboards are Non professionals can confidently say that one solution is better than another .

The virus is mutating , Epidemic prevention measures also need to be constantly updated , We need to make scientific adjustments according to the actual situation . A complete reset in the past does not necessarily mean a complete reset in the future , If we want to coexist in the future, it does not mean that we need to coexist now . The problem of epidemic prevention should not be turned into a problem of standing in line .

In my simulation experiment in the virtual world ：

• Any extreme solution is not a good choice .
• No matter the hybrid scheme is adopted , Whether the implementation is in place directly affects the results
• Improve the vaccination rate , Especially the vaccination rate of high-risk groups , It is equivalent to reducing the transmissibility and severe disease rate , This is effective for either scheme .

in addition , Although not reflected in our model , But it is also very important to ensure the basic livelihood of the people . In the simulator “ people ” Just don't eat, drink and Lazar data , But in reality , This is the life of each of us .

Last , Although I failed to show you a perfect solution , But there was a very bad situation ：

Number of infections 67608 Number of deaths 55

In limine , A large number of cases have been caused for some reasons , The flow regulation efficiency cannot keep up , But still do not seek truth from facts to adjust the strategy , The nominal precise prevention and control has become the actual inaccurate prevention and control . Then it got really serious , Hastily turn to comprehensive prevention and control , It's full of holes , From time to time, there is a positive overflow , In addition, the basic living security has not been solved well , Generate too many unplanned contacts .

The end result is ： It consumes a lot of resources , And failed to control the epidemic , And let the people in the area suffer constantly . If you do this , It's really better to lie flat , Some countries and regions on the earth do choose this way . But you said , Is this the problem of the epidemic prevention strategy itself ？

The above is my personal simulation experiment and some thoughts based on this virus transmission model , Procedure is python Written , Is open source , You can use it to adjust the parameters to run .

All the results and inferences in the video are only for the virtual model in the program , Inaction is a simulation of reality . But I hope it can arouse some thoughts , Epidemic situation and epidemic prevention can be viewed more rationally , Of course, I hope the epidemic can be completely ended as soon as possible , We don't need to discuss this again .