A dynamic method for controlling the epidemic situation of an infectious disease

Abstract

The present invention discloses a dynamic method for infectious disease epidemic control, which can propose specific control measures and intensities according to the epidemic control objectives, and can also evaluate the effects of epidemic control measures based on the actual development trend of the epidemic, so as to achieve accurate prediction and precise prevention and control of the epidemic. This method first establishes an epidemic control dynamic model CUME according to the epidemic control characteristics, then determines the conversion relationship between the population to be controlled and the population under control for a specific control strategy, and then determines the control parameters of the control function of the population under control according to the set target quantity of the population under control for the epidemic. Finally, the epidemic control rate is obtained according to the control function of the population under control, and the optimal control strategy is obtained through the epidemic control rate, and at the same time, accurate prediction of the epidemic prevention and control strategy is realized, so as to achieve precise prevention and control with an effective epidemic prevention and control strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of infectious disease epidemic control, and particularly to a dynamic method for infectious disease epidemic control. Background Art

[0002] On January 30, 2020, WHO determined COVID-19 as a public health emergency of international concern, and announced it as a global pandemic on March 11. Now, the number of new infections is still increasing at a rate of more than a hundred thousand per day within the region. COVID-19 is classified as a Class B infectious disease and is managed and prevented in accordance with Class A infectious diseases.

[0003] Regarding the infectious disease epidemic, how to formulate effective prevention and control strategies is the basis for epidemic control. However, there is currently no method for dynamic control of the prevention and control strategies for infectious disease epidemics. After setting the epidemic control target, how to formulate specific control measures accordingly and determine the control effect, so as to pre-evaluate each control strategy, is an unsolved problem at present. Summary of the Invention

[0004] In view of this, the present invention provides a dynamic method for infectious disease epidemic control, which can propose specific control measures and intensities according to the epidemic control target, and can also evaluate the effects of epidemic control measures based on the actual development trend of the epidemic, realizing accurate prediction and prevention of the epidemic.

[0005] To achieve the above object, the technical solution of a dynamic method for infectious disease epidemic control provided by the present invention includes the following steps:

[0006] Step 1: According to the epidemic control characteristics, an epidemic control dynamic model CUME is established. The population for infectious disease epidemic control is divided into two categories. One is the controlled population, and the control function of the controlled population is c(t), which represents the proportion of the controlled population in the epidemic control population changing with time. The viruses in the controlled population no longer spread to each other. The other is the population to be controlled, and the control function of the population to be controlled is u(t), which represents the proportion of the population to be controlled in the epidemic control population changing with time. The viruses can still spread to each other.

[0007] Step 2: When the control strategy is issued, it is determined that during the process of the population to be controlled u(t) being converted into the controlled population c(t), the conversion rate between the population to be controlled u(t) and the controlled population c(t) is μ. μ represents the proportion of the controlled population and the population to be controlled converted every day. When converting from the population to be controlled to the controlled population, μ takes a positive value, and vice versa:

[0008]

[0009] μ is positively correlated with c(t), that is, μ = μ 0 c(t), μ0 is the basic conversion coefficient. For the same control strategy μ 0 is a constant, representing the actual proportion of the daily conversion between the controlled population and the population to be controlled:

[0010]

[0011]

[0012] Step 3: Set the target value of the epidemic-controlled population as ζ, 0 ≤ ζ ≤ 1, that is, the proportion of the total controlled population in the total population in the prevention and control of infectious disease epidemics. The effective time of the control strategy issued by the control department is τ, and the controlled population control function is specifically

[0013]

[0014] Step 4: Set the target control rate of the epidemic as λ a , and the initial control rate of the epidemic is λ 0 , then c(t) = C(t) - λ 0 , ζ = λ a -λ 0 , where C(t) is the epidemic control rate, and the epidemic control rate is:

[0015]

[0016] Use the epidemic control rate to evaluate the current control strategy. If the difference between the epidemic control rate and ζ exceeds the threshold, modify the control strategy and return to Step 2 until the difference between the epidemic control rate and ζ is less than the set threshold, and determine that the current control strategy is effective.

[0017] Furthermore, in Step 3,

[0018] u(τ) + c(τ) = ζ (6)

[0019] Then

[0020]

[0021] The time when the epidemic control measures take effect is the inflection point of the function c(t), that is:

[0022] c″(τ) = 0 (8)

[0024] Furthermore, if all people change from the population to be controlled to the controlled population, that is, the change amount ζ of the epidemic target control is 1, the controlled population control function is specifically:

[0025]

[0026] Furthermore, the epidemic control function for infectious asymptomatic infected persons is:

[0027]

[0028] where λ ca is the target control rate of asymptomatic infected persons, and λ c0 is the initial control rate of asymptomatic cases, and μ a is the conversion coefficient of asymptomatic infected persons, that is, the mutual ratio between the population to be controlled and the controlled population among asymptomatic infected persons, and τ a is the effective time of the control strategy issued for asymptomatic infected persons.

[0029] Furthermore, the epidemic control function for symptomatic infected persons with infectivity is C s (t), that is, the effect produced by the control strategy for symptomatic infected persons:

[0030]

[0031] where λ sa is the target control rate of symptomatic infected persons, and λ s0 is the initial control rate of symptomatic infected persons, and μ a is the conversion coefficient of symptomatic infected persons, that is, the mutual ratio between the population to be controlled and the controlled population among symptomatic infected persons, and τ s is the effective time of the control strategy issued for symptomatic infected persons.

[0032] Beneficial effects:

[0033] A method for controlling the dynamics of infectious disease epidemics provided by the present invention first establishes an epidemic control dynamics model CUME according to the characteristics of epidemic control, then determines the conversion relationship between the population to be controlled and the controlled population for a specific control strategy, and then determines the control parameters of the control function of the controlled population according to the set target amount of the epidemic controlled population. Finally, the epidemic control rate is obtained according to the control function of the controlled population, and the best control strategy is obtained through the epidemic control rate, while realizing accurate prediction of the epidemic prevention and control strategy, so as to achieve precise prevention and control with an effective epidemic prevention and control strategy. Description of the drawings

[0034] Figure 1 is a schematic flow chart of a method for controlling the dynamics of infectious disease epidemics provided by an embodiment of the present invention;

[0035] Figure 2 is a graph showing the trend of changes in COVID-19 epidemic control variables over time in a certain city. Detailed implementation manners

[0036] The present invention will be described in detail below with reference to the accompanying drawings and by way of examples.

[0037] The present invention provides a kinetic method for infectious disease epidemic control, and its process is as Figure 1 shown, including the following steps:

[0038] Step 1: According to the characteristics of epidemic control, construct an epidemic control kinetic model (CUME, Controlled - Uncontrolled Model for the Epidemic). Divide the population for infectious disease epidemic control into two categories. One is the controlled population, denoted as c(t), representing the proportion of the controlled population in the epidemic control population changing with time. In the controlled population, the virus no longer spreads among individuals. The other is the population to be controlled (Uncontrolled population who will be controlled in the future), denoted as u(t), representing the proportion of the population to be controlled in the epidemic control population changing with time, and the virus can still spread among individuals.

[0039] Step 2: When the control department issues social distancing and protection instructions, there is a reaction process for the population to be controlled to transform into the controlled population. Therefore, it is necessary to consider the process of transforming from the uncontrolled state u(t) to the controlled state c(t). Obviously, its transformation rate is proportional to u(t). Let the conversion rate between the population to be controlled and the controlled population be μ, representing the proportion of the controlled population and the population to be controlled converted every day. When converting from the population to be controlled to the controlled population, μ takes a positive value, and vice versa. Thus, we can obtain:

[0040]

[0041] When the proportion of c(t) is higher, due to the influence and demonstration effect of panic psychology and other factors in society, the population to be controlled u(t) is accelerated to transform into the controlled population c(t). Therefore, μ is positively correlated with c(t). Assume that μ is proportional to c(t), that is, μ = μ 0 c(t), μ 0 is the basic conversion coefficient. For the same control strategy, μ 0 is a constant, representing the actual proportion of the conversion between the controlled population and the population to be controlled every day. Then Equation (1) is expressed as:

[0042]

[0043] (It is not difficult to obtain:

[0044]

[0045] Step 3. Let the target variable value of the population with the epidemic under control be ζ (0 ≤ ζ ≤ 1). (The goal of the control strategy is set artificially and controlled to a certain intensity. Note: The control goal can only be set artificially. Just like when I am actually driving a car, how many kilometers per hour I need to travel depends on the driver's needs. Once the vehicle speed is determined, objective indicators such as fuel consumption on the same road are determined), that is, the proportion of the change in the population with the infectious disease epidemic under control in the total population. Obviously, u(t) + c(t) = ζ.

[0046] Let the time when the epidemic control measures take effect be τ. Then:

[0047] u(τ) + c(τ) = ζ (4)

[0048] Solving this equation gives

[0049]

[0050] The time when the epidemic control measures take effect is the inflection point of the control function c(t), that is,

[0051] c″(τ) = 0 (6)

[0052] Solving equation (6) gives c(τ) = ζ / 2. Substituting it into equation (5) gives

[0053]

[0054] In particular, if all people change from the population to be controlled to the population with the epidemic under control, that is, the epidemic target control value is 1, then:

[0055]

[0056] Step 4. Let c(t) = C(t) - λ 0 , ζ = λ a -λ 0 , where C(t) is the epidemic control rate and λ a is the epidemic target control rate, and λ 0 is the initial epidemic control rate. Then equation (7) becomes:

[0057]

[0058] The epidemic control function for asymptomatic infectious carriers is:

[0059]

[0060] λ ca is the target control rate of asymptomatic infectious carriers, and λ c0 is the initial control rate of asymptomatic cases, and μ a is the conversion coefficient of asymptomatic infectious carriers (i.e., the mutual proportion of the population to be controlled and the population with the epidemic under control).

[0061] The epidemic control function for infectious symptomatic infected persons is the effect produced by the control measures for symptomatic infected persons:

[0062]

[0063] Among them, λ sa is the target control rate of symptomatic infected persons, and λ s0 is the initial control rate of symptomatic infected persons, and μ a is the conversion coefficient of symptomatic infected persons, that is, the mutual ratio between the population to be controlled and the controlled population among symptomatic infected persons, and τ s is the effective time of the control strategy issued for symptomatic infected persons.

[0064] The control rate is the effect produced by the control measures for infected persons. The current control strategy is evaluated using the epidemic control rate. If the difference between the epidemic control rate and ζ exceeds the threshold, the control strategy is modified and returned to step two until the difference between the epidemic control rate and ζ is less than the set threshold, and it is determined that the current control strategy is effective. The set threshold should be set as small as possible, that is, to make the epidemic control rate as close to ζ as possible.

[0065] Regarding the changing trend of the COVID-19 epidemic control variables in a certain city over time, the adjoint method is applied to invert the parameters, and C s and C a change over time as Figure 2 shown.

[0066] In summary, the above is only the preferred embodiment of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A kinetic method for infectious disease epidemic control, characterized in that, it includes the following steps: Step 1: According to the characteristics of epidemic control, an epidemic control kinetic model CUME is established. The population for infectious disease epidemic control is divided into two categories. One is the controlled population, and the control function of the controlled population is c(t), which represents the proportion of the controlled population in the epidemic control population changing with time. In the controlled population, the virus no longer spreads among each other. The other is the population to be controlled, and the control function of the population to be controlled is u(t), which represents the proportion of the population to be controlled in the epidemic control population changing with time. The virus can still spread among each other; Step 2: When the control strategy is issued, it is determined that during the process of the population to be controlled u(t) being converted into the controlled population c(t), the conversion rate between the population to be controlled u(t) and the controlled population c(t) is μ. μ represents the conversion ratio of the controlled population to the population to be controlled per day. When converting from the population to be controlled to the controlled population, μ takes a positive value, and vice versa, it takes a negative value: μ is positively correlated with c(t), i.e., μ = μ 0 c(t), μ 0 is the basic conversion coefficient. For the same control strategy μ 0 is a constant, representing the actual proportion of the daily conversion between the controlled population and the population to be controlled: Step 3: Set the target value of the epidemic controlled population as ζ, 0 ≤ ζ ≤ 1, that is, the proportion of the total population controlled in the prevention and control of infectious diseases. The effective time of the control strategy issued by the government is τ. The specific control function of the controlled population is Step 4, set the epidemic target control rate as λ a , and the initial epidemic control rate is λ 0 , then c(t) = C(t) - λ 0 , ζ = λ a -λ 0 , where C(t) is the epidemic control rate, and the epidemic control rate is: Use the epidemic control rate to evaluate the current control strategy. If the difference between the epidemic control rate and ζ exceeds the threshold, modify the control strategy and return to Step 2 until the difference between the epidemic control rate and ζ is less than the set threshold, and determine that the current control strategy is effective.

2. The method according to claim 1, characterized in that, in the said Step 3, u(τ) + c(τ) = ζ(6) then the effective time of the epidemic control measure is the inflection point of the function c(t), that is: c″(τ) = 0(8).

3. The method according to claim 1, characterized in that, if all people change from the population to be controlled to the controlled population, that is, the change amount of the epidemic target control ζ is 1, then the specific control function of the controlled population is:

4. The method according to claim 1, 2 or 3, characterized in that, the epidemic control function for infectious asymptomatic infected persons is: where λ ca is the target control rate of asymptomatic infected persons, λ c0 is the initial control rate of asymptomatic cases, μ a is the conversion coefficient of asymptomatic infected persons, that is, the mutual ratio between the population to be controlled and the controlled population among asymptomatic infected persons, τ a is the effective time of the control strategy issued for asymptomatic infected persons.

5. The method according to claim 1, 2 or 3, characterized in that, The epidemic control function for infectious symptomatic infected individuals is C s (t), which is the effect generated by the control strategy for symptomatic infected individuals: where λ sa is the target control rate of symptomatic infected individuals, λ s0 is the initial control rate of symptomatic infected individuals, μ a is the conversion coefficient of symptomatic infected individuals, that is, the mutual conversion ratio between the population to be controlled and the controlled population among symptomatic infected individuals, τ s is the effective time of the control strategy issued for symptomatic infected individuals.

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