CN111710433B - Infectious disease development trend prediction method and system - Google Patents
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Abstract
The invention provides a method and a system for predicting the development trend of infectious diseases, which comprises the following steps: acquiring the data of the total number of the infected persons with complete morbidity of any plurality of existing infectious diseases, and respectively constructing a development trend equation of each existing infectious disease through a fitting method; obtaining a mathematical relation equation of the current number of newly-transmitted infectious diseases and the accumulated number of the newly-transmitted infectious diseases of the same type through a fitting method according to a plurality of development trend equations of the existing infectious diseases of the same type and the data of the existing infectious people of the newly-transmitted infectious diseases; constructing an infection period mathematical relation formula of the new infectious disease and the existing infectious diseases of the same type according to a development trend equation of the existing infectious diseases of the same type and the existing infectious people data of the new infectious disease; and constructing a development trend prediction model of the new infectious disease, and predicting the accumulated number and change of the infected persons of the new infectious disease at different time nodes through cyclic calculation. The method of the invention has scientific and accurate prediction and can provide scientific guidance for assisting infectious disease control.
Description
Technical Field
The invention belongs to the field of disease prediction, and particularly relates to a method and a system for predicting the development trend of an infectious disease.
Background
Infectious diseases are a class of diseases caused by various pathogens that can be transmitted from person to person, animal to animal, or both. The infectious disease has the characteristics of popularity, periodicity, regularity and the like, and the rules and the trend of the development and the change of the infectious disease can be better mastered in a way of combining the determinacy and the quantification. By applying a scientific and practical method, the development trends of the accumulated number of people infected with a certain similar infectious disease, the infectious disease development cycle and the like are predicted, so that the method is favorable for deeply knowing the law of the infectious disease and lays a foundation for scientifically implementing infectious disease prevention and control. In the prior art, the existing data are generally sampled to predict the development trend of a certain novel infectious disease through a statistical method, the data only have reference significance and cannot reflect the propagation rule and the propagation characteristics of the novel infectious disease scientifically, the correlation of the development trend of the infectious disease for multiple times is not fully considered, the prediction method has certain limitation, and meanwhile, the existing prediction method depends on the experience of experts rather than the scientific method.
Accordingly, there is a need in the art for improvements.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a system for predicting the development trend of infectious diseases.
Based on one aspect of the embodiment of the invention, the invention discloses a method for predicting the development trend of infectious diseases, which comprises the following steps:
acquiring the data of the total number of the infected persons with complete morbidity of any plurality of existing infectious diseases, and respectively constructing a development trend equation of each existing infectious disease by a fitting method;
calculating the mathematical relationship between the accumulated infectious disease number of the existing infectious diseases of the same type and the current accumulated infectious disease number of the new infectious disease through a development trend equation of a plurality of existing infectious diseases of the same type and the existing infectious person number data of the new infectious disease, and obtaining the mathematical relationship equation between the current accumulated infectious disease number of the new infectious disease and the accumulated infectious disease number of the existing infectious diseases of the same type through a fitting method;
according to the development trend equation of the existing infectious diseases of the same type and the data of the existing infectious people of the new infectious diseases, establishing a mathematical relation formula of the infection period of the new infectious diseases and the existing infectious diseases of the same type by comparing the data of the new infection rate;
and constructing a development trend prediction model of the new infectious disease through the development trend equation of the existing infectious diseases of the same type, the mathematical relation equation of the number of the newly-sent infectious diseases infected with the existing infectious diseases of the same type and the accumulated infectious people of the existing infectious diseases of the same type, the mathematical relation equation of the infection period of the new infectious diseases and the existing infectious people data of the new infectious diseases, and predicting the accumulated infectious people and change of the new infectious diseases at different time nodes through cyclic calculation.
According to the method of the present invention, preferably, the acquiring the onset data of any plurality of existing infectious diseases, and the constructing the development trend equation of each infectious disease by the fitting method respectively comprises:
drawing a disease data curve of the existing infectious diseases;
fitting a change curve of the accumulated number of infected persons of the infectious disease by using a Gaussian equation;
and obtaining a development trend equation of the existing infectious disease according to the fitting result.
According to the method of the present invention, preferably, the equation for the development trend of the existing infectious disease obtained according to the fitting result is:
wherein t represents the number of days, f i (t) the cumulative number of infected persons on day t of the ith established infectious disease, a 1 ，a 2 ，a 3 ，b 1 ，b 2 ，b 3 ，c 1 ，c 2 ，c 3 And calculating to obtain the fitting parameters according to the fitting result.
According to the method of the present invention, preferably, the calculating the mathematical relationship between the cumulative infected person number of the existing infectious diseases of the same type and the current cumulative infected person number of the new infectious diseases through the development trend equation of the existing infectious diseases of the same type and the data of the existing infected person number of the new infectious diseases, and the fitting method to obtain the mathematical relationship equation between the current cumulative infected person number of the new infectious diseases and the current cumulative infected person number of the existing infectious diseases of the same type includes:
counting the data of the number of infected persons of the new infectious disease in a certain time period and the data of the number of infected persons of the same type of infectious disease in the same time period;
fitting a relation curve of the accumulated infectious disease number of the two infectious diseases by using a power exponent approximation algorithm;
and obtaining a relational equation of the accumulated infectious population of the two infectious diseases according to the fitting calculation result.
According to the method of the present invention, preferably, the equation of relationship between the total infectious disease number of two infectious diseases obtained according to the fitting calculation result is:
f j (x)＝a×x b +c；
wherein x is the cumulative number of known infections of the ith species, and f j (x) And (4) accumulating the number of newly-transmitted infectious diseases j, and calculating according to the fitting result by using a, b and c as fitting parameters.
According to the method of the present invention, preferably, the establishing of the new infectious disease infection rate calculation formula by comparing the data of the new infectious disease with the existing infectious people data of the new infectious disease through the development trend equation of the existing infectious diseases of the same type includes:
constructing a new infectious disease infection probability model;
counting the newly increased infection rate data of the new infectious diseases in a set time period and the infection rate data of the existing infectious diseases of the same type in the same time period;
constructing an infection period mathematical relation formula of the new infectious disease and the existing infectious diseases of the same type.
According to the method of the present invention, preferably, the constructing of the probability model of infection with the new infectious disease is:
in the formula, p k The new infection rate on day k of the newly-developed infectious disease, x k The transmission of new hairNewly infected persons on day k of the disease.
According to the method of the present invention, preferably, the mathematical relationship formula for the infection cycle of the new infectious disease and the existing infectious diseases of the same type is:
wherein r represents the comparison relationship between the epidemic situation of the newly-developed infectious disease and the existing infectious disease of the same type, q (j) is the control strength of the newly-developed infectious disease j, and the value range is 0 to 1,p (i) t The new infection rate of the same type of existing infectious diseases i on the t day, p (j) t The new infection rate of the existing infectious disease j on the t day is increased.
According to the method of the present invention, preferably, the method comprises the steps of constructing a new infectious disease development trend prediction model by using a development trend equation of the same type of existing infectious disease, a mathematical relationship equation between the number of newly-released infectious diseases and the cumulative number of infectious diseases of the same type of existing infectious diseases, a mathematical relationship equation between the new-released infectious diseases and the infection periods of the same type of existing infectious diseases, and the data of the number of newly-released infectious diseases, and predicting the cumulative number of infectious diseases and changes of the new-released infectious diseases at different time nodes by cyclic calculation:
f j (t)＝a×f i (x(t)) b +c；
x(t)＝r×t；
in the formula (f) j (t) cumulative number of newly-developed infectious disease j at time t, f i (t) represents the accumulated infectious people of the existing infectious disease i of the same type at the time t, r represents the comparison relation of two epidemic periods, t represents the number of days, and x (t) represents the approximate time of the new infectious disease j in the existing infectious disease i of the same type.
Based on one aspect of the embodiments of the present invention, the present invention discloses a system for predicting the development trend of infectious diseases, comprising:
the infectious disease development trend equation calculation module calls a fitting equation according to the historical data of the occurring infectious diseases to obtain a development trend mathematical equation of various types of the transmitted infectious diseases;
the system comprises an infectious disease accumulated infectious disease number mathematical relation calculation module, a data analysis module and a data analysis module, wherein the infectious disease accumulated infectious disease number mathematical relation calculation module receives data obtained by the infectious disease development trend equation calculation module, calculates the mathematical relation between the same type of existing infectious disease accumulated infectious disease number and the current new infectious disease infected number through a development trend equation of the same type of existing infectious disease and the existing infectious disease number data of the new infectious disease, and obtains a mathematical relation equation between the current new infectious disease infected number and the same type of existing infectious disease accumulated infected number through a fitting method;
the infectious disease development period mathematical relation calculation module receives the data obtained by the infectious disease development trend equation calculation module, calculates the newly increased infection rate of the newly-increased infectious disease and the existing infectious diseases of the same type in a certain time period, and constructs an infection period mathematical relation formula of the newly-increased infectious disease and the existing infectious diseases of the same type through the comparison of the newly-increased infection rate;
the infectious disease development prediction calculation module receives data obtained by data calculation of the infectious disease development trend equation calculation module, the infectious disease accumulated infected person number mathematical relation calculation module and the infectious disease development period mathematical relation calculation module, constructs a new infectious disease development trend prediction model, and predicts the accumulated infected person number and change of new infectious diseases at different time nodes through cyclic calculation.
Compared with the prior art, the invention has the following advantages:
according to historical data of similar infectious diseases, a Gaussian equation is used to fit a typical infectious disease development trend curve, a typical infectious disease development trend equation based on the Gao Sifang process is established, a reference coordinate is provided for predicting the development trend of a certain infectious disease, a power exponential function is used to fit a correlation curve between the certain infectious disease and the number of persons infected with the typical infectious disease, a correlation equation between the certain infectious disease and the number of persons infected with the typical infectious disease is established, a mathematical model of newly increased infection rate is established, a mathematical relation between the existing infectious disease and the number of newly increased infectious disease development days is obtained through a comparison relation between the existing infectious disease and the newly increased infectious disease infection rate, the correlation relation between the number and the period of newly increased infectious disease and the existing infectious disease development trend is calculated, and finally, the accumulated infectious disease number change situation and the development trend data such as the period and the like are predicted.
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Fig. 1 is a schematic structural diagram of a system for predicting the infectious disease development trend according to the present invention.
Fig. 2 is a flowchart of a method for predicting the infectious disease development trend according to the present invention.
In the figure: 1 infectious disease development trend equation calculation module, 2 infectious disease accumulated infectious people number mathematical relation calculation module, 3 infectious disease development cycle mathematical relation calculation module and 4 infectious disease development prediction calculation module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method and system for predicting the infectious disease development trend provided by the present invention are described in more detail below with reference to the accompanying drawings and embodiments.
Fig. 1 is a schematic structural diagram of an infectious disease development trend prediction system according to the present invention, as shown in fig. 1, the infectious disease development trend prediction system includes:
the infectious disease development trend equation calculation module 1 calls a fitting equation according to historical data of the occurred infectious diseases to obtain development trend mathematical equations, related parameters and fitting effect parameters of various types of sent infectious diseases, firstly draws curves in the infectious disease development trend equation calculation module 1, then fits the curves, and finally constructs an equation to realize construction of the infectious disease development trend equation;
the mathematical relationship calculation module 2 for the infectious disease cumulative infectious population receives part of data (all data in the same period as the new infectious disease) of the infectious disease development trend equation calculation module 1, is used for fitting a mathematical relationship equation, related parameters and fitting effect parameters of the new infectious disease and the cumulative infectious population at a certain stage of the existing infectious disease, performs curve fitting through statistical data in the mathematical relationship calculation module 2 for the infectious disease cumulative infectious population, and then constructs a mathematical relationship equation for the infectious disease cumulative infectious population;
the infectious disease development cycle mathematical relation calculation module 3 receives part of data (all data in the same cycle with the new infectious disease) of the infectious disease development trend equation calculation module 1, calculates the newly increased infection rate of the new infectious disease and the existing infectious disease in a certain time period, and calculates to obtain a mathematical relation equation and related parameters of the infectious disease development cycles of two times by comparing the newly increased infection rate, and in the infectious disease development cycle mathematical relation calculation module 3, a new increased infection rate model is established, then statistical data are established, and a mathematical relation equation is established;
the infectious disease development prediction calculation module 4 receives data of the infectious disease development trend equation calculation module 1, the infectious disease accumulated infected person number mathematical relation calculation module 2 and the infectious disease development period mathematical relation calculation module 3, calculates accumulated infected person number of each time node in the future in a circulating mode, draws a curve to obtain an infectious disease development prediction model, constructs the infectious disease development prediction model according to mathematical equations established by the infectious disease development trend equation calculation module 1, the infectious disease accumulated infected person number mathematical relation calculation module 2 and the infectious disease development period mathematical relation calculation module 3, and performs model calculation after relevant data is input to obtain a prediction result.
Fig. 2 is a flowchart of a method for predicting the infectious disease development trend according to the present invention, as shown in fig. 2, the method for predicting the infectious disease development trend includes:
acquiring the data of the total number of the infected persons with the complete morbidity of any plurality of existing infectious diseases, and respectively constructing development trend equations of various infectious diseases by a fitting method;
calculating the mathematical relationship between the accumulated infectious disease number of the multiple infectious diseases and the current accumulated infectious disease number of the new infectious diseases through a development trend equation of the multiple existing infectious diseases and the data of the existing infectious disease number of the new infectious diseases, and obtaining the mathematical relationship equation between the current accumulated infectious disease number of the new infectious diseases and the accumulated infectious disease number of the multiple infectious diseases through a fitting method;
30, calculating a mathematical relation equation of the multiple infectious disease development cycles by comparing the data of the newly increased infectious diseases through the development trend equation of a plurality of existing infectious diseases and the data of the number of the newly transmitted infectious diseases, and constructing a calculation formula of the newly transmitted infectious disease infection rate;
and 40, constructing a development trend prediction model of the new infectious disease through a development trend equation of each infectious disease, a mathematical relation equation of the number of newly-sent infectious disease infected persons and the accumulated number of the infectious diseases of multiple infectious diseases, a mathematical relation equation of the development period of the multiple infectious diseases and the data of the number of the newly-sent infectious diseases, and predicting the accumulated number and change of the newly-sent infectious disease at different time nodes through cyclic calculation.
The method for acquiring the data of the total number of the infected persons with the complete morbidity of any plurality of existing infectious diseases, respectively constructing a development trend equation of each infectious disease through a fitting method, and obtaining the development trend mathematical equation of various infectious diseases through the fitting method according to the historical data of the infectious diseases which are easy to occur comprises the following steps:
drawing a disease data curve of the existing infectious diseases; for example, data of a certain type of existing infectious disease i is obtained, and the statistical time length is from the beginning of outbreak to the basic end, including time t and the accumulated number of infected persons f i (t) and on the abscissa, the number of infected persons f is accumulated i And (t) is a vertical coordinate, and a curve is drawn.
Fitting a change curve of the accumulated number of infected persons of the infectious disease by using a Gaussian equation;
and obtaining a development trend equation of the existing infectious disease according to the fitting result.
The development trend equation of the existing infectious disease is as follows:
wherein t represents the number of days, f i (t) cumulative number of infected persons on day t of the ith infectious disease, a 1 ，a 2 ，a 3 ，b 1 ，b 2 ，b 3 ，c 1 ，c 2 ，c 3 And calculating to obtain the fitting parameters according to the fitting result.
The method comprises the following steps of calculating the mathematical relationship between the accumulated infectious disease number of multiple infectious diseases and the current accumulated infectious disease number of new infectious diseases through a development trend equation of multiple existing infectious diseases and the data of the existing infectious disease number of new infectious diseases, and obtaining the mathematical relationship equation between the current accumulated infectious disease number of new infectious diseases and the accumulated infectious disease number of multiple infectious diseases through a fitting method, wherein the mathematical relationship equation comprises the following steps:
counting the data of the number of infected persons of the new infectious disease in a certain time period and the data of the number of infected persons of the same type of infectious disease in the same time period; for example, acquiring t after outbreak of newly-occurring infectious disease j 0 To t k The accumulated infectious people number data of the time period and the data of the same time period of the existing infectious diseases i of the same type;
fitting a relation curve of the number of the two infectious diseases accumulated infected persons by using a power exponent approximation algorithm;
and obtaining a relation equation of the accumulated infectious people number of the two infectious diseases according to the fitting calculation result.
The relation equation of the accumulated infectious population of the two infectious diseases is as follows:
f j (x)＝a×x b +c；(2)
wherein x is the cumulative number of known infections of the ith species, and f j (x) And (4) accumulating the number of newly-transmitted infectious diseases j, and calculating according to the fitting result by using a, b and c as fitting parameters.
The method comprises the following steps of calculating a mathematical relation equation of the development cycle of multiple infectious diseases by comparing the data of newly increased infectious diseases through a plurality of development trend equations of existing infectious diseases and the data of the number of newly increased infectious diseases, and constructing a calculation formula of the infection rate of the newly increased infectious diseases, wherein the calculation formula comprises the following steps:
constructing a new infectious disease infection probability model;
counting the newly increased infection rate of the newly-occurred infectious disease in a set time period and the infection rate of the existing infectious diseases of the same type in the same time period, e.g. calculating t after the newly-occurred infectious disease j outbreak 0 To t k Data of newly increased infection rate of the time period and data of the same time period of the same type of transmitted disease i;
constructing an infection period mathematical relation formula of the new infectious disease and the existing infectious diseases of the same type.
The probability model of the new infectious disease infection is as follows:
in the formula, p k The new infection rate on day k of the newly-developed infectious disease, x k The number of newly-infected people on the k day of new infectious diseases.
The mathematical relationship formula of the infection period of the new infectious disease and the existing infectious diseases of the same type is constructed as follows:
wherein r represents the comparison relationship between the epidemic situation of the new infectious disease and the existing infectious disease of the same type, q (j) is the control strength of the new infectious disease j, and the value range is 0 to 1,p (i) t New infection rate of the established infectious disease i on day t, p (j) t The new infection rate of the existing infectious disease j on the t day is increased.
The method comprises the following steps of constructing a new infectious disease development trend prediction model according to formula 1, formula 2, formula 3 and formula 4:
f j (t)＝a×f i (x(t)) b +c；
x(t)＝r×t；
in the formula, f j (t) represents the cumulative infectious disease number of newly-released infectious disease j at the moment t, r represents the comparison relation of two epidemic periods, t represents the number of days, and x (t) represents the approximate time of infectious disease j in infectious disease i.
Calculating the future of newly-developed infectious disease according to equation 5
When the accumulated number of infected people is stable, namely the newly-increased number of infected people is less than 100-50, the newly-increased infectious disease j is considered to be basically finished.
In one specific example, the data of the infectious disease in 2003 is used to predict the development trend of the infectious disease in 2020 based on the existing infectious disease data.
1. Construction of the equation for the development tendency of SARS
According to the original data of the accumulated number of the infected people of SARS in 2003, a development trend equation is obtained by fitting a Gaussian equation
Cumulative infectious person number data of certain infectious disease in 2003
Fitting by using a Gaussian equation, wherein the SARS development trend equation is as follows:
wherein t represents the number of days, f i (t) the cumulative number of infected persons on day t of SARS, a 1 ＝2402，a 2 ＝ 1485，a 3 ＝484，b 1 ＝42.48，b 2 ＝20.76，b 3 ＝8.99，c 1 ＝1485，c 2 ＝12.81， c 3 ＝9.2。
2. Relation equation between accumulated infectious disease number in 2020 year and infectious disease number in 2003 year
And fitting to obtain a comparison relation of the accumulated infection data of the two epidemic situations according to the conditions of the accumulated infectious population data of the certain infectious disease in 2020 and the accumulated infectious population data of the certain infectious disease in 2003. Because the data of the epidemic situation of a certain infectious disease has large fluctuation in 2020, the data of the person infected by the certain infectious disease is influenced by a certain subjectivity, for example, the person infected by the certain infectious disease cannot be completely detected due to insufficient detection capability, sudden conversion between suspected cases and confirmed cases, and the like, so that the data of the person infected by the certain infectious disease in 2020.
Accumulated infected person number comparison data in the first 10 days
The relation equation of the accumulated infectious disease number in 2020 to the infectious disease number in 2003 is obtained by power index fitting:
f j (x)＝a×x b +c；(7)
wherein x is the cumulative number of infectious diseases in 2003, fj (x) is the cumulative number of infectious diseases in 2020, and a =0.0178, b =1.735, c = -385.7.
3. Equation for relation between epidemic days of certain infectious disease in 2020 and development cycle of certain infectious disease in 2003
The newly increased infection rate data of the two epidemic situations are as follows, because the 1 st day data of a certain infectious disease in 2003 does not exist, the 1 st day data of the two epidemic situations are excluded, the epidemic situation control force of the certain infectious disease in 2020 is 0.48, and the proportion of the two epidemic situations in days is obtained according to a formula 3: 0.852.
data of newly increased infection rate of certain infectious disease in 2020 and certain infectious disease in 2003
4. Model equation for predicting infectious disease development trend in 2020
According to the formula 6 and the formula 7, a prediction model equation of the infectious disease development trend in 2020 is obtained:
f j (t)＝a×f i (x(t)) b +c；(8)
x(t)＝r×t
wherein, f j (t) represents the cumulative infectious population of a certain infectious disease at time t in 2020, r =0.852 represents the comparison relationship between two epidemic periods, and t represents the number of days.
5. Calculation results
And (3) performing cyclic calculation by using a formula 8 to finally obtain that the accumulated infected people tend to be stable in 45-48 days from the statistical data of the certain infectious disease in 2020 (24 days in 1 month), the predicted epidemic situation is basically stable, and the accumulated infected people are 13770.
It will be evident to those skilled in the art that the embodiments of the present invention are not limited to the details of the foregoing illustrative embodiments, and that the embodiments of the present invention are capable of being embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the embodiments being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units, modules or means recited in the system, apparatus or terminal claims may also be embodied by one and the same item, module or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention and not for limiting, and although the embodiments of the present invention are described in detail with reference to the above preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the embodiments of the present invention without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for predicting the development trend of an infectious disease, which is characterized by comprising the following steps:
acquiring the data of the total number of the infected persons with complete morbidity of any plurality of existing infectious diseases, and respectively constructing a development trend equation of each existing infectious disease through a fitting method;
calculating the mathematical relationship between the accumulated infectious disease number of the existing infectious diseases of the same type and the current accumulated infectious disease number of the new infectious disease through a plurality of development trend equations of the existing infectious diseases of the same type and the data of the existing infectious disease number of the new infectious disease, and obtaining the mathematical relationship equation between the current accumulated infectious disease number of the new infectious disease and the accumulated infectious disease number of the existing infectious disease of the same type through a fitting method;
according to the development trend equation of the existing infectious diseases of the same type and the existing infectious people number data of the new infectious diseases, establishing an infection period mathematical relation formula of the new infectious diseases and the existing infectious diseases of the same type by comparing the data of the new infectious rates;
and constructing a development trend prediction model of the new infectious disease through the development trend equation of the existing infectious diseases of the same type, the mathematical relation equation of the number of the newly-sent infectious diseases infected with the existing infectious diseases of the same type and the accumulated infectious people of the existing infectious diseases of the same type, the mathematical relation equation of the infection period of the new infectious diseases and the existing infectious people data of the new infectious diseases, and predicting the accumulated infectious people and change of the new infectious diseases at different time nodes through cyclic calculation.
2. The method of predicting the infectious disease progression according to claim 1, wherein the step of obtaining the data on the onset of any of a plurality of established infectious diseases and constructing the respective infectious disease progression equations by a fitting method comprises:
drawing a curve of the disease data of the existing infectious diseases;
fitting a change curve of the accumulated number of infected persons of the infectious disease by using a Gaussian equation;
and obtaining a development trend equation of the existing infectious disease according to the fitting result.
3. The method of predicting the infectious disease spreading trend according to claim 2, wherein the equation of spreading trend of the existing infectious disease is obtained according to the fitting result:
wherein t represents the number of days, f i (t) the cumulative number of infected persons on day t of the ith established infectious disease, a 1 ，a 2 ，a 3 ，b 1 ，b 2 ，b 3 ，c 1 ，c 2 ，c 3 And calculating to obtain the fitting parameters according to the fitting result.
4. An infectious disease development trend prediction method as set forth in claim 1, wherein the step of calculating a mathematical relationship between the cumulative infected person with the same type of existing infectious disease and the current cumulative infected person with the new infectious disease through the development trend equation of the same type of existing infectious disease and the data of the number of existing infectious persons with the new infectious disease comprises the steps of:
counting the number of the newly-released infectious diseases in a certain time period and the number of the newly-released infectious diseases in the same time period of a certain infectious disease of the same type;
fitting a relation curve of the accumulated infectious disease number of the two infectious diseases by using a power exponent approximation algorithm;
and obtaining a relational equation of the accumulated infectious population of the two infectious diseases according to the fitting calculation result.
5. An infectious disease development trend prediction method as claimed in claim 4, wherein the equation of relationship between the cumulative infectious disease number of two infectious diseases obtained according to the fitting calculation result is:
f j (x)＝a×x b +c；
wherein x is the cumulative number of known infections of the ith species, and f j (x) And (4) accumulating the number of the newly-released infectious diseases j, and calculating according to fitting parameters a, b and c.
6. An infectious disease development trend prediction method as claimed in claim 1, wherein the step of establishing a new infectious disease infection rate calculation formula by comparing the data of new infectious diseases with the development trend equation of the existing infectious diseases of the same type and the data of the number of the existing infectious people of the new infectious diseases comprises:
constructing a new infectious disease infection probability model;
counting the data of newly increased infection rate of new infectious diseases in a set time period and the infection rate data of the existing infectious diseases of the same type in the same time period;
constructing an infection period mathematical relation formula of the new infectious disease and the existing infectious diseases of the same type.
7. The method of predicting the infectious disease development tendency according to claim 6, wherein the constructing of the new infectious disease infection probability model comprises:
in the formula, p k The new infection rate on day k of the newly-developed infectious disease, x k The new number of newly infected people on the k day of new infectious disease.
8. An infectious disease development trend prediction method as claimed in claim 7, wherein the mathematical relationship formula of the infection cycle between the new infectious disease and the existing infectious disease of the same type is as follows:
wherein r represents the comparison relationship between the epidemic situation of the new infectious disease and the existing infectious disease of the same type, q (j) is the control strength of the new infectious disease j, and the value range is 0 to 1,p (i) t New infection rate of the same type of existing infectious disease i on day t, p (j) t The infection rate of the existing infectious disease j on the t day is increased.
9. An infectious disease development trend prediction method as claimed in claim 1, wherein the new infectious disease development trend prediction model is constructed by using the development trend equation of the existing infectious diseases of the same type, the mathematical relationship equation of the number of newly-released infectious diseases infected with the accumulated infectious diseases of the existing infectious diseases of the same type, the mathematical relationship equation of the infection cycles of the new released infectious diseases with the existing infectious diseases of the same type, and the existing infectious disease number data of the new released infectious diseases, and the accumulated infectious diseases and changes of the new released infectious diseases at different time nodes are predicted by cyclic calculation as follows:
f j (t)＝a×f i (x(t)) b +c；
x(t)＝r×t；
in the formula (f) j (t) cumulative number of newly-developed infectious disease j at time t, f i (t) represents the accumulated infectious population of the same type of the existing infectious disease i at the time t, r represents the comparison relation of two epidemic periods, t represents the number of days, and x (t) represents the approximate time of the new infectious disease j in the same type of the existing infectious disease i.
10. A system for predicting a trend of an infectious disease, comprising:
the infectious disease development trend equation calculation module calls a fitting equation according to historical data of the occurring infectious diseases to obtain a development trend mathematical equation of various types of transmitted infectious diseases;
the system comprises an infectious disease accumulated infectious disease number mathematical relation calculation module, an infectious disease development trend equation calculation module, an infectious disease total infectious disease number mathematical relation calculation module and an infectious disease total infectious disease number mathematical relation calculation module, wherein the data obtained by the infectious disease development trend equation calculation module are received, the mathematical relation between the same type of existing infectious disease accumulated infectious disease number and the current new infectious disease infected number is calculated through a development trend equation of the same type of existing infectious disease and the current infectious disease number data of the new infectious disease, and a mathematical relation equation between the current new infectious disease infected number and the same type of existing infectious disease accumulated infectious disease infected number is obtained through a fitting method;
the infectious disease development cycle mathematical relation calculation module receives the data obtained by the infectious disease development trend equation calculation module, calculates the newly increased infection rate of the newly increased infectious disease and the existing infectious diseases of the same type in a certain time period, and constructs an infection cycle mathematical relation formula of the newly increased infectious disease and the existing infectious diseases of the same type through comparison of the newly increased infection rate;
the infectious disease development prediction calculation module receives data obtained by data calculation of the infectious disease development trend equation calculation module, the infectious disease accumulated infectious person number mathematical relation calculation module and the infectious disease development period mathematical relation calculation module, constructs a new infectious disease development trend prediction model, and predicts the accumulated infectious person number and change of new infectious diseases at different time nodes through cyclic calculation.
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