Infection number prediction device, infection number prediction method, infection number prediction program, and computer-readable recording medium

Abstract

To provide an infected person number prediction device, an infected person number prediction method, an infected person number prediction program and a computer-readable recording medium capable of predicting the number of infected persons more accurately.SOLUTION: An infected person number prediction device is configured to predict the number of infected persons of an infectious disease in a specific area, and comprises an infected person number prediction unit 41d that predicts a higher number of infected persons as the temperature in the specific area becomes lower. The infected person number prediction unit 41d predicts the number of infected persons so that an increase rate of the number of infected persons at the time when the temperature becomes low within a range equal to or lower than a set optimum temperature is higher than an increase rate of the number of infected persons at the time when the temperature becomes low within a range higher than the optimal temperature.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an infected person number prediction device, an infected person number prediction method, an infected person number prediction program, and a computer-readable recording medium. [Background technology]

[0002] 2. Description of the Related Art Conventionally, there is known a prediction device that predicts the spread of an infectious disease based on the number of patients (the number of infected people) who have visited a medical institution and been diagnosed with an infectious disease (see, for example, Patent Documents 1 and 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-081321 A [Patent Document 2] JP 2011-128935 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the devices described in Patent Documents 1 and 2 are limited to predicting epidemics by determining trends in increases and decreases based on the actual number of patients, and there is room for improvement in terms of accuracy.

[0005] The present invention has been made to solve such conventional problems, and its purpose is to provide an infected person number prediction device, an infected person number prediction method, an infected person number prediction program, and a computer-readable recording medium that can predict the number of infected people with greater accuracy. [Means for solving the problem]

[0006] The infected person number prediction device of the present invention is an infected person number prediction device that predicts the number of people infected with an infectious disease in a specific area, and is equipped with a prediction means for predicting the number of infected people in the specific area, and the prediction means predicts the number of infected people by setting the rate of increase in the number of infected people when the temperature drops to a range below a set optimal temperature higher than the rate of increase in the number of infected people when the temperature drops to a range above the optimal temperature.

[0007] The method for predicting the number of infected people according to the present invention is a method for predicting the number of infected people by an infected person prediction device that predicts the number of people infected with an infectious disease in a specific area, and includes a prediction step of predicting the number of infected people in a specific area, in which the prediction step predicts the number of infected people by setting the rate of increase in the number of infected people when the temperature drops to a range below a set optimal temperature higher than the rate of increase in the number of infected people when the temperature drops to a range above the optimal temperature.

[0008] In addition, the infected number prediction program of the present invention is an infected number prediction program for causing a computer to function as the above-mentioned infected number prediction device, and the computer-readable recording medium of the present invention is a computer-readable recording medium on which the above-mentioned infected number prediction program is recorded. Effect of the Invention

[0009] According to the present invention, the number of infected people is predicted by setting the increase rate of the number of infected people higher than the increase rate of the number of infected people when the temperature falls below the optimum temperature and when the temperature falls above the optimum temperature. Here, the inventors of the present invention have found that the immune defense function of humans is reduced due to the atrophy of the tonsils caused by cold stimulation of the extremities, and that the immune defense function is significantly reduced especially when the temperature falls below the optimum temperature. For this reason, for example, when the temperature falls by 1 degree above the optimum temperature, the increase rate of the number of infected people is small in the former case and very large in the latter case. Therefore, by making a prediction taking into account the increase rate of the number of infected people with the optimum temperature as a boundary, it is possible to predict the epidemic more accurately. [Brief description of the drawings]

[0010] [Figure 1] 1A and 1B are hardware configuration diagrams showing an infected person number prediction device according to an embodiment of the present invention, in which (a) is an external view and (b) is a block diagram. [Diagram 2] FIG. 2 is a software configuration diagram showing a CPU of the infected person number prediction device according to the embodiment of the present invention. [Diagram 3] FIG. 1 is a diagram showing an arithmetic formula required for predicting the number of infected people. [Figure 4] FIG. 13 is a diagram showing the correlation between the coefficient β shown in the formula (4) and the temperature. [Diagram 5] 4 is a flowchart showing the process of the infected person number prediction device according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] The present invention will be described below along with preferred embodiments. Note that the present invention is not limited to the embodiments shown below, and can be modified as appropriate within the scope of the present invention. In addition, in the embodiments shown below, some configurations are omitted from illustration and description, but it goes without saying that publicly known or well-known technologies are appropriately applied to the details of the omitted technologies within the scope of the contents described below.

[0012] FIG. 1 is a hardware configuration diagram showing an infected person number prediction device according to an embodiment of the present invention, where (a) shows an external view and (b) shows a block diagram.

[0013] 1(a) and 1(b) is realized as a function of a personal computer, for example, and predicts the number of infected people in a specific area based on information input by an operator. Such an infected person prediction device 1 is equipped with operation means such as a keyboard 2 and a mouse 3, and predicts the number of infected people through operations on the operation means.

[0014] Such an infected person number prediction device 1 includes a CPU (Central Processing Unit) 4, a display 5, a communication I / F (interface) section 6, and a HDD (Hard Disk Drive) 7, in addition to an operation means.

[0015] The CPU 4 controls the entire infected number prediction device 1 according to this embodiment, and includes a ROM (Read Only Memory) 4a and a RAM (Random Access Memory) 4b. The ROM 4a is a read-only memory that stores an infected number prediction program for operating the infected number prediction device 1. The RAM 4b is a readable and writable memory that stores various data and has an area necessary for the processing operations of the CPU 4.

[0016] The display 5 displays images input by operating the keyboard 2 or mouse 3, and displays the number of infected people predicted by the infected number prediction device 1. The communication I / F unit 6 is an interface for communicating with other devices. The contents stored in a memory unit (reference numeral 42) described later may be obtained from other devices through this communication I / F unit 6.

[0017] The HDD 7 is an auxiliary storage device connected to a personal computer. The HDD 7 may store an infected number prediction program for making the infected number prediction device 1 function, similar to the ROM 4a. That is, the CPU 4 may realize each function of the infected number prediction device 1 according to the present embodiment according to the program stored in the HDD 7. If possible, a USB (Universal Serial Bus) or the like may be provided instead of or in addition to the HDD.

[0018] In the following description, it is assumed that the infected number prediction device 1 is used in a medical institution, but the infected number prediction device 1 may also be used in other organizations such as a local government or a fire department. In particular, when used in a local government, the number of infected people in the area can be predicted and used as a guide for vaccine production. If applicable, the infected number prediction device 1 may also be used in places other than the above. Furthermore, in this embodiment, the infected number prediction device 1 is described as one function of a personal computer, but the present invention is not limited to this, and the infected number prediction device 1 may be configured by a system consisting of a mobile terminal such as a smartphone and a server, or a system consisting of two or more personal computers.

[0019] Fig. 2 is a software configuration diagram showing the CPU 4 of the infected person number prediction device 1 according to the embodiment of the present invention. As shown in Fig. 2, the CPU 4 executes an infected person number prediction program stored in the ROM 4a (see Fig. 1(b)), thereby causing a processing unit 41 including a display control unit 41a, an input unit 41b, a temperature estimation unit 41c, and an infected person number prediction unit (prediction means) 41d to function. The CPU 4 also includes a storage unit 42.

[0020] The storage unit 42 shown in FIG. 2 stores data and calculation formulas required for the temperature estimation unit 41c to perform calculations to estimate future temperatures. The storage unit 42 stores the temperatures (average temperatures) for each period (for example, for each day or week) for each area (for example, for each country, region, and city / town / village) over a long period such as the past 10 years. The storage unit 42 also stores a calculation formula for estimating future (future) temperatures from past temperature data for each area. The calculation formula may be one that simply averages past temperatures, or one that averages temperatures excluding temperatures that are singular points, or one that estimates future temperatures from changes in past temperatures (such as the average temperature gradually increasing every year) (for example, if the average temperature increases by one degree every year, the temperature of last year may be estimated by adding one degree). Furthermore, the temperature estimation unit 41c can apply any known or publicly known method of temperature estimation.

[0021] The memory unit 42 also stores data and calculation formulas required for the infected person number prediction unit 41d to perform the calculation for predicting the number of infected people. Fig. 3 is a diagram showing the calculation formulas required for the calculation for predicting the number of infected people. As shown in Fig. 3, the memory unit 42 stores formulas (1) to (4) for performing the calculation for predicting the number of infected people.

[0022] In these formulas, S is the susceptible population (the population that may be infected), I is the number of infected people, and R is the number of people who have acquired immunity (the number of people who have recovered from an infected state). p is a number indicating the area, and for example, if there are 47 areas corresponding to the 47 prefectures of Japan, p will be any number between "1" and "47". t indicates a period (for example, days). For example, when a value indicating Tokyo (a specific area) is substituted for p, S p,t +I p,t +R p,t = 12 million people (total population of Tokyo). Also, β is the coefficient related to infection, and γ is the coefficient related to recovery.

[0023] Here, equation (1) is the decrease in the number of recipients, ΔS p,t+1 This shows the population of recipients S in the current period t. p,t In contrast, the number of infected people in the current period t is I p,t Assuming that a person comes into contact with another person, this equation shows the decrease in the receptive population due to new infections based on coefficient β. Since the receptive population decreases when an infection occurs, equation (1) has a "-" added before coefficient β.

[0024] Equation (2) expresses the increase or decrease in the number of infected people, ΔI p,t+1 This represents the reduction in the susceptible population (i.e., the number of newly infected people who have recovered (those who have acquired immunity)) shown in equation (1) minus the number of newly infected people (those who have acquired immunity).

[0025] Equation (3) is the number of people who recover and become immune, ΔR p,t+1 This indicates the number of infected people in the current period t, I p,t The number of people who recover at a rate of coefficient γ for ΔR p,t+1This shows that.

[0026] Equation (4) shows the details of the coefficient β related to infection. Here, the coefficient β is calculated from an arithmetic expression including a first coefficient β1, a second coefficient β2, and a third coefficient β3. The first coefficient β1 is the temperature T p,t The second coefficient β2 is the coefficient indicating the infection based on the temperature T p,t and the optimum temperature T inf The third coefficient β3 is a coefficient related to the infection rate based on the population density, number of workplaces, number of schools, etc. in each area.

[0027] Figure 4 shows the relationship between the coefficient β in equation (4) and temperature T p,t It should be noted that Figure 4 shows the correlation when a particular infectious disease and area are specified. As shown in Figure 4, the coefficient β is p,t The lower the temperature, the higher the value. In addition, the coefficient β p,t is the optimum temperature T inf The slope is small above the temperature T p,t is the optimum temperature T inf It is considered that the shape will have a large inclination in the following range.

[0028] Referring again to Fig. 2, the storage unit 42 stores, in addition to the above formulas (1) to (4), data required for predictive calculations such as initial values ​​and population density for each specific area. Note that the storage unit 42 may store the correlation shown in Fig. 4 instead of formula (4) shown in Fig. 3.

[0029] Furthermore, the memory unit 42 stores the optimum temperature T inf It is preferable to store the optimum temperature T inf is the temperature based on the human body. In humans, cold stimulation of the extremities causes the tonsils to shrink, and the immune defense function is weakened. The optimal temperature T infis the temperature at which the immune defense function begins to drop drastically. The immune defense function is influenced by genetic information such as race. In addition, the resistance to cold stimuli differs between people living in hot areas and people living in cold areas. For this reason, the memory unit 42 stores the optimal temperature T inf It is preferable to store the above information.

[0030] The display control unit 41a controls the display contents to be displayed on the display 5 (see FIG. 1(a)), and when an area for predicting the number of infected people is specified via an operation means, for example, the display unit 41a displays the area and displays the number of infected people predicted by the infected number prediction unit 41d as a numerical value or a graph. The input unit 41b reads data and the like required for estimating the temperature and predicting the number of infected people from the storage unit 42 or an external device, and supplies the data and the like to the temperature estimation unit 41c and the infected number prediction unit 41d.

[0031] The infected person number prediction unit 41d predicts the number of infected people of an infectious disease. Here, the predicted number of infected people may be an accurate number shown to the one digit, or may be a number in which the one digit or the ten digit is truncated or rounded off.

[0032] The infected person number prediction unit 41d predicts the number of infected people based on the formulas (1) to (4) as described above. In particular, as shown by the coefficient β in FIG. inf The following range and the optimum temperature T inf The slope of the coefficient β is large in the former range and small in the latter range. inf The rate of increase in the number of infected people when the temperature drops within the following range and the optimal temperature T inf The number of infected people will be predicted by setting the former higher than the latter, and the latter when the temperature drops to a range exceeding 100°C. This will allow for more accurate predictions of the number of infected people.

[0033] Furthermore, the input unit 41b according to this embodiment is capable of inputting information that a specific area for which the number of infected people is predicted corresponds to a restricted area. Restricted areas are areas where people are prohibited from moving around or going out, such as lockdown areas, areas under a state of emergency, and areas where preventive measures against the spread of infection are applied, or where calls are made to restrict such movement or going out.

[0034] Furthermore, when information indicating that a specific area is a restricted area is input by the input unit 41b, the infected person number prediction unit 41d predicts the number of infected people by converting the temperature of the specific area to a higher value during the period in which the specific area is restricted. For this reason, the storage unit 42 stores temperature rise data corresponding to the restriction content, such as lockdown "2°C", state of emergency declaration "1°C", and spread prevention measures "0.5°C", for example.

[0035] In this way, by predicting the number of infected people by converting the temperature to a higher value when the area falls within the restricted area, it is possible to suppress the complexity of the prediction calculation without requiring a complex and new calculation formula when the area falls within the restricted area.

[0036] Next, a description will be given of the processing of the infected number prediction device 1 according to this embodiment. Fig. 5 is a flowchart showing the processing of the infected number prediction device 1 according to this embodiment.

[0037] 5, the processing unit 41 of the infected number prediction device 1 determines whether an area for predicting the number of infected people is specified (S1). If the area is not specified (S1: NO), this process is repeated until the area is specified.

[0038] When an area is specified (S1: YES), the area is thereafter treated as a specific area, and the input unit 41b reads past temperature data, population, population density, and other data of the specific area from the storage unit 42 (S2).

[0039] Next, the processing unit 41 judges whether a prediction period for predicting the number of infected people has been specified (S3). The prediction period here may be one period (for example, only a specific day) when one day is one period, or may be a period spanning multiple periods (for example, from January 1 to January 31). The period does not have to be in units of one day, and may be a week, etc. Furthermore, when the prediction period is a period spanning multiple periods, the multiple periods do not have to be consecutive, and may be discontinuous (for example, it may be only Tuesdays from January 1 to January 31).

[0040] If the prediction period is not specified (S3: NO), this process is repeated until the prediction period is specified. On the other hand, if the prediction period is specified (S3: YES), the temperature estimation unit 41c estimates the temperature in the prediction period for predicting the number of infected people (S4). The temperature estimation unit 41c estimates the temperature in the prediction period taking into account, for example, averaging or recent changes.

[0041] After that, the processing unit 41 judges whether or not the prediction period corresponds to a period requiring restriction (S5). That is, the processing unit 41 judges whether or not the specific area is a restricted area during the prediction period.

[0042] If the predicted period does not correspond to a period requiring restriction (S5: NO), the process proceeds to step S7. On the other hand, if the predicted period corresponds to a period requiring restriction (S5: YES), the infected person number prediction unit 41d corrects the temperature estimated in step S4 for the period requiring restriction to the upward side (S6). The amount of increase to be corrected differs depending on the type of restriction. Then, the process proceeds to step S7.

[0043] In step S7, the infected person prediction unit 41d first specifies the previous period (t=0) in order to predict the number of infected people in the first period of the prediction period (S7). Next, the decrease in the acceptable population ΔS p,t+1 , the increase or decrease in the number of infected people ΔI p,t+1 , and the number of people who will become newly immune ΔR p,t+1 is calculated based on the formulas (1) to (4) shown in FIG. 3 (S8).

[0044] Next, the infected person number prediction unit 41d calculates the number of infected people I p,t , the increase or decrease in the number of infected people ΔI calculated in step S8 p,t+1 Adding this, the number of infected people in the next period t+1, I p,t+1 In the process of step S9, the acceptable population S for the next period t+1 is calculated (predicted) for the calculation process in the period after next t+2 (processing of S8). p,t+1 and the number of people who acquire immunity R p,t+1 Also, at t=0, a pre-input initial value may be used for the number of infected people in the period immediately preceding the prediction period, or the calculation contents from before the prediction period may be used. The latter will be explained in detail. For example, assume that the current date is January 1st and the number of infected people is 100. The prediction period is from February 1st to February 10th. In this case, the number of infected people is predicted sequentially for January 2nd to January 31st, which is before the prediction period, based on the number of infected people of 100 on January 1st, and the number of infected people as of January 31st is calculated. This allows a more accurate value to be used for the number of infected people in the period immediately preceding the prediction period.

[0045] Thereafter, the infected number prediction unit 41d judges whether the prediction calculation of the number of infected people has been performed until the end of the prediction period (S10). If it is judged that the prediction calculation of the number of infected people has not been performed until the end of the prediction period (S10: NO), the infected number prediction unit 41d sets t=t+1 (S11) and the process proceeds to step S8.

[0046] On the other hand, if it is determined that the prediction calculation of the number of infected people has been performed until the end of the prediction period (S10: YES), the display control unit 41a displays the number of infected people in the prediction period using numerical values, graphs, etc. (S12). After that, the process shown in FIG. 5 ends.

[0047] In this way, according to the infected person number prediction device 1, the infected person number prediction method, the infected person number prediction program, and the computer-readable recording medium of the present embodiment, the optimal temperature T infThe rate of increase in the number of infected people when the temperature drops within the following range and the optimal temperature T inf The number of infected people is predicted by setting the former higher than the latter, and the latter being the rate of increase in the number of infected people when the temperature drops to a range exceeding the optimal temperature T inf We found that the immune defense function is significantly reduced when the temperature falls below the optimal temperature T inf They found that when the temperature drops by 1 degree above the optimum temperature range, the increase in the number of infected people is small in the former case, and very large in the latter case. Therefore, the optimum temperature T inf By making predictions that take into account the rate of increase in the number of infected people around this boundary, it is possible to make more accurate epidemic predictions.

[0048] In addition, by predicting the number of infected people in a specific area based on at least one of the population density, number of workplaces, and number of schools in the area, it is possible to predict the number of infected people taking into account population density, which is the frequency of contact between infected and non-infected people, and environments such as workplaces and schools, which are prone to close contact.

[0049] In addition, the optimum temperature T inf is a value set for each specific area. Here, the inventor of the present invention defines the optimal temperature T inf It was found that there are differences in the optimum temperature T due to the habituation of people living in cold regions and genetic factors such as race. inf Setting this for each specific area will contribute to more accurate prediction of the number of infected people.

[0050] In addition, if a specific area falls under a restricted area for infectious disease control, the number of infected people is predicted by converting the temperature of the specific area to a higher value during the restricted period. In this way, when a specific area becomes a restricted area, by converting the temperature instead of using a special calculation formula, it is possible to contribute to more accurate prediction of the number of infected people while suppressing the complexity of the prediction calculation.

[0051] The present invention has been described above based on an embodiment, but the present invention is not limited to the above embodiment, and modifications may be made or known technologies may be combined without departing from the spirit of the present invention.

[0052] For example, the infected number prediction device 1 in this embodiment is equipped with a temperature estimation unit 41c, but is not limited to this. Without being equipped with the temperature estimation unit 41c, a process of reading an estimate already made by an external institution or device may be performed, or the temperature may be input by the user.

[0053] In addition, in the process shown in FIG. 5, a flowchart is exemplified in which one area is designated as the specific area, but this is not limiting. Two or more areas may be designated as specific areas, and after predicting the number of infected people in the first area, the number of infected people may be predicted in the second and subsequent areas. Also, two or more areas may be integrated to predict the number of infected people. In this case, the optimal temperature T inf may be averaged, or one of them may be used.

[0054] Furthermore, in this embodiment, when a specific area falls under a restricted area, the number of infected people is predicted by converting the temperature into an upward conversion, but this is not limited to this, and an arithmetic formula or the like may be provided for when the area falls under a restricted area.

[0055] The infected person number prediction unit 41d according to the present embodiment predicts the number of infected people based on the formulas (1) to (4), but is not limited thereto. For example, in contrast to a publicly known or well-known method of predicting the number of infected people, the infected person number is predicted to be higher as the temperature decreases, and the temperature decrease is closer to the optimal temperature T inf When the temperature drop is within the range below, the optimum temperature T inf For example, in the case of influenza, the number of infected people per day from October 1st to March 31st is averaged over the past 10 years to calculate the number of infected people.inf When the temperature drop is within the range below, the optimum temperature T inf A correction may be made so that the number of infected people is larger than when the range is exceeded.

[0056] Furthermore, in the above embodiment, the infected number prediction program is stored in the ROM 4a of the infected number prediction device 1, but this is not limited to this and may be stored in other types of recording media such as an HDD, USB, CD-ROM, CD-R, etc.

[0057] In addition, in the above embodiment, the infected person number prediction device 1 is assumed to be a single device, but the present invention is not limited to this and may be a system formed of a plurality of devices. [Explanation of symbols]

[0058] 1: Infection number prediction device 41: Processing section 41a: Display control unit 41b: Input section 41c: Temperature estimation section 41d: Infected person number prediction section (prediction means) 42: Storage section

Claims

1. An infected person number prediction device that predicts the number of infected people of an infectious disease in a specific area, Equipped with a forecasting tool to predict the number of infected people in a specific area, The prediction means predicts the number of infected people by setting the rate of increase in the number of infected people when the temperature falls within a range below a set optimum temperature and the rate of increase in the number of infected people when the temperature falls within a range above the optimum temperature higher than the former. An infected person prediction device characterized by the above.

2. The prediction means predicts the number of infected people in a specific area based on at least one of population density, number of workplaces, and number of schools in the specific area. The device for predicting the number of infected people according to claim 1 .

3. The optimum temperature is a value set for each specific area.

3. The infected person number prediction device according to claim 1 or 2.

4. When the specific area corresponds to a restricted area for infectious disease countermeasures, the prediction means predicts the number of infected people by converting the temperature of the specific area to be higher during the period in which the specific area is the restricted area. The device for predicting the number of infected persons according to any one of claims 1 to 3.

5. An infected person number prediction method by an infected person number prediction device that predicts the number of infected people of an infectious disease in a specific area, A prediction process is provided to predict the number of infected people in a specific area, In the prediction step, the number of infected people is predicted by setting the increase rate of the number of infected people when the temperature falls within a range below a set optimum temperature and the increase rate of the number of infected people when the temperature falls within a range above the optimum temperature higher than the former. A method for predicting the number of infected people.

6. An infected person number prediction program for causing a computer to function as the infected person number prediction device according to any one of claims 1 to 4.

7. A computer-readable recording medium on which the program for predicting the number of infected persons according to claim 6 is recorded.

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