Infection risk estimation device, infection risk estimation method, and program

Abstract

An infection risk estimation device (100) comprises: a first acquisition unit (102a) that acquires visitor information including an attribute of a visitor to a target place; a second acquisition unit (102b) that acquires infection condition information including an infection condition of an infection disease in each region; and an estimation unit (104) that acquires, by using the visitor information and infection condition information, a first risk index R1 indicating the degree of risk of infection with the infection disease in the target place.

Description

Technical Field

[0001] The present invention relates to an infection risk estimation device, an infection risk estimation method, and a program.

Background Art

[0002] Various techniques for estimating the infection risk of contracting an infectious disease have been proposed.

[0003] For example, a disclosed information providing method executed by a computer of an information providing system that provides information regarding an infectious disease described in Patent Document 1. According to Patent Document 1, the computer acquires regional infection information from one or more voice recognition devices connected via a network, and calculates an infection risk value representing the magnitude of the infection risk for each of the one or more regions based on the acquired regional infection information. Then, the computer generates output information according to the calculated infection risk value for each of the one or more regions, and transmits the generated output information for each of the one or more regions to a device existing in the region corresponding to the output information via the network. According to the description of Patent Document 1, the regional infection information indicates one or more infection caution levels obtained by analyzing voice signals by the one or more voice recognition devices, and one or more regions associated with the one or more infection caution levels.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In the information providing method described in Patent Document 1, an infection risk value is calculated based on regional infection information acquired from one or more voice recognition devices. However, it is considered that infectious diseases may spread as people move, and in order to take appropriate measures to prevent the spread of infectious diseases, it is desirable to be able to know the risk of contracting infectious diseases in various places, for example.

[0006] The present invention has been made in view of the above circumstances, and one of its objects is to support appropriate measures for preventing the spread of infectious diseases.

Means for Solving the Problems

[0007] To achieve the above object, an infection risk estimation device according to a first aspect of the present invention includes: an acquisition means for acquiring visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region; an estimation means for using the visitor information and the infection status information to acquire a first risk index indicating the degree of risk of contracting the infectious disease at the target location 、 Output means for outputting output information for assisting in preventing the spread of the infectious disease based on the first risk index and 、 The estimation means further obtains a second risk index, which is an index corresponding to the number of visitors by residential area, using the first risk index and the visitor information When the first risk index satisfies a first standard and the second risk index satisfies a second standard, the output means outputs, as the output information, diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second standard is provided.

[0008] To achieve the above object, an infection risk estimation method according to a second aspect of the present invention includes: a computer acquiring visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region; using the visitor information and the infection status information to acquire a first risk index indicating the degree of risk of contracting the infectious disease at the target location; using the first risk index and the visitor information to acquire a second risk index which is an index corresponding to the number of visitors by residential area; When the first risk index satisfies the first criterion and the second risk index satisfies the second criterion, diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion is provided to assist in preventing the spread of the infectious disease. of the output including outputting it as power information.

[0009] To achieve the above object, a program according to a third aspect of the present invention causes a computer to acquire visitor information including the attributes of visitors to a target location and infection status information including the infection status of an infectious disease in each region, acquire a first risk index indicating the degree of risk of infection with the infectious disease at the target location using the visitor information and the infection status information, acquire a second risk index, which is an index corresponding to the number of visitors by residential area, using the first risk index and the visitor information, When the first risk index satisfies the first criterion and the second risk index satisfies the second criterion, diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion is provided to assist in preventing the spread of the infectious disease. of the output output it as power information and is a program for causing the above to be executed.

Advantages of the Invention

[0010] According to the present invention, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

Brief Description of the Drawings

[0011]

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Embodiments for Carrying Out the Invention

[0012] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are denoted by the same reference numerals, and the description will be omitted as appropriate.

[0013] <<Embodiment 1>> The infection risk estimation device 100 according to Embodiment 1 of the present invention is a device that supports the prevention of the spread of infectious diseases by obtaining a first risk index R1 indicating the degree of the risk of infection with an infectious disease at a plurality of target locations.

[0014] The target location is a place where people may visit from various places, such as tourist spots and facilities. Examples of tourist spots include shrines, temples, and famous places. Examples of facilities include landmarks, theme parks, parks, service areas, movie theaters, art museums, museums, theaters, exhibition halls, stadiums, ballparks, gymnasiums, golf courses, amusement parks, and shopping malls. Note that the target locations are not limited to these, and one or more may be appropriately determined.

[0015] Infectious diseases include, for example, influenza and COVID-19, but are not limited thereto.

[0016] <Functional configuration of the infection risk estimation device 100> As shown in FIG. 1 for the functional configuration, the infection risk estimation device 100 according to the present embodiment includes cameras 101_1 to 101_N (N: an integer of 1 or more), an acquisition unit 102 including a first acquisition unit 102a and a second acquisition unit 102b, an estimation unit 104, a risk index storage unit 105, a facility storage unit 106, and an output unit 107.

[0017] Each of the cameras 101_1 to 101_N is a camera installed in a parking lot or a target location. Each of the cameras 101_1 to 101_N is connected to the infection risk estimation device 100 via a network so as to be able to transmit and receive information to and from each other, and the generated traffic facility information is acquired by the infection risk estimation device 100.

[0018] Hereinafter, when the cameras 101_1 to 101_N are not particularly distinguished, they are simply referred to as "camera 101".

[0019] The camera 101 installed in the parking lot is provided, for example, at the entrance of the parking lot, photographs the license plate of an automobile parked in the parking lot, and generates image information including an image of the photographed license plate. The camera 101 installed in the target location photographs visitors to the target location and generates visitor image information indicating an image of the photographed visitors.

[0020] Each of the cameras 101 installed in the parking lot is associated with the target location based on a predetermined association condition. The association condition includes, for example, being installed in a parking lot within a predetermined distance from the target location, and the parking lot as the target location being attached to the target location.

[0021] Here, when the road near the target location is congested, the parking lots near the target location may be full, and visitors to the target location may use a parking lot farther away than when there is no congestion. Therefore, when the road near the target location has been congested for a predetermined time (for example, one hour) or more, the association conditions, such as associating a parking lot farther away than when there is no congestion, may be changed according to whether the road near the target location is congested or not.

[0022] The first acquisition unit 102a acquires visitor information 110. In addition, the first acquisition unit 102a acquires wearing rate information indicating the wearing rate of those among the visitors who are wearing a mask as a covering for covering the mouth.

[0023] The visitor information 110 is information regarding visitors to the target location and includes attributes of the visitors such as the residential area Ai of the visitors and the age group of the visitors.

[0024] As shown in FIG. 2, the visitor information 110 according to the present embodiment includes date information, target location information, the total number of visitors to the target location, the total number SN, the number of visitors by residential area and the age composition as attributes of the visitors.

[0025] The date information indicates the date. The target location information is information for identifying the target location and includes, for example, a name and an address indicating the location.

[0026] The total number of visitors to the target location indicates the total number of visitors who came to the target location on the day indicated by the date information. The first acquisition unit 102a acquires the total number of visitors counted at the entrance of the target location by the user input. Note that the first acquisition unit 102a may also be acquired by counting the number of people identified using conventional image processing techniques.

[0027] The total number indicates the total number of automobiles parked in the parking lot associated with the target location on the day indicated by the date information.

[0028] The number of visitors by place of residence indicates the number of visitors by place of residence who came to the target location on the day indicated by the date information. The place of residence Ai according to this embodiment is each prefecture, and i is an integer from 1 to 47. Note that the place of residence is not limited to prefectures, and may be an appropriately determined area such as an area corresponding to the place name indicating the base of automobile use (that is, the jurisdiction area of the automobile).

[0029] The age composition indicates the age composition of the visitors who came to the target location on the day indicated by the date information. For example, it is the ratio of the visitors by age group to the total number of visitors. Note that the age composition may be the number of visitors by age group who came to the target location on the day indicated by the date information.

[0030] Specifically, the first acquisition unit 102a acquires traffic facility information and past visitor information at the target location in order to acquire the number of visitors by place of residence and the age composition.

[0031] The traffic facility information is information obtained from a parking lot as a traffic facility, and is information obtained from a parking lot associated according to an association condition with the target location. to be predicted It is information obtained from a parking lot associated according to an association condition with the target location.

[0032] The traffic facility information according to this embodiment includes image information indicating an image captured by a camera 101 installed in a parking lot. The first acquisition unit 102a acquires the number of visitors by place of residence by estimating the number of visitors by place of residence based on the image information included in the traffic facility information.

[0033] The past visitor information at the target location includes the age composition of past visitors as an attribute of past visitors. Therefore, the first acquisition unit 102a acquires the age composition of past visitors included in the past visitor information at the target location as the age composition of visitors at the target location.

[0034] The location attribute information is information indicating the attributes of the target location. Examples of the attributes of the target location include the type of whether it is an indoor facility or an outdoor facility, and the type of whether it is a facility where the density of people exceeds a predetermined level.

[0035] Furthermore, the first acquisition unit 102a acquires visitor image information from the camera 101, and acquires the wearing rate information of the target location by performing image processing on the visitor image information. This image processing uses, for example, a learned learning model that inputs an image of a person and outputs information indicating whether the person is wearing a mask. The first acquisition unit 102a acquires the wearing rate information of the target location by obtaining the ratio of the persons wearing masks among the persons included in the visitor image information.

[0036] The second acquisition unit 102b acquires infection status information including the infection status of infectious diseases in each region Ai.

[0037] The infection status of infectious diseases in each region Ai is, for example, the infection rate of infectious diseases in each prefecture. The infection rate of infectious diseases in each prefecture is obtained, for example, by dividing the number of newly infected persons announced daily in each prefecture by the population of the corresponding prefecture.

[0038] Note that the infection status of infectious diseases in each region is not limited to this, and may be, for example, the infection rate of infectious diseases in each municipality, or the infection rate by region including the whole country or a plurality of prefectures. The infection rate of infectious diseases may be a moving average of the infection rate over a predetermined period (for example, two weeks).

[0039] The estimation unit 104 acquires the first risk index R1 using the visitor information, the wearing rate information, and the infection status information respectively acquired by the first acquisition unit 102a and the second acquisition unit 102b. Then, the estimation unit 104 further acquires a second risk index R2 and a third risk index R3, which are indices corresponding to the number of visitors by residential area, using the first risk index R1 and the visitor information.

[0040] Furthermore, the estimation unit 104 determines whether the first risk indicator R1, the second risk indicator R2, and the third risk indicator R3 satisfy a predetermined criterion.

[0041] More specifically, as described above, the first risk indicator R1 is an indicator indicating the degree of risk of contracting an infectious disease at the target location.

[0042] The first risk indicator R1 according to the present embodiment is obtained, for example, as shown in Equation (1), by obtaining the product of the number of visitors and the infection rate for each residential area Ai, and multiplying the sum of this product for all residential areas Ai by the coefficients p to r.

[0043]

Equation

[0044] The area Ai in Equation (1) is the prefecture as described above. In this case, the first risk indicator R1 is obtained by multiplying the sum of the products of the estimated number of visitors and the infection rate for each prefecture by the coefficients p to r for the 47 prefectures.

[0045] The coefficients p to r are values determined according to the location attribute information and the wearing rate, respectively.

[0046] For the coefficient p, a value appropriately determined according to whether the target location is an outdoor facility provided or an indoor facility is set. Generally, since ventilation is better in outdoor facilities than in indoor facilities, it may be more difficult to contract an infectious disease. In such a case, the coefficient p for outdoor facilities may be set to a smaller value than the coefficient p for indoor facilities. to

[0047] For the coefficient q, a value appropriately determined according to the density of people at the target location is set. Generally, it may be more difficult to contract an infectious disease in a facility with a high density of people than in a facility with a low density of people. In such a case, the coefficient q for high density may be set to a larger value than the coefficient q for low density.

[0048] ​ A value appropriately determined according to the wearing rate information is set for the coefficient r. Generally, the higher the proportion of people wearing masks, the less likely they are to be infected with an infectious disease. In such a case, it is advisable to set a value for the coefficient r such that it decreases as the value of the wearing rate information increases.

[0049] The second risk index R2 is an index according to the number of visitors by residential area for the visitors to the target location. For example, an index indicating the degree of the number of visitors by residential area relative to the total number of visitors is adopted.

[0050] Specifically, for example, the second risk index R2 is the proportion of visitors by residential area, and is obtained by dividing the number of visitors by residential area by the total number of visitors. Note that the second risk index R2 may also be the number of visitors by residential area.

[0051] The third risk index R3 is an index according to the number of visitors by age group for the visitors to the target location. For example, a value indicating the degree of the number of visitors by age group relative to the total number of visitors to the target location is adopted.

[0052] Specifically, for example, the third risk index R3 is the proportion of visitors by age group. Note that the third risk index R3 may also be the number of visitors by age group.

[0053] Note that the third risk index R3 only needs to be an index indicating the degree of the number of visitors by age group. For example, it may be the number of visitors by residential area for the visitors to the target location itself.

[0054] Further, as criteria used by the estimation unit 104 for determination, the following first to third criteria are held in advance.

[0055] The first criterion is a criterion for determining whether the risk of being infected with an infectious disease at the target location is high. The first criterion is determined in advance regarding the first risk index R1, for example, "the first risk index R1 is equal to or greater than a first threshold value (for example, "0.5")."

[0056] The second criterion is a criterion for determining whether the risk of the infectious disease spreading from the target location to the visitor's residential area Ai is high. The second criterion is predefined with respect to the second risk indicator, for example, "the second risk indicator is equal to or greater than the second threshold value (for example, "0.3")."

[0057] The third criterion is a criterion for determining the age group with a high risk of the infectious disease spreading from the target location to the visitor's residential area Ai. The third criterion is predefined with respect to the third risk indicator, for example, "the age group that accounts for 90% of the total number of visitors."

[0058] The risk indicator storage unit 105 is a storage unit that stores the first risk indicator R1, the second risk indicator R2, and the third risk indicator R3 for each target location. The first risk indicator R1, the second risk indicator R2, and the third risk indicator R3 are stored in the risk indicator storage unit 105 by the estimation unit 104.

[0059] The facility storage unit 106 is a storage unit that stores in advance age group - facility information for associating age groups with facilities in each region. In the present embodiment, the age group - facility information is composed of age group - facility type information 111a and regional facility information 111b, as illustrated in FIGS. 3 and 4.

[0060] FIG. 3 is a diagram showing an example of the age group - facility type information 111a according to the present embodiment. In the age group - facility type information 111a, an age group and a facility type indicating the type of the facility are associated. The age group and the facility type in the age group - facility type information 111a may be associated with the facility type indicating the type of facility that a person belonging to the age group generally frequently uses.

[0061] FIG. 4 is a diagram showing an example of the regional facility information 111b. The regional facility information 111b shows the facilities for each facility type in each region. The regional facility information 111b shown in FIG. 4 includes, for example, "○○ Elementary School" as a facility of the facility type "elementary school" in "Tokyo Metropolis."

[0062] Note that although FIG. 4 shows an example in which facilities are identified by their names, the facilities may be identified not only by their names but also by, for example, addresses, codes appropriately assigned, etc. Further, the regional facility information 111b may not be stored in the facility storage unit 106 but may be acquired from another device (not shown) via a network. In this case, the age group - facility information may be composed only of the age group - facility type information 111a.

[0063] Based on the first risk index R1, the output unit 107 outputs output information for supporting the prevention of the spread of infectious diseases. The output unit 107 may output the output information, for example, by displaying it, or may output the output information by transmitting it to an external device (not shown) via a network.

[0064] The output information includes, for example, target location risk information 112a, occurrence location information 112b, diffusion location information 112c, and caution facility information 112d.

[0065] The target location risk information 112a is information in which the first risk index R1 is associated with the target location.

[0066] FIG. 5 shows an example of the target location risk information 112a. The target location risk information 112a shown in the figure includes the first risk index R1 for each day in a predetermined period and its two - week moving average at the target location "Facility A".

[0067] Note that in FIG. 5, the moving average shows an example of a two - week moving average, but the period for calculating the moving average is not limited to two weeks and may be changed as appropriate. The moving average may not be included in the target location risk information 112a. Further, the target location risk information 112a may be information including the first risk index R1 for a specific day at the target location, and may further include a part or all of the visitor information 110.

[0068] The occurrence location information 112b is information regarding a target location with a high risk of contracting an infectious disease. For example, it is output when it is determined that the first risk index R1 of the target location satisfies the first criterion, and the occurrence location information 112b includes information for identifying the target location corresponding to the first risk index R1 that satisfies the first criterion. The information for identifying the target location is, for example, the name of the facility that is the target location, the location of the target location, and the like.

[0069] The diffusion location information 112c is information regarding the residential area of a visitor, and indicates an area Ai where there is a risk of the infectious disease spreading from a target location with a high risk of contracting the infectious disease.

[0070] For example, it is output when the first risk index R1 satisfies the first criterion and the second risk index R2 satisfies the second criterion, and the diffusion location information112c indicates the residential area Ai corresponding to the second risk index R2 that satisfies the second criterion.

[0071] FIG. 6 shows an example of output information including the occurrence location information 112b and the diffusion location information 112c.

[0072] In the output information shown in FIG. 6, the target location information, the first risk index R1, and the attributes of the visitor indicated by the date information are associated.

[0073] The target location information includes the region where the target location is located and its name. The first risk index R1 is the first risk index R1 of the target location identified by the target location information. In the example shown in FIG. 6, the target location "Facility A" corresponding to the first risk index R1 that satisfies the first criterion (for example, being 0.5 or more) is indicated by hatching. In this way, FIG. 6 shows an example in which the occurrence location information 112b is shown by the target location corresponding to the first risk index R1 that satisfies the first criterion being shown in a different manner from other target locations.

[0074] The attributes of the visitor include the age composition and the residential area Ai of the visitors who came to the target location identified by the target location information.

[0075] The residential area Ai of the output information shown in FIG. 6 is a residential area where the first risk index R1 satisfies the first standard and the second risk index R2 satisfies the second standard. In the example shown in FIG. 6, the residential areas "Tokyo" and "Kanagawa Prefecture", where the first risk index R1 satisfies the first standard and the second risk index R2 satisfies the second standard, are indicated by hatching. In this way, in FIG. 6, an example in which the diffusion location information 112c is shown is shown by showing the residential areas where the first risk index R1 satisfies the first standard and the second risk index R2 satisfies the second standard in a different manner from other residential areas.

[0076] The age composition of the output information shown in FIG. 6 indicates the age group in which the first risk index R1 satisfies the first standard, the second risk index R2 satisfies the second standard, and the third risk index R3 satisfies the third standard. for the year age group.

[0077] Note that the diffusion location information 112c may be output when it is determined that the first risk index R1 of the target location satisfies the first standard. In this case, based on the visitor information of the facility corresponding to the first risk index R1 that satisfies the first standard, the diffusion location information 112c indicating the residential area Ai of all visitors may be output.

[0078] The caution facility information 112d is information about facilities associated with the age group of the visitor among the facilities provided in the residential area Ai of the visitor. The caution facility information 112d indicates facilities where there is a risk of the spread of an infectious disease from a target location with a high risk of infection with the infectious disease.

[0079] For example, it is output when the first risk index R1 satisfies the first standard, the second risk index R2 satisfies the second standard, and the third risk index R3 satisfies the third standard. In this case, the caution facility information 112d indicates facilities associated with the age group of visitors who satisfy the third standard among the facilities provided in the residential area corresponding to the second risk index R2 that satisfies the second standard.

[0080] More specifically, for example, among the facilities provided in the residential area corresponding to the second risk index R2 that satisfies the second standard, the facilities associated with the age group of visitors that satisfy the third standard are identified by the following method.

[0081] The output unit 107 identifies the facility types associated with the age group of visitors that satisfy the third standard in the age group - facility type information 111a. Then, the output unit 107 identifies, in the regional facility information 111b, the facilities associated with the identified facility types among the facilities provided in the residential area corresponding to the second risk index R2 that satisfies the second standard. The output unit 107 outputs the caution facility information 112d including the identified facilities.

[0082] FIG. 7 shows an example of the caution facility information 112d. The caution facility information 112d in FIG. 7 shows the names of the facilities in the residential areas "Tokyo" and "Kanagawa" associated with the age group "19 to 35 years old". Note that the facilities included in the caution facility information 112d are not limited to the names, and may include information such as the address that can identify the facilities.

[0083] Note that when the first risk index R1 satisfies the first standard and the second risk index R2 satisfies the second standard, caution facility information indicating all of the facilities associated with the age group of visitors among the facilities provided in the residential area corresponding to the second risk index R2 that satisfies the second standard may be output.

[0084] <Physical Configuration of the Infection Risk Estimation Device 100>

[0085] Physically, the infection risk estimation device 100 is realized by, for example, a general-purpose computer, and as shown in FIG. 8, includes a bus 1010, a processor 1020, a memory 1030, a storage device 1040, a network interface 1050, and a user interface 1060.

[0086] The bus 1010 connects the processor 1020, the memory 1030, the storage device 1040, network the interface 1050, userThe interface 1060 is a data transmission path for transmitting and receiving data to and from each other. However, the method of connecting processors 1020 and the like to each other is not limited to bus connection.

[0087] The processor 1020 is a processor realized by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.

[0088] The memory 1030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0089] The storage device 1040 is an auxiliary storage device realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a memory card, a ROM (Read Only Memory), or the like. The storage device 1040 stores program modules for realizing each functional unit of the contract terminal 101. By the processor 1020 loading these program modules into the memory 1030 and executing them, each functional unit corresponding to the program module is realized.

[0090] The user interface 10 6 0 is a touch panel, a keyboard, a mouse, etc. as an interface for the user to input information, and a liquid crystal panel, etc. as an interface for presenting information to the user.

[0091] The network interface 10 5 0 is an interface for connecting the infection risk estimation device 100 to the network N. The network interface 10 5 0 is connected to one or more cameras 101_1 to 101_N via the network.

[0092] <Operation of the infection risk estimation device 100> Hereinafter, the operation of the infection risk estimation device 100 according to the present embodiment will be described with reference to the drawings.

[0093] FIG. 9 is a flowchart showing an example of the infection risk estimation process according to the present embodiment. The infection risk estimation process is a process for supporting the prevention of the spread of infectious diseases by obtaining a first risk index R1 indicating the degree of the risk of infection with an infectious disease at a plurality of target locations. The infection risk estimation process may be automatically started at a predetermined cycle (for example, one day), or may be started in response to a user's instruction.

[0094] The first acquisition unit 102a acquires the total number of visitors to the target location, transportation facility information, past visitor information, wearing rate information, and location attribute information (step S101).

[0095] The transportation facility information acquired in step S101 includes image information generated by the camera 101 installed in the parking lot and visitor image information generated by the camera 101 installed at the target location. Then, the first acquisition unit 102a acquires the wearing rate information about the visitors to the target location based on the visitor image information.

[0096] The second acquisition unit 102b acquires infection status information including the infection status of infectious diseases in each region Ai (step S102).

[0097] The first acquisition unit 102a estimates the number of visitors by residential area based on the total number of visitors to the target location and the transportation facility information acquired in step S101 (step S103).

[0098] The transportation facility information used in step S103 is the image information generated by the camera 101 installed in the acquired parking lot. An example of a method for estimating the number of visitors by residential area in step S103 will be described below.

[0099] (Example of method for estimating the number of visitors by residential area) The license plate contains the name of the place indicating the place of use and the classification number indicating the use. The first acquisition unit 102a identifies the name of the place and the classification number included in the license plate by performing image processing on the image including the license plate. For this image processing, conventional image processing techniques such as pattern matching and machine learning may be used.

[0100] The first acquisition unit 102a acquires the identified place name as the visitor's residential area Ai. Further, the first acquisition unit 102a determines whether the vehicle in the image is a bus or a passenger car other than a bus according to the identified classification number.

[0101] Then, the first acquisition unit 102a multiplies the number of buses BNi and the number of passenger cars PNi determined to be buses for each residential area Ai by predetermined default values PD1 and PD2, respectively.

[0102] The first acquisition unit 102a obtains a weight Gi for each residential area Ai based on the number of buses BNi and passenger cars PNi for each residential area Ai and the default values PD1 and PD2 for buses and passenger cars. The weight Gi of the residential area Ai is obtained, for example, by the formula "number of buses BNi × default value PD1 for buses + number of passenger cars PNi × default value PD2 for passenger cars".

[0103] An example of a target place called "Facility A" located in Tokyo will be described. Regarding the residential area "Tokyo" of "Facility A", assume that the number of buses BNi is 2 and the number of passenger cars PNi is 1. Regarding the residential area "Kanagawa", assume that the number of passenger cars PNi is 2. Regarding the residential area "Shizuoka", assume that the number of buses BNi is 1.

[0104] Also, for example, assume that the default value PD1 for buses is "10" and the default value PD2 for passenger cars is "2".

[0105] In this case, at the target place "Facility A", the weight of the residential area "Tokyo" is 22, the weight of the residential area "Kanagawa Prefecture" is 4, and the weight of the residential area "Shizuoka Prefecture" is 10.

[0106] The first acquisition unit 102a determines whether there are many visitors using means of transportation other than automobiles based on predetermined conditions, and acquires an estimated value of the number of visitors by region according to the result of the determination.

[0107] The condition here is that the total number of visitors is equal to or greater than the value obtained by multiplying the total number of automobiles SN (= the total number of buses SBN + the total number of passenger cars SPN) by a predetermined value PV.

[0108] In the above example, at the target location "Facility A", since the total number SN is 6, when the predetermined value PV is "100", the condition is that the total number of visitors is more than 600 people.

[0109] When the total number of visitors is less than the value obtained by multiplying the total number of vehicles SN by the predetermined value PV (that is, when the above condition is not satisfied), the first acquisition unit 102a obtains an estimated value of the number of visitors for each residential area Ai by formula (2).

[0110]

Equation

[0111] For example, in the above example, when the total number of visitors to the target location "Facility A" is 100 people, the number of visitors from Tokyo is estimated to be 61 (= 100×22 / (22 + 4 + 10)) people. Similarly, the number of visitors from Kanagawa Prefecture is estimated to be 11 people, and the number of visitors from Shizuoka Prefecture is estimated to be 28 people.

[0112] That is, assuming that all visitors come to the target location by automobile, an estimated value of the number of visitors for each residential area Ai is obtained by allocating the total number of visitors according to the weight Gi.

[0113] When the total number of visitors is equal to or greater than the value obtained by multiplying the total number of automobiles SN by the predetermined value PV, an estimated value of the number of visitors in the region Ai is obtained using different formulas (3) and (4) according to whether the target location belongs to the region Ai.

[0114] More specifically, when the total number of visitors is equal to or greater than the value obtained by multiplying the total number of automobiles SN by a predetermined value PV, the first acquisition unit 102a acquires an estimated value of the number of visitors in a region Ai other than the region At to which the target location belongs according to Expression (3).

[0115]

Number

[0116] For example, in the above example, when the total number of visitors to the target location "Facility A" is 10,600, the number of visitors from Kanagawa Prefecture is estimated to be 67 (= 100 × 6 × 4 / (22 + 4 + 10)) people. Similarly, the number of visitors from Shizuoka Prefecture is estimated to be 167 people.

[0117] That is, the number of visitors by automobile is a number corresponding to the value obtained by multiplying the total number SN by the predetermined value PV, and it is assumed that all visitors from the region Ai (excluding the region At) visited the target location by automobile. Under such an assumption, by allocating the number of visitors by automobile according to the weight Gi, an estimated value of the number of visitors in the region Ai other than the region At is obtained.

[0118] Also, when the total number of visitors is equal to or greater than the value obtained by multiplying the total number of automobiles SN by a predetermined value PV, the first acquisition unit 102a acquires an estimated value of the number of visitors in the region At to which the target location belongs according to Expression (4).

[0119]

Number

[0120] For example, in the above example, when the total number of visitors to the target location "Facility A" is 10,600, the number of visitors from Tokyo is estimated to be 100,366 (= (10,600 - 100 × 6) + 100 × 6 × 22 / (22 + 4 + 10)) people.

[0121] That is, it is assumed that the number of visitors by automobile is a number corresponding to the value obtained by multiplying the total number SN by the predetermined value PV, and the automobilevehicle All visitors other than those coming by [means not specified] are assumed to be visitors from Region At. Under such an assumption, the estimated number of visitors to Region At is obtained by adding the number of visitors other than those coming by [means not specified] and the number obtained by apportioning the number of visitors coming by automobile with the weight Gi. vehicle Note that the method for obtaining the number of visitors by residential area described here is only an example and may be changed as appropriate. For example, the weight Gi for each region may be obtained based on the number of visitors by residential area included in the past visitor information at the target location or the residential area composition of the visitors obtained by questionnaires to the visitors, and the number of visitors by residential area may be obtained by apportioning the total number of visitors with the weight Gi.

[0122]

[0123] Based on the information obtained in steps S101 to S103, the estimation unit 104 obtains the first risk index R1 to the third risk index R3 (step S104). The estimation unit 104 stores the obtained first risk index R1 to the third risk index R3 in the risk index storage unit 105.

[0124] The first risk index R1 is obtained by the above formula (1). The number of visitors to Region Ai is the estimated value obtained in step S103. The infection rate of Region Ai is the infection rate included in the infection status information obtained in step S103.

[0125] provided The coefficient p is a coefficient corresponding to whether the target location included in the location attribute information obtained in step S101 is an outdoor facility or an indoor facility. The coefficient q is a coefficient corresponding to the density of people at the target location included in the location attribute information obtained in step S101. The coefficient p corresponding to whether the target location is an outdoor facility or an indoor facility and the coefficient q corresponding to the density of people at the target location may be, for example, held in the estimation unit 104 in advance.

[0126] ​​The coefficient r is a coefficient corresponding to the wearing rate information obtained in step S101. For example, coefficients r corresponding to each level of the wearing rate divided into, for example, 0 to 50%, 50% to 80%, 80% to 100%, etc. may be held in advance in the estimation unit 104.

[0127] The second risk index R2 is, for example, the ratio of the number of visitors by residential area estimated in step S103, and is obtained by dividing the number of visitors by residential area by the total number of visitors.

[0128] The third risk index R3 is, for example, the ratio of the number of visitors by age group included in the past visitor information obtained in step S101, and is obtained based on the past visitor information.

[0129] The output unit 107 outputs the target location risk information 11a (step S105).

[0130] Specifically, the output unit 107 acquires the first risk index R1 for a predetermined or user-specified period from the risk index storage unit 105, and obtains a two-week moving average of the first risk index R1. As a result, the output unit 107 generates and outputs the target location risk information 11a including the first risk index R1 for each day and the two-week moving average of the first risk index R1, as shown in FIG. 5, for example.

[0131] By referring to the target location risk information 112a, the user can easily grasp the risk of contracting an infectious disease at the target location for a predetermined or user-specified period. Therefore, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

[0132] Again, refer to FIG. 9. The output unit 107 extracts the target locations where the first risk index R1 satisfies the first criterion (step S106).

[0133] The output unit 107 extracts the residential area Ai where the first risk index R1 satisfies the first criterion and the second risk index R2 satisfies the second criterion (step S107).

[0134] The output unit 107 outputs the occurrence location information 112b including the target location extracted in step S106 and the diffusion location information 112c including the residential area Ai extracted in step S107 (step S108).

[0135] FIG. 6 is an example of output information including the occurrence location information 112b and the diffusion location information 112c output from the output unit 107 in step S108. In FIG. 6, the target location extracted in step S106 and the residential area Ai extracted in step S107 are shown by hatching.

[0136] Note that, in this embodiment, an example is shown in which the occurrence location information 112b and the diffusion location information 112c are included in one piece of output information. However, the occurrence location information 112b and the diffusion location information 112c may be output from the output unit 107 as individual output information.

[0137] By referring to the occurrence location information 112b, the user can easily grasp the target location with a high risk of contracting an infectious disease as the occurrence location. Therefore, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

[0138] By referring to the diffusion location information 112c, the user can easily grasp the area Ai where an infectious disease is likely to spread from the occurrence location as the diffusion location. Therefore, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

[0139] Refer to FIG. 9 again. The output unit 107 extracts a facility associated with the age group of visitors that satisfies the third criterion among the facilities provided in the residential area Ai where the first risk index R1 satisfies the first criterion and the second risk index R2 satisfies the second criterion (step S109).

[0140] The output unit 107 outputs the caution facility information 112d indicating the facility extracted in step S109 (step S110).

[0141] Figure 7 is an example of the caution facility information 112d output from the output unit 107 in step S110. By referring to such caution facility information 112d, the user can easily identify facilities where there is a high risk of infectious diseases spreading from the occurrence location as caution facilities. Therefore, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

[0142] Note that in step S110, the output unit 107 may output the caution facility information by transmitting it to a device (not shown) installed in the facility indicated by the caution facility information. As a result, employees of the facility can know that the risk of infectious disease infection is high in the facility and can take appropriate measures. Therefore, it becomes possible to support appropriate measures for preventing the spread of infectious diseases.

[0143] So far, Embodiment 1 according to the present invention has been described.

[0144] According to the present embodiment, the infection risk estimation device 100 uses visitor information 110 including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region to obtain a first risk index R1 indicating the degree of the risk of contracting an infectious disease at the target location.

[0145] By referring to the first risk index R1, the user can easily know the target locations with a high infection risk. Also, by transmitting the first risk index R1 to a predetermined device or the like, information on target locations with a high infection risk can be provided. As a result, measures can be taken to prevent the spread of infection, such as visitors to the target location refraining from going out and those related to the target location raising awareness. Therefore, it becomes possible to support actions for preventing the spread of infection.

[0146] The present invention is not limited to the above-described Embodiment 1 and may be modified as follows.

[0147] (Modification Example 1: Modification Example of Method for Obtaining Number of Visitors by Residential Area) In the embodiment, an example in which the number of visitors by residential area is traffic obtained based on facility information has been described, but the method for obtaining the number of visitors by residential area is not limited to this. For example, the number of visitors by residential area may be obtained based on movement route information, accommodation guest information, etc.

[0148] The movement route information is information including the movement route by the means of movement for the visitor to visit the target location. Examples of the means of movement include railways, automobiles, and bicycles.

[0149] The railway movement route information includes the boarding station and the alighting station of the passengers getting off at the station. The railway movement route information is obtained, for example, by the automatic ticket gate when making an electronic payment at the time of leaving the station using the automatic ticket gate of the station, and is obtained by the first acquisition unit 102a via a server device (not shown) of the railway company, etc.

[0150] In this case, when the alighting station included in the movement route information is within a predetermined distance from the target location, the first acquisition unit 102a acquires the movement route information as the movement route information of the visitor to the target location. The first acquisition unit 102a acquires the area Ai where the boarding station included in the movement route information is provided as the residential area Ai of the visitor.

[0151] The automobile movement route information includes the movement route from the departure place to the destination of the automobile. The automobile movement route information is obtained by a GPS (Global Positioning System) device mounted on the automobile or a control device for controlling autonomous driving, and is obtained by the first acquisition unit 102a from these devices (not shown) via a network.

[0152] In this case, when the end destination included in the movement route information is a parking lot associated with the target location according to the above-described association condition, the first acquisition unit 102a acquires the movement route information as the movement route information of a visitor to the target location. Further, the first acquisition unit 102a acquires the area including the departure place included in the movement route information as the residential area of the visitor to the target location.

[0153] The movement route information of a bicycle includes the movement route from the boarding point to the alighting point. Such movement route information is, for example, in the case of a bicycle provided by a rental cycle, the bicycle parking facility where the bicycle is rented is the boarding point, and the bicycle parking facility where the bicycle is returned is the alighting point. A rental cycle is a service that lends bicycles that can be used between bicycle parking facilities provided at predetermined bases.

[0154] In this case, when the alighting point included in the movement route information is a bicycle parking facility within a predetermined range from the target location, the first acquisition unit 102a acquires the movement route information as the movement route information of a visitor to the target location. Further, the first acquisition unit 102a acquires the area including the boarding point included in the movement route information as the residential area of the visitor to the target location.

[0155] The accommodation guest information is information regarding the guests at the accommodation facility, and includes, for example, the name or address of the accommodation facility, the address and age of the guests, and the like.

[0156] The first acquisition unit 102a acquires the accommodation guest information as the accommodation guest information of a visitor to the target location when, for example, the accommodation facility identified by the name or address of the accommodation facility is within a predetermined distance from the target location. The first acquisition unit 102a acquires the area including the address of the guest included in the accommodation guest information as the residential area Ai of the visitor. Further, the first acquisition unit 102a acquires the age included in the accommodation guest information as the age group of the visitor. Note that the residential area Ai may include nationality.

[0157] The first acquisition unit 102a may acquire at least one of the movement history information of at least one of railways, automobiles, and bicycles and the accommodation user information, in addition to or instead of the transportation facility information according to the embodiment. Then, the first acquisition unit 102a may acquire the number of visitors by residential area based on any one of the boarding station, the departure place, and the boarding base of the acquired movement history information. When the movement history information of an automobile is acquired, the transportation facility information according to the embodiment may not be acquired.

[0158] (Modification Example 2: Modification Example of Acquisition Method of Visitor Age Group) For example, the first acquisition unit 102a may acquire visitor image information from the camera 101 installed at the target location, and perform image processing on the visitor image information to acquire the age group of the visitors to the target location. Also, for example, the first acquisition unit 102a may acquire image information including the passengers of an automobile from the camera 101 installed in the parking lot, and perform image processing on the image information to acquire the age group of the visitors to the target location. The image processing applied in these cases may be a conventional image processing technique. For example, it uses a trained learning model that inputs an image of a person and outputs the age group of that person.

[0159] (Modification Example 3: Modification Example Where Total Number of Visitors Is Unnecessary) In the embodiment, an example was described in which the number of visitors for each residential area Ai is estimated using different formulas (2) or formulas (3) to (4) depending on whether the total number of visitors is less than the value obtained by multiplying the total number of automobiles SN by a predetermined value PV. However, without using the total number of visitors, the weights Gi of all residential areas may be adopted as the number of visitors for each residential area Ai.

[0160] According to this modification example, even when the total number of visitors cannot be acquired, the risk indicators R1 to R3 can be obtained. In particular, it is effective when almost all visitors come to the target location by automobile.

[0161] (Modification Example 4: First Example of Vaccination Status Information and Negative Status Information) The first acquisition unit 102a may further acquire at least one of vaccination status information and negative status information.

[0162] The vaccination status information is information indicating the degree of those who have received the vaccination against the infectious disease. For example, it indicates the number N1 of vaccinated persons against the infectious disease at the target location. The negative status information is information indicating the degree of those who have obtained a negative certificate for the infectious disease. For example, it indicates the number N2 of those who have obtained a negative certificate for the infectious disease at the target location.

[0163] In this case, for example, the number of visitors to area Ai is obtained by Expression (5) substituting for Expression (2) and Expression (6) substituting for Expression (4). That is, in Expressions (5) and (6), "total number of visitors - number N1 - number N2" is adopted instead of "total number of visitors" in Expressions (2) and (4) according to the embodiment. Vaccinated persons and those who have obtained a negative certificate are generally considered to have a low infection risk. of And the number of visitors to area Ai according to this modified example is the number of visitors by region for those who have an infection risk of a certain level or more.

[0164]

Equation

[0165]

Equation

[0166] By obtaining the first risk index R1 using the number of visitors by region for those who have an infection risk of a certain level or more, a more appropriate index indicating the degree of the risk of contracting the infectious disease can be obtained. Therefore, it becomes possible to support actions to prevent the spread of infection.

[0167] (Modified Example 5: First Modified Example of Expression (1) for Obtaining the First Risk Index R1) The vaccination status information may be any information indicating the degree of those who have received vaccinations against infectious diseases, and is not limited to information indicating the number of vaccinated persons. For example, the vaccination status information may be information indicating the proportion of vaccinated persons nationwide, or may be information indicating the proportion of vaccinated persons in the area including the target location.

[0168] The negative status information may be any information indicating the degree of those who have obtained negative certificates for infectious diseases, and is not limited to information indicating the number of those who have obtained negative certificates. The negative status information may be, for example, information indicating the proportion of those who have obtained negative certificates nationwide, or may be information indicating the proportion of those who have obtained negative certificates in the area including the target location.

[0169] And the first risk index R1 may be obtained by multiplying the sum of the values in 47 prefectures by either one or both of the coefficients s and t corresponding to the vaccination status information and the negative status information, instead of or in addition to the coefficients p to r.

[0170] For example, a value appropriately determined according to the vaccination status information is set for the coefficient s. Generally, infection may be suppressed by receiving vaccinations against infectious diseases. In such a case, it is preferable that a value is set for the coefficient s such that it becomes smaller as the value of the vaccination status information becomes larger.

[0171] For example, a value appropriately determined according to the negative status information is set for the coefficient t. Generally, it is considered that the higher the proportion of negative persons, the less likely it is to be infected with infectious diseases. In such a case, it is preferable that a value is set for the coefficient t such that it becomes smaller as the value of the negative status information becomes larger.

[0172] (Variant Example 6: Second Variant Example of Equation (1) for Obtaining the First Risk Index R1) Some (one or more) of the coefficients p to t may be adopted to obtain the first risk index R1, and the coefficients p to t may not be adopted to obtain the first risk index R1.

[0173] However, by using some or all of the coefficients p to t to obtain the first risk index R1, a more appropriate index indicating the degree of risk of contracting an infectious disease can be obtained. Therefore, it becomes possible to support actions to prevent the spread of infection.

[0174] (Modification Example 7: Modification Example of Indexes R1 to R3) In the present embodiment, an example in which substantially continuous numerical values are adopted as the indexes R1 to R3 has been described. However, the indexes R1 to R3 may be indexes (numerical values, alphabets, etc.) that indicate the degree of risk or quantity step by step. The indexes R1 to R3 are not limited to the values obtained daily, and may be obtained at predetermined intervals, or may be average values of a predetermined period, etc.

[0175] <<Embodiment 2>> Functionally, the infection risk estimation device 200 according to Embodiment 2 of the present invention includes an acquisition unit 202 and an estimation unit 204, as shown in FIG. 10.

[0176] The acquisition unit 202 acquires visitor information and infection status information.

[0177] The visitor information is information including the attributes of visitors to the target location, similar to Embodiment 1. Also, the infection status information is information including the infection status of infectious diseases in each region Ai, similar to Embodiment 1.

[0178] The visitor information according to the present embodiment includes, for example, the residential area Ai of the visitor as an attribute of the visitor, and the acquisition unit 202 may acquire the visitor information by an appropriate method.

[0179] Specifically, for example, the acquisition unit 202 may acquire visitor information based on visitor image information from a camera (not shown), similar to Embodiment 1. Also, for example, the acquisition unit 202 may acquire visitor information by user input. Further, for example, the acquisition unit 202 may acquire visitor information from an external device (not shown) via a network N or the like.

[0180] The estimation unit 204 acquires a first risk index R1 by using the visitor information and the infection status information acquired by the acquisition unit 202. Similar to the first embodiment, the first risk index R1 is an index indicating the degree of risk of contracting an infectious disease at the target location.

[0181] The first risk index R1 according to the present embodiment is obtained, for example, as shown in Equation (7), by obtaining the product of the number of visitors and the infection rate for each residential area Ai and summing up this product for all residential areas Ai.

[0182]

Equation

[0183] The infection risk estimation device 200 according to the second embodiment may be physically configured in the same manner as the infection risk estimation device 100 according to the first embodiment (see FIG. 8).

[0184] Hereinafter, the operation of the infection risk estimation device 200 according to the present embodiment will be described with reference to the drawings.

[0185] The acquisition unit 202 acquires visitor information and infection status information (step S201).

[0186] The estimation unit 204 acquires the first risk index R1 based on the information acquired in step S201 (step S202).

[0187] Specifically, for example, the estimation unit 204 acquires the number of visitors in the area Ai based on the visitor information acquired in step S201. Further, the estimation unit 204 acquires the infection status of the infectious disease in the area Ai based on the infection status information acquired in step S201. Then, by applying these acquired values formula to (1), the first risk index R1 of the target location is acquired.

[0188] Also according to this embodiment, the infection risk estimation device 200, similar to the first embodiment, uses visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region to obtain a first risk index R1 indicating the degree of the risk of contracting an infectious disease at the target location.

[0189] Thereby, similar to the first embodiment, by referring to the first risk index R1, the user can easily know the target locations with a high infection risk. Also, by transmitting the first risk index to a predetermined device or the like, information on target locations with a high infection risk can be provided. As a result, measures can be taken to prevent the spread of infection, such as visitors to the target location refraining from going out and related persons at the target location raising awareness. Therefore, it becomes possible to support actions to prevent the spread of infection.

[0190] As described above, the embodiments and modified examples of the present invention have been described with reference to the drawings, but these are examples of the present invention, and various configurations other than the above can also be adopted.

[0191] For example, in the plurality of flowcharts used in the above description, a plurality of steps (processes) are described in order, but the execution order of the steps executed in each of the embodiments is not limited to the described order. In each of the embodiments, the order of the illustrated steps can be changed within a range that does not substantially affect the content. Also, the above-described embodiments and modified examples can be combined within a range where the contents do not conflict.

[0192] Some or all of the above embodiments can also be described as follows in the appended claims, but are not limited thereto.

[0193] 1. An acquisition means for acquiring visitor information including the attributes of visitors to a target location and infection status information including the infection status of infectious diseases in each region, and an estimation means for obtaining a first risk index indicating the degree of the risk of contracting the infectious disease at the target location using the visitor information and the infection status information. An infection risk estimation device. 2. The attributes of the visitor include the residential area of the visitor. The infection risk estimation device according to 1 above. 3. The output means for outputting output information for assisting in preventing the spread of the infectious disease based on the first risk index is further provided. The infection risk estimation device according to 1 or 2 above. 4. The output means outputs the target location risk information associated with the target location by the first risk index as the output information. The infection risk estimation device according to 3 above. 5. When the first risk index satisfies a first criterion, the output means outputs, as the output information, occurrence location information regarding the target location with a high risk of contracting the infectious disease. The infection risk estimation device according to 3 or 4 above. 6. When the first risk index satisfies a first criterion, the output means outputs, as the output information, diffusion location information regarding the residential area of the visitor based on the visitor information. The infection risk estimation device according to any one of 3 to 5 above. 7. The estimation means further obtains a second risk index, which is an index corresponding to the number of visitors by residential area, using the first risk index and the visitor information. The infection risk estimation device according to any one of 3 to 6 above. 8. When the first risk index satisfies the first criterion and the second risk index satisfies a second criterion, the output means outputs, as the output information, diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion. The infection risk estimation device according to 7 above. 9. The attributes of the visitor further include the age group of the visitor, When the first risk index satisfies the first criterion and the second risk index satisfies a second criterion, the output means outputs, as the output information, caution facility information regarding the facility associated with the age group of the visitor among the facilities provided in the residential area corresponding to the second risk index that satisfies the second criterion. The infection risk estimation device according to 7 or 8 above. 10. The estimation means further obtains a third risk index, which is an index corresponding to the number of visitors by age group, using the first risk index and the visitor information. When the first risk index satisfies the first criterion, the second risk index satisfies the second criterion, and the third risk index satisfies the third criterion, the output means outputs, as the output information, caution facility information regarding a facility associated with the age group of the visitors satisfying the third criterion among the facilities provided in the residential area corresponding to the second risk index that satisfies the second criterion. The infection risk estimation device according to 9 above. 11. The infection status information includes the infection rate of the infectious disease in each region as the infection status of the infectious disease in each region. The infection risk estimation device according to any one of 1 to 10 above. 12. The acquisition means further obtains a wearing rate indicating the proportion of visitors wearing a covering for covering the mouth, and the estimation means further uses the wearing rate to obtain the first risk index. The infection risk estimation device according to any one of 1 to 11 above. 13. The acquisition means obtains the wearing rate based on an image captured by a photographing means provided at the target location. The infection risk estimation device according to 12 above. 14. The acquisition means further obtains at least one piece of information among location attribute information indicating the attribute of the target location, vaccination status information indicating the degree of persons vaccinated against the infectious disease, and negative status information indicating the degree of persons who have obtained a negative certificate for the infectious disease, and the risk estimation means further uses the at least one piece of information to obtain the first risk index. The infection risk estimation device according to any one of 1 to 13 above. 15. The acquisition means acquires the residential area included in the visitor information by using at least one of traffic facility information obtained from traffic facilities pre-associated with the target location, movement route information including the movement route by the means of movement for the visitor to visit the target location, past visitor information at the target location, and accommodation guest information at accommodation facilities within a predetermined distance from the target location. The infection risk estimation device according to any one of 1 to 14 above. 16. The traffic facility information includes an image of the license plate of a motor vehicle photographed by photographing means provided at a parking lot as the traffic facility. The infection risk estimation device according to 15 above. 17. A computer acquires visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region, and includes acquiring a first risk index indicating the degree of risk of infection with the infectious disease at the target location by using the visitor information and the infection status information. Infection risk estimation method. 18. A computer is caused to acquire visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region, and acquire a first risk index indicating the degree of risk of infection with the infectious disease at the target location by using the visitor information and the infection status information for a program to execute.

[0194] This application claims priority based on Japanese Patent Application No. 2021-050714 filed on March 24, 2021, and incorporates all of its disclosure herein.

Explanation of Signs

[0195] 100, 200 Infection risk estimation device 101, 101_1 to 101_N Camera 102, 202 Acquisition unit 102a First acquisition unit 102b Second acquisition unit 104 Estimation unit 105 Risk index memory unit 106 Facility memory unit 107 Output unit 110 Visitor information 111a Age group - facility type information 111b Regional facility information 112a Target location risk information 112b Occurrence location information 112c Diffusion location information 112d Caution facility information

Claims

1. An acquisition means for acquiring visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region; An estimation means for obtaining a first risk index indicating the degree of risk of infection with the infectious disease at the target location by using the visitor information and the infection status information; An output means for outputting output information for assisting in preventing the spread of the infectious disease based on the first risk index, and The estimation means further obtains a second risk index which is an index corresponding to the number of visitors by residential area by using the first risk index and the visitor information, When the first risk index satisfies a first criterion and the second risk index satisfies a second criterion, the output means outputs diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion as the output information. An infection risk estimation device.

2. The attributes of the visitor include the residential area of the visitor. The infection risk estimation device according to claim 1.

3. The output means outputs the target location risk information associated with the target location as the output information when the first risk index satisfies the first criterion. The infection risk estimation device according to claim 1 or 2.

4. When the first risk index satisfies the first criterion, the output means outputs occurrence location information regarding the target location with a high risk of infection with the infectious disease as the output information. The infection risk estimation device according to any one of claims 1 to 3.

5. The attributes of the visitor further include the age group of the visitor, and When the first risk index satisfies the first criterion and the second risk index satisfies the second criterion, the output means outputs, as the output information, caution facility information regarding facilities associated with the age group of the visitor among the facilities provided in the residential area corresponding to the second risk index that satisfies the second criterion. The infection risk estimation device according to any one of claims 1 to 4.

6. A computer, acquires visitor information including the attributes of visitors to the target location and infection status information including the infection status of infectious diseases in each region; obtains a first risk index indicating the degree of risk of infection with the infectious disease at the target location by using the visitor information and the infection status information; obtains a second risk index which is an index corresponding to the number of visitors by residential area by using the first risk index and the visitor information; When the first risk index satisfies a first criterion and the second risk index satisfies a second criterion, outputting output information for assisting in preventing the spread of the infectious disease, the output information including diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion Infection risk estimation method.

7. On a computer,[[]] obtaining visitor information including the attributes of visitors to the target location and infection status information including the infection status of the infectious disease in each region; using the visitor information and the infection status information to obtain a first risk index indicating the degree of the risk of infection with the infectious disease at the target location; using the first risk index and the visitor information to obtain a second risk index which is an index corresponding to the number of visitors by residential area; when the first risk index satisfies a first criterion and the second risk index satisfies a second criterion, outputting output information for assisting in preventing the spread of the infectious disease, the output information including diffusion location information regarding the residential area corresponding to the second risk index that satisfies the second criterion A program for causing the above to be executed.

Images