Exposure risk evaluation system

Abstract

The exposure risk evaluation system according to the present invention evaluates the risk of exposure to infectious microorganisms by a subject staying in a subject region, and is provided with a control unit. The control unit acquires exposure risk-related information related to the exposure risk, and evaluates, on the basis of the exposure risk-related information, the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, said evaluation items being distinguished by at least one element selected from the position, time, and action of the subject in the subject region. Based on the evaluation results of the exposure risks of each of the plurality of evaluation items, the priority of the infection measures against the infectious microorganisms in the plurality of evaluation items is determined, and evaluation result-related information including information on the determined priority is output.

Description

Technical Field

[0001] The present invention relates to a technology for improving the efficiency of measures to prevent infection with infectious microorganisms. Background Art

[0002] The following technology is known: from the perspective of appropriately carrying out infection countermeasures for infectious microorganisms such as bacteria and viruses, the risk of exposure to infectious microorganisms and the risk of infection are evaluated. For example, Patent Document 1 discloses a placement device: based on the virus concentration in a given area and the user's presence time, the user's viral exposure is calculated, and when it is determined that the calculated result is above a given threshold, the user can be notified. For example, Non-Patent Document 1 discloses a technology for simulating the exposure of SARS-CoV-2 among the audience of an event to evaluate the infection risk of COVID-19. For example, Non-Patent Document 2 discloses a model that can simulate the infection risk of each infection path using influenza virus as the object.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Laid-Open No. 2015-117950

[0006] Non-patent literature

[0007] Non-patent literature 1: M. Murakami et al., COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games, Microbial Risk Analysis, Available online 21 March 2021, 100162. doi: 10.1016 / j.mran.2021.100162, URL: https: / / doi.org / 10.1016 / j.mran.2021.100162

[0008] Non-patent literature 2: Nicas, M., and Jones, RM (2009). Relative contributions of four exposure pathways to influenza infection risk. RiskAnalysis: An International Journal, 29(9), 1292-130 Summary of the Invention

[0009] An exposure risk assessment system according to one aspect of the present invention assesses the exposure risk of a subject staying in a target area to infectious microorganisms and includes a control unit.

[0010] The control unit performs the following processing: obtaining exposure risk-related information associated with the exposure risk, evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, which are distinguished by at least one factor selected from the position, time, and behavior of the subject person within the target area based on the exposure risk-related information, determining the priority of the infection countermeasures against the infectious microorganisms in the plurality of evaluation items based on the evaluation results of the exposure risk in each of the plurality of evaluation items, and outputting evaluation result-related information including information about the determined priority.

[0011] Furthermore, an exposure risk assessment method for assessing exposure risk according to another aspect of the present invention is an exposure risk assessment method for assessing the exposure risk of a subject staying in a target area to infectious microorganisms.

[0012] The exposure risk assessment method includes: a step of obtaining exposure risk-related information associated with the exposure risk; a step of evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, which are distinguished by at least one factor selected from the position, time and behavior of the subject person in the target area, based on the exposure risk-related information; a step of determining the priority of infection countermeasures against the infectious microorganisms in the plurality of evaluation items based on the evaluation results of the exposure risk of each of the plurality of evaluation items; and a step of outputting evaluation result-related information including information about the determined priority.

[0013] In addition, another embodiment of the present invention relates to a program for evaluating exposure risk, which is used to evaluate the exposure risk of a subject staying in a target area to infectious microorganisms, and causes an information processing device to execute: a step of obtaining exposure risk-related information associated with the exposure risk; a step of evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, which are distinguished by at least one factor selected from the position, time, and behavior of the subject within the target area, based on the exposure risk-related information; a step of determining the priority of infection countermeasures against the infectious microorganisms in the plurality of evaluation items based on the evaluation results of the exposure risk of each of the plurality of evaluation items; and a step of outputting evaluation result-related information including information about the determined priority. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a diagram illustrating the configuration of an exposure risk assessment system according to the first embodiment of the present invention.

[0015] Figure 2 (A) is a diagram showing the hardware configuration of a server included in the above system, and (B) is a diagram showing the hardware configuration of a terminal device included in the above system.

[0016] Figure 3 A schematic map showing a target area (restaurant or restaurant) serving as a target of an operation example of the present embodiment.

[0017] Figure 4 This is a sequence diagram illustrating the flow of processing of the above-mentioned system in the above-mentioned operation example.

[0018] Figure 5 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0019] Figure 6 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0020] Figure 7 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0021] Figure 8 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0022] Figure 9 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0023] Figure 10 This is a diagram showing an example of a display screen of the first terminal device in ST11 of the above-mentioned operation example.

[0024] Figure 11 (A) is a diagram schematically showing an example of a contact scenario assumed in the above-mentioned operation example, and (B) is a diagram schematically showing an example of a contact phenomenon.

[0025] Figure 12 This is a diagram showing an example of a display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0026] Figure 13 This is a flowchart showing the flow of processing of the server according to a modification of the above-described operation example.

[0027] Figure 14 This is a diagram showing an example of another display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0028] Figure 15This is a diagram showing an example of another display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0029] Figure 16 This is a diagram showing an example of another display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0030] Figure 17 This is a diagram showing an example of another display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0031] Figure 18 This is a diagram showing an example of another display screen of the second terminal device in ST42 of the above-mentioned operation example.

[0032] Figure 19 This is a diagram illustrating an example of a simulation model for exposure risk assessment that can be employed in the above-described embodiment, and is a diagram illustrating the transition of states in a long-distance infection pathway of an infectious virus.

[0033] Figure 20 This is a sequence diagram illustrating the flow of processing of the infection countermeasure support system in one operational example of the second embodiment of the present invention.

[0034] Figure 21 This is a diagram showing an example of a display screen of the second terminal device in ST44 of the above-mentioned operation example.

[0035] Figure 22 This is a flowchart showing the flow of processing of the server according to a modification of the above-described operation example.

[0036] Figure 23 This is a diagram showing an example of another display screen of the second terminal device in ST44 of the above-mentioned operation example.

[0037] Figure 24 This is a diagram showing an example of another display screen of the second terminal device in ST44 of the above-mentioned operation example.

[0038] Figure 25 This is a diagram showing an example of a display screen of a second terminal device according to another embodiment of the present invention. DETAILED DESCRIPTION

[0039] Facilities and the like subject to infection control measures face complex and diverse situations where there is a risk of exposure to infectious microorganisms. Therefore, in order to reduce the burden of sanitation management in these facilities and the like, there is a need to make infection control measures against infectious microorganisms more efficient.

[0040] The present invention relates to a technology capable of improving the efficiency of countermeasures against infection by infectious microorganisms.

[0041] The following describes embodiments of the present invention with reference to the accompanying drawings. In this specification, a "system" is defined as comprising one or more information processing devices. For example, a single information processing device can constitute a system, and when multiple information processing devices work together to implement functions such as a web server, these information processing devices can also constitute a system. Furthermore, as described in the following embodiments, a "system" can include an information processing device that functions as a web server, one or more terminal devices, and one or more inspection devices.

[0042] <First embodiment>

[0043] [System Overview]

[0044] The system according to the first embodiment of the present invention is configured as a system via the Internet, for example. In this embodiment, the system functions as an exposure risk assessment system for assessing the risk of exposure to infectious microorganisms.

[0045] exist Figure 1 In the example shown, the system involved in this embodiment includes a server 100 on the Internet N, a first terminal device 200A, a second terminal device 200B, a detection device 300, and a measuring device 400. The first terminal device 200A and the second terminal device 200B can have the same hardware structure and are also referred to as terminal devices 200. In addition, the detection device 300 and the measuring device 400 each function as an inspection device 500 used for inspection for obtaining exposure risk related information described later. In addition, in Figure 1 In the embodiment, the system includes two terminal devices 200 , but the system may include three or more terminal devices 200 . In addition, the system may include three or more inspection devices 500 .

[0046] The server 100 can be, for example, a web server (information processing device) operated by an operator of an infection countermeasure assistance service that assists in infection countermeasures against infectious microorganisms. The infection countermeasure assistance service can be, for example, a service that assists an administrator who performs sanitation management of the target area with infection countermeasures in the target area. In this embodiment, the person who performs sanitation management of the target area on the service provider side is referred to as a "administrator." The server 100 is connected to, for example, a plurality of terminal devices 200 and a plurality of inspection devices 500 via the Internet N. The server 100 can, for example, process information input from the first terminal device 200A and the inspection device 500A (detection device 300 and measurement device 400), and provide the infection countermeasure assistance service to the administrator who uses the second terminal device 200B via an application or a web site.

[0047] Terminal device 200 (200A, 200B, ...) can be, but is not limited to, a smartphone, desktop PC, laptop PC, tablet PC, smartwatch, etc. Terminal device 200 accesses server 100, receives web pages generated by server 100, and displays them on a screen using a browser or the like.

[0048] In this embodiment, the first terminal device 200A can receive input of, for example, inspection results for the target area and the behavioral history of individuals who have stayed in the target area (at least a portion of the exposure risk information described below), and transmit this information to the server 100. The first terminal device 200A can be used by an inspector who conducts inspections in the target area to obtain the exposure risk information described below. The inspector can be, for example, the operator of the infection control support service, a person commissioned by the operator, or the administrator of the target area.

[0049] The second terminal device 200B can display, for example, information related to infection countermeasure support generated by the server 100. The terminal device 200B can be used by an administrator registered in the infection countermeasure support service.

[0050] The detection device 300 is a testing device that detects and tests infectious microorganisms using samples collected from the environment of a target area. The detection device 300 can be connected to the server 100 via the Internet N and transmits the detection results to the server 100.

[0051] The measuring device 400 is, for example, an inspection device that measures indicators related to exposure risk in the environment of a target area. In this embodiment, the measuring device 400 is, for example, a device that measures the CO2 concentration in a space. The measuring device 400 can connect to the server 100 via the Internet N and transmit measurement results to the server 100.

[0052] In this specification, a “target area” is an area that is subject to sanitation treatment by a user (manager) of the infection control support service, and may include facilities, outdoor areas, public transportation facilities, residences, and the like.

[0053] Examples of facilities include commercial facilities, accommodation facilities, educational facilities, childcare facilities, medical facilities, nursing facilities, business facilities, food and beverage facilities, health promotion facilities, activity facilities, and complexes thereof. Examples of commercial facilities include shopping malls, supermarkets, movie theaters, and entertainment facilities. Examples of accommodation facilities include hotels, inns, and guesthouses. Examples of educational facilities include various schools and cultural centers. Examples of childcare facilities include nurseries and temporary care facilities for infants and young children. Examples of medical facilities include hospitals. Examples of business facilities include office buildings and factories. Examples of food and beverage facilities include restaurants, cafes, and fast food restaurants. Examples of health promotion facilities include fitness facilities and hot tub facilities.

[0054] Examples of outdoor areas include parks, gardens, green areas, construction sites, etc. Examples of public transportation include those calculated from railways, buses, taxis, ships, and aircraft.

[0055] In this specification, a "subject" is a person staying in the target area, including real-life subjects and virtual subjects. Specifically, the subject can be a person actually observed in the target area or a person imagined through simulation or the like.

[0056] In this specification, "infectious microorganisms" are microorganisms that are the cause of infectious diseases, including at least one selected from viruses, bacteria, parasites, fungi, and other infectious microorganisms. Among these, from the viewpoint of public health, the infectious microorganisms set as the evaluation object preferably include at least one selected from viruses, bacteria, protozoa, and fungi that have high necessity for infection countermeasures. As a specific example of viruses, influenza virus, RS virus, coronavirus, adenovirus, enterovirus, mumps virus, rubella virus, human metapneumovirus, norovirus, rotavirus, dengue virus, etc. can be enumerated. As a specific example of bacteria, Staphylococcus aureus, hemolytic streptococci, pneumococcus, tuberculosis, pathogenic Escherichia coli, Salmonella, Vibrio parahaemolyticus, Clostridium botulinum, Clostridium perfringens, Shigella, cholera bacillus, Legionella, etc. As a specific example of fungi, Aspergillus, Cryptococcus, etc. can be enumerated. Protozoa refers to single-celled microorganisms among parasites, and examples thereof include malarial protozoa, pathogenic amoeba, Giardia, Cryptosporidium, etc. The system of this embodiment can target one or more of these infectious microorganisms.

[0057] In this specification, "exposure" typically refers to the risk of infectious microorganisms attaching to a subject's skin or hair or invading the body. "Exposure risk" typically refers to the risk of infectious microorganisms attaching to a subject's skin or hair or invading the body. Furthermore, "infection countermeasures" refer to measures to prevent the establishment of infection in a subject's body, including, for example, measures to suppress exposure to infectious microorganisms and measures to reduce the amount of exposure.

[0058] [Hardware Structure of Information Processing Device]

[0059] like Figure 2 As shown in FIG. 1A , the server 100 includes, for example, a CPU (Central Processing Unit) 11 , a ROM (Read Only Memory) 12 , a RAM (Random Access Memory) 13 , an input / output interface 15 , and a bus 14 interconnecting these.

[0060] The CPU 11 accesses the RAM 13 and other devices as needed, performs various computations, and generally controls all blocks of the server 100. The ROM 12 is a nonvolatile memory that permanently stores the operating system (OS), programs, various parameters, and other firmware that the CPU 11 executes. The RAM 13 is used as a work area for the CPU 11, temporarily storing the OS, various applications being executed, and various data being processed.

[0061] The input / output interface 15 is connected to a display unit 16 , an operation receiving unit 17 , a storage unit 18 , a communication unit 19 , and the like.

[0062] The display unit 16 is a display device using, for example, an LCD (Liquid Crystal Display), an OELD (Organic Electro Luminescence Display), a CRT (Cathode Ray Tube), or the like.

[0063] The operation accepting unit 17 is, for example, a pointing device such as a mouse, a keyboard, a touch panel, or other input devices. When the operation accepting unit 17 is a touch panel, the touch panel can be integrated with the display unit 16 .

[0064] The storage unit 18 is a nonvolatile memory such as a HDD (Hard Disk Drive), a flash memory (SSD; Solid State Drive), or other solid state memory. The storage unit 18 stores the aforementioned OS, various applications, and various data.

[0065] In this embodiment, the storage unit 18 may contain, in addition to the programs required for the exposure risk assessment process described below, the target area database described below, and other databases used in the process. Databases such as the target area database are referenced as needed during the system's processing. Furthermore, these databases may be stored not in the storage unit 18 but in a storage device or server externally connected to the server 100.

[0066] The communication unit 19 is, for example, a NIC (Network Interface Card) for Ethernet, a wireless LAN, or other various modules for wireless communication, and is responsible for communication processing with the terminal device 200 .

[0067] like Figure 2 As shown in FIG. 1B , the terminal device 200 , like the server 100 , includes, for example, a CPU 21 , a ROM 22 , a RAM 23 , a bus 24 , an input / output interface 25 , a display unit 26 , an operation accepting unit 27 , a storage unit 28 , and a communication unit 29 .

[0068] Furthermore, the detection device 300 may have, for example, a detection unit for detecting an indicator related to infectious microorganisms in addition to the same configuration as the server 100. The measurement device 400 may have, for example, a measurement unit for measuring CO2 concentration in addition to the same configuration as the server 100.

[0069] [Database structure example]

[0070] The target area database stores, for each target area, the attribute information of the target areas registered with the infection control support service. The attribute information of the target areas is not particularly limited, and for example, in addition to general information such as the name, an ID for identifying the target area, the classification of the target area (facility classification, etc.), the name and / or ID of the operator operating the target area, and the address (region), it also includes information on the sub-areas that define the target area, map information on the target area, and attribute information on individuals staying in the target area. For example, the attribute information preferably includes information on attributes related to exposure risk, risk of severe illness, and / or risk of morbidity. Examples of such attributes include, in addition to age group, position, and type of work, the prevalence rate, pre-existing condition rate, and morbidity rate of diseases related to these risks. Furthermore, sub-area information includes the name of the sub-area and its location information. This location information can be stored in association with the location on a map of the target area.

[0071] In this embodiment, the target area database includes, in addition to the aforementioned attribute information, information on multiple evaluation items (described below) for each target area, as well as acquired exposure risk-related information. Furthermore, the target area database may include, for example, information related to infectious microorganisms targeted for evaluation in the target area (e.g., classification, infection route, infection risk, risk of severe illness), as well as other information used in processing.

[0072] In this embodiment, the multiple evaluation items are distinguished by at least one factor selected from the location, time, and behavior of the subject within the target area, and are used to evaluate exposure risk. In this embodiment, the evaluation items serve as the processing unit for the exposure risk assessment process. The multiple evaluation items are determined based on, for example, the behavior of the subject within the target area, the infection pathways of infectious microorganisms, and hygiene management items within the target area.

[0073] For example, evaluation items can be mapped to multiple scenarios, each categorized by the subject's actions related to their exposure risk. The scenarios associated with these evaluation items are those in which the subject performs a given action. Examples include scenarios where typical subjects are located along their movement paths within the target area (e.g., restrooms, dining, conversations), and scenarios corresponding to activities performed within the target area (e.g., reception, entry, exit, etc.). Furthermore, each evaluation item associated with a scenario can be mapped to location information within the target area (e.g., area information) where the scenario occurs.

[0074] Alternatively, the assessment items can be mapped to zones within the target area, differentiated by exposure risk. For example, zones within the target area can be defined by walls or partitions (e.g., conference rooms, staff lounges, kitchens, etc.), or zones within these zones with different exposure risks (e.g., dining areas, disinfection areas, etc.).

[0075] Alternatively, the evaluation items may correspond to time periods differentiated by exposure risk (eg, morning, noon, evening, morning, afternoon, etc.).

[0076] Furthermore, the evaluation items may be differentiated by multiple factors selected from the location within the target area, time, and the behavior of the subject. Examples of such evaluation items include those differentiated by time period and area, those differentiated by time period and scene, and those differentiated by area and scene.

[0077] In this embodiment, the evaluation items are preferably stored in association with at least one infection route by infectious microorganisms, thereby facilitating the selection of inspection items for obtaining exposure risk-related information, which will be described later.

[0078] Specifically, the infection pathways based on infectious microorganisms correspond to the types of infectious microorganisms, and include, for example, at least one selected from droplet infection, contact infection, airborne infection, oral infection, carrier infection, and other infection pathways. The infection pathway corresponding to each evaluation item is selected from the infection pathways based on infectious microorganisms that are the target, and is set, for example, based on the actions of the subject corresponding to each evaluation item, the environment corresponding to each evaluation item (e.g., environmental surface, space, etc.), etc. The infection pathways corresponding to each evaluation item may be one or more. Taking the case where the evaluation item corresponds to the scene as an example, the scene where the subject uses an item that is frequently touched, for example, can be stored in correspondence with contact infection. In addition, the scene where the subjects are in close contact with each other, for example, can be stored in correspondence with droplet infection, contact infection based on droplets, and airborne infection.

[0079] Exposure risk-related information is information related to exposure risk and is used in exposure risk assessment processing by server 100. In this embodiment, the exposure risk-related information includes at least one selected from information input by first terminal device 200A and transmitted to server 100 and information regarding inspection results transmitted by inspection device 500.

[0080] In this embodiment, the exposure risk-related information preferably includes information associated with the exposure risk in each of the multiple assessment items. For example, the exposure risk-related information preferably includes information associated with the exposure risk based on at least one infection pathway corresponding to each of the multiple assessment items. For example, the exposure risk-related information preferably includes at least one piece of information selected from the behavioral risk information and the environmental risk information, as described later.

[0081] In this embodiment, behavioral risk information is information related to an individual's actions associated with their exposure risk in a situation corresponding to at least one of multiple evaluation items. By including behavioral risk information in exposure risk-related information, a wide range of exposure risks, including contact infection, droplet infection, and airborne infection, can be assessed.

[0082] For example, behavioral risk information preferably includes at least one selected from information regarding actions related to the subject's exposure risk and information regarding conditions that may alter the exposure risk due to the subject's actions. Actions related to exposure risk include, for example, actions that may alter the exposure risk to infectious microorganisms. Examples of such actions include conversations with others, actions that generate droplets such as speaking, sneezing, and coughing, contact with environmental surfaces, and infection control measures such as finger hygiene, cleaning, and wearing a mask. Conditions that may alter the exposure risk due to the subject's actions include, for example, the infection control conditions described below.

[0083] For example, behavioral risk information can include information related to the actions associated with the exposure risk of one or more sample subjects observed in situations corresponding to the assessment item. Sample subjects can be actual subjects observed in the target area or virtual subjects observed in a virtual space corresponding to the target area. Examples of methods for observing real sample subjects include direct observation at the target area and observation of images captured of the target area.

[0084] For example, behavioral risk information preferably includes information regarding contact scenarios involving multiple sample subjects, as subjects, observed in situations corresponding to the evaluation item. In this specification, "contact" between multiple (sample) subjects encompasses not only actions involving direct contact between the skin or clothing of these (sample) subjects, but also actions involving close communication such as conversation. Furthermore, "contact scenarios" are scenarios involving contact actions involving multiple sample subjects, observed in situations corresponding to the evaluation item, and are distinct from the "scenario" used as the evaluation item.

[0085] Specifically, behavioral risk information preferably includes information on at least one of the following: the duration of one or more sample subjects' stay in the contact scene; the droplet-generating behaviors of one or more sample subjects in the contact scene; the positional relationships of the sample subjects in the contact scene; and the infection control measures in the contact scene. Examples of information on the duration of stay include information on the length of time multiple sample subjects spend in close proximity. Information on the positional relationships include information on the distance between sample contacts and the positional relationships of the seats of the sample contacts (facing each other, diagonally, etc.). Examples of droplet-generating behaviors include conversation, vocalization, sneezing, and coughing. Information on droplet-generating behaviors includes information on the presence, timing, frequency, and number of droplet-generating behaviors. Examples of infection control status include finger hygiene, cleaning, wearing masks, and the installation of partition walls. Information on the infection control status includes the presence or absence of infection control status, the number of infection control actions (finger hygiene, cleaning, etc.), the location and / or number of partition walls, and information on the materials of masks.

[0086] In this embodiment, environmental risk information is information associated with the exposure risk caused by the environment corresponding to at least one evaluation item among multiple evaluation items. In this specification, the environment in the target area includes, for example, the environmental surfaces within the target area, the space within the target area, and the water used in the target area. In this specification, the above-mentioned environmental surfaces can include, for example, the surfaces of buildings contained in the target area (floors, walls, etc.), the surfaces of objects placed in the target area, etc. The so-called objects can be either fixed objects or unfixed objects. The material of the objects is also not limited. Examples of objects include furniture, electrical products, objects in water-using areas, building materials, construction tools, clothing, bedding, etc.

[0087] In the present embodiment, the environmental risk information preferably includes information about the test results related to infectious microorganisms in the environment. The test results related to infectious microorganisms can include, for example, the test results of infectious microorganisms or at least one of the test results of indicators associated with infectious microorganisms. As the test results of infectious microorganisms, for example, the test results of proteins or fragments thereof contained in infectious microorganisms, the test results of the genetic genes of infectious microorganisms, etc. can be included. As the detection method of proteins or fragments thereof, for example, methods using antigen-antibody reactions such as ELISA, immunochromatography, and biosensors can be cited. As the detection method of genes, for example, methods using PCR, real-time PCR, LAMP, etc. can be cited. As the test results of indicators associated with infectious microorganisms, they can be appropriately selected according to the type of infectious microorganisms, for example, the test results of components contained in saliva, the test results of ATP, the test results of biosensors, etc. can be cited.

[0088] Environmental risk information, for example, includes information about test results related to infectious microorganisms in the environment, and preferably includes information about test results related to infectious microorganisms on environmental surfaces. As a method for collecting samples for detection from environmental surfaces, for example, a method of bringing an appropriate collection unit (absorbent cotton, non-woven fabric, sponge, cotton swab, swab, etc.) into contact with the environmental surface can be cited. In this case, the collection unit is preferably in a state of being soaked in an appropriate liquid (an aqueous solution containing a surfactant, physiological saline, buffer, a liquid combined therefrom, etc.). In addition, environmental risk information may include information about test results related to infectious microorganisms in the environmental space. As a method for collecting samples for detection from the environmental space, for example, capture using a filter, capture of liquid using bubbling, etc., capture using electrostatic adsorption, suction using a pump, etc. can be cited. In addition, the collection method can also be passive sampling without using a pump, or capture using grading.

[0089] In this embodiment, the environmental risk information preferably includes, for example, the test results for saliva components and / or fecal components such as bile acids in the environment. In particular, it preferably includes the test results for saliva components in the environment (e.g., surfaces) that are highly correlated with contact infection. For example, the saliva components targeted for testing preferably include amylase. Amylase is an enzyme found in human saliva. By including the test results for saliva components such as amylase in the environmental risk information, it is possible to assess the contamination status of the environment caused by saliva droplets. The test results for saliva components can include, for example, information regarding the detected amount of the component and the detection frequency of the component.

[0090] In this embodiment, the environmental risk information preferably includes, for example, information on ATP detection results in the environment, and particularly preferably, information on ATP detection results on environmental surfaces. ATP can be detected using electrochemical methods such as chemiluminescence. By including ATP detection results in the environmental risk information, it is possible to assess not only contamination caused by microorganisms themselves in the environment, but also contamination caused by organic matter associated with microbial proliferation, thereby assessing the risk of proliferation of infectious microorganisms in the environment. For example, ATP on environmental surfaces can be rapidly detected using ATP swab tests, etc.

[0091] In this embodiment, the environmental risk information preferably includes, for example, information related to the ventilation conditions of the space. Examples of information related to the ventilation conditions of the space include information regarding the measurement results of the CO2 concentration in the space, information regarding the measurement results of the ventilation volume in the space, information regarding the capacity and power of the ventilation equipment, information regarding the ventilation frequency of the space, and information regarding the measurement results of the wind speed, volume, and / or direction of the airflow within the space.

[0092] In addition to the examples above, environmental risk information may also include information on water-borne exposure risks via the water within the target area. Examples of information related to such water-borne exposure risks include microbial testing results and water quality testing results for wastewater discharged from the target area and water used within the target area (tap water, pool water, bathtub water, canal water, river water, lake water, etc.).

[0093] In this embodiment, the storage unit 18 may further include a user database. The user database stores attribute information of each user registered in the infection control support service. In this embodiment, a user is a user who can access the infection control support service, including, for example, inspectors who register test results and administrators. User attribute information is not particularly limited and may include, for example, general information such as the user's name (nickname), an ID for identifying the user, the user's category (e.g., administrator, inspector, etc.), the user's affiliation, and the user's contact information, as well as information on the area of ​​responsibility for each user.

[0094] [System operation example]

[0095] Next, an example of the operation of the system configured as described above will be described. The operations of the server 100 described below are performed by the collaborative operation of hardware such as the CPU 11 and the communication unit 19, and software stored in the storage unit 18. Similarly, the operations of the first and second terminal devices 200A and 200B are performed by the collaborative operation of hardware such as the CPU 21 and the communication unit 29, and software stored in the storage unit 28. The same applies to each inspection device 500.

[0096] In this example, the target area is store A, a restaurant, and the targeted infectious microorganisms are enveloped viruses (such as influenza viruses and coronaviruses) that cause infections through contact, droplet infection, and airborne infection. In this example, an inspector using a first terminal device 200A performs a predetermined inspection in the target area and inputs the inspection results or information related to the inspection results into the first terminal device 200A. Furthermore, an inspection device 500 (e.g., a detection device 300 and a measurement device 400) located in the target area obtains the inspection results and transmits them to the server 100. Based on the received information, the server 100 performs an exposure risk assessment. The server 100 then transmits the processed results to the terminal device 200B used by the hygiene manager of the target area (hereinafter referred to as the "manager"), a user of the infection control support service. However, the system operations in this embodiment are not limited to the following example.

[0097] Figure 3An example of a map of a store 50, which is a restaurant and is the target area of ​​this action example, is shown. The store 50 includes, for example, a shared area 510 used by customers and employees, and an employee area 520 used by employees. Furthermore, the shared area 510 includes, for example, an entrance area 511 and a dining area 512. The entrance area 511 includes an entrance and exit 513 and a waiting area 514. The dining area 512 includes a passage area 515, a plurality of tables 516A, 516B, etc., and a toilet 517. The employee area 520 includes a kitchen area 521 and an employee lounge 522. The information of these areas is stored in, for example, a target area database. In addition, the information of such a map is also preferably stored in, for example, a target area database.

[0098] A typical user (customer) of store 50 enters store 50 through entrance 513, disinfects their hands at a disinfectant 518 located near entrance 513, waits in a waiting area 514, and then proceeds to the food area 512. The customer sits at a designated table 516A, selects a menu, and places an order. A staff member then serves the food to table 516A. The customer then eats and converses at table 516A, uses the restroom 517 as needed, and leaves the store.

[0099] In this action example, the target area database stores, for example, evaluation items corresponding to various scenes on the predetermined customer movement routes as described above. In this action example, the evaluation items include, for example, alcohol disinfection, waiting, occupying a seat, menu selection, ordering, serving food, dining, conversation, restroom, leaving the table, and leaving the store. Table 1 shows examples of evaluation items in this action example. Information on each of these evaluation items (scenes) is associated with information on infection routes that may become exposure wind (e.g., contact infection, droplet infection, airborne infection). In addition, the information on each evaluation item is preferably also associated with information on the target area.

[0100] [Table 1]

[0101]

[0102] The inspector performs an inspection to obtain information related to exposure risk. The inspection can be selected for each evaluation item based on information corresponding to the infection route, actual customer behavior, etc. In this action example, an action inspection is performed to observe the behavior of the sample subject in scenes such as dining and conversation that may include contact scenes. In addition, in scenes such as menu selection, dining, conversation, and bathroom where there is a risk of contamination of environmental surfaces, saliva components and ATP are inspected on the environmental surfaces. In addition, the inspector selects an area with a risk of spatial contamination (such as the dining area 512) and sets up a measuring device 400 for measuring the CO2 concentration.

[0103] (Acquisition and processing of exposure risk-related information)

[0104] First, refer to Figure 4 The first terminal device 200A used by the inspector receives input of at least a portion of the exposure risk-related information (ST11) and transmits at least a portion of the exposure risk-related information to the server 100 (ST12). In this operational example, the exposure risk-related information received by the first terminal device 200A includes, for example, information regarding the results of the behavioral inspection included in the behavioral risk information and information regarding the results of the saliva droplet inspection included in the environmental risk information. Furthermore, for ATP and CO2 inspections, the first terminal device 200A also receives and transmits information such as the location information of the inspection device 500 associated with the inspection results.

[0105] First, an example of action checking will be described.

[0106] Inspectors conducting behavioral checks can visit stores in the target area to observe their behavior. For example, they can also conduct behavioral observations based on images stored by cameras installed in the stores. For example, the inspector selects, from among the scenarios associated with droplet infection, contact scenes that include sample subjects (the subjects and their contacts) who are the subject of the inspection. For example, the inspector can conduct behavioral checks at predetermined intervals. In this case, when observing the same group of sample subjects at different time periods, behavioral checks can be conducted separately.

[0107] Next, the inspector displays a screen for inputting the inspection results of the contact scene in order to input the results of the behavior inspection to the first terminal device 200A. First, the inspector using the first terminal device 200A can log in to the infection control support service application. The display unit 26 of the first terminal device 200A displays the target area selection screen 201 ( Figure 5 (A)). The target area selection screen 201 includes information on a plurality of target areas registered in the infection control support service. The inspector selects a target area (e.g., store A) to be inspected by a tap or other operation on the target area selection screen 201, causing the display unit 26 to display the inspection item selection screen 202 ( Figure 5 (B)).

[0108] Figure 5 The inspection item selection screen 202 shown in (B) includes information on a plurality of inspection items. The inspector can select an inspection item (here, an action inspection) to be inspected on the inspection item selection screen 202. Next, the display unit 26 of the first terminal device 200A can display an evaluation item selection screen 203 ( Figure 6(A)). For example, the inspector selects a scene to be inspected ("conversation" in this example) on the evaluation item selection screen 203, and causes the display unit 26 to display a selection screen 204 for a sample subject (hereinafter also referred to as "inspected subject") to be inspected. Figure 6 (B)).

[0109] For example, the examiner selects the measurement button 204a of the examinee who is to be examined in the sample examinee selection screen 204, and causes the display unit 26 to display the stay time measurement screen 205 ( Figure 6 (C)). Figure 6 The example stay time measurement screen 205 shown in (C) includes an input field 205a for the subject's behavior, an input field 205b for contact 1's behavior, an input field 205c for contact 2's behavior, a comment input field 205i, and a complete inspection button 205j. The subject's behavior input field 205a includes, for example, a stay time measurement button 205d and a mask presence registration button 205e. For example, when the action input fields 205b and 205c for contact 1 and contact 2 are selected by tapping, similar stay time measurement buttons and mask presence registration buttons are displayed.

[0110] In this example, the examiner observes the actions of the subject being examined in a contact scenario within a conversation scene. For example, upon starting a contact scenario between the subject being examined and the contact person, the examiner selects the dwell time measurement button 205d by tapping or the like. CPU 21 then begins measuring the dwell time of the subject being examined in the contact scenario. Furthermore, the examiner selects the mask presence registration button 205e to register whether the subject being examined is wearing a mask in the contact scenario. Furthermore, the examiner similarly begins measuring the dwell time between the subject being examined and the contact person, and also registers whether the contact person is wearing a mask. For example, upon ending contact between the subject being examined and the contact person, the examiner selects the dwell time measurement button 205d again to terminate dwell time measurement.

[0111] In this example, the inspector can register information related to the exposure risk of the inspected person and the contacts other than the above-mentioned stay time. For example, the inspector selects the three-point reader 205f arranged near the inspected person's action input field 205a, and displays the inspected person registration screen 206 ( Figure 7 (A)). Figure 7The test subject registration screen 206 illustrated in (A) includes, for example, a field 206a for the test subject's age group, a field 206b for the mask type, a field 206c for the volume of sound, a field 206d for the breathing volume, a field 206e for finger hygiene, a field 206f for cleaning activities, and an OK button 206g. The test subject registers their information in these fields and selects the OK button 206g. This inputs the test subject's detailed information into the first terminal device 200A.

[0112] Similarly, the examiner selects the three-point reader 205g (205h) arranged near the contact's action input field 205b (205c), and displays the contact registration screen 207 ( Figure 7 (B)). Figure 7 The contact registration screen 207 illustrated in (B) includes, for example, a field 207a for the subject's age group, a field 207b for the type of mask, a field 207c for the distance from the subject, a field 207d for the presence of a partition wall, and an OK button 207e. The examiner registers the contact information in these fields and selects OK button 207e. This inputs detailed contact information related to the exposure risk into the first terminal device 200A.

[0113] When the inspection in the contact scene is completed, the inspector selects the inspection completion button 205j on the stay time measurement screen 205, causing the display unit 26 to display the inspection result display screen 208. The inspection result display screen 208 includes, for example, a display field 208a for inspection information (such as the inspection date and time, the inspector's name), an inspection subject information display field 208b, a contact information display field 208c, a comment display field 208d, and an OK button 208e. The inspector confirms the displayed items on the inspection result display screen 208 and selects the OK button 208e.

[0114] Thus, the CPU 21 of the first terminal device 200A receives inputs such as basic information of the action inspection (information about the target area, evaluation items (scenes), inspection date and time, inspector, etc.), action risk information about the inspected person (information about the stay time, age group, whether a mask is worn, sound volume, breathing volume, finger hygiene, cleaning contact scenes, etc.), and action risk information about the contact (information about the stay time, age group, whether a mask is worn, distance from the inspected person, presence of partition walls, etc.), and sends these information to the server 100 in correspondence.

[0115] Next, an example of saliva droplet inspection will be described.

[0116] In this action example, the saliva droplet test is set as a test for detecting amylase. First, the inspector can select the inspection object part with contact infection risk in the evaluation item (e.g., scene) of the inspection object that becomes the target area. Then, the inspector can collect the inspection sample at the inspection object part. The collection of the inspection sample is performed, for example, by wiping the surface of the inspection object part with a given collection tool. The inspector can use the collected sample to extract and detect amylase. The extraction and detection of amylase can be performed, for example, using a commercially available kit. The detection of amylase is performed, for example, by a method that utilizes an antigen-antibody reaction and / or an enzyme reaction. The inspector can visually confirm the amylase detection result displayed on the kit, etc. In addition, the inspector can, for example, use the first terminal device 200A to take a picture of the amylase detection result.

[0117] Next, similar to the example of the action inspection, the inspector uses the first terminal device 200A to log in to the infection support countermeasure application, selects store A on the target area selection screen 201, and selects the saliva droplet inspection ( Figure 5 (A) and (B)). Next, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen for the saliva droplet test. The evaluation item selection screen can be Figure 6 The evaluation item selection screen of (A) is similarly configured. The inspector selects a scene to be inspected on the evaluation item selection screen, and displays the inspection object setting screen 209 ( Figure 8 (A)).

[0118] Figure 8 The inspection object setting screen 209 illustrated in (A) includes, for example, an inspection object location information selection column 209a, an inspection information display column 209b for each inspection object, and a map location registration button 209d. The inspection information display column 209b includes, for example, the name of the inspection object and measurement buttons 209c for each inspection object portion of the inspection object. The inspection object and its portion information may be pre-registered in the target area database of the server 100, or the inspector may register the inspection object on the inspection object registration screen 210 ( Figure 8 (B)). In addition, when the map information of the target area is registered in the target area database in advance, the inspector can select the map position registration button 209d on the inspection object setting screen 209 to register the position information of the inspection object on the map. The inspector selects the measurement button 209c of the inspection object portion for which the inspection result is obtained, and the display unit 26 displays the inspection result registration screen 211 ( Figure 8 (C)).

[0119] Figure 8The examination result registration screen 211 illustrated in (C) includes, for example, an examination information display field 211a, an examination result image display field 211b, an examination result registration field 211c, a comment input field 211d, and an OK button 211e. The examination information display field 211a includes information such as the measurement date and time, the examiner's name, the examination area, the name and / or image of the examination object, and the name and / or image of the examination site. The examination result image display field 211b includes image information uploaded by the examiner, including kits and reagents, representing the examination results. The examination result registration field 211c is a field for registering information on the examination results visually determined by the examiner (e.g., positive / negative, colorimetric test results, etc.). The examiner uploads an image of the examination result and registers the visually determined examination result in the examination result registration field 211c. After registering all examination results, the examiner selects the OK button 211e.

[0120] Thus, the first terminal device 200A can receive input of basic information of the examination (measurement date and time, name of the examiner, examination area, name and / or image of the examination object, name and / or image of the examination object part, etc.) and examination result information (image information of the examination result, registration information of the examination result), and send these information to the server 100 in a corresponding manner as information about the detection result of amylase as a component contained in saliva.

[0121] Meanwhile, regarding the results of the ATP and CO2 tests included in the environmental risk information, the inspection device 500 (e.g., the detection device 300 and the measurement device 400) obtains the test results (ST21) and can transmit the test results as part of the exposure risk-related information (ST22). Furthermore, as described below, the inspection device 500, server 100, and first terminal device 200A can collaborate to obtain information related to these tests.

[0122] An example illustrating ATP checking.

[0123] This example operation uses, for example, an ATP swabbing method using a detection device 300 that detects ATP using chemiluminescence and can read the test results. In this example operation, the examiner can select, for example, a target area of ​​the examination subject with a risk of contact infection from the evaluation items to be evaluated and collect a test sample from the target area. The test sample is collected by swabbing the surface of the target area with a predetermined collection tool. The examiner sets the collection tool on the detection device 300 and operates the detection device 300 to start the detection process. This allows the detection device 300 to obtain the test results.

[0124] Next, similar to the example of the action inspection, the inspector logs into the infection countermeasure application using the first terminal device 200A, selects store A on the target area selection screen 201, and selects the ATP inspection to be inspected on the inspection item selection screen 202. Figure 5 (A) and (B)). Thus, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen that is a target of ATP inspection. The evaluation item selection screen can be Figure 6 The evaluation item selection screen of (A) is similarly configured. For example, the inspector selects a scene to be inspected in the evaluation item selection screen, and displays the inspection target setting screen 212 ( Figure 9 (A)).

[0125] Figure 9 The inspection object setting screen 212 illustrated in (A) includes, for example, a section information selection bar 212a where the inspection object is located, an inspection information display bar 212b for each inspection object, a map position registration button 212c, a detection device connection button 212e, and the like. The inspection information display bar 212b includes, for example, measurement buttons 212d for each inspection object part in the inspection object. The information of the inspection object and its parts can be pre-registered in the object area database of the server 100, or the inspector can register it in the inspection object registration screen. In addition, when the map information of the object area is pre-registered in the object area database, the inspector can also select the map position registration button 212c to register the position information of the inspection object on the map. For example, the inspector selects the detection device connection button 212e to cause the display unit 26 to display the detection device connection screen 213 ( Figure 9 (B)).

[0126] The inspector can Figure 9 The detection device 300 that has obtained the detection result is selected from the detection devices 300 included in the detection device connection screen 213 shown in (B). As a result, the selected detection device 300 can transmit information about the detection result of the ATP associated with the identification information of the detection device 300 to the server 100 via the Internet N. For example, the first terminal device 200A can receive information about the detection result of the ATP from the server 100 and display the inspection result registration screen 214 ( Figure 9 (C)).

[0127] Figure 9The examination result registration screen 214 illustrated in (C) includes, for example, an examination information display field 214a, an examination object selection field 214b, an examination object site registration field 214c, an examination result information display field 214d, a comment input field 214e, and an OK button 214f. The examination information display field 214a includes, for example, information such as the measurement date and time, the examiner's name, and the area of ​​the examination object. The examination result information display field 214d includes, for example, information on the test results obtained from the connected testing device 300 (e.g., quantitative information (positive / negative, etc.) and / or qualitative information (test values, etc.)). The examiner can register information on the examination object and its site corresponding to the test result using the examination object selection field 214b and the examination object site registration field 214c. After registering all examination results, the examiner selects, for example, the OK button 214f.

[0128] Thus, the first terminal device 200A can accept the input of basic information of the inspection (inspection date and time, name of the inspector, inspection area, name and / or image of the inspection object, name and / or image of the inspection object part, etc.), and send this information to the server 100 in correspondence with the inspection result information as information related to the ATP detection result.

[0129] Next, the CO2 inspection will be described.

[0130] For example, the inspector can install a measuring device 400 for measuring the CO2 concentration in the air in a zone (e.g., a food zone) corresponding to an evaluation item (e.g., a conversation scene) in the target area. The inspector can use the first terminal device 200A to input operations for starting measurement with the measuring device 400 and for associating identification information of the measuring device 400 with information such as the installation location.

[0131] Next, similar to the example of the action inspection, the inspector logs into the infection support countermeasure application using the first terminal device 200A, selects store A on the target area selection screen 201, and selects the CO2 inspection to be inspected on the inspection item selection screen 202 ( Figure 5 (A) and (B)). Next, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen to be measured for CO2. The evaluation item selection screen can be Figure 6 The evaluation item selection screen of (A) is similarly configured. For example, the inspector selects a scene to be inspected in the evaluation item selection screen, and displays the measurement device setting screen 215 ( Figure 10 (A)).

[0132] Figure 10The measurement device setting screen 215 illustrated in (A) includes, for example, a selection field 215a for the parcel information where the measurement device 400 is located, a field 215b displaying identification information of the measurement device 400, a measurement button 215c for each measurement device 400, and an add button 215d for each measurement device 400. To register a new measurement device 400, the examiner can select the add button 215d to display the measurement device registration screen 216 on the display unit 26, and then enter the identification information (such as the serial number) of the measurement device 400 in the identification information input field 216a.

[0133] Thus, the first terminal device 200A receives input of information such as the position information and identification information of the measurement device 400 , and transmits these information to the server 100 in association with each other.

[0134] The examiner selects, for example, the measurement button 215c corresponding to the measurement device 400 to start measurement on the measurement device setting screen 215. The selected measurement device 400 then acquires the CO2 concentration measurement result and transmits information about the measurement result associated with the identification information of the measurement device 400 to the server 100 via the Internet N.

[0135] like Figure 4 As shown, the CPU 11 of the server 100 receives (acquires) exposure risk-related information transmitted from the first terminal device 200A and the inspection device 500 (detection device 300 and measurement device 400 ) ( ST31 ), and stores the information in the target area database of the storage unit 18 .

[0136] (Evaluation and treatment of exposure risks)

[0137] like Figure 4 As shown, CPU 11 evaluates the exposure risk in each of the multiple evaluation items based on the exposure risk association information (ST32). In this action example, CPU 11 can perform the evaluation for each scenario serving as an evaluation item using the exposure risk association information corresponding to the evaluation item. In the evaluation of each evaluation item, CPU 11 can, for example, separately evaluate the exposure risk based on each inspection result and derive the evaluation result of each evaluation item based on these evaluation results. Alternatively, CPU 11 can apply all the inspection results corresponding to the evaluation item to a machine learning model, etc., to derive the evaluation result of the evaluation item. In this action example, the evaluation result of the exposure risk can be derived as an exposure risk index that serves as an indicator of the exposure risk. The exposure risk index can be expressed as a numerical value (score) or as a rating other than a numerical value.

[0138] For example, the CPU 11 may evaluate exposure risk using a machine learning model for deriving evaluation results from exposure risk-related information. Alternatively, the CPU 11 may evaluate exposure risk using a table stored in the storage unit 18 that associates inspection results with corresponding evaluation results. Furthermore, as described later, the CPU 11 may evaluate exposure risk using a simulation model that simulates exposure risk based on information contained in the exposure risk-related information. To increase the speed of information processing involved in deriving evaluation results, it is more preferable to use a table, a simulation model, or a combination thereof.

[0139] In this example operation, the CPU 11 can evaluate the exposure risk of each evaluation item based on at least one exposure risk-related information selected from the action risk information and environmental risk information corresponding to each evaluation item. For example, the CPU 11 can calculate an exposure risk index for each evaluation item based on each inspection result obtained as exposure risk-related information. Alternatively, the CPU 11 can calculate at least one selected from the total value, average value, maximum value, median value, etc. of the exposure risk index calculated based on each inspection result. In addition, the CPU 11 can also calculate the exposure risk index for each infection path for each evaluation item based on the inspection results corresponding to each infection path. In addition, when adding exposure risk indicators derived from different inspection results, the CPU 11 can calculate a value obtained by multiplying the exposure risk index derived from each inspection result by a coefficient corresponding to the importance of the exposure risk (e.g., contribution, etc.) and add the calculated value.

[0140] An example of evaluation processing using action risk information will be described.

[0141] In this example action, CPU 11 can assess exposure risk based on action risk information obtained through action inspection. Specifically, in this example action, CPU 11 can assess the exposure risk of one or more sample contacts (the subject of inspection and / or the contact) based on information related to the contact scenario corresponding to each evaluation item. In this example action, action risk information related to the contact scenario includes, for example, basic information about the action inspection (information regarding the target area, evaluation items (scenario), inspection date and time, inspector, etc.), action risk information about the subject of inspection (information regarding age group, whether or not a mask was worn, sound volume, breathing volume, finger hygiene, cleaning, and duration of stay in the contact scenario), and action risk information about the contact (information regarding age group, whether or not a mask was worn, distance from the subject of inspection, presence of a partition wall, etc.).

[0142] Specifically, the CPU 11, for example, assumes that at least one of the sample subjects is a subject who harbors infectious microorganisms. Based on the behavioral risk information and the infection pathways of the infectious microorganisms, the CPU 11 simulates the exposure risk of sample subjects other than the subject, i.e., non-subjects, thereby assessing the exposure risk in the contact scenario. In this exemplary operation, the CPU 11 simulates the amount of virus transferred from the subject and / or the environment to the contact by assuming the subject is a subject and the contact is a non-subject, thereby assessing the contact's exposure risk to the virus.

[0143] Furthermore, if a contact scenario includes three or more sample subjects, CPU 11 can divide the contact scenario into multiple contact events, each including one subject subject and one non-subject subject, and calculate an exposure risk index for each contact event, i.e., an indicator of the non-subject subject's exposure risk. CPU 11 can then evaluate the exposure risk in the contact scenario based on the calculated exposure risk indexes for the multiple contact events. Specifically, CPU 11 can evaluate the exposure risk in the contact scenario by calculating at least one selected from the sum, average, maximum, and median values ​​of the exposure risk indexes for the multiple contact events, for example.

[0144] In this specification, a contact event refers to a situation in which all sample subjects constituting a contact scenario have a one-on-one contact with another sample contact. In this specification, an exposure risk indicator refers to an indicator of exposure risk, and can be, for example, at least one indicator selected from the group consisting of the estimated exposure dose to infectious microorganisms, the estimated exposure rate, and the estimated positive test rate.

[0145] use Figure 11 To illustrate the contact phenomenon. Figure 11 Figure (A) shows an example of the arrangement of three sample subjects observed at table 516A in store A. Sample subjects H1, H2, and H3 are seated at table 516A in the store, and a conversation scenario is in progress. In this example, the conversation scenario of sample subjects H1, H2, and H3 around table 516A during a certain time period is defined as one contact scenario. Furthermore, when CPU 11 obtains inspection results for multiple contact scenarios from the same group of sample subjects, it can assess exposure risk based on the inspection results (behavior risk information) for the contact scenarios in each time period. This allows for highly accurate assessment of exposure risk in contact scenarios that extend over a long period of time.

[0146] like Figure 11As shown in the example of (B), the contact scenario is divided into a contact event V1 including sample subjects H1 and H2, a contact event V2 including sample subjects H1 and H3, and a contact event V3 including sample subjects H2 and H3. For each of contact events V1, V2, and V3, CPU 11 sets one sample subject as a target person and the other sample subject as a non-target person, and calculates the exposure risk index for the non-target person using a simulation model. CPU 11 then calculates at least one selected from the sum, average, maximum, and median values ​​of the exposure risk indexes calculated for each of contact events V1, V2, and V3, thereby calculating the exposure risk index for the contact scenario including sample subjects H1, H2, and H3 within a certain time period.

[0147] Furthermore, when CPU11 obtains action risk information corresponding to multiple contact scenarios in an evaluation project, it can evaluate the exposure risk based on the overall action risk information of the evaluation project by calculating at least one selected from the total value, average value, maximum value, central value, etc. of the exposure risk indicators in the multiple contact scenarios.

[0148] In this embodiment, the simulation model can be selected appropriately based on the infection pathway of the infectious microorganism, etc. For example, the simulation model can be either a probabilistic model or a deterministic model, or a combination thereof. A specific example of the simulation model used in this example action is described below.

[0149] Next, an example of evaluation processing using environmental risk information will be described.

[0150] In this operation example, the CPU 11 can evaluate the exposure risk due to the environment of each evaluation item based on the acquired environmental risk information, for example.

[0151] For example, the CPU 11 can evaluate the exposure risk based on information about the detection results of infectious microorganisms in the environment. Thus, the exposure risk of infectious microorganisms in the environment can be evaluated. The evaluation result of the exposure risk can also use the detection result itself and can be expressed as an exposure risk index that is an indicator of the exposure risk. For example, the CPU 11 can use a machine learning model for calculating the exposure risk index based on the detection result to calculate the exposure risk index. Alternatively, the CPU 11 can also use a table stored in the storage unit 18 that establishes a correspondence between the detection result and the corresponding exposure risk index to calculate the exposure risk index. In addition, the CPU 11 can also use a simulation model that calculates the exposure risk index based on the above-mentioned detection results to calculate the exposure risk index.

[0152] In this example, environmental risk information may include multiple test results for a single inspection target location. For example, in the example above, the inspection target location, "the surface of a table," may include test results for two types of enzymes: amylase and ATP. In this case, CPU 11 can calculate the exposure risk index for the single inspection target location by, for example, calculating an exposure risk index based on each test result and selecting at least one of their sum, average, maximum, and median values. Furthermore, if the importance of the multiple test results to the exposure risk (e.g., reliability, contribution, etc.) differs, CPU 11 can calculate the exposure risk index for the single inspection target location by, for example, multiplying the exposure risk index calculated from each test result by a predetermined coefficient corresponding to the importance, etc., and then calculating at least one of their sum, average, maximum, and median values ​​to calculate the exposure risk index for the single inspection target location.

[0153] In this example operation, the environmental risk information may include, for example, information regarding detection results at multiple inspection locations for each evaluation item. For example, in the above example, for the evaluation item "conversation," detection results for two inspection locations, the "surface" and the "edge," of the "table," are obtained. In this case, the CPU 11 may calculate an exposure risk index based on the individual inspection results for the multiple inspection locations corresponding to the evaluation item, calculating at least one selected from the sum, average, maximum, or median of these values ​​to thereby calculate the exposure risk index for the inspection location corresponding to the evaluation item. Furthermore, if the multiple inspection locations have different exposure risks, etc., the CPU 11 may calculate, for example, a value obtained by multiplying the index values ​​calculated based on the inspection results for each inspection location by a predetermined coefficient corresponding to the exposure risk, etc., and then calculate at least one selected from the sum, average, maximum, or median of these values ​​to thereby calculate the exposure risk index for the multiple inspection locations.

[0154] In this example operation, the CPU 11 can evaluate the exposure risk based on, for example, information related to the ventilation conditions of the space associated with each evaluation item. For example, the CPU 11 can evaluate the exposure risk based on space-related indicators (e.g., CO2 concentration, ventilation volume, air volume, wind speed, etc.) that represent the ventilation conditions of the space.

[0155] For example, the CPU 11 may evaluate exposure risk using a machine learning model that derives exposure risk indicators from spatial correlation indicators included in the environmental risk information. Alternatively, the CPU 11 may evaluate exposure risk using a table stored in the storage unit 18 that associates spatial correlation indicators with their corresponding exposure risk indicators. Furthermore, the CPU 11 may evaluate exposure risk using a simulation model that derives exposure risk indicators from spatial correlation indicators.

[0156] In this embodiment, when environmental risk information includes a spatial correlation index and corresponding location information, CPU 11 can use this spatial correlation index to evaluate the exposure risk in the assessment item corresponding to the location information. In this example, for example, if a CO2 concentration measurement device 400 is located in a food and beverage area, CPU 11 can use the measurement results of measurement device 400 to evaluate the exposure risk of each scene in the food and beverage area. Furthermore, CPU 11 can also evaluate the exposure risk caused by ventilation conditions in the assessment item based on the correspondence between the location of measurement device 400 and the area corresponding to the assessment item.

[0157] (Priority determination process)

[0158] Then, if Figure 4 As shown, the CPU 11 determines the priority of infection countermeasures against infectious microorganisms among the multiple evaluation items based on the exposure risk assessment results of each of the multiple evaluation items (ST33). The priority can be expressed as a rating or as a priority order of the evaluation items. For example, the CPU 11 can determine the priority of the evaluation items based on the exposure risk scores. In this case, the CPU 11 can determine the priority order from high to low scores, or it can determine a range of scores and corresponding ratings.

[0159] Table 2 shows an example of the exposure risk evaluation results and their priority levels for each scenario. In this example, the exposure risk evaluation is expressed as a score for each scenario (a numerical value in parentheses), and the priority level is expressed using a five-level priority rating system: A, B, C, D, and E. Furthermore, as shown in Table 3, each priority rating corresponds to a range of exposure risk scores.

[0160] [Table 2]

[0161]

[0162] [Table 3]

[0163]

[0164] As another example, the CPU 11 may determine priority based on the exposure risk evaluation results derived from highly important exposure risk-related information. Highly important exposure risk-related information may, for example, be exposure risk-related information corresponding to a given infection path or exposure risk-related information corresponding to the results of a given examination. Specifically, the importance of exposure risk-related information can be set based on, for example, the reliability of the data, its relevance to exposure risk and / or infection risk, the ease of infection countermeasures, and the like. The highly important exposure risk-related information used in the priority process can be set for each evaluation item or be the same for all evaluation items. Furthermore, highly important exposure risk-related information may be stored in the target area database through user settings such as administrators. Alternatively, the CPU 11 may determine highly important exposure risk-related information based on, for example, infection paths associated with the evaluation items. This allows for the determination of priority for infection countermeasures with higher usefulness. Furthermore, if, for example, an administrator sets and registers the importance, a priority can be determined that corresponds to the administrator's needs.

[0165] (Output processing of evaluation result-related information)

[0166] Next, CPU 11 outputs evaluation result-related information including information regarding the determined priority (ST34). In this example, CPU 11 can transmit this evaluation result-related information to second terminal device 200B. This evaluation result-related information can be transmitted using, for example, an application providing the aforementioned infection management support service, a notification function on a website, or through email or various communication applications. CPU 11 can also output the output information to an external device such as a printer. This allows the evaluation result-related information to be provided to administrators of the target area via paper media such as direct mail.

[0167] Furthermore, the evaluation result-related information may include information regarding the evaluation results of the exposure risk for each of the multiple evaluation items. Examples of this information include the exposure risk score and / or rating for each evaluation item, and the exposure risk score and rating derived from the individual inspection results associated with each evaluation item.

[0168] In addition, the assessment result-related information may also include analytical information analyzing the exposure risks in the target area and / or assessment items. For example, the analytical information may include information such as charts generated using the obtained inspection results and the derived exposure risk indicator data. Charts are not particularly limited, and examples include bar charts, line charts, bubble charts, Pareto charts, pie charts, and radar charts. Furthermore, the analytical information may also include annotations and explanations of the assessment results.

[0169] The second terminal device 200B receives the evaluation result-related information (ST41) and displays the received evaluation result-related information on the display unit 26 (ST42). In this operational example, the display unit 26 of the second terminal device 200B functions as a "display unit for displaying the evaluation result-related information output from the control unit."

[0170] like Figure 12 As illustrated, the display unit 26 can display a screen showing the evaluation results of the exposure risk for each evaluation item (e.g., scenario) and the priority of infection countermeasures for each scenario. Furthermore, this screen can include annotations related to the evaluation results. Furthermore, the display unit 26 can also display the priority levels using color grading. This allows the user of the second terminal device 200B to intuitively understand the priority levels.

[0171] [Effects of this embodiment]

[0172] The exposure risk assessment system of this embodiment outputs information regarding the priority of infection countermeasures among multiple evaluation items, making it possible to clearly indicate to managers managing the hygiene of the target area which evaluation items (such as location, scene, and time period) should be prioritized for infection countermeasures. Since infection countermeasures for the target area are complex and diverse, the aforementioned structure reduces the effort required of managers managing the hygiene of the target area to prioritize infection countermeasures. Furthermore, this reduces the processing burden, such as data analysis, on the second terminal device 200B used by the manager. Therefore, the system of this embodiment can streamline infection countermeasures within the target area.

[0173] Furthermore, by including, for example, information related to contact scenarios involving multiple observed sample contacts in the exposure risk-related information, the action risk information can be used to assess exposure risk using highly reliable information regarding actions with high exposure risk. This allows for a highly accurate assessment of exposure risk based on action risk information. Furthermore, by assuming that at least one of the sample subjects is a subject who possesses infectious microorganisms and simulating the exposure risk of sample subjects other than the subject, i.e., non-subjects, based on the action risk information and the infection pathways of infectious microorganisms, it is possible to more accurately assess exposure risk based on action risk information.

[0174] Furthermore, when a contact scenario involves three or more sample subjects, the CPU 11 (control unit) divides the contact scenario into multiple contact events, each including one subject and one non-subject. For each contact event, the CPU 11 calculates an exposure risk index for the subject, and then aggregates the exposure risk indexes for the multiple contact events. This allows for a highly accurate assessment of the exposure risk for the entire contact scenario. Consequently, in a contact scenario involving three or more sample subjects, the transfer of infectious microorganisms from one subject to one non-subject can be quantitatively assessed for each contact event, each involving a one-on-one contact with each sample subject. This enables simulation of realistic infection scenarios and more accurate assessment of exposure risk.

[0175] [Modification]

[0176] like Figure 13 As shown, the CPU 11 may determine the comprehensive evaluation of the exposure risk in the target area based on the exposure risk information ( ST35 ). In this case, the CPU 11 may output an evaluation result association including at least information on priority and information on the comprehensive evaluation ( ST34 ).

[0177] CPU11 can determine the comprehensive evaluation of exposure risk based on the evaluation results of exposure risk derived from each of the multiple evaluation items. For example, CPU11 can determine the comprehensive evaluation of exposure risk by calculating at least one selected from the total value, average value, maximum value, central value, etc. of the exposure risk index calculated in each of the multiple evaluation items. In this case, the information about the comprehensive evaluation can include information about the numerical value and / or rating of the calculated exposure risk index. In addition, when information about the importance of each evaluation item is stored, CPU11 can refer to the information about the importance of each evaluation item to determine the comprehensive evaluation. For example, CPU11 can calculate the value obtained by multiplying the exposure risk index of each evaluation item by a coefficient determined based on the importance, and use this value to determine the comprehensive evaluation.

[0178] Alternatively, CPU 11 may determine a comprehensive exposure risk assessment for the target area based on the exposure risk association information, separately from the exposure risk assessment process for each of the multiple assessment items. For example, CPU 11 may determine a comprehensive exposure risk assessment for the target area using exposure risk association information associated with one or more inspection results associated with the target area. This comprehensive assessment may be determined based on multiple inspection results or derived based on each inspection result.

[0179] Therefore, reference Figure 4The second terminal device 200B receives the evaluation result-related information including the information on the comprehensive evaluation ( ST41 ), and can display the received information on the display unit 26 ( ST42 ).

[0180] In addition, the screen displayed on the display unit 26 is not limited to Figure 12 The following describes a modification of the display screen.

[0181] like Figure 14 As illustrated, the display unit 26 can display analysis information detailing the results of the exposure risk assessment. The screen shown in the figure includes action risk information for a specific assessment item (Area A), with the assessment items divided into individual areas, and the assessment and / or analysis results regarding that exposure risk. This screen includes information regarding conversation time, information regarding the exposure risk due to droplet infection based on actions including the conversation ("Droplet Risk"), information regarding the exposure risk due to contact infection based on those actions ("Contact Risk"), and a bubble chart showing an example of the transition between droplet risk and contact risk based on conversation time. This allows an administrator using the second terminal device 200B to gain a more detailed understanding of the exposure risk caused by the actions of the subject person.

[0182] As another example of displaying the evaluation results of exposure risk, Figure 15 The exemplary display unit 26 can display a screen showing the evaluation results and / or analysis results of the exposure risk of the corresponding infection route for each evaluation item. Figure 15 The screen shown includes information on amylase test results for each evaluation item (here, a patch), along with information on the viral exposure level derived from that result. Furthermore, the screen can include a bar graph of viral exposure levels for each evaluation item as analytical information. This allows an administrator using the second terminal device 200B to intuitively understand which evaluation items have a high exposure risk for a given infection route (e.g., contact infection).

[0183] Other examples of displays of exposure risk assessment results include Figure 16 As shown, the display unit 26 can display a screen including analysis information analyzing the environmental risk information and / or the evaluation results of the exposure risk based thereon. Figure 16 The screen shown includes a radar chart showing the evaluation results of the ATP test and saliva droplet test for each inspection object corresponding to the parcel A in which the evaluation items are divided into each parcel, and a bar chart showing the evaluation results for each part of one inspection object.

[0184] Or, as Figure 17As shown, the display unit 26 may include a Pareto chart showing the evaluation results of the ATP test and the saliva droplet test for each inspection object in a certain evaluation item (slice B) as analysis information. Figure 16 as well as Figure 17 Based on such analysis results, the administrator using the second terminal device 200B can clearly grasp the location with a high exposure risk on the environmental surface.

[0185] In addition, the display unit 26 may also display detailed information about the comprehensive evaluation. For example, Figure 18 The screen shown in the example includes information on a comprehensive evaluation of all inspection results for the target area (here, Facility B), as well as comprehensive evaluations based on the results of behavioral inspections, CO2 inspections, ATP inspections, and saliva droplet inspections. This allows for a comprehensive assessment of the exposure risk of the target area, effectively assisting managers in their infection control measures.

[0186] [Specific example of simulation model]

[0187] A specific example of a simulation model for simulating exposure risk based on action risk information that can be used in this embodiment will be described. However, the simulation model used in this embodiment is not limited to the following example.

[0188] When a contact scenario includes three or more sample subjects, this simulation model can segment the contact scenario into multiple contact events, each including one subject and one non-subject, and calculate an exposure risk index for the non-subject for each contact event. Specifically, in each contact event, the simulation model calculates the estimated exposure of infectious microorganisms from the subject to the non-subject for each infection route. By summing the estimated exposures calculated for each infection route, the estimated exposure to the non-subject for each contact event can be calculated.

[0189] The following description uses viruses as examples of infectious microorganisms that are transmitted through saliva droplets and other aerosols. Examples of such viruses include SARS-CoV-2. In this example, the infection pathways include long-range and short-range routes. Long-range routes include airborne and contact transmission, while short-range routes include droplet transmission.

[0190] refer to Figure 19 , to explain how to calculate exposure for long-distance infection routes.

[0191] As shown in the figure, to accurately estimate exposure through long-distance infection routes, this simulation model divides the temporal evolution of the virus into multiple states. The transitions between these states are modeled as single reactions, and the amount of virus transferred to non-infected individuals is calculated as the exposure. These multiple states include, for example, "Room Air," "Textile Surfaces," "Nontextile Surfaces," "Hands," "Facial Membranes," "Lower Respiratory Tract," "Loss of Viability," and "Exhausted from the Room."

[0192] Figure 19 The state transition model shown can be described using the ordinary differential equations shown in the following equations (1) to (8). The specific numerical values ​​of the parameters in each of the following equations can be appropriately set by referring to, for example, known exposure risk simulation models such as those disclosed in Non-Patent Documents 1 and 2.

[0193] [Mathematical formula 1]

[0194]

[0195] [Mathematical formula 2]

[0196]

[0197] [Mathematical formula 3]

[0198]

[0199] [Formula 4]

[0200]

[0201] [Formula 5]

[0202]

[0203] [Formula 6]

[0204]

[0205] [Formula 7]

[0206]

[0207] [Formula 8]

[0208]

[0209] In these formulas, λ ij is the transition rate constant when transitioning from state i to state j. In addition, Q1, Q2, and Q3 are the virus distribution amounts to each state in the event of droplet generation (coughing, sneezing, talking, etc.) (the dimension is the amount of virus per unit [PFU / s]). In this simulation model, the model described in non-patent document 1 is used as a reference, and the virus distribution amounts Q1, Q2, and Q3 are determined as shown in equations (9) to (11). In the following equations, Q large , Q small Respectively represents the volume of large droplets and small droplets produced per unit time due to coughing, talking, sneezing, etc. saliva is the virus concentration in saliva ([PFU / mL]). In addition, f textile 、f nontextile is the ratio of the fiber surface to the hard surface in the environment. By solving equations (1) to (11) based on the initial conditions (initial viral load), the temporal variation of the viral load in each state can be obtained.

[0210] [Formula 9]

[0211]

[0212] [Formula 10]

[0213]

[0214] [Mathematical formula 11]

[0215]

[0216] In this simulation model, the infection route by inhaling droplet nuclei floating in the air is called "Respirable". respirable Equivalent to Figure 19 N6.

[0217] [Mathematical formula 12]

[0218]

[0219] In this simulation model, the infection route by touching a contaminated surface with a finger and then contacting the facial mucosa with the finger is called "Hand Contact". hand Equivalent to Figure 19 N5.

[0220] [Mathematical formula 13]

[0221]

[0222] Next, we'll explain how to calculate exposure for close-range infection routes. In this simulation model, two close-range routes are considered: "Spray" and "Inspirable." Spray is a route where large droplets from coughing, sneezing, or talking hit the mucous membranes, leading to infection. Inspirable is a route where small droplets from coughing, sneezing, or talking are inhaled, leading to infection.

[0223] In this simulation model, the amount of spray exposure can be estimated according to the following concept.

[0224] (1) Conical spray of droplets.

[0225] (2) The large particles that contribute to the spray pass evenly over the base area of ​​the cone.

[0226] (3) The probability of a droplet hitting the mucosa is expressed by the ratio of the surface area of ​​the mucosa to the base area of ​​the cone.

[0227] (4) The infected are located near the infected at a constant frequency.

[0228] (5) The virus concentration in saliva is constant and independent of the droplet diameter.

[0229] Based on this idea, the exposure amount of Spray D spray The temporal variation of is expressed by the following equations (14) and (15).

[0230] [Mathematical formula 14]

[0231]

[0232] [Mathematical formula 15]

[0233]

[0234] Here, Q large is the total volume of large droplets produced per unit time due to coughing / talking / sneezing. In this example, only large droplets contribute to Spray. proximity It is the frequency with which an infected person is located near an infected person, and referring to Non-Patent Document 2, it can be set to 0.05, for example.

[0235] In this simulation model, the exposure to Inspirable is estimated based on the cone, similar to Spray. The differences from Spray are as follows: the small particles contributing to Inspirable float evenly within the cone volume; and the probability of inhaling the generated droplets is expressed as the ratio of "breathing frequency" to "breathing flow rate." Based on this concept, the exposure to Inspirable, D spray The temporal variation of is expressed by the following equations (16) and (17). In addition, 0.5 is the ratio of the suction droplets in the suction volume.

[0236] [Formula 16]

[0237]

[0238] [Mathematical formula 17]

[0239]

[0240] Furthermore, in this simulation model, the infection risk can be calculated based on the calculated estimated exposure amount.

[0241] For example, the Dose-Response Model is a known model for expressing the probability of infection caused by a certain microorganism or virus. This model can be used when there is no threshold for infection. In this simulation model, for example, the "Exponential Model" among the Dose-Response Models can be used to estimate the infection risk (probability) based on the exposure to the virus. In the Exponential Model, the exposure to the virus D i and infection risk R i The relationship is expressed as follows.

[0242] [Mathematical formula 18]

[0243]

[0244] Here, the subscript i corresponds to the path (Respirable, Hand Contact, Spray, Inspirable). In addition, α i It is a parameter that shows the ease of infection. In this simulation model, since Respirable causes infection in the lower respiratory tract, the parameter α can be combined with other infection routes (Hand Contact, Spray, Inspirable). i Calculate separately.

[0245] [Mathematical formula 19]

[0246]

[0247] [Mathematical formula 20]

[0248]

[0249] The total risk R considering all exposure pathways total It can be obtained using the inclusion-exclusion principle. By using the inclusion-exclusion principle, it is possible to calculate the infection risk that matches the actual situation, such as "infection occurs only once," without repeatedly calculating the infection risk of each path.

[0250] [Mathematical formula 21]

[0251]

[0252] Contribution rate of each path Φ i For example, it is defined by the following formula (22).

[0253] [Mathematical formula 22]

[0254]

[0255] Thus, the infection risk of each infection route can be calculated using Formula (23) adjusted so that the sum of the infection risks of each route is equal to the total infection risk.

[0256] [Mathematical formula 23]

[0257]

[0258] As described above, in this simulation model, not only a deterministic model with relatively fast calculation speed is adopted, but also the estimated exposure amount for each infection route is calculated. Therefore, the exposure risk can be calculated with high accuracy at a fast processing speed.

[0259] <Second embodiment>

[0260] Hereinafter, a second embodiment of the present embodiment will be described. In this embodiment, description of the same configuration as that of the first embodiment will be omitted as appropriate.

[0261] [System Overview]

[0262] The system according to the second embodiment of the present invention can function as an infection countermeasure support system for assisting in countermeasures against infection by infectious microorganisms in a target area. The system includes, as in the first embodiment, a server 100 on the Internet N, a first terminal device 200A, and a second terminal device 200B, and may further include a detection device 300 and a measurement device 400 as an inspection device 500 (see Figure 1 ).

[0263] In this embodiment, similar to the first embodiment, the server 100 obtains exposure risk association information associated with the exposure risk in each of the multiple evaluation items and evaluates the exposure risk in each of the multiple evaluation items based on the exposure risk association information. Unlike the first embodiment, the server 100 generates a recommendation for an infection control measure to reduce the exposure risk for at least one of the multiple evaluation items and predicts the exposure risk if the infection control measure is implemented. Thus, the server 100 can output infection control supplementary information including the exposure risk assessment result, the generated infection control measure recommendation, and the exposure risk prediction result.

[0264] The hardware configuration of each device is, for example, the same as that of the first embodiment (see Figure 2 (A) and (B)). In addition, the storage unit 18 of the server 100 includes the same countermeasure area information database as that of the first embodiment.

[0265] [System operation example]

[0266] Next, use Figure 20 The operation of the server 100 described below is performed by the cooperation of hardware such as the CPU 11 and the communication unit 19 and software stored in the storage unit 18. The same applies to other devices.

[0267] In this example, as in the first embodiment, the target area is store A, a restaurant, and the infectious microorganisms are viruses that cause infections through contact, droplet infection, and airborne transmission. Furthermore, the following steps in this example are the same as in the first embodiment, and therefore their detailed descriptions are omitted: the first terminal device 200A receives input of at least a portion of the exposure risk information (ST11); transmits at least a portion of this exposure risk information to the server 100 (ST12); the inspection device 500 obtains inspection results (ST21), transmits information regarding these measurement results to the server 100 as part of the exposure risk information (ST22); the server 100 obtains the exposure risk information (ST31); and the CPU 11 evaluates the exposure risk for each of a plurality of evaluation items based on the exposure risk information (ST32). This example differs from the first embodiment in that the exposure risk evaluation results are primarily utilized in generating recommendations for infection countermeasures, and furthermore, the exposure risk after the infection countermeasures are implemented is predicted.

[0268] (Generation processing is recommended)

[0269] In this operational example, after the priority determination step ( ST33 ), the CPU 11 generates a suggestion on an infection countermeasure for reducing the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items ( ST35 ).

[0270] For example, the CPU 11 may generate infection countermeasure recommendations for each of the evaluation items for which exposure risk has been assessed. Alternatively, the CPU 11 may generate infection countermeasure recommendations for at least one evaluation item selected based on the exposure risk assessment results. Alternatively, the CPU 11 may generate recommendations for evaluation items assessed as having a high exposure risk. For example, if the target area database stores information regarding the importance of evaluation items, the CPU 11 may also generate infection countermeasure recommendations for evaluation items with a high importance.

[0271] Furthermore, as described in the first embodiment, for example, when the CPU 11 determines the priority among a plurality of evaluation items (see Figure 4 In ST33), suggestions for infection countermeasures for the high-priority evaluation items can also be generated. This allows specific improvement measures to be suggested for the high-priority evaluation items.

[0272] In this step, CPU 11 can select an infection countermeasure from the recommended evaluation item for the target. For example, CPU 11 can select an infection countermeasure stored in association with the recommended evaluation item for the target. Alternatively, if information about the infection path for each evaluation item and information about the infection countermeasure associated with each infection path is stored, CPU 11 can select an infection countermeasure corresponding to the infection path for the recommended evaluation item for the target. In this case, CPU 11 can, for example, select an infection path corresponding to an infection path assessed as having a high exposure risk.

[0273] Furthermore, if the target area database stores the importance of evaluation items and / or infection paths, CPU 11 can select infection countermeasures for highly important evaluation items and / or infection paths. Furthermore, if information regarding the effort and / or cost associated with each infection countermeasure is stored, CPU 11 can select infection countermeasures that fall within the acceptable effort and / or cost ranges registered by an administrator or the like.

[0274] Examples of infection countermeasures against contact infection include implementing infection countermeasures, specifically cleaning, wearing masks (e.g., non-woven masks), and finger hygiene. Examples of infection countermeasures against droplet infection include wearing masks (e.g., non-woven masks), self-control in conversation, installing partition walls, improving ventilation efficiency, and providing location indicators (e.g., posters, markers, etc.).

[0275] As another example, CPU 11 can select infection countermeasures associated with the subject's actions and / or infection countermeasure status included in the behavioral risk information. Examples of the subject's actions included in the behavioral risk information include the presence or timing of conversations, the wearing of masks, the type of masks, the volume of voices, breathing volume, finger hygiene, and cleaning behaviors. Furthermore, examples of infection countermeasure status include partition wall installation and ventilation conditions (such as ventilation volume and frequency). CPU 11 can, for example, select an infection countermeasure to improve at least one of the aforementioned actions and / or infection countermeasure statuses.

[0276] Next, CPU 11 can generate suggestions for each selected infection countermeasure. For example, CPU 11 can generate suggestions using fixed sentences stored in association with the selected infection countermeasure. Fixed sentences are preferably prepared for each infection countermeasure. Alternatively, CPU 11 can generate suggestions using keywords stored in association with the selected infection countermeasure. In this case, CPU 11 can generate suggestions using, for example, known article generation technology that automatically creates articles based on keywords.

[0277] (Exposure risk prediction processing)

[0278] CPU 11 predicts the exposure risk for the evaluation items after implementation of the infection control measures (ST36). For example, CPU 11 changes the value of at least one parameter corresponding to the selected infection control measure, included in the exposure risk-related information, and uses the changed parameter value to evaluate the exposure risk in the same manner as in step ST32, thereby predicting the exposure risk. The parameter values ​​mentioned here are not limited to actual numerical values ​​and include numerically quantifiable indicators such as "present" and "absent," "high," and "low."

[0279] For example, parameters included in the behavioral risk information include parameters related to the subject's behavior and / or infection control measures. Parameters related to the subject's behavior include the presence or timing of conversations, whether a mask was worn, the type of mask, the volume of sound, breathing volume, finger hygiene, and cleaning. Parameters related to infection control measures include the presence or absence of partition walls and ventilation conditions (such as ventilation volume and frequency). The parameters to be changed can be one or more of these. For example, if "mask wearing" is selected as an infection control measure, CPU 11 can change the "mask wearing" parameter from the current "no mask" to "mask wearing" to evaluate exposure risk in the same manner as in evaluation step (ST32).

[0280] Examples of parameters included in environmental risk information include detection indicators related to detection of infectious microorganisms, specifically, detection indicators for saliva components and ATP. The parameters to be modified can be one or more of these. If the selected infection control measures include infection control measures associated with these detection results (such as cleaning and finger hygiene), the CPU 11 can, for example, modify the detection indicators related to infectious microorganisms to more optimal values ​​and evaluate the exposure risk in the same manner as in the evaluation step (ST32).

[0281] Other parameters included in the environmental risk information include indicators related to ventilation conditions, specifically ventilation volume, ventilation frequency, etc. If the selected infection countermeasures include infection countermeasures specific to ventilation conditions, CPU 11 may, for example, modify the indicators related to ventilation conditions to more preferred values ​​and evaluate the exposure risk in the same manner as in evaluation step ( ST32 ).

[0282] (Output processing of auxiliary information on infection countermeasures)

[0283] Next, CPU 11 outputs supplementary infection control information (ST37) including the exposure risk assessment results, recommendations for infection control measures, and exposure risk prediction results. Furthermore, the supplementary infection control information may also include analysis information analyzing the exposure risk assessment results and / or prediction results. In this example, CPU 11 can transmit this supplementary infection control information to the second terminal device 200B. The supplementary infection control information can be output using, for example, the same method as for the assessment result-related information described in the first embodiment.

[0284] Furthermore, the infection countermeasure auxiliary information may include a comprehensive evaluation of the exposure risk in the target area, which has been described as a modified example of the first embodiment.

[0285] As a result, the second terminal device 200B receives the supplementary infection control information (ST43) and displays the received information on the display unit 26 (ST44). In this operational example, the display unit 26 of the second terminal device 200B functions as a "display unit for displaying the supplementary infection control information output from the control unit."

[0286] like Figure 21As shown, the display unit 26 can display a screen that includes the exposure risk assessment results, exposure risk prediction results, and recommendations for infection control measures for each assessment item (e.g., scenario). This clearly shows the change in exposure risk before and after infection control measures are implemented for each assessment item, enabling the provision of persuasive recommendations. Furthermore, this screen can include a comprehensive assessment of exposure risk. Furthermore, this screen can include the priority level of infection control measures for each scenario (e.g., A, B, C, D, E), and the display unit 26 can also display the priority levels using color coding.

[0287] [Effects of this embodiment]

[0288] According to the infection countermeasures support system in this embodiment, it is possible to generate evaluation results for the exposure risk of each of the multiple evaluation items and suggestions for infection countermeasures, and then predict and output the exposure risk after the implementation of the infection countermeasures, thereby increasing the persuasiveness of the necessity of the infection countermeasures. In addition, by prompting suggestions for infection countermeasures, infection countermeasures can be clearly recommended. Furthermore, through the above-mentioned structure, the effort of the administrator to analyze the exposure risk before and after the infection countermeasures for determining specific infection countermeasures can be reduced, and the processing burden of the second terminal device 200B, such as analysis and processing, can be reduced. Therefore, according to the system of this embodiment, the infection countermeasures in the target area can be made more efficient, and the burden of infection countermeasures on the administrator and others can be reduced.

[0289] [Modification]

[0290] like Figure 22 As illustrated, the recommendation generation step (ST35) can also be performed after the exposure risk prediction step (ST36). In this case, CPU 11 can select an infection control measure for at least one of the multiple evaluation items to reduce the evaluated exposure risk and predict the exposure risk for that evaluation item after implementation of the infection control measure (ST36). CPU 11 can then generate a recommendation regarding the infection control measure (ST35). This allows CPU 11 to output similar infection control supplementary information.

[0291] In addition, the screen displayed on the display unit 26 is not limited to Figure 21 The following describes a modification of the display screen.

[0292] For example, Figure 23 As shown, the display unit 26 can display a screen containing analysis information and recommendations, where the chart includes an icon indicating the relationship between the presence or absence of an infection control measure (e.g., mask wearing) and exposure risk for each evaluation item (e.g., scenario), and the recommendation recommends the infection control measure (e.g., mask wearing). This allows the results of the exposure risk analysis to be displayed while also providing recommendations for convincing infection control measures.

[0293] For example, Figure 24 As shown, the display unit 26 can display analysis information of the evaluation results and analysis information of the prediction results for a certain evaluation item. Figure 24 For example, the displayed screen includes analysis results (e.g., bubble charts) regarding the risk of contact infection exposure before and after infection control measures (reduced session time, reduced dwell time, reduced droplet-generating actions) for a specific evaluation item. This allows for a clearer display of the risk of exposure before and after infection control measures. Furthermore, in this case, the display unit 26 can display recommendations on other display screens.

[0294] <Other Implementation Methods>

[0295] Furthermore, although the embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications can be made without departing from the spirit of the present invention. For example, the contents described in the various embodiments can be combined and implemented as much as possible.

[0296] In the example operations of the above embodiment, four tests for obtaining exposure risk-related information are exemplified: a behavioral test, a saliva droplet test, an ATP test, and a CO2 concentration test. However, the present invention is not limited to these tests. Furthermore, the number of tests for obtaining exposure risk-related information is not limited to multiple types; a single type may also be sufficient.

[0297] Furthermore, if the behavioral risk information includes information regarding attributes of the sample subjects as information about the sample subjects observed in the contact scenario, the CPU 11 can evaluate and / or predict the exposure risk based on the behaviors of the sample subjects classified according to the attributes. Attributes of the sample subjects include attributes related to exposure risk, risk of severe illness, and / or risk of morbidity. For example, in addition to age group, position, and type of work, the prevalence rate, pre-existing medical condition rate, and attack rate of diseases associated with exposure risk, risk of severe illness, and / or risk of morbidity can also be cited.

[0298] Figure 25 The screen shown in the example includes a bubble chart analyzing the results of droplet infection exposure risk analysis during a chorus event at facility B. This screen, for example, categorizes the sample subjects into choristers, audience members, and staff, and includes the evaluation results of their respective droplet infection exposure risks. Furthermore, the screen includes exposure risk prediction results for situations such as 100% mask wearing in any group and distance between audience members. This allows evaluation results to be obtained for each sample subject group based on different exposure risks, severe disease risks, etc., making infection countermeasures more efficient.

[0299] In addition to exposure risk-related information, the CPU 11 can also utilize information regarding the infectivity and / or dangerousness of infectious microorganisms in its exposure risk assessment and / or prediction process. Examples of such information include information regarding infectious diseases caused by infectious microorganisms (e.g., symptoms of infectious diseases, risk levels), tables that correspond to test results and risk levels, information regarding the titer of infectious microorganisms (e.g., 50% infection dose, infection establishment dose), which is a parameter used in exposure risk simulations using dose-response functions, information regarding the prevalence of infectious microorganisms (e.g., infection rate within a city, number of infected individuals), and information regarding the status of immunity to infectious microorganisms (e.g., antibody retention rate, vaccination rate, etc.). This information is stored, for example, in the storage unit 18 and can be appropriately referenced during the exposure risk assessment and / or prediction process performed by the server 100.

[0300] Furthermore, the system configuration is not limited to the example above. For example, if the administrator themselves inspects the target area, a single terminal device can function as both an input receiving unit and a display unit. Furthermore, the inspection device 500 that constitutes the system is not limited to the example above. Alternatively, the system may not even have an inspection device.

[0301] Explanation of symbols

[0302] 11, 21…CPU

[0303] 18, 28…Storage

[0304] 100…Server (information processing device)

[0305] 200A, 200B…Terminal devices

[0306] 300…Detection device

[0307] 400...Measuring device

[0308] 500…Inspection device.

[0309] Industrial applicability

[0310] According to the present invention, countermeasures against infection by infectious microorganisms can be made more efficient.

Claims

1. An exposure risk assessment system for assessing the exposure risk of a subject staying in a target area to infectious microorganisms, The exposure risk assessment system includes a control unit that performs the following processing: Obtaining exposure risk related information associated with the exposure risk, evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, differentiated by at least one element selected from a position within the target area, a time, and an action of the subject person, based on the exposure risk-related information; determining the priority of the infection countermeasure against the infectious microorganism among the plurality of evaluation items based on the evaluation results of the exposure risk of each of the plurality of evaluation items, Evaluation result-related information including information on the determined priority is output.

2. The exposure risk assessment system according to claim 1, wherein: The evaluation item is associated with at least one infection route of the infectious microorganism. The exposure risk-related information includes information related to the exposure risk based on the infection pathway corresponding to each of the plurality of evaluation items.

3. The exposure risk assessment system according to claim 1 or 2, wherein: The exposure risk-related information includes action risk information related to an action associated with the exposure risk of the subject in a situation corresponding to at least one evaluation item among the plurality of evaluation items.

4. The exposure risk assessment system according to claim 3, wherein: The action risk information includes information on contact scenarios encountered by a plurality of sample subjects as the subject observed in a situation corresponding to the evaluation item.

5. The exposure risk assessment system according to claim 4, wherein: The action risk information includes information about at least one selected from the stay time of the sample subject in the contact scene, the droplet-generating action of the sample subject in the contact scene, the positional relationship between the sample subjects in the contact scene, and the infection countermeasure status in the contact scene.

6. The exposure risk assessment system according to claim 4 or 5, wherein: The control unit performs the following processing: It is assumed that at least one of the sample subjects is a holder who possesses the infectious microorganism, and the exposure risk of the sample subjects other than the holder, i.e., non-holders, is simulated based on the action risk information and the infection path of the infectious microorganism, thereby evaluating the exposure risk in the contact scenario.

7. The exposure risk assessment system according to claim 6, wherein: The control unit performs the following processing: When the plurality of sample subjects in the contact scene include three or more sample subjects, The contact scenario is divided into a plurality of contact events including one of the holder and one of the non-holder, and for each of the plurality of contact events, an exposure risk index serving as an indicator of the exposure risk of the non-holder is calculated. The exposure risk in the contact scenario is evaluated based on the calculated exposure risk indicators for the plurality of contact phenomena.

8. The exposure risk assessment system according to any one of claims 1 to 7, wherein: The exposure risk-related information includes environmental risk information associated with the exposure risk, where the exposure risk is caused by an environment corresponding to at least one evaluation item among the plurality of evaluation items.

9. The exposure risk assessment system according to claim 8, wherein: The environmental risk information includes information on detection results related to the infectious microorganisms in the environment.

10. The exposure risk assessment system according to claim 9, wherein: The environmental risk information includes information on detection results of components contained in saliva in the environment.

11. The exposure risk assessment system according to claim 9 or 10, wherein: The environmental risk information includes information on detection results of ATP in the environment.

12. The exposure risk assessment system according to any one of claims 8 to 11, wherein: The environmental risk information includes information on a ventilation condition of a space within the target area.

13. The exposure risk assessment system according to any one of claims 1 to 12, wherein: The plurality of evaluation items respectively correspond to a plurality of scenarios classified based on actions of the subject person related to the exposure risk.

14. The exposure risk assessment system according to any one of claims 1 to 13, wherein: The plurality of evaluation items respectively correspond to a plurality of parcels divided in the target area.

15. The exposure risk assessment system according to any one of claims 1 to 12, wherein: The exposure risk is the exposure risk to the infectious microorganisms produced in the subject area, The plurality of evaluation items each corresponds to at least one selected from a plurality of scenes distinguished based on an action related to the exposure risk of the subject person, a plurality of parcels distinguished in the target area, and a plurality of time periods distinguished by the exposure risk.

16. The exposure risk assessment system according to any one of claims 1 to 15, wherein: The evaluation result-related information further includes information on evaluation results of the exposure risk in each of the plurality of evaluation items.

17. The exposure risk assessment system according to any one of claims 1 to 16, wherein: The control unit further determines a comprehensive evaluation of the exposure risk in the target area based on the exposure risk related information. The evaluation result-related information further includes information on the comprehensive evaluation.

18. The exposure risk assessment system according to any one of claims 1 to 17, wherein: The exposure risk assessment system further comprises: A display unit displays the evaluation result-related information output from the control unit.

19. The exposure risk assessment system according to any one of claims 1 to 18, wherein: The exposure risk assessment system further comprises: An input receiving unit receives an input of at least a portion of the exposure risk-related information.

20. The exposure risk assessment system according to any one of claims 1 to 19, wherein: The infectious microorganisms include at least one selected from viruses, bacteria, protozoa and fungi.

21. An exposure risk assessment method for assessing the exposure risk of a subject staying in a target area to infectious microorganisms. The control unit of the information processing device performs the following processing: Obtaining exposure risk related information associated with the exposure risk, evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, differentiated by at least one element selected from a position within the target area, a time, and an action of the subject person, based on the exposure risk-related information; determining the priority of the infection countermeasure against the infectious microorganism among the plurality of evaluation items based on the evaluation results of the exposure risk of each of the plurality of evaluation items, Evaluation result-related information including information on the determined priority is output.

22. The exposure risk assessment method according to claim 21, wherein: The exposure risk is the exposure risk to the infectious microorganisms produced in the subject area, The plurality of evaluation items each corresponds to at least one selected from a plurality of scenes distinguished based on an action related to the exposure risk of the subject person, a plurality of parcels distinguished in the target area, and a plurality of time periods distinguished by the exposure risk.

23. A program for evaluating the risk of exposure of a subject staying in a target area to infectious microorganisms, the program causing an information processing device to execute: The step of obtaining exposure risk related information associated with the exposure risk; a step of evaluating the exposure risk in each of a plurality of evaluation items for evaluating the exposure risk, differentiated by at least one element selected from a position in the target area, a time, and an action of the subject person, based on the exposure risk-related information; a step of determining a priority of infection countermeasures against the infectious microorganisms among the plurality of evaluation items based on evaluation results of the exposure risk of each of the plurality of evaluation items; and A step of outputting evaluation result-related information including information on the determined priority.

24. The program according to claim 23, wherein The exposure risk is the exposure risk to the infectious microorganisms produced in the subject area, The plurality of evaluation items each corresponds to at least one selected from a plurality of scenes distinguished based on an action related to the exposure risk of the subject person, a plurality of parcels distinguished in the target area, and a plurality of time periods distinguished by the exposure risk.

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