Infection risk reduction support device and infection risk reduction support program

Abstract

To obtain an infection risk suppression support device and an infection risk suppression support program that can reduce future infection risks more easily and effectively. [Solution] The control device 10 (infection risk suppression support device) includes: an acquisition unit 11A that acquires an index that corresponds to the ventilation rate of the target room and allows prediction of changes over time due to changes in the ventilation rate; an extraction unit 11B that derives infection risk information indicating the infection risk of the target room from the present time onward by applying the index acquired by the acquisition unit 11A to an extended model which is an extended model that expands a steady evaluation model that can evaluate the steady infection risk in the room according to the ventilation rate to a model that can evaluate the infection risk according to the non-steady changing ventilation rate from the present time onward; and a control unit 11C that uses the infection risk information derived by the extraction unit 11B to perform control to suppress the infection risk of the target person in the target room.

Description

[Technical Field]

[0001] This invention relates to an infection risk suppression support device and an infection risk suppression support program. [Background technology]

[0002] Reducing the risk of infection (hereinafter also referred to as "infection risk") in various rooms such as hospital rooms where patients with infectious diseases like COVID-19, influenza, measles, and tuberculosis are hospitalized, waiting rooms at hospitals where such patients are treated, and rooms in the patients' homes where they are recuperating (hereinafter also referred to as "target rooms") is extremely important in controlling infectious disease outbreaks and the strain on the healthcare system.

[0003] Furthermore, in order to reduce the risk of infection, it is important to reduce the concentration of the virus inside the target room as much as possible, and to achieve this, it is necessary to effectively ventilate the room using ventilation equipment.

[0004] Conventionally, the following technologies have been applicable to effectively ventilate the target room.

[0005] Patent Document 1 discloses a ventilation device that aims to enable a predetermined ventilation operation to be performed only after a person has entered a room and ventilation is actually needed.

[0006] This ventilation system is characterized by comprising: a ventilation means for ventilating a sanitary space; and a control means that, upon detecting a person entering or leaving the sanitary space using a detection means, controls the ventilation means to perform ventilation operation after a predetermined waiting period has elapsed.

[0007] Although this technology is intended for sanitary spaces, by applying it to the aforementioned rooms targeted for infection risk reduction instead of the sanitary spaces, the infection risk in those rooms can be reduced.

[0008] In addition, Patent Document 2 discloses an infection risk quantification method aimed at probabilistically quantifying the infection risk by taking in, as input information, epidemiological data including the community infection situation in addition to the environmental data measured within the facility.

[0009] This infection risk quantification method is an infection risk quantification method for evaluating the infection risk of at least one section within a facility, and includes a measurement step of measuring the CO2 concentration within the section while measuring the CO2 concentration outside the facility, a step of obtaining at any time the number of reported infected cases nr in the region to which the facility belongs regarding at least one infectious disease from an epidemiological data viewing site, and a step of deriving at any time the infection probability P within the section using a mathematical model.

[0010] By performing ventilation on the target room targeted for reduction of the above-described infection risk using the infection probability P obtained by this technique, the infection risk in the target room can be reduced.

Prior Art Documents

Patent Documents

[0011]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0012] However, in the technique of controlling the ventilation of the target room by applying the technique disclosed in Patent Document 1, since it is a technique for controlling after entering the target room, there is a problem that the reduction of the infection risk is insufficient.

[0013] In addition, in the technology of controlling the ventilation of the target room by applying the technology disclosed in Patent Document 2, there is a problem that the control becomes complicated because the control is performed based on an index that is generated by both infected and non-infected persons, namely the CO2 concentration, and the infection probability of the region is used.

[0014] The present disclosure has been made in view of the above facts, and an object thereof is to provide an infection risk suppression support device and an infection risk suppression support program that can more simply and effectively reduce a future infection risk.

Means for Solving the Problems

[0015] The infection risk suppression support device according to the present invention described in claim 1 includes an acquisition unit that acquires an index that can predict a change over time associated with a change in the ventilation volume of a target room, and a steady-state evaluation model that can evaluate a steady-state infection risk in the room according to the ventilation volume. An extended model that can evaluate the infection risk according to the non-steady ventilation volume after the current time is extended, and by applying the index acquired by the acquisition unit to the extended model, an infection risk information indicating the infection risk after the current time of the target room is derived. And a control unit that performs control for suppressing the infection risk of the target person due to the target room using the infection risk information derived by the derivation unit.

[0016] According to the infection risk suppression support device of the present invention as described in claim 1, an index is acquired that corresponds to the ventilation rate of the target room and allows prediction of changes over time due to changes in the ventilation rate. By applying the acquired index to an extended model, which expands a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, infection risk information indicating the infection risk of the target room from the present time onward is derived. By using the derived infection risk information to control the infection risk of the target person in the target room, the control can be performed using the infection risk information from the present time onward, resulting in a simpler and more effective reduction of future infection risks.

[0017] The infection risk suppression support device according to claim 2 is the infection risk suppression support device according to claim 1, wherein the indicator is the quanta concentration.

[0018] According to the infection risk suppression support device of the present invention as described in claim 2, by using the quanta concentration as the indicator, the risk of infection can be reduced more simply and effectively when the quanta concentration is used as the indicator.

[0019] The infection risk suppression support device according to claim 3 is the infection risk suppression support device according to claim 1 or claim 2, wherein the steady-state evaluation model is the Wells-Riley model.

[0020] According to the infection risk suppression support device of the present invention as described in claim 3, by using the Wells-Riley model as the steady-state evaluation model, the infection risk can be reduced more simply and effectively when the Wells-Riley model is used as the steady-state evaluation model.

[0021] The infection risk suppression support device according to claim 4 is the infection risk suppression support device according to claim 3, wherein the extended model is a model obtained by applying numerical integration over a small time interval to the Wells-Riley model.

[0022] According to the infection risk suppression support device of the present invention as described in claim 4, the extended model can be obtained more easily by using a model obtained by applying numerical integration over a small time interval to the Wells-Riley model.

[0023] The infection risk suppression support device according to claim 5 is the infection risk suppression support device according to claim 1 or claim 2, wherein the control unit performs at least one of the following controls as controls for suppressing the infection risk: control of opening and closing of entrances and exits in the target room, control of the ventilation volume, and control of presenting information regarding the infection risk to the target person.

[0024] According to the infection risk suppression support device of the present invention as described in claim 5, by performing at least one of the following controls to suppress the risk of infection: control of opening and closing of entrances and exits in the target room, control of ventilation volume, and control of presenting information on the risk of infection to the target person, the risk of future infection can be reduced more easily and effectively depending on the control applied.

[0025] The infection risk suppression support program according to claim 6 of the present invention acquires an index that is in accordance with the ventilation rate of a target room and allows prediction of changes over time due to changes in the ventilation rate, and applies the acquired index to an extended model which extends a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate to a model that can evaluate the infection risk according to the ventilation rate that changes non-steadily from the present time onward, thereby deriving infection risk information that shows the infection risk of the target room from the present time onward, and using the derived infection risk information, causes a computer to execute a process to suppress the infection risk of a target person in the target room.

[0026] According to the infection risk suppression support program of the present invention as described in claim 6, an index is obtained that corresponds to the ventilation rate of the target room and allows prediction of changes over time due to changes in the ventilation rate. By applying the obtained index to an extended model, which expands a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, infection risk information indicating the infection risk of the target room from the present time onward is derived. By using the derived infection risk information to control the infection risk of the target person in the target room, the control can be performed using the infection risk information from the present time onward, resulting in a simpler and more effective reduction of future infection risks. [Effects of the Invention]

[0027] As described above, the present invention makes it possible to reduce the risk of future infection more easily and effectively. [Brief explanation of the drawing]

[0028] [Figure 1] This is a block diagram showing an example of the hardware configuration of the control system according to the embodiment. [Figure 2] This figure shows an example of the configuration of hospital equipment according to the embodiment. [Figure 3] This is a block diagram showing an example of the functional configuration of a control device according to the embodiment. [Figure 4] This is a schematic diagram showing an example of the configuration of a patient room information database according to the embodiment. [Figure 5] This is a schematic diagram showing an example of the configuration of an entry information database according to the embodiment. [Figure 6] This flowchart shows an example of the control process flow according to the embodiment. [Figure 7] This figure shows an example of a condition setting screen according to the embodiment. [Figure 8]This figure shows an example of an entry restriction display screen according to the embodiment. [Figure 9] This figure shows an example of the updated state of the entry restriction display screen according to the embodiment. [Figure 10] This graph shows an example of the results of an embodiment according to the present invention. [Figure 11] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 12] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 13] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 14] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 15] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 16] This figure shows another example of the configuration of hospital facilities according to the present invention. [Figure 17] This figure shows another example of the configuration of hospital facilities according to the present invention. [Modes for carrying out the invention]

[0029] The following describes in detail an example of a control system to which the infection risk suppression support device and infection risk suppression support program according to the present invention are applied. Here, we will describe the case in which the target room of the technology disclosed herein is a hospital room in a predetermined hospital where patients with infectious diseases are hospitalized. However, the target room of the technology disclosed herein is not limited to hospital rooms, and other rooms requiring ventilation, such as waiting rooms in hospitals where patients with infectious diseases are treated, or rooms in the patient's home where they are recuperating, may also be applied as the target room of the technology disclosed herein.

[0030] First, the configuration of the control system 90 according to this embodiment will be described with reference to Figure 1. Figure 1 is a block diagram showing an example of the hardware configuration of the control system 90 according to this embodiment.

[0031] As shown in Figure 1, the control system 90 according to this embodiment includes control devices 10 and hospital equipment 70, each connected to a network 60. The control system 90 according to this embodiment is a system for controlling hospital equipment 70, which are ventilation equipment installed in a hospital. In this embodiment, the control device 10 is installed in the central monitoring room of the target hospital, but is not limited to this, and for example, the control device 10 may be installed in the nurses' station of the hospital. The control device 10 corresponds to the infection risk suppression support device of the technology of this disclosure.

[0032] The control device 10 according to this embodiment includes a CPU (Central Processing Unit) 11 as a computer, a memory 12 as a temporary storage area, a non-volatile storage unit 13, an input unit 14 such as a keyboard and mouse, a display unit 15 such as a liquid crystal display, a media read / write device (R / W) 16, and a communication interface (I / F) unit 18. The CPU 11, memory 12, storage unit 13, input unit 14, display unit 15, media read / write device 16, and communication I / F unit 18 are connected to each other via bus B. The media read / write device 16 reads information written on the recording medium 17 and writes information to the recording medium 17.

[0033] The storage unit 13 in this embodiment is implemented by an HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, etc. The storage unit 13, as a storage medium, stores a control program 13A. The control program 13A is stored (installed) in the storage unit 13 when the recording medium 17 on which the program 13A is written is set in the media read / write device 16, and the media read / write device 16 reads the program 13A from the recording medium 17. The CPU 11 reads the control program 13A from the storage unit 13 as appropriate, loads it into the memory 12, and sequentially executes the processes that the program 13A has.

[0034] Furthermore, the memory unit 13 stores the patient room information database 13B and the admission information database 13C. Details of the patient room information database 13B and the admission information database 13C will be described later.

[0035] Figure 2 shows an example of the configuration of the hospital facilities 70 according to this embodiment. In the example shown in Figure 2, the patient rooms and corridors in which the hospital facilities 70 are installed are also shown in order to illustrate the layout of the hospital facilities 70. Furthermore, in order to avoid confusion, the example shown in Figure 2 illustrates the case in which only two patient rooms and two corridors are provided.

[0036] As shown in Figure 2, the hospital according to this embodiment has two adjacent patient rooms, patient room 80A and patient room 80B. In addition, a corridor 82A is provided adjacent to patient room 80A on the opposite side from patient room 80B, and a corridor 82B is provided adjacent to patient room 80B on the opposite side from patient room 80A.

[0037] Furthermore, patient room 80A is equipped with an individual air conditioner 72A, and patient room 80B is equipped with an individual air conditioner 72B. In the following, when patient room 80A and patient room 80B are not distinguished, they will be collectively referred to as "patient room 80." Similarly, when corridor 82A and corridor 82B are not distinguished, they will be collectively referred to as "corridor 82," and when individual air conditioners 72A and individual air conditioners 72B are not distinguished, they will be collectively referred to as "individual air conditioner 72."

[0038] The individual air conditioner 72 according to this embodiment takes in the air inside the patient room 80 (hereinafter referred to as "indoor air"), heats it, and supplies the temperature-adjusted air back to the patient room 80. Therefore, the temperature of the patient room 80 can be controlled by the individual air conditioner 72 and the outdoor air handling unit 78, which will be described later. The individual air conditioner 72 may be, for example, an indoor unit of a packaged air conditioner or a fan coil unit, but is not limited to these.

[0039] Furthermore, the hospital is equipped with an outside air handling unit (hereinafter referred to as "outside air") 78 for supplying air that has been taken in, heat-treated, and temperature-controlled from outside the hospital to multiple rooms, and an exhaust fan 79 for discharging the indoor air from the above-mentioned rooms to the outside of the hospital.

[0040] Meanwhile, an air intake vent 74A is provided in corridor 82A, an air intake vent 74B in patient room 80A, an air intake vent 74C in patient room 80B, and an air intake vent 74D in corridor 82B, each connected to the air handling unit 78 via a duct. Additionally, an exhaust vent 76A is provided in patient room 80A, and an exhaust vent 76B in patient room 80B, each connected to the exhaust fan 79 via a duct. In the following, when describing air intake vents 74A to 74D without distinction, they will be collectively referred to as "air intake vent 74," and when describing exhaust vents 76A to 76B without distinction, they will be collectively referred to as "exhaust vent 76."

[0041] Here, corridor 82A and patient room 80A are connected via a through-hole 84A, and corridor 82B and patient room 80B are connected via a through-hole 84B. Therefore, by operating the air handling unit 78 and exhaust fan 79, corridor 82 becomes positive pressure and patient room 80 becomes negative pressure. As a result, by operating the air handling unit 78 and exhaust fan 79, outside air flows into patient room 80 and corridor 82, and the inside air from patient room 80 and corridor 82 is discharged to the outside of the hospital via patient room 80, thereby ventilating the entire area.

[0042] In the control system 90 according to this embodiment, the individual air conditioners 72, the air handling unit 78, and the exhaust fan 79 are connected to the control device 10 via the network 60 as the hospital equipment 70 described above. Therefore, the operation of these pieces of equipment can be controlled by the control device 10. Of these pieces of equipment, the air handling unit 78 and the exhaust fan 79 are for ventilation, and therefore these pieces of equipment will be referred to as "ventilation equipment" below.

[0043] Although not shown in the illustration, the patient room 80 according to this embodiment is equipped with an electronic lock on the door used for entry and exit, and the locking and unlocking of the electronic lock can also be controlled by the control device 10. Furthermore, although not shown in the illustration, a display device for displaying various information (hereinafter referred to as the "patient room front display device") is provided near the door outside the patient room 80 according to this embodiment, and the control device 10 can also control the patient room front display device.

[0044] Next, the control method performed by the control system 90 according to this embodiment will be described.

[0045] To reduce the risk of infection in patient room 80, it is important to reduce the concentration of the virus inside patient room 80 as much as possible, and to achieve this, it is necessary to effectively ventilate the room using ventilation equipment.

[0046] Conventionally, methods to increase ventilation volume have been employed to control ventilation by operating the ventilation system at high speed or increasing the ventilation rate. However, when the ventilation system is operating at high speed, the operating noise of the ventilation system is louder compared to normal operation. Also, increasing the ventilation rate increases the ventilation volume, so the longer the period of noise generation, the higher the ventilation rate. For this reason, for example, it is difficult to operate the ventilation system at high speed or increase the ventilation rate at night when patients are sleeping in hospital room 80. Here, "ventilation rate" is synonymous with the ventilation volume, which is the value obtained by multiplying the volume of the target hospital room 80 by the ventilation rate. Therefore, "ventilation rate" and "ventilation volume" are interconnected physical quantities.

[0047] On the other hand, the time that people other than patients, such as medical professionals like doctors and nurses, visitors to patients, and cleaning staff for room 80 (hereinafter simply referred to as "entrants"), spend in room 80 is limited. Therefore, in order to rationally reduce the risk of infection for entrants, it is sufficient to reduce the virus concentration during the time they are in the room (hereinafter referred to as "virus concentration"), and it is not necessary to keep the ventilation system running at full power at all times or to increase the ventilation rate. Therefore, by switching the ventilation system to full power or increasing the ventilation rate immediately before entrants enter room 80, it is possible to simultaneously reduce the risk of infection for entrants, the burden on patients, and also save energy.

[0048] However, with this method, it takes a certain amount of time for the virus concentration inside patient room 80 to decrease after the ventilation system's operating state is switched. Therefore, if it were possible to predict the time from the moment the ventilation system's operating state is switched until it becomes possible for patients to enter patient room 80, it would improve convenience for patients.

[0049] Therefore, in the control system 90 according to this embodiment, a method for predicting the risk of infection inside the hospital room 80 a relatively short time after switching the operating state of the ventilation equipment from a steady state to a transient state is derived and applied.

[0050] Figure 3 is a functional block diagram showing an example of the functional configuration of the control device 10 according to this embodiment.

[0051] As shown in Figure 3, the control device 10 according to this embodiment includes an acquisition unit 11A, an output unit 11B, and a control unit 11C. The CPU 11 of the control device 10 executes a control program 13A, and the CPU 11 functions as the acquisition unit 11A, the output unit 11B, and the control unit 11C.

[0052] The acquisition unit 11A according to this embodiment acquires an index (quanta concentration in this embodiment) that corresponds to the ventilation rate of the target room (patient room 80 in this embodiment) and allows prediction of changes over time due to changes in the ventilation rate. The control unit 11C according to this embodiment increases the ventilation rate and restricts the subject's entry into the target room if the index does not satisfy a predetermined standard value at the time when the target person (the person entering the room as described above in this embodiment) is about to enter the target room.

[0053] Furthermore, the acquisition unit 11A in this embodiment acquires predicted values ​​of the time-dependent change of an index corresponding to the ventilation rate control by the control unit 11C. Then, after a waiting period has elapsed until the predicted value acquired by the acquisition unit 11A satisfies the standard value, the control unit 11C in this embodiment performs control to release the restriction on the subject entering the target room.

[0054] In this embodiment, the control unit 11C performs control to switch between an entry-response control, which controls the ventilation volume so that the indicator satisfies a standard value during the first period when the subject is staying in the target room, and a normal ventilation control, which performs control to reduce the ventilation volume compared to the first period during the second period excluding the first period. Specifically, the control unit 11C switches from normal ventilation control to entry-response control when the subject is about to enter the target room, and switches from entry-response control to normal ventilation control when the subject leaves the target room.

[0055] Furthermore, in the control system 90 according to this embodiment, the ventilation system satisfies the ventilation rate of 2 (times / hour) or more, which is recommended by the Ministry of Health, Labour and Welfare, during normal ventilation control.

[0056] On the other hand, the derivation unit 11B according to this embodiment applies an extended model that expands a steady-state evaluation model, which can evaluate the steady-state infection risk in a room according to the ventilation rate, to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward. Furthermore, the derivation unit 11B according to this embodiment derives infection risk information indicating the infection risk of the target room from the present time onward by applying the index acquired by the acquisition unit 11A to the extended model.

[0057] The control unit 11C in this embodiment then uses the infection risk information derived by the derivation unit 11B to perform controls to suppress the infection risk of the subject in the target room. As controls to suppress the infection risk, the control unit 11C in this embodiment performs at least one of the following controls (all of these controls in this embodiment): control of opening and closing of entrances and exits in the target room (control to restrict the subject's entry into the target room as described above), control of ventilation volume, and control to present the subject with information regarding the infection risk.

[0058] In the control system 90 according to this embodiment, the Wells-Riley model is applied as the steady-state evaluation model, and a model obtained by applying numerical integration over small time intervals to the Wells-Riley model is applied as the extended model. However, the system is not limited to this form, and a Dose-Response model may also be applied as the steady-state evaluation model. The Wells-Riley model is widely used because it is a simple model with few parameters and is easy to couple with CFD (computational fluid dynamics), while the Dose-Response model is a sophisticated model, but it requires many conditions to be identified for both the source of infection and the infected human body, making it difficult to apply. For this reason, the control system 90 according to this embodiment employs the Wells-Riley model.

[0059] The following describes the extension of the Wells-Riley model to an extended model.

[0060] In the Wells-Riley model, the evaluation is based on the average virus concentration (quantum concentration q) in the room. First, the equilibrium equation for the total amount of virus (quantum amount Q(t)) in the entire room is evaluated. When the time step is Δt, the total amount of virus Q(t + Δt) in the target room at a certain time t and the next time t + Δt is evaluated by the following equation (1).

[0061] Q(t + Δt) = Q(t) + Q (t) - Q vent (t) (1)

[0062] Here, Q oc (t) is the amount of virus scattered from the infected person during the time from t to t + Δt, and Q vent (t) is the amount of virus reduced by ventilation during the time from t to t + Δt, and they are evaluated by the following equations (2) and (3) respectively. Therefore, the virus amount Q(t + Δt) is expressed by equation (4).

[0063] Q oc (t) = (1 - ε IPFM ) × I × q × Δt (2)

[0064] Q vent (t) = NV × Δt × Q(t) / V = N × Δt × Q(t) (3)

[0065] Q(t + Δt) = Q(t) + (1 - ε IPFM ) × I × q × Δt - N × Δt × Q(t) = (1 - NΔt) × Q(t) + (1 - ε IPFM ) × I × q × Δt (4)

[0066] Here, I is the number of infected people in the room (persons), q is the quantum generation amount (quanta / h), which is the amount of virus generated per person per unit time, V is the volume of the room (m 3 ), ε IPFM is the attenuation rate (collection rate) (%) by the mask of the infected person, and N is the number of air changes per unit time (times / h).

[0067] The above evaluated the total viral load Q(t) for the entire room. However, since the amount of virus an entrant is exposed to depends on their respiratory rate, assuming a uniform viral concentration throughout the room, we convert it to the viral concentration per unit volume (quanta concentration) q(t) using the following formula.

[0068] q(t)=Q(t) / V (5)

[0069] q(t+Δt)=(1-NΔt)×q(t)+(1-ε IPFM ) × I × q × Δt / V (6)

[0070] Here, the evaluation was conducted under the assumption that the virus concentration is uniform throughout the room, as described above. However, it is also possible to use the virus concentration evaluated by the airflow simulation results.

[0071] In the control system 90 according to this embodiment, an acceptable infection risk value is set in advance, and the corresponding virus quanta concentration is calculated as the target quanta concentration. Equation (7) is given as an equation for evaluating the infection risk from the quanta concentration, and this is transformed to obtain equation (8). By using equation (8), the target quanta concentration can be calculated from a pre-set acceptable infection risk value.

[0072] P0 = 1 - exp(-q t pT × (1-ε SPFM )) (7)

[0073] q t = -log(1-P0) / (pT×(1-ε SPFM )) (8)

[0074] Here, P0 is the acceptable infection risk level (%), q t is the target quanta concentration, and p is the respiratory rate of the person entering the room (m). 3 / h), T is the time spent in the hospital room (h), ε SPFM This represents the attenuation rate (capture rate) (%) of the masks of those entering the room.

[0075] Next, with reference to Figure 4, the patient room information database 13B according to this embodiment will be described. Figure 4 is a schematic diagram showing an example of the configuration of the patient room information database 13B according to this embodiment.

[0076] As shown in Figure 4, the hospital room information database 13B according to this embodiment stores information such as hospital room ID (Identification), volume, and infected person information.

[0077] The above-mentioned room ID is information pre-set to be unique to each of the 80 rooms in the hospital, and the above-mentioned volume is information indicating the volume of the corresponding room 80. In addition, the above-mentioned infected person information is information about infected people hospitalized in the corresponding room, and includes information on the number of people, respiratory volume, and quanta generation amount.

[0078] The above number indicates the number of infected patients (hereinafter referred to as "hospitalized infected patients") admitted to the corresponding hospital room 80, the above respiratory volume indicates the respiratory volume per unit time and per person by hospitalized infected patients, and the above quanta generation indicates the amount of quanta generated by hospitalized infected patients as described above.

[0079] Next, with reference to Figure 5, the entry information database 13C according to this embodiment will be described. Figure 5 is a schematic diagram showing an example of the configuration of the entry information database 13C according to this embodiment.

[0080] As shown in Figure 5, the admission information database 13C according to this embodiment stores information such as the date, room ID, patient ID, respiratory rate, scheduled admission time, and length of stay, with these information associated with each other.

[0081] The above schedule indicates the dates on which a patient can enter room 80 at the target hospital, and the above room ID is the same as the room ID in the room information database 13B. In addition, the above patient ID is information that is set in advance to be different for each patient in order to identify each patient individually, the above respiratory rate indicates the respiratory rate per unit time of the corresponding patient, the above scheduled entry time indicates the time when the corresponding patient is scheduled to enter the corresponding room 80, and the above stay time indicates the time when the corresponding patient is scheduled to stay in the corresponding room 80 from the corresponding scheduled entry time.

[0082] In the example shown in Figure 5, on October 1, 2024, in room 80 with room ID "HR001", the resident ID was "A001", and the respiratory rate was 0.54 (m³). 3 An example is given where information is registered indicating that a person entering the room ( / h) will stay for 10 minutes starting at 9:00.

[0083] Next, the operation of the control device 10 according to this embodiment will be explained with reference to Figures 6 to 9. Figure 6 is a flowchart showing an example of the control process flow according to this embodiment. This control process is initiated when the control device 10 executes the control program 13A when a predetermined time (10 minutes before in this embodiment) arrives before the scheduled time of entry of any patient into any of the hospital rooms 80 (hereinafter referred to as the "target room") as indicated by the hospital room information database 13C. To avoid confusion, this explanation will describe a case where the ventilation capacity of the ventilation equipment to be controlled can be selectively set to one of three levels: strong operation, medium operation, and weak operation. Furthermore, this explanation will describe a case where, in each hospital room 80, if there are no patients present, the ventilation equipment is subjected to the normal ventilation control described above (weak operation in this embodiment).

[0084] In step 100, as shown in Figure 6, the CPU 11 reads all information corresponding to the target room from the patient room information database 13B. Also in step 100, the CPU 11 reads all information corresponding to the day's schedule and the target room from the admission information database 13C.

[0085] In step 102, the CPU 11 controls the display unit 15 to display a condition setting screen with a predetermined configuration, and in step 104, the CPU 11 waits until predetermined information is entered.

[0086] Figure 7 shows an example of the condition setting screen according to this embodiment. As shown in Figure 7, the condition setting screen according to this embodiment displays a message prompting the user to input conditions, and also displays a first input area 15A for inputting the attenuation rate of masks used by infected patients and entrants hospitalized in the target room. Furthermore, the condition setting screen according to this embodiment displays a second input area 15B for inputting the number of ventilations per unit time for each of the three operating stages of the ventilation equipment when performing the entry control described above. In addition, the condition setting screen according to this embodiment displays a third input area 15C for inputting an acceptable infection risk value.

[0087] When the condition setting screen shown in Figure 7 is displayed, the user of the control device 10 (hereinafter simply referred to as "user") inputs the mask attenuation rate, the number of ventilations per unit time, and the acceptable infection risk value into the corresponding input areas of the first input area 15A, the second input area 15B, and the third input area 15C, and then specifies the exit button 15D via the input unit 14. When the user specifies the exit button 15D, step 104 becomes a positive determination and proceeds to step 106.

[0088] In step 106, the CPU 11 uses the values ​​obtained from the above process to calculate the target quanta concentration q using equation (8) described above. t Calculate.

[0089] In step 108, the CPU 11 uses the values ​​obtained through the above processing to calculate the quanta concentration q(t+Δt) after Δt (1 minute in this embodiment) using equation (6) described above.

[0090] In step 110, CPU 11 determines that the calculated quanta concentration q(t+Δt) is equal to the calculated target quanta concentration q t The system determines whether the following conditions are met. If the result is positive, the control process terminates; otherwise, it proceeds to step 112.

[0091] In step 112, the CPU 11 controls the electronic lock installed in the target room to be locked.

[0092] In step 114, CPU 11 sets the quanta concentration q(t+Δt) to the target quanta concentration q t The following operating states of the ventilation equipment are derived using room entry control. In this embodiment, these operating states are derived by applying the ventilation rates for strong, medium, and weak operation obtained via the condition setting screen, and by matching them to a predetermined ventilation pattern for each number of patients in the target room.

[0093] In step 116, CPU 11 calculates the quanta concentration q(t+Δt) and the target quanta concentration q t From the difference, the quanta concentration q(t+Δt) when the entry response control is performed is the target quanta concentration q t The time until the following conditions are met is derived as the waiting time for those entering the room.

[0094] In step 118, the CPU 11 uses the above-mentioned waiting time to control the patient room display device to display a predetermined entry restriction notification screen.

[0095] Figure 8 shows an example of the entry restriction notification screen according to this embodiment. As shown in Figure 8, the entry restriction notification screen according to this embodiment displays a message indicating that entry will be temporarily unavailable, the current Quanta concentration status, and the calculated waiting time (in the example shown in Figure 8, it is displayed as "Estimated time until entry is possible"). Therefore, the user can grasp this information.

[0096] In step 120, the CPU 11 switches the control of the ventilation equipment for the target room from normal ventilation control to the derived entry-response control.

[0097] In this embodiment, the entry control system performs the following step-by-step control as an example of ventilation equipment control.

[0098] First, the ventilation system in the target room is set to high operation, and the quanta concentration q(t+Δt) is set to the target quanta concentration q t A lower threshold value (in this embodiment, the target quanta concentration q) is set to a smaller value. t If the value falls below 80% of the specified value, it switches to medium operation.

[0099] Next, the medium-speed operation is continued until the quanta concentration q(t+Δt) reaches the target quanta concentration q t Switch to high speed before it exceeds that level.

[0100] Next, the system is operated at high power, and when the quanta concentration q(t+Δt) falls below the lower threshold mentioned above, it is switched to medium power. From this point onward, the control of switching the operation of the ventilation equipment described above is repeated.

[0101] In this example, the entry-response control involves switching the ventilation system between high and medium operation, but this is not the only configuration. For example, if the ventilation system is switched from low operation to medium operation immediately before the entry-response control is performed, the quanta concentration q(t+Δt) will reach the target quanta concentration q tThe system determines whether the following conditions are met. If the determination is positive, the ventilation system is switched to medium operation; only if the determination is negative, the system switches between high and medium operation as described above.

[0102] In step 122, the CPU 11 waits until the waiting time has elapsed. In step 124, the CPU 11 controls the electronic lock installed in the target room to lock, and in step 126, the CPU 11 updates the display content of the entry restriction notification screen.

[0103] Figure 9 shows an example of the updated state of the entry restriction notification screen according to this embodiment. As shown in Figure 9, the updated entry restriction notification screen according to this embodiment displays a message indicating that entry is now permitted. Therefore, by referring to the updated entry restriction notification screen, the user can understand that entry is now permitted and enter the target room.

[0104] In step 128, the CPU 11 waits until the corresponding stay time has elapsed, waiting until the person entering the room leaves the room. In step 130, the CPU 11 switches to normal ventilation control for the ventilation equipment in the room, and then terminates this control process.

[0105] Here, we will describe a specific embodiment of the control process described above, as provided by the inventors of the technology of this disclosure. First, the conditions applied in this embodiment are as follows.

[0106] The volume V of the room in question is 100 (m³). 3 ) Furthermore, it is assumed that the ventilation equipment in question has three operating states: high, medium, and low. For each operating state, the ventilation rate in high operation is 12 times / h (= ventilation volume of 1200 m³). 3 The ventilation rate is set to 4 times / h (= ventilation volume of 400m³) during medium operation. 3 The ventilation rate is set to 2 times / h (= ventilation volume of 200m³) in low-power operation. 3 Let's use / h).

[0107] We will consider four cases, with one infected person in Case 1, two in Case 2, three in Case 3, and four in Case 4. In other words, we will assume a common four-bed room in each case, with one to four patients hospitalized in that room.

[0108] Furthermore, as a parameter related to infected individuals, the attenuation rate ε of the mask being worn was used. IPFM Set the percentage to 65% and the respiratory volume P to 0.54(m 3 Let the amount of quanta generated corresponding to the infection be 20 (quanta), and set the amount of quanta generated q to 20 (q / h).

[0109] Furthermore, assuming a resident's stay time T is 0.5 (h) and a respiratory rate P is 0.54 (m), 3 Let ε be the decay rate of the mask worn by the person entering the room ( / h). SPFM Let's assume it's 99%.

[0110] Furthermore, the predetermined acceptable infection risk level is set at 0.015% or less per entry into a patient's room (30 minutes).

[0111] Under the above conditions, first, the target quanta concentration is calculated from the predetermined acceptable infection risk value. Equation (8) is modified to obtain equation (9) by setting the above parameters. From this equation (9), the target quanta concentration q t This is calculated to be 0.055. Based on this result, the target quanta concentration q t Let this be 0.05 (quanta).

[0112] q t =-log(1-0.00015) / (0.54×0.5×(1-0.99)) (9)

[0113] Next, input the set parameters into equation (6), and the quanta concentration q(t) calculated from equation (6) is the target quanta concentration q tThe operating conditions are derived so that the value does not exceed 0.05. The operating conditions applied to each of Cases 1 to 4 are shown in Table 1. That is, as shown in Table 1, the more patients there are in the hospital room, the longer the period of high-power operation becomes.

[0114] [Table 1]

[0115] For each of the ventilation equipment controls described above, the predicted quanta concentration is as shown in Figure 10. It can be confirmed that in all cases, the quanta concentration is below the target quanta concentration of 0.05 during the 0 to 0.5 hours before the patient enters the room. In the example shown in Figure 10, in Case 1, since there is only one inpatient, the quanta concentration is always below the target quanta concentration, and there is no need to switch from normal ventilation control to admission-responsive control. In the example shown in Figure 10, time 0 (zero) represents the time when the patient enters the room.

[0116] As shown in Figure 10, it has been confirmed that, with the technology of this disclosure, for at least four-bed rooms, the risk of infection for patients entering the room can be reasonably reduced simply by switching the operating state of the ventilation system a few minutes before the patient enters the room, depending on the number of inpatients.

[0117] In the above embodiment, the amount of quanta generated (virus production) by the infected person is kept constant, but it is also possible to change it according to the infected person's activity level (sleeping, resting, speaking) and control the operation of the ventilation system accordingly.

[0118] The following are two other examples of specific ventilation equipment control methods using the technology of this disclosure.

[0119] • Example 1: When the nurse call button is pressed or the door open / close switch for the patient's room is activated, the ventilation system's operating status is changed to high, and a display is placed at the room entrance indicating the extent to which the risk of infection has been reduced compared to when the system was operating at low.

[0120] • Second example: Depending on the activity level of the infected person, especially considering that the amount of virus produced decreases during sleep, the ventilation system should be controlled to operate at a low setting.

[0121] As described above, according to this embodiment, an index is obtained that corresponds to the ventilation rate of the target room and allows for the prediction of changes over time due to changes in the ventilation rate. If the index does not meet a predetermined standard value at the time when a person attempts to enter the target room, the ventilation rate is increased and control is performed to restrict the person from entering the room. Therefore, since this control can be performed using the predicted subsequent index, the risk of infection can be reduced more simply and effectively.

[0122] Furthermore, according to this embodiment, a predicted value of the time-dependent change in an indicator corresponding to the control of ventilation volume is obtained, and after a waiting period has elapsed until the predicted value satisfies the standard value, control is performed to lift the restriction on the person entering the target room. Therefore, the risk of infection can be reduced more reliably.

[0123] Furthermore, according to this embodiment, when switching between an entry-response control, which controls the ventilation volume so that the indicator satisfies a standard value during the first period when the subject stays in the target room, and a normal ventilation control, which controls the ventilation volume to be lower than that during the second period excluding the first period, the control switches from normal ventilation control to entry-response control when the subject is about to enter the target room, and switches from entry-response control to normal ventilation control when the subject leaves the target room. Therefore, the risk of infection during the subject's stay in the target room can be reduced more simply and effectively.

[0124] Furthermore, according to this embodiment, the indicator is the quanta concentration. Therefore, when using the quanta concentration as an indicator, the risk of infection can be reduced more simply and effectively.

[0125] Furthermore, according to this embodiment, a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate is extended to an extended model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward. By applying the acquired index to this extended model, infection risk information indicating the infection risk of the target room from the present time onward is derived, and control is performed to suppress the infection risk of the target person in the target room using the derived infection risk information. As a result, since this control can be performed using infection risk information from the present time onward, the future infection risk can be reduced more simply and effectively.

[0126] Furthermore, according to this embodiment, the steady-state evaluation model is the Wells-Riley model. Therefore, when using the Wells-Riley model as the steady-state evaluation model, the risk of infection can be reduced more simply and effectively.

[0127] Furthermore, according to this embodiment, the extended model is obtained by applying numerical integration over a small time interval to the Wells-Riley model. Therefore, the extended model can be obtained more easily.

[0128] Furthermore, according to this embodiment, at least one of the following controls is performed to suppress the risk of infection: control of opening and closing of entrances and exits in the target room, control of ventilation volume, and control of presenting information about the risk of infection to the target person. Therefore, depending on the control applied, the risk of future infection can be reduced more simply and effectively.

[0129] In the above embodiment, the case in which the infection risk suppression support device of the disclosed technology is applied to a control device 10 configured as a single device has been described, but the invention is not limited to this. For example, the infection risk suppression support device of the disclosed technology may be configured by multiple devices.

[0130] An example of this configuration is one in which at least one of the control program 13A, the patient room information database 13B, and the admission information database 13C is registered on an external server or other device different from the control device 10, and the control program 13A is executed by the control device 10. Alternatively, a single control program 13A may be divided into multiple sub-processes and processed in a distributed manner by multiple devices.

[0131] Furthermore, while the above embodiment describes a case where the timing of a person's entry and exit is determined using the scheduled entry time and length of stay registered in the entry information database 13C, it is not limited to this. For example, the timing of a person's entry and exit may be determined using the location tracking function of a mobile device carried by the person. Alternatively, the timing of a person's entry and exit may be determined in conjunction with a nurse call, or an open / close button may be provided on the door of the patient room 80, and the timing of a person's entry and exit may be determined in conjunction with the pressing operation of the open / close button. Moreover, a motion sensor may be provided on the door of the patient room 80, and the timing of a person's entry and exit may be determined in conjunction with the detection result from the motion sensor, or a combination of multiple of these forms may be applied.

[0132] Furthermore, in the above embodiment, we have described a case in which a control is applied to prevent a person from entering the patient room 80 by locking the electronic lock on the patient room 80 and displaying a message indicating that entry is not permitted, but this is not the only possible configuration. For example, only one of these controls may be applied as a control to prevent a person from entering the patient room 80. Alternatively, the door to the patient room 80 may be an automatic door, and a control that prevents the automatic door from opening may be applied as a control to prevent a person from entering the patient room 80.

[0133] Furthermore, although the above embodiment describes a case in which the number of patients hospitalized in room 80 is pre-registered in the room information database 13B, it is not limited to this. For example, the number may be entered by the user via the input unit 14 of the control device 10, or the number of patients present in room 80 may be counted using a monitoring system with a camera or the like.

[0134] Furthermore, although the above embodiment describes a scenario where all hospitalized patients and entrants are wearing masks, it is not limited to this. For example, the mask-wearing status of at least one of the hospitalized patients and entrants may be detected using a conventionally known mask detection technique, and the detection result of the mask-wearing status may be reflected in the infection risk value.

[0135] Furthermore, the respiratory volume and viral concentration of hospitalized patients vary depending on the patient's condition (e.g., when waking up, when going to sleep, and whether they are wearing a mask). For this reason, for example, the patient's condition may be reflected in the infection risk value.

[0136] Furthermore, while the above embodiment describes a case where ventilation is performed by increasing the amount of outside air, it is not limited to this. For example, instead of increasing the amount of outside air, the equivalent ventilation volume may be increased by an air purification system using a high-performance filter, or both increasing the amount of outside air and increasing the equivalent ventilation volume by an air purification system may be used in combination. This configuration can shorten the time until a patient can enter the hospital room. Examples of prior art documents relating to this technology include "Kurabuchi, Tokyo University of Science: Rethinking Ventilation Design as an Infection Control Measure, 2021" and "Obuchi: Risk Assessment of Airborne Infection of COVID-19 Targeting Medical Facilities, Architectural Institute of Japan Convention, 2022".

[0137] Furthermore, the configuration of the hospital equipment 70 exemplified in the above embodiment is not limited to that shown in Figure 2. Figures 11 to 17 show other examples of the configuration of the hospital equipment 70 according to the above embodiment.

[0138] The hospital equipment 70 shown in Figures 11 to 13 is an example of a hospital equipment configuration 70 when the ventilation capacity of the hospital equipment 70 shown in Figure 2 is insufficient depending on the volume of the target room. Here, the example shown in Figure 11 is an example in which two air handling units 78 are used, while the examples shown in Figures 12 and 13 are examples in which only one air handling unit 78 is used, but two exhaust fans 79 are used. Furthermore, in the example shown in Figure 12, the air from the air handling unit 78 is supplied to both the patient room 80 and the corridor 82, whereas in the example shown in Figure 13, the air from the air handling unit 78 is supplied only to the corridor 82.

[0139] On the other hand, Figures 14 and 15 show examples of hospital equipment configurations for hospital equipment 70, focusing on the case where ventilation control is performed for a single patient room 80. Here, the example shown in Figure 14 is a configuration example for negative pressure ventilation when supplying air to both the patient room 80 and the corridor 82, while the example shown in Figure 15 is a configuration example for negative pressure ventilation when supplying air only to the corridor 82.

[0140] Furthermore, Figures 16 and 17 show examples of hospital equipment configurations where an operating panel is provided on the outside of each patient room 80 to operate when opening and closing the door. Here, Figure 16 shows an example configuration where an operating panel is provided for each patient room 80, while Figure 17 shows an example configuration where an operating panel is provided near a door leading to a corridor 82 common to multiple patient rooms 80. In the examples shown in Figures 16 and 17, a changing area partitioned by a curtain is provided, and it is possible to change into protective clothing to further protect against infection in this changing area.

[0141] In these examples, the control panel may be equipped with a button that is pressed when opening or closing the door, and the system may switch from normal ventilation control to room entry control when this button is pressed. Alternatively, the control panel may be equipped with the aforementioned room entry display device, and the room entry restriction display screen (see also Figures 8 and 9) may be displayed.

[0142] Other examples of ventilation system technologies by the applicant of the technology disclosed herein include the technology disclosed in Japanese Patent Publication No. 2023-132970.

[0143] Furthermore, in the above embodiment, for example, the hardware structure of the processing unit that executes the acquisition unit 11A, the derivation unit 11B, and the control unit 11C can be any of the following types of processors. As mentioned above, these types of processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as programmable logic devices (PLDs), such as FPGAs (Field-Programmable Gate Arrays), which are processors whose circuit configuration can be changed after manufacturing, and dedicated electrical circuits, such as ASICs (Application Specific Integrated Circuits), which are processors with circuit configurations specifically designed to execute specific processes.

[0144] The processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the processing unit may consist of a single processor.

[0145] Examples of configuring a processing unit with a single processor include, firstly, a configuration where one or more CPUs and software combine to form a single processor, as is common in client and server computers, and this processor functions as the processing unit. Secondly, a configuration using a processor that realizes the functions of the entire system, including the processing unit, on a single IC (Integrated Circuit) chip, as is common in System-on-a-Chip (SoC) systems. Thus, the processing unit is configured, in terms of hardware structure, using one or more of the above-mentioned types of processors.

[0146] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.

[0147] The following additional information is disclosed regarding the above-described embodiments.

[0148] [Note 1] An acquisition unit that acquires an index corresponding to the ventilation rate of the target room and that allows for the prediction of changes over time due to changes in the ventilation rate, An extended model, which expands a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate, to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, is used to derive infection risk information indicating the infection risk of the target room from the present time onward by applying the index acquired by the acquisition unit to the extended model, and A control unit that uses the infection risk information derived by the derivation unit to perform control to suppress the infection risk of the subject in the subject room, An infection risk reduction support device equipped with the following features. [Note 2] The aforementioned indicator is the quanta concentration. The infection risk suppression support device described in Appendix 1. [Note 3] The aforementioned steady-state evaluation model is the Wells-Riley model. An infection risk suppression support device as described in Appendix 1 or Appendix 2. [Note 4] The aforementioned extended model is This model was obtained by applying numerical integration over a small time interval to the aforementioned Wells-Riley model. The infection risk suppression support device described in Appendix 3. [Note 5] The control unit performs at least one of the following controls to suppress the risk of infection: control of opening and closing of entrances and exits in the target room, control of the ventilation volume, and control of presenting information regarding the risk of infection to the target person. An infection risk suppression support device as described in any one of the appendices 1 through 4. [Note 6] An index is obtained that corresponds to the ventilation rate of the target room and allows for the prediction of changes over time due to changes in said ventilation rate. By applying the acquired index to an extended model, which is an extension of a steady-state assessment model that can evaluate the steady-state infection risk in a room according to the ventilation rate, to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, infection risk information indicating the infection risk of the target room from the present time onward is derived. Using the derived infection risk information, controls are implemented to suppress the risk of infection for the subject in the aforementioned room. A program that helps reduce the risk of infection by having a computer perform the processing. [Explanation of Symbols]

[0149] 10 Control device 11 CPU 11A Acquisition Department 11B Derivation part 11C Control Unit 12 memory 13 Storage section 13A Control Program 13B Patient Room Information Database 13C Room Entry Information Database 14 Input section 15 Display section 15A First Input Area 15B Second Input Area 15C Third Input Area 15D Exit button 16. Media reading / writing device 17 Recording media 18 Communication I / F Section 60 Networks 70 Hospital facilities 72, 72A, 72B Individual air conditioners 74, 74A, 74B, 74C, 74D Air supply port 76, 76A, 76B exhaust port 78 Outside control machine 79 Exhaust fan Rooms 80, 80A, and 80B Corridors 82, 82A, 82B 84A, 84B through hole 90 Control Systems

Claims

1. An acquisition unit that acquires an index corresponding to the ventilation rate of the target room and that allows for the prediction of changes over time due to changes in the ventilation rate, An extended model, which expands a steady-state evaluation model that can evaluate the steady-state infection risk in a room according to the ventilation rate, to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, is used to derive infection risk information indicating the infection risk of the target room from the present time onward by applying the index acquired by the acquisition unit to the extended model, and A control unit that uses the infection risk information derived by the derivation unit to perform control to suppress the infection risk of the subject in the subject room, An infection risk reduction support device equipped with the following features.

2. The aforementioned indicator is the quanta concentration. The infection risk suppression support device according to claim 1.

3. The aforementioned steady-state evaluation model is the Wells-Riley model. The infection risk suppression support device according to claim 1 or claim 2.

4. The aforementioned extended model is This model was obtained by applying numerical integration over a small time interval to the aforementioned Wells-Riley model. The infection risk suppression support device according to claim 3.

5. The control unit performs at least one of the following controls to suppress the risk of infection: control of opening and closing of entrances and exits in the target room, control of the ventilation volume, and control of presenting information regarding the risk of infection to the target person. The infection risk suppression support device according to claim 1 or claim 2.

6. An index is obtained that corresponds to the ventilation rate of the target room and allows for the prediction of changes over time due to changes in said ventilation rate. By applying the acquired index to an extended model, which is an extension of a steady-state assessment model that can evaluate the steady-state infection risk in a room according to the ventilation rate, to a model that can evaluate the infection risk according to the non-steady-state changing ventilation rate from the present time onward, infection risk information indicating the infection risk of the target room from the present time onward is derived. Using the derived infection risk information, controls are implemented to suppress the risk of infection for the subject in the aforementioned room. A program that helps reduce the risk of infection by having a computer perform the processing.

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