JP6967329B1 - Infection risk quantification system and infection risk quantification method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system or a method for probabilistically quantifying an infection risk by incorporating epidemiological data including a community-acquired infection status as input information in addition to environmental data measured in a facility. SOLUTION: The method of the present invention is a step S1 of measuring the CO2 concentration outside the facility while measuring the CO2 concentration in the section, and a step S2 of acquiring infectious disease epidemic information of the area to which the facility belongs from an epidemiological data browsing site. And step S6 for deriving the infection probability P in the compartment at any time using a mathematical model. The method of the present invention preferably includes step S5 of determining the alarm threshold TA for determining the safety level of the compartment using a mathematical model. Further, in order to change the operation status of the equipment by using the mathematical model and the step S3 of arranging the equipment monitoring control unit equipped with at least one equipment for adjusting the air environment in the section and checking the operation status of the equipment. It is preferable to further include the device control threshold determination step S5 for determining the device control threshold TD. [Selection diagram] Fig. 2

Description

The present invention relates to a system and a method for quantifying the risk of droplet nuclei and droplet infection inside a building of a facility such as a hospital. More specifically, it relates to a system and a method for quantifying the infection risk while measuring the status of infection contributing factors inside the building in real time while taking into account the status of community-acquired infection.

In addition to the coronavirus that has become prevalent in recent years, humankind has been threatened by infectious diseases such as influenza virus, measles virus, and tuberculosis bacterium. Since the pathogens that cause these infectious diseases are so small that they are invisible, nosocomial infections frequently occur in hospitals where the infectious diseases should be treated. Under these circumstances, it is desired to quantify the infection risk in real time for each specific section in a facility such as a hospital and notify the medical staff.

(Patent Document 1 as Prior Art)
As a prior art corresponding to the above request, for example, Patent Document 1 discloses an in-facility monitoring system. In the system described in Patent Document 1, the environmental parameters (temperature, humidity, etc.) in the facility are monitored, the risk of occurrence of each infectious disease in each section (hospital room) is acquired, and the caution notification display data is displayed on the PC of the nurse station. It can be sent to a mobile terminal or a mobile terminal to display and warn of a room at risk of a specific infectious disease.

(Technical Issues in Patent Document 1)
However, the system described in Patent Document 1 only measures environmental parameters such as temperature and humidity in the facility (more specifically, each hospital room). In addition, when evaluating the risk of infection, only a threshold value for determining whether each environmental parameter being measured belongs to the "reference range", "need attention", or "warning" is arbitrarily set. (Refer to FIG. 16 of Patent Document 1), the setting of each threshold value does not reflect the epidemiological guideline by a public institution such as WHO. That is, the judgment by the system (evaluation of whether it is within the reference range or whether it requires attention) largely depends on the subjectivity of the system provider or the medical staff who operates the system.

In addition, the system described in Patent Document 1 only uses the environmental parameters in the facility to be measured when evaluating the infection risk, and does not reflect the influence of the ever-changing community-acquired infection status outside the facility. For example, in the case of influenza, the risk of infection varies depending on the season, and it is desirable that the status of community-acquired infections outside the facility be reflected in the assessment of the risk of infection.

Further, the system described in Patent Document 1 merely monitors changes in environmental parameters when evaluating an infection risk, and does not quantitatively derive an infection probability.

(Examples of mathematical models for estimating the risk of airborne infection in Non-Patent Documents 1 and 2)
The Wells-Riley model is known as a mathematical model for estimating the risk of airborne infection. This mathematical model was obtained from the experimental results (see Non-Patent Document 1) that the infection probability of M. tuberculosis follows the Poisson process. Further, a Rudnick and Milton model disclosed in Non-Patent Document 2 which is an improvement of the Wells-Riley model is also known.

(Patent Document 2 as Prior Art)
Further, in the influenza prediction display device described in Patent Document 2, the outside air temperature and the outside air humidity are measured by a sensor in order to predict the influenza epidemic, and the water vapor pressure and the like are calculated based on these measured values to cause an epidemic (danger). Degree) is determined. Then, the prediction result can be displayed by a display unit such as an LED notification means, or the humidification operation can be driven by the humidification unit.

(Technical Issues in Patent Document 2)
However, although the device described in Patent Document 2 measures the environmental parameters outside the facility, it does not measure the environmental parameters inside the facility (for example, each section (each hospital room) in the facility). Further, in the apparatus described in Patent Document 2, the temperature and relative humidity actually measured from each sensor, and the fluctuation of the absolute humidity and the water vapor pressure calculated from these actually measured values are monitored, and when the threshold value arbitrarily set in advance is exceeded. , It is judged from "low risk" to "medium risk" or "high risk".

Therefore, the device described in Patent Document 2 does not reflect any epidemiological guidelines by a public institution such as WHO when setting each threshold value, as in the technique described in Patent Document 1. It does not quantify the risk of infection stochastically. Furthermore, it does not quantify the risk of infection while monitoring the environmental parameters in the facility while taking into account the status of infection in the city.

(Patent Document 3 as Prior Art)
Further, in the information providing system described in Patent Document 3, a plurality of pathogen detection devices (specifically, virus sensors) are used to detect pathogens in the air in public transportation stations and vehicles, and the detection results (specifically, pathogens). The user can determine the transportation route to the station based on the risk of infection with pathogens).

(Technical Issues in Patent Document 3)
However, although it is said that the virus concentration is measured by a virus sensor, there is no device that can measure many virus concentrations such as coronavirus in a realistic and real-time manner.

Further, the system described in Patent Document 3 does not reflect any epidemiological guidelines by public institutions such as WHO when setting each threshold value, as in the techniques described in Patent Documents 1 and 2. Nor is it a probabilistic quantification of infection risk.

Further, in the system described in Patent Document 3, it is also described that influenza pandemic information is acquired from the National Institute of Infectious Diseases and local governments as an environmental information database and used for evaluation of infection risk information. However, as shown in FIG. 4, the acquired influenza pandemic information is only classified into three stages of "none", "caution" and "alarm" according to arbitrary criteria.

In other words, only the information indicating which of the three stages the current epidemic level has been acquired is used for the subsequent evaluation of infection risk information, and the measured value of the epidemic level (patients in each region). The number) is not input as it is as one of the parameters of the mathematical model to evaluate and quantify the infection risk information.

Japanese Unexamined Patent Publication No. 2019-07913 Japanese Unexamined Patent Publication No. 2004-270998 Japanese Unexamined Patent Publication No. 2020-00869

W. F. Wells, Airborne Connection and Air Hygiene (An Ecological Study of Droplet Infections), Harvard University Press, Cambridge, 1955. Rudnik SN, Milton DK, Risk of indoor airborne infection transmission transmission setimated from carbon carbon Dioxide connection, Indicator Air, 237-45, 2003

(Purpose of the present invention)
The present invention has been made in view of such circumstances, and in addition to the environmental data measured in the facility, epidemiological data including the community-acquired infection status is used as input information (input parameter used in the mathematical model). The purpose is to provide a method and system for incorporating and centralizing and probabilistically quantifying the risk of infection.

Another object of the present invention is to set a threshold value for determining the risk of infection in a certain section (for example, evaluation of safety, caution, or danger) by a public organization such as WHO. To provide an infection risk quantification method and its system to which the epidemiological guidelines and criteria can be directly applied.

Further, another object of the present invention is to set an epidemiological guideline / standard by a public institution such as WHO for setting a threshold value for changing the operating condition of a device for adjusting the air environment in a certain section. It is to provide an infection risk quantification method and a system thereof that can be directly applied and enables automatic control of the operation of these devices.

After diligent studies, the present inventors have found a novel system and method that can brilliantly solve the above-mentioned problems, and have completed the present invention.

ここで、Ｃ_ｉは前記区画内の前記ＣＯ_２濃度であり、Ｃ_ｏは前記施設外の前記ＣＯ_２濃度（但し、前記区画内ＣＯ_２濃度が夜間に前記施設外の前記ＣＯ_２濃度の値まで下がる場合は、前記区画内ＣＯ_２濃度の前記夜間の前記値で代用可能）であり、Ｃ_ａは人の呼気で発生するＣＯ_２濃度の割合（Ｃ_ａ＝０．０３８）であり、Ｆは前記感染症の前記地域における流行特性が前記施設内の在室者に与える影響因子であり、前記地域の全人口ｎ_ｔに対する前記感染者報告数ｎ_ｒの割合であり、ｑは前記感染症に感染した者の呼気による感染性粒子発生速度である、
ことを特徴とする感染リスク定量化方法。
（態様２）
前記数理モデルを用いて、前記区画の安全レベルを判断するための警報閾値Ｔ_Ａを少なくとも１つ決定する警報閾値決定工程を更に含み、かつ、
前記警報閾値決定工程は、
室内側環境基準Ｂ _１ を第１公的指針から算定する工程と、
疫学側環境基準Ｂ _２ を第２公的指針から算定する工程と、
前記基準Ｂ _１ ，Ｂ _２ を前記数理モデルに代入し、得られた感染確率Ｐを閾値根拠基準Ｂ _３ として設定する工程と、
前記基準Ｂ _３ を基に前記警報閾値Ｔ _Ａ を決定する工程と、
を含む、
ことを特徴とする態様１に記載の感染リスク定量化方法。
（態様３）
空気環境を整えるための少なくとも１つの機器を備えた機器監視制御部を前記区画内に配置して、前記機器の運転状況を確認する工程と、
前記数理モデルを用いて、前記機器の前記運転状況を変更するための機器制御閾値Ｔ_Ｄを少なくとも１つ決定する機器制御閾値決定工程と、
前記感染確率Ｐが前記機器制御閾値Ｔ_Ｄ未満であると判断されれば運転状態にある前記機器の数を減らす一方、前記感染確率Ｐが前記機器制御閾値Ｔ_Ｄ以上であると判断されれば運転状態にある前記機器の数を増やす機器運転変更工程と、
を更に含み、かつ、
前記機器制御閾値決定工程は、
室内側環境基準Ｂ _１ を第１公的指針から算定する工程と、
疫学側環境基準Ｂ _２ を第２公的指針から算定する工程と、
前記基準Ｂ _１ ，Ｂ _２ を前記数理モデルに代入し、得られた感染確率Ｐを閾値根拠基準Ｂ _３ として設定する工程と、
前記基準Ｂ _３ を基に前記機器制御閾値Ｔ _Ｄ を決定する工程と、
を含む、
ことを特徴とする態様１又は２に記載の感染リスク定量化方法。
（態様４）
前記数理モデルにより導出された感染確率Ｐをユーザが操作可能な端末に随時送信して、該端末の画面に表示可能にする、
ことを特徴とする態様１〜３のいずれかに記載の感染リスク定量化方法。
（態様５）
施設内の少なくとも１つの区画の感染リスクを評価する感染リスク定量化システムであって、
通信網に接続された通信部と記憶部と演算部とを備えたシステムサーバと、
前記通信網に直接又は間接的に接続され、かつ、前記区画内のＣＯ_２濃度を計測する室内環境センサと前記施設外のＣＯ_２濃度を計測する屋外環境センサとを備えた計測監視部と、
前記通信網に接続され、かつ、少なくとも１つの感染症に関する前記施設の属する地域の感染者報告数ｎ_ｒを随時蓄積する疫学データ閲覧サイトと、
を含み、かつ、
前記記憶部では、前記通信部を介して、前記計測監視部で取得されたＣＯ_２濃度と、前記疫学データ閲覧サイトで蓄積された前記感染者報告数ｎ_ｒを記憶し、
前記演算部では、前記記憶部で記憶された各ＣＯ_２濃度と、前記感染者報告数ｎ_ｒとを以下の数式の数理モデルに代入して、前記区画での感染確率Ｐを導出する、

ここで、Ｃ_ｉは前記区画内の前記ＣＯ_２濃度であり、Ｃ_ｏは前記施設外の前記ＣＯ_２濃度（但し、前記区画内ＣＯ_２濃度が夜間に前記施設外の前記ＣＯ_２濃度の値まで下がる場合は、前記区画内ＣＯ_２濃度の前記夜間の前記値で代用可能）であり、Ｃ_ａは人の呼気で発生するＣＯ_２濃度の割合（Ｃ_ａ＝０．０３８）であり、Ｆは前記感染症の前記地域における流行特性が前記施設内の在室者に与える影響因子であり、前記地域の全人口ｎ_ｔに対する前記感染者報告数ｎ_ｒの割合であり、ｑは前記感染症に感染した者の呼気による感染性粒子発生速度である、
ことを特徴とする感染リスク定量化システム。
（態様６）
前記システムサーバの前記演算部では、前記数理モデルを用いて、前記区画の安全レベルを判断するための警報閾値Ｔ_Ａを少なくとも１つ決定し、
前記システムサーバの前記記憶部では、前記警報閾値Ｔ_Ａを記憶し、かつ、
前記システムサーバの前記演算部は、
室内側環境基準Ｂ _１ を第１公的指針から算定し、
疫学側環境基準Ｂ _２ を第２公的指針から算定し、
前記基準Ｂ _１ ，Ｂ _２ を前記数理モデルに代入し、得られた感染確率Ｐを閾値根拠基準Ｂ _３ として設定し、かつ、
前記基準Ｂ _３ を基に前記警報閾値Ｔ _Ａ を決定する、
を含む、
ことを特徴とする態様５に記載の感染リスク定量化システム。
（態様７）
前記感染リスク定量化システムは、空気環境を整えるための少なくとも１つの機器を備えた機器監視制御部と、
を更に含み、かつ、
前記システムサーバの前記制御部では、前記機器の運転状況を確認し、
前記システムサーバの前記演算部では、前記数理モデルを用いて、前記機器の前記運転状況を変更するための機器制御閾値Ｔ_Ｄを少なくとも１つ決定し、
前記システムサーバの前記制御部は、前記感染確率Ｐが前記機器制御閾値Ｔ_Ｄ未満であると判断すれば運転状態にある前記機器の数を減らす一方、前記感染確率Ｐが前記機器制御閾値Ｔ_Ｄ以上であると判断すれば運転状態にある前記機器の数を増やし、かつ、
前記システムサーバの前記演算部は、
室内側環境基準Ｂ _１ を第１公的指針から算定し、
疫学側環境基準Ｂ _２ を第２公的指針から算定し、
前記基準Ｂ _１ ，Ｂ _２ を前記数理モデルに代入し、得られた感染確率Ｐを閾値根拠基準Ｂ _３ として設定し、かつ、
前記基準Ｂ _３ を基に前記機器制御閾値Ｔ _Ｄ を決定する、
を含む、
ことを特徴とする態様５又は６に記載の感染リスク定量化システム。
（態様８）
前記感染リスク定量化システムは前記通信網に接続されたユーザ操作端末を更に含み、
前記ユーザ操作端末は、前記システムサーバから、前記数理モデルにより導出された感染確率Ｐを随時受信して、該端末の画面に表示可能にする、
ことを特徴とする態様５〜７のいずれかに記載の感染リスク定量化システム。 That is, the present invention has, for example, the following configurations and features.
(Aspect 1)
An infection risk quantification method that assesses the risk of infection in at least one section of a facility.
A measurement process for measuring _{the CO 2} concentration outside the facility while measuring _{the CO 2} concentration inside the section.
The process of acquiring _{at least one infectious disease-related infectious person report number nr} in the area to which the facility belongs from the epidemiological data browsing site at any time.
The process of deriving the infection probability P in the section using a mathematical model at any time, and
Including and
The mathematical model can be obtained by the following mathematical formula.

Here, _{C i} is the CO ₂ concentration in the compartment, _{C o} is the outside the facility of the CO ₂ concentration (however, the CO ₂ concentration value of the facility outside the compartment CO ₂ concentration at night when down to is substitutable) by the value of the nighttime said compartment CO ₂ concentration, _{C a} is the fraction of CO ₂ concentration that occurs in human breath _(C a = 0.038), F is the impact factor is epidemic characteristics in the area of the infection is given to the occupants of the facility, it is the proportion of the infected people report the number n _r with respect to the total population n _t of the region, q is the infectious diseases The rate of infectious particle generation due to the exhaled breath of a person infected with
A method for quantifying infection risk.
(Aspect 2)
Using said mathematical model, further saw including an alarm threshold determination step of determining at least one alarm thresholds T _A for determining the safety level of the partition, and,
The alarm threshold determination step is
A step of calculating the indoor environmental standards B ₁ from the first public hands,
A step of calculating the epidemiological side environmental standards B ₂ from the second public hands,
A step _{of substituting the criteria B 1} and B ₂ into the mathematical model and setting the obtained infection probability P as the threshold basis criterion B _3;
And determining the alarm threshold T _A on the basis of the reference B _3,
including,
The method for quantifying an infection risk according to the first aspect.
(Aspect 3)
A process of arranging a device monitoring control unit equipped with at least one device for adjusting the air environment in the section and confirming the operating status of the device, and a process of confirming the operation status of the device.
Using said mathematical model, the device control threshold value determining step of determining at least one device control threshold T _D for changing the operating conditions of the device,
While the infection probability P reduces the number of the devices in the operation state when it is determined to be less than the device control threshold T _D, if it is determined that the probability of infection P is the device control threshold T _D or A device operation change process that increases the number of the devices in operation, and
Further only it contains, and,
The device control threshold determination step is
A step of calculating the indoor environmental standards B ₁ from the first public hands,
A step of calculating the epidemiological side environmental standards B ₂ from the second public hands,
A step _{of substituting the criteria B 1} and B ₂ into the mathematical model and setting the obtained infection probability P as the threshold basis criterion B _3;
The step of determining the device control threshold value T _D based on the reference B _{3 and}
including,
The method for quantifying infection risk according to aspect 1 or 2, wherein the method is characterized by the above.
(Aspect 4)
The infection probability P derived by the mathematical model is transmitted to a terminal that can be operated by the user at any time so that the infection probability P can be displayed on the screen of the terminal.
The method for quantifying an infection risk according to any one of aspects 1 to 3 , wherein the method is characterized by the above.
(Aspect 5)
An infection risk quantification system that assesses the risk of infection in at least one compartment within a facility.
A system server equipped with a communication unit, a storage unit, and an arithmetic unit connected to a communication network,
A measurement monitoring unit that is directly or indirectly connected to the communication network and includes an indoor environment sensor that measures _{the CO 2} concentration in the compartment and an outdoor environment sensor that measures _{the CO 2 concentration outside the facility.}
Connected to the communication network, and the epidemiological data browsing sites for storing at any time infected persons reported number n _r of the area belongs the facility for at least one infection,
Including and
_{The storage unit stores the CO 2} concentration acquired by the measurement and monitoring unit and the _{number of reported infected persons nr} accumulated at the epidemiological data browsing site via the communication unit.
In the calculation unit, each CO ₂ concentration stored in the storage unit and the number of reported infected persons _nr are substituted into the mathematical model of the following mathematical formula to derive the infection probability P in the section.

Here, _{C i} is the CO ₂ concentration in the compartment, _{C o} is the outside the facility of the CO ₂ concentration (however, the CO ₂ concentration value of the facility outside the compartment CO ₂ concentration at night when down to is substitutable) by the value of the nighttime said compartment CO ₂ concentration, _{C a} is the fraction of CO ₂ concentration that occurs in human breath _(C a = 0.038), F is the impact factor is epidemic characteristics in the area of the infection is given to the occupants of the facility, it is the proportion of the infected people report the number n _r with respect to the total population n _t of the region, q is the infectious diseases The rate of infectious particle generation due to the exhaled breath of a person infected with
An infection risk quantification system characterized by this.
(Aspect 6)
In the arithmetic unit of the system server, using said mathematical model, the alarm threshold value T _A for determining the safety level of the compartment to determine at least one,
In the storage unit of the system server, storing the alarm threshold T _A, and
The arithmetic unit of the system server
Calculate the indoor environmental standard B ₁ from the first public guideline,
The epidemiology side environmental standards B ₂ calculated from the second public hands,
The criteria B ₁ and B ₂ are substituted into the mathematical model, and the obtained infection probability P is set as the _{threshold basis criterion B 3 and}
Determining the alarm threshold T _A on the basis of the reference B _3,
including,
The infection risk quantification system according to the fifth aspect.
(Aspect 7)
The infection risk quantification system includes a device monitoring and control unit equipped with at least one device for adjusting the air environment.
Including, and
In the control unit of the system server, the operating status of the device is confirmed, and the operation status of the device is confirmed.
In the arithmetic unit of the system server, using said mathematical model, the device control threshold T _D for changing the operating conditions of the device to determine at least one,
The control unit of the system server, while the infection probability P reduces the number of the devices in the operation state when it is judged to be less than the device control threshold T _D, the probability of infection P is the device control threshold T _D increase the number of said devices in the operation state when it is judged to be equal to or greater than, and,
The arithmetic unit of the system server
Calculate the indoor environmental standard B ₁ from the first public guideline,
The epidemiology side environmental standards B ₂ calculated from the second public hands,
The criteria B ₁ and B ₂ are substituted into the mathematical model, and the obtained infection probability P is set as the _{threshold basis criterion B 3 and}
The device control threshold value T _D is determined based on the reference B _3.
including,
The infection risk quantification system according to aspect 5 or 6 , characterized in that.
(Aspect 8)
The infection risk quantification system further includes a user-operated terminal connected to the communication network.
The user-operated terminal receives the infection probability P derived by the mathematical model from the system server at any time and makes it displayable on the screen of the terminal.
The infection risk quantification system according to any one of aspects 5 to 7 , characterized in that.

According to the method of the present invention, a quantitative infection probability can be calculated using a mathematical model, and a more quantitative infection risk can be evaluated and visualized.

In addition, in quantifying the infection risk of the present invention, in addition to changes in the environmental data inside the facility, epidemiological data over time regarding the infection status outside the facility (the community-acquired status of the area to which the facility belongs) is also used. The calculated infection probability reflects the actual epidemiological level of infectious diseases that tends to fluctuate depending on the season and region.

Further, according to the method of the present invention, the guideline / standard of a public institution such as WHO can be directly applied to the setting of the threshold value in the determination of the infection risk. In the present invention, the basis for setting the threshold value becomes more reliable than in the prior art. Further, according to a preferred embodiment of the present invention, an epidemiological guideline by a public institution such as WHO can be used to set a threshold value for changing the operating condition of a device for adjusting the air environment in a section. The criteria can be applied directly and the operation of these devices can be automatically controlled.

It is a figure which showed the schematic structure of the infection risk quantification system of this invention. It is a flowchart which shows each step of the infection risk quantification method of this invention. It is a figure which showed the detail and outline of the process of determining various thresholds of this invention. It is a figure which showed the operation screen (home screen) of the user operation terminal of this invention. It is a figure which showed the operation screen (facility management screen, division management screen, and user management screen) of the user operation terminal of this invention. It is a figure which showed the operation screen (monitoring screen and graph screen) of the user operation terminal of this invention. It is a figure which showed the operation screen (threshold value setting screen) of the user operation terminal of this invention.

Hereinafter, the technical contents of the present invention will be described based on the following specific embodiments with reference to the accompanying drawings, but the present invention is not limited to these embodiments.

(Main configuration of infection risk quantification system)
FIG. 1 shows the infection risk quantification system 1 of the present invention (hereinafter, also simply referred to as “system”). The system 1 includes a system server 2, an environmental data input / output device 3, a user operation terminal 4, an epidemiological data browsing site 5, a measurement monitoring unit 6, and a device monitoring / control unit 7. Each of these components 2-7 will be described in detail below.

(Overview of system server)
The system server 2 plays a central role in the infection risk assessment process in the system 1. The system server 2 may be of a stand-alone type that does not go through the communication network W or a network type that goes through the communication network W (for example, a cloud server as shown in FIG. 1). In the example of FIG. 1, the system server 2 is provided with a communication unit 21, a storage unit 22, a calculation unit 23, a control unit 24, a browsing display unit 25, and the like.

The communication unit 21 exchanges information with the environment data input / output device 3 and the user operation terminal 4 via the communication network W. The communication unit 21 acquires epidemiological data, which will be described later, from the epidemiological data browsing site 5.

The storage unit 22 stores signals and data acquired from the components 3 to 7 outside the system server 2 via the communication unit 21, and also stores the calculation data calculated by the calculation unit 23 in the system server 2. can do.

The calculation unit 23 calculates infection risk information as shown in the quantification method described later while using the input information acquired by the communication unit 21 and stored in the storage unit 22.

The control unit 24 controls the transmission / reception of data between the environment data input / output device 3, the user operation terminal 4, and the epidemiological data browsing site 5 connected to the system server 2 via the communication network W, and the calculation unit 23. in utilizing the calculated risk of infection information (infection probabilities P below, device control threshold T _D and the warning threshold _{T a (T A1, T A2} )), or making changes later operating conditions of the equipment monitoring control unit 7 can do.

The browsing display unit 25 can display the infection risk information calculated by the calculation unit 23 on the screen of the system server 2 or the user operation terminal 4 in real time for each infectious disease (pathogen). In addition to this, the input information acquired by the communication unit 21 is displayed, the selection screen of various parameters (described later) such as the threshold value used in the infection risk assessment by the calculation unit 23 is displayed, and the measurement monitoring unit is displayed. It is also possible to display the operating status of the various sensors 61 and 62 and the device monitoring and control unit 7 in 6. The same content as that displayed on the screen of the system server 2 may be displayed on the operation screen 4d of the user operation terminal 4.

(Overview of environmental data input / output device)
The environment data input / output device 3 is connected to the system server 2 via the communication network W, and is also connected to the measurement monitoring unit 6 and the device monitoring control unit 7. In the illustrated example, the connection between the environmental data input / output device 3 and the measurement monitoring unit 6 and the device monitoring control unit 7 is direct, but the connection may be via the communication network W.

The environment data input / output device 3 is provided with a communication unit 31, a signal input / output unit 32, and the like. The signal input / output unit 32 receives, for example, the environmental data measured by various sensors 61 and 62 described later in the measurement monitoring unit 6 and transmits the environmental data to the system server 2 via the communication unit 31.

Further, the signal input / output unit 32 receives the operating status of the devices 71, 72, 73 from the device monitoring control unit 7 and transmits the operation status to the system server 2. The signal input / output unit 32 also receives a signal from the system server 2 to the device monitoring control unit 7. Specifically, the control signal emitted from the control unit 24 of the system server 2 is received via the communication unit 31 of the environmental data input / output device 3, and the operating status of various devices 71 to 73 in the device monitoring control unit 7 is received. To change. As the signal input / output unit 32, for example, a commercially available PLC (Programmable Logic Controller) can be used.

(Overview of user-operated terminals)
The user operation terminal 4 is premised on being used in a section (for example, a nurse station, a waiting room, a hospital room) having a predetermined space in a facility (for example, a hospital or a long-term care facility), but outside the facility. It can also be used. The user operation terminal 4 may be in the form of a stationary terminal 41 installed in a nurse station or the like, or may be in the form of a mobile terminal 42 carried by a medical worker.

(Overview of epidemiological data browsing site)
The epidemiological data browsing site 5 is a site where infectious disease epidemic information such as information on infected persons by region of at least one kind of infectious disease (pathogen) can be browsed and acquired. For example, the National Institute of Infectious Diseases and local governments of the site is above epidemic information (for example, another infected person reporting the number n _{r region)} has been published, it is possible to browse and get these information. Examples of infectious diseases include influenza virus, tuberculosis, measles, and new coronavirus.

(Outline of measurement monitoring unit)
_{The measurement monitoring unit 6 includes, for example, an indoor environment sensor 61 that measures the carbon dioxide (CO 2} ) concentration inside the facility (such as a hospital room or a waiting room) and an outdoor environment sensor 61 that measures the carbon dioxide (CO ₂ ) concentration outside the facility. 62 and are provided.

(Overview of equipment monitoring and control unit)
The device monitoring control unit 7 includes, for example, a sterilizing device 71 (for example, a sterilizing device 71) for the purpose of killing or inactivating a virus floating in a target space (a section such as a hospital room or a waiting room) monitored by the measurement monitoring unit 6. An ultraviolet irradiation device), a ventilation blower 72 capable of ventilating the air in the target space, and a filter filtration device 73 (for example, an air purifier) capable of sucking the air in the target space and filtering it with a filter are provided.

It is desirable that at least one of the devices 71 to 73 of the device monitoring and control unit 7 is installed in each section of the monitored space, and the system 1 of the present invention has a high risk of infection in a certain section (“Caution”). Or "warning"), it operates so that the virus floating in the compartment can be sterilized, and the air in the compartment can be cleaned by ventilating or filtering. In addition, when a plurality of devices 71 to 73 of the device monitoring and control unit 7 are arranged, it is desirable to determine the priority of the operation order as to which device 71 to 73 is preferentially operated. For example, according to the experience of the present inventors, when it is determined that the risk of infection is high, the sterilizer 71 (ultraviolet irradiation device), the filter filtration device 73 (air purifier), and the ventilation blower 72 are prioritized in this order. It is more desirable to operate (increase) the stage.

(Method for Quantifying Infection Risk of the Present Invention)
Next, the infection risk quantification method of the present invention will be described in detail with reference to FIG. 2.

First, the sensors 61 and 62 of the measurement monitoring unit 6 are operated. In this embodiment, the CO ₂ concentration of each space (compartment) of the monitored facility with indoor environmental sensor 61 as well as measured in real time, CO ₂ facilities outside using outdoor environment sensor 62 (outdoor) The concentration is measured in real time (step S1). _{The CO 2} concentration data measured in this way is sent to the system server 2 via the environmental data input / output device 3 and the communication network W, and is stored and stored in the storage unit 22. Here, CO ₂ concentration in the compartment, generally, during the day, in order to generate a person in the room cage CO _2, such as patients and medical personnel in the compartment, the lower outside the facility populated outdoor CO ₂ Higher than the concentration. However, at night, depending on the compartment, the number of people in the room may decrease or the situation may not exist at all, and the CO ₂ concentration in the compartment approaches the outdoor CO _{2 concentration.}

Therefore, only when there is no occupant in the monitoring section at night and the CO ₂ concentration in the section acquired by the indoor environment sensor 61 drops to a value equivalent to the outdoor CO ₂ concentration, the drop is made at night. It is also possible to substitute the CO ₂ concentration in the compartment (hereinafter, also referred to as “initial value”) as the outdoor CO _{2 concentration.} As a result, the outdoor environment sensor 62 can be temporarily suspended to suppress its power consumption, or the installation of the outdoor environment sensor 62 can be eliminated.

Next, the system server 2 accesses the epidemiological data browsing site 5 to acquire epidemic information (in other words, the infection status in the city) of the area (prefecture) where the facility to be monitored exists, and stores it in the storage unit 22. -Accumulate (step S2). For example, on the site of the National Institute of Infectious Diseases, the number of infected people by prefecture and by infectious disease (pathogen) is updated and accumulated daily.

Further, the system server 2 confirms the types and operating conditions of the devices 71 to 73 that can be used for the above-mentioned device monitoring and control unit 7 (process S3). If the device monitoring control unit 7 is not installed in the section to be monitored, it is arranged and connected to the system 1 to check the operating status.

The operator (also referred to as “user”) of the system 1 selects an infectious disease (pathogen) for which monitoring (that is, quantification of the infection risk) is desired in the system 1 (step S4). In the example shown in FIG. 4, etc., a total of four pathogens can be selected from influenza virus, tuberculosis, measles, and new coronavirus.

It is desirable to determine _{the device control threshold T D} and the alarm threshold T _A ( _TA1 , _TA2 ) corresponding to the infectious disease selected in step S4 (step S5). Here, the device control threshold _{T D} and the warning threshold _{T A (T A1, T A2} ) can be determined using a mathematical model which will be described later. Note that the device control threshold T _D, the control unit 24 of the system server 2 is a reference value of whether to change the operating state of the device 71 to 73 in the equipment monitoring control unit 7, the alarm threshold value T _{A (T A1} , _TA2 ) is an index for the control unit 24 of the system server 2 to determine the safety level of the section from the current infection probability P in the watch section.

When the input values (environmental data, epidemiological data) acquired in the above steps S1 to S2 and the operating conditions and setting conditions in the system 1 selected in the steps S3 to S4 are met, the calculation unit 23 of the system server 2 will be described later. The infection probability P (infection probability P in the selected infectious disease) in each section to be monitored is calculated by using the mathematical model (step S6). The calculation of the infection probability P is continuously executed at regular intervals. The resulting infection probability P is above setting conditions (various threshold values T _D, T _A, instrument operating conditions) is displayed on the operation screen 4d are sent to the user operation terminal 4 together (step S7). The same infection risk information may be displayed on the screen of the system server 2.

Infection probability P of each compartment from time to time calculated above various threshold T _D, is compared to T _A. Specifically, it is determined whether or not the infection probability P exceeds the device control threshold value T _{D (step S8).} If the infection probability P does not exceed the threshold value T _D, the control unit 24 transmits a signal to reduce the number of devices 71 to 73 of equipment monitoring control unit 7 of the operating state (step S81). If there is only one device monitoring and control unit 7 in the operating state, the device monitoring and control unit 7 is in the stopped state. Further, when the device monitoring control unit 7 is already in the stopped state, the devices 71 to 73 in the operating state do not exist, so that the stopped state is continued.

On the other hand, if the infection probability P of the monitored zone is exceeded the device control threshold T _D is at least one is equipment 71-73 mutable equipment monitoring control unit 7 to the operating state from a stopped state exists It is determined whether or not to do so (step S82). If it exists, the additional operation of the devices 71 to 73 of the device monitoring and control unit 7 is started according to the predetermined operation priority (process S83). By such processing of the control unit 24 of the system 1, automatic control regarding the operation of the equipment monitoring control unit 7 becomes possible. The device control threshold value T _D is not limited to one value, and a plurality of values may be set.

After completing this step S8～S83, control unit 24 determines whether the infection probability P exceeds the alarm threshold _{T A} (step S9 (S9A)). Alarm threshold T _A, as in the example shown in FIG. 2, large and small two kinds of threshold T _A1, T _A2 the values are different may be prepared. If neither of the alarm thresholds _TA1 and _TA2 is exceeded, it is determined to be "safe" (process S91), and the signal is transmitted to the user operation terminal 4 (process S10). If "Caution" or "Warning", which will be described later, is determined in the previous routine processing, the determination is canceled. In this case, the signal "safety" is displayed in the safety level display column of the target section on the operation screen 4d of the system server 2 or the user operation terminal 4 (see FIG. 4).

In contrast, it is determined whether infection probability P is relatively not only a relatively small alarm threshold T _A1 or greater alarm threshold T _A2 above (step S9B). When the infection probability P is less than the _{threshold value TA2 (TA1} ≤ P < _TA2 ), it is determined as "caution" (step S92), and the signal is transmitted to the user operation terminal 4 (step S10). .. In this case, the signal "Caution" is displayed in the safety level display column of the target section on the operation screen 4d of the system server 2 or the user operation terminal 4 (see FIG. 4).

Further, when the infection probability P falls within the range of the _{alarm threshold TA2 or more (TA2} ≦ P) having a relatively large alarm value, it is determined as “warning” and the signal is transmitted to the user operation terminal 4. (Step S93). In this case, the signal "warning" is displayed in the safety level display column of the target section on the operation screen 4d of the system server 2 or the user operation terminal 4 (see FIG. 4).

(Derivation of mathematical model used for this system)
Next, a mathematical model for calculating the infection probability P in the above-mentioned step S6 in real time will be described in detail. This model is a mathematical formula originally developed by the present inventors from the infection probability model (formula 3) of Rudnick and Milton described in Non-Patent Document 2.

Here, f is _{the ratio of the CO 2} concentration derived from exhaled breath to the total _{indoor CO 2} concentration, I is the number of infected persons in a closed space, and q is the exhaled breath of a person infected with a certain infectious disease (pathogen). Infectious particle generation rate due to (also called "quanta", unit is [1 / h]), t is the indoor stay time, and n is the number of people in the compartment (indoor).

Further, f is represented by the following formula 4, and the above-mentioned _{measured values of each CO 2} concentration can be used.

Here, _{C i} is the compartment CO ₂ concentration measured by the indoor environmental sensor 61, _{C o} outdoor CO ₂ concentration measured by the outdoor environment sensor 62 (where, at night compartment CO ₂ concentration of the above When the value drops to the value of the outdoor CO ₂ concentration, the above-mentioned value (initial value) of the nighttime _{CO 2 concentration in the compartment can be substituted), and C a} is the ratio of _{the CO 2} concentration generated by human exhalation _{(C a).} = 0.038 constant value). C _i and C _o is measured by sensors 61 and 62 described above, it can be utilized environment data stored in the storage unit 22 of the system server 2.

However, the present inventors have noticed that the known formula 3 treats the number of infected persons I as a "constant". That is, since it is not possible to directly monitor the infection status of the occupants in the monitoring section and the amount of infectious particles floating in the air, it is not possible to obtain the infection probability in real time with this mathematical formula 3 as it is.

Therefore, the present inventors acquired the epidemiological data published on the epidemiological data browsing site 5 in order to give the number of infected persons I real-time, and from now on, the influence factor F that the regional epidemiological characteristics have on the occupants is determined. After estimating, the number of infected persons I was specified. For example, by dividing the number of infected persons on the day (the number of reported cases of infected persons _{by prefecture nr} ) from the acquired epidemiological data by the population of the corresponding prefecture, the influence factor that the regional epidemic characteristics have on the occupants. F (eg, F = (some infected people report the number n _r of the _province) / (prefecture population n _t of the _Prefecture)) and, to this effect factor F, which was multiplied by the occupants number n of the monitored compartment Was defined as the number of infected persons I (I = n × F). That is, the mathematical model of the present invention can be rewritten into the following mathematical formula 5.

Here, q is the rate of infectious particle generation (quanta, unit is [1 / h]) due to the exhaled breath of a person infected with a certain infectious disease (pathogen), and is a default value determined for each pathogen. For example, Table 1 shows the infectious particle generation rates q of the four infectious diseases (pathogens) monitored in this example.

According to this formula 5, the evaluation of the infection probability P by the system 1 is based on the fluctuation of the community-acquired infection situation in the area to which the monitored facility belongs, and the infection risk is quantified in a more real-time manner and more reflects the local situation. Will be realized. By using the statistical values (epidemiological data) of the community-acquired infection status in this way, it is possible to supplement the infection risk with higher accuracy than the evaluation method using only the environmental data obtained in the facility, and the carbon dioxide inside and outside the facility. by using the difference between the carbon concentration (C i _{-C o),} increased risk due to the so-called "dense" situation it is possible to reflect the risk of infection.

The present inventors also assume that equipment monitoring control units 7 such as a sterilizer 71, a ventilation blower 72, and a filter filtration device 73 are installed in the monitored section, and these devices 71 to 73 are operated. This allows the pathogens in the air to be inactivated or eliminated. Therefore, the present inventors have derived the following formula 6 by incorporating the pathogen elimination effect of the operation of these device monitoring and control units 7 into the formula 5.

Here, η is the one-pass removal rate of the equipment monitoring and control unit 7 installed in the compartment (room), Q _M is the processing air volume of the equipment monitoring and control unit 7 installed in the room, and V is the room. It is the volume of (monitoring target).

Equipment performance monitoring control unit 7 of the air cleaner and the like are specified out essentially as a "one-pass removal ratio η" and "process air volume Q _M". The one-pass removal rate η indicates the ratio of particles that can be removed when air passes through the air purifier once. Incidentally, removal of actual infectious particles are those obtained by multiplying the processing air volume Q _M and pass removal rate eta, it will be obtained by multiplying the more infectious particle concentrations and equipment operating time. Then, when the removed amount is expressed as a concentration, the removed amount may be divided by the air volume V, and when expanded to the case where there are a plurality of devices, it is expressed by the following mathematical formula 7.

In this system 1, it is assumed that a plurality of equipment monitoring and control units 7 such as a sterilizer 71, a ventilation blower 72, and a filter filtration device 73 are installed in a section to be monitored. Therefore, the above formula is expressed in the form of the total number of devices. m indicates the device number, and N indicates the concentration of infectious particles in the compartment. Then, by reflecting the mathematical formula 7 in the mathematical formula 6, the mathematical model is expressed by the following mathematical formula 8.

This mathematical formula 8 becomes a mathematical model that can be used in the infection risk quantification method of the present invention, and input information such as environmental data, signals, and epidemiological data acquired by the measurement monitoring unit 6 and the equipment monitoring control unit 7 of the present system. By substituting into the formula 8, the infection probability P can be quantified in real time and notified to the user of the system 1 (for example, a medical worker).

(Calculation method of device control threshold and alarm threshold)
The details of the implementation contents of the above-mentioned step S5 ( _{calculation method of the device control threshold value T D} and the alarm threshold value T _A (TA ₁ , TA ₂ )) will be described with reference to FIGS. 3 (a) and 3 (b). These thresholds _T D, in determining the _{T A,} the present inventors have found that 1) compartment and in-room side environmental standards _{B 1,} 2) Epidemiology side (outdoor side) determines the environmental standards _{B 2,} 3 ) We decided to use the infection probability P obtained by substituting these two indexes B ₁ and B ₂ into the above-mentioned mathematical model as the threshold basis standard B ₃ .

(Use of public guidelines for environmental hygiene (first public guidelines) for indoor environmental standards)
First, the indoor environmental standard B _{1 is an environmental hygiene guideline regarding CO 2} concentration published by government agencies such as the Ministry of Health, Labor and Welfare (that is, the indoor CO ₂ concentration should be less than or equal to the value obtained by adding 700 ppm to the outdoor CO _{2 concentration.} It is calculated from the guideline (also referred to as "first public guideline")) (step S51). That is, the indoor environmental standard B ₁ can be expressed by the following mathematical formula 9.

(Use of public hygiene guidelines (second public guidelines) for epidemiological (outdoor) environmental standards)
On the other hand, epidemiological side (outdoor side) environmental standards B ₂ is, both the alarm guidance on the epidemic level of each infection such as the World Health Organization (WHO) and the National Institute of Infectious Diseases is published ( "the second official guidelines" It is calculated from (call)) (step S52).

For example, as the second official guideline, in the case of tubercle bacillus, there is a guideline that caution should be exercised when the annual morbidity rate is 10 or more per 100,000 people, so the epidemiological side (outdoor side) environmental standard B ₂ Can be expressed by the following formula 10.

(Determination of threshold basis criteria)
_{The criteria B 1} and B ₂ determined in this way are substituted into the above equations 7 and 8 as parameters of the mathematical model, and the finally obtained infection probability P is _{set as the threshold basis criterion B 3} (step S53). .. For example, _{by substituting the above specific numerical values of B 1} and B ₂ , the infection probability P (threshold basis basis B ₃ ) = 25 × ^10-8 (= 0.000025%) can be obtained (infectious disease shown in FIG. 7). See also column 3).

(Determining and adjusting the alarm threshold based on the threshold basis criteria)
Based on the threshold rationale reference _{B 3} above, it may be determined alarm threshold _{T A (T A1, T A2} ) and device control threshold _{T D} arbitrarily by the system administrator or the user (step S54). For example, a relatively large alarm threshold _{T A2} set to greater than or equal to the threshold value basis reference _{B 3,} a relatively small alarm threshold _{T A1} is somewhat smaller than the threshold rationale reference _{B 3} (e.g., about 80-90% ) May be set.

For example, the user may Prevalence threshold rationale reference B ₃ (e.g., if a stage 3 equivalent availability determination of the new coronavirus) while checking the, before it reaches the value of the threshold rationale reference B ₃ to "caution" sends a (arousal), the threshold rationale reference B ₃ and optionally in response to a little individual needs of the user, such as to be exceeded After transmitting the "warning" (stimulate) the alarm threshold T _A1, T _A2 You will be able to set it. Of course, the value of the threshold threshold standard B ₃ may be set as it is as the value of the alarm threshold _TA1 (caution) or _{TA2 (warning).}

(Determination and adjustment of device control threshold value based on threshold threshold criteria)
Further, it is also possible device control threshold T _D is determined with reference to the threshold rationale reference B ₃ as well. For example, it may be set to substantially small value (for example, about 60% to 70%) than the threshold value _{B 3.} These thresholds _{T A (T A1, T A2} ), of _{T D} set, the system (specifically, the setting screen 4d ₇ as shown in FIG. 7) server operation screen 4d of 2 and the user operation terminal 4 above The setting may be easily changed by operating the GUI (for example, the slider icon _SL ( _SL1 , _SL2 , _SL3 , _{SL4) for each infectious disease).} Further, when selecting an infectious disease (pathogen) to be monitored by this system 1 in the above step S4, the presence or absence of selection is switched by pressing the toggle button TB on the _{same setting screen 4d 7.} be able to.

(Operation screen of system server or user operation terminal)
FIGS. 4 to 7 show an example of the operation screen 4d of the system server 2 or the user operation terminal 4. _{In addition to the home screen 4d 1} shown in FIG. 4, the operation screen 4d includes the _{facility management screen 4d 2} shown in FIG. 5 (a), the _{section management screen 4d 3} shown in FIG. 5 (b), and FIG. 5 (c). The user management screens 4d ₄ shown in the above are provided, and the display screens can be switched between each other by clicking the icons corresponding to _{the respective screens 4d 2 to 4d 4.}

As shown in FIG. 5B, the section management screen 4d ₃ displays a list of sections registered as monitoring targets (four in the figure) and evaluation results (display of any of safety, caution, and warning). When an arbitrary section display section in the section display section list is selected, the screen _{switches to the monitoring screen 4d 5} (see FIG. 6A) of the section, which will be described later.

Further, as shown in FIG. 5A, the registration information (for example, address, telephone number, e-mail address, etc.) of the facility to be monitored can be displayed _{on the facility management screen 4d 2.} On the other hand, as shown in FIG. 5C, the user management screen 4d ₄ can display a list of users registered in the system 1, and registration information of each user (for example, name, system usage) can be displayed. Authority, email address, registration date, active status, etc.) can be displayed. The facility management screen 4d ₂ and the user management screen 4d ₄ may be displayed only on the operation screen 4d of the system server 2.

(Home Screen)
As shown in FIG. 4, the home screen 4d ₁ shows the number of sections currently being monitored (for example, the number of rooms), the number of user operation terminals 4 logged in to the system 1, and the number of operators (users). Is displayed, and an overview of the monitoring status for each section currently being monitored is shown. When any of the section display units being monitored is selected on the home screen 4d ₁ , the screen switches to _{the monitoring screen 4d 5 of the section shown in FIG. 6 (a).} On the monitoring screen 4d ₅ , the infection probability P quantified by this system 1 for each infectious disease (pathogen) is displayed as a bar graph in order to improve visibility.

(Monitoring screen)
The partition management screens 4d ₃ are provided with screens 4d _{5 to 4d 7 which will be described later.} More specifically, the monitoring screen 4d ₅ for each section to be monitored is also provided with a column for displaying environmental data inside and outside the facility, the air conditioning status inside the facility, and the operating status of the equipment monitoring control unit 7 and the like (Fig.). 6 (a)).

(Risk fluctuation graph)
Further, from the compartment management screen 4d _{3 , a risk fluctuation graph (graph screen 4d 6} ) showing the time variation of the infection probability P for each pathogen (infectious disease 1 to 4) as shown in FIG. 6 (b) is displayed. be able to. In the figure, time-dependent data regarding the infection probability P of infectious disease 2 is displayed. Which are presented in conjunction "Safety" and "Caution" and alarm threshold T _A1 to divide the _"attention" and "Warning" alarm separating the threshold T _A2, also the threshold rationale reference B ₃ in the graph, for example, It is possible to determine at a glance whether the safety level of the monitoring area has fallen within the range of "Caution" or "Warning" within the last few days or hours.

According to the results of an independent survey conducted by the present inventors on medical professionals, in addition to grasping the risk of community-acquired infections such as influenza pandemic information and monitoring the concentration of viruses and bacteria in the air in the facility, these viruses It was found that there is a high demand and interest in controlling in-facility equipment to constantly control the concentration of influenza and bacteria.

Ideally, direct monitoring of airborne virus and bacterial concentrations is desirable, but direct virus monitoring is not feasible at current state of the art.

Therefore, the system of the present invention, which accurately quantifies the infection probability by combining the carbon dioxide concentration directly monitored in the facility and the epidemiological data on the community-acquired infection situation, is a realistic alternative to the ideal virus direct monitoring. It can be said that it is a relatively reliable technology.

Therefore, the infection risk quantification system and the quantification method of the present invention have high industrial utility value and utility.

1 Infection risk quantification system 2 System server 3 Environment data input / output device 4 User operation terminal 4d, 4d ₁ , 4d ₂ , 4d ₃ Operation screen, home screen, facility management screen, partition management screen 4d ₄ , 4d ₅ , 4d ₆ , 4d ₇ User management screen, monitoring screen, graph screen, setting screen 5 Epidemiological data browsing site 6 Measurement monitoring unit 7 Equipment monitoring control unit 21, 22, 23, 24, 25 Communication unit, storage unit, calculation unit, control unit, Browsing display unit 31, 32 Communication unit, signal input / output unit 41, 42 Stationary terminal, mobile terminal 61, 62 Indoor environment sensor, outdoor environment sensor 71, 72, 73 Sterilizer, ventilation blower, filter filtering device B ₁ , B _{2, B 3} indoor environmental standards, epidemiology side (outdoor side) environmental standards, the threshold rationale P reference probability of infection _{S L (S L1, S L2} , S L3, S L4) slider icon _{T A (T A1, T A2} ) , T _D alarm threshold, device control threshold TB toggle button W communication network

Claims (8)

An infection risk quantification method that assesses the risk of infection in at least one section of a facility.
A measurement process for measuring _{the CO 2} concentration outside the facility while measuring _{the CO 2} concentration inside the section.
The process of acquiring _{at least one infectious disease-related infectious person report number nr} in the area to which the facility belongs from the epidemiological data browsing site at any time.
The process of deriving the infection probability P in the section using a mathematical model at any time, and
Including and
The mathematical model can be obtained by the following mathematical formula.

Here, _{C i} is the CO ₂ concentration in the compartment, _{C o} is the outside the facility of the CO ₂ concentration (however, the CO ₂ concentration value of the facility outside the compartment CO ₂ concentration at night when down to is substitutable) by the value of the nighttime said compartment CO ₂ concentration, _{C a} is the fraction of CO ₂ concentration that occurs in human breath _(C a = 0.038), F is the impact factor is epidemic characteristics in the area of the infection is given to the occupants of the facility, it is the proportion of the infected people report the number n _r with respect to the total population n _t of the region, q is the infectious diseases The rate of infectious particle generation due to the exhaled breath of a person infected with
A method for quantifying infection risk. Using said mathematical model, further saw including an alarm threshold determination step of determining at least one alarm thresholds T _A for determining the safety level of the partition, and,
The alarm threshold determination step is
A step of calculating the indoor environmental standards B ₁ from the first public hands,
A step of calculating the epidemiological side environmental standards B ₂ from the second public hands,
A step _{of substituting the criteria B 1} and B ₂ into the mathematical model and setting the obtained infection probability P as the threshold basis criterion B _3;
And determining the alarm threshold T _A on the basis of the reference B _3,
including,
The method for quantifying an infection risk according to claim 1. A process of arranging a device monitoring control unit equipped with at least one device for adjusting the air environment in the section and confirming the operating status of the device, and a process of confirming the operation status of the device.
Using said mathematical model, the device control threshold value determining step of determining at least one device control threshold T _D for changing the operating conditions of the device,
While the infection probability P reduces the number of the devices in the operation state when it is determined to be less than the device control threshold T _D, if it is determined that the probability of infection P is the device control threshold T _D or A device operation change process that increases the number of the devices in operation, and
Further only it contains, and,
The device control threshold determination step is
A step of calculating the indoor environmental standards B ₁ from the first public hands,
A step of calculating the epidemiological side environmental standards B ₂ from the second public hands,
A step _{of substituting the criteria B 1} and B ₂ into the mathematical model and setting the obtained infection probability P as the threshold basis criterion B _3;
The step of determining the device control threshold value T _D based on the reference B _{3 and}
including,
The method for quantifying an infection risk according to claim 1 or 2, wherein the method is characterized by the above. The infection probability P derived by the mathematical model is transmitted to a terminal that can be operated by the user at any time so that the infection probability P can be displayed on the screen of the terminal.
The method for quantifying an infection risk according to any one of claims 1 to 3 , wherein the method is characterized by the above. An infection risk quantification system that assesses the risk of infection in at least one compartment within a facility.
A system server equipped with a communication unit, a storage unit, and an arithmetic unit connected to a communication network,
A measurement monitoring unit that is directly or indirectly connected to the communication network and includes an indoor environment sensor that measures _{the CO 2} concentration in the compartment and an outdoor environment sensor that measures _{the CO 2 concentration outside the facility.}
Connected to the communication network, and the epidemiological data browsing sites for storing at any time infected persons reported number n _r of the area belongs the facility for at least one infection,
Including and
_{The storage unit stores the CO 2} concentration acquired by the measurement and monitoring unit and the _{number of reported infected persons nr} accumulated at the epidemiological data browsing site via the communication unit.
In the calculation unit, each CO ₂ concentration stored in the storage unit and the number of reported infected persons _nr are substituted into the mathematical model of the following mathematical formula to derive the infection probability P in the section.

Here, _{C i} is the CO ₂ concentration in the compartment, _{C o} is the outside the facility of the CO ₂ concentration (however, the CO ₂ concentration value of the facility outside the compartment CO ₂ concentration at night when down to is substitutable) by the value of the nighttime said compartment CO ₂ concentration, _{C a} is the fraction of CO ₂ concentration that occurs in human breath _(C a = 0.038), F is the impact factor is epidemic characteristics in the area of the infection is given to the occupants of the facility, it is the proportion of the infected people report the number n _r with respect to the total population n _t of the region, q is the infectious diseases The rate of infectious particle generation due to the exhaled breath of a person infected with
An infection risk quantification system characterized by this. In the arithmetic unit of the system server, using said mathematical model, the alarm threshold value T _A for determining the safety level of the compartment to determine at least one,
In the storage unit of the system server, storing the alarm threshold T _A, and
The arithmetic unit of the system server
Calculate the indoor environmental standard B ₁ from the first public guideline,
The epidemiology side environmental standards B ₂ calculated from the second public hands,
The criteria B ₁ and B ₂ are substituted into the mathematical model, and the obtained infection probability P is set as the _{threshold basis criterion B 3 and}
Determining the alarm threshold T _A on the basis of the reference B _3,
including,
The infection risk quantification system according to claim 5. The infection risk quantification system includes a device monitoring and control unit equipped with at least one device for adjusting the air environment.
Including, and
In the control unit of the system server, the operating status of the device is confirmed, and the operation status of the device is confirmed.
In the arithmetic unit of the system server, using said mathematical model, the device control threshold T _D for changing the operating conditions of the device to determine at least one,
The control unit of the system server, while the infection probability P reduces the number of the devices in the operation state when it is judged to be less than the device control threshold T _D, the probability of infection P is the device control threshold T _D increase the number of said devices in the operation state when it is judged to be equal to or greater than, and,
The arithmetic unit of the system server
Calculate the indoor environmental standard B ₁ from the first public guideline,
The epidemiology side environmental standards B ₂ calculated from the second public hands,
The criteria B ₁ and B ₂ are substituted into the mathematical model, and the obtained infection probability P is set as the _{threshold basis criterion B 3 and}
The device control threshold value T _D is determined based on the reference B _3.
including,
The infection risk quantification system according to claim 5 or 6. The infection risk quantification system further includes a user-operated terminal connected to the communication network.
The user-operated terminal receives the infection probability P derived by the mathematical model from the system server at any time and makes it displayable on the screen of the terminal.
The infection risk quantification system according to any one of claims 5 to 7.

Images