Method and device for drawing atmosphere heavy pollution sensitive disease spectrum

Abstract

The invention provides a drawing method and device for an atmospheric heavy pollution sensitive disease spectrum, and relates to the technical field of computer data processing, and the method comprises the steps: collecting historical atmospheric environment exposure data and crowd health data; according to the historical atmospheric environment exposure data, identifying a plurality of heavy pollution events with historical differentiated concentrations and durations; calculating a heavy pollution exposure comprehensive score according to the heavy pollution event; according to the heavy pollution event and the crowd health data, utilizing a fitting model to quantitatively analyze a chronic exposure-reaction relationship between heavy pollution and diseases of different disease species; according to the chronic exposure-reaction relationship between the heavy pollution and the diseases of different disease categories, the heavy pollution exposure comprehensive score and the coupled disease burden, calculating the heavy pollution related disease burden; and sequencing the burden of the heavy pollution related diseases, and drawing a sensitive disease spectrum.

Description

Technical Field

[0001] The present invention relates to the technical field of computer data processing, and in particular to a method and device for drawing a spectrum of diseases sensitive to severe atmospheric pollution. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section.

[0003] Exposure to suspended matter during the London smog incident in the 1950s led to a significant increase in the risk of death. With the development of air pollution monitoring technology, previous studies have found that PM2.5, a small particle size, can be used to monitor the air quality of the air. 2.5 Pollution can cause increased mortality and morbidity from cardiovascular diseases. 2.5 Studies on the health effects of severe pollution events with PM as the primary pollutant are limited to a single severe pollution event, and the research results cannot be extrapolated to other pollution events. 2.5 Study on health risks of severe pollution events, PM 2.5 Severe pollution incidents have not received enough attention, and the necessary health risk warning system cannot be established, so PM 2.5 The protective measures against health hazards associated with severe pollution incidents need to be further improved. The existing disease spectrum selection technology has the following main shortcomings:

[0004] First, existing technical methods are only applicable to the acute effects of severe air pollution events and are not suitable for the quantitative evaluation of the chronic effects of severe pollution exposure. However, the effects of long-term exposure to air pollution are greater.

[0005] Second, existing technical methods are only applicable to single severe pollution events and are not suitable for situations where severe pollution weather occurs twice or more each year;

[0006] Third, existing technical methods are limited to quantitative assessment of the impact of heavy pollution on human health, and do not involve the mapping of sensitive disease spectra, which is of great significance for further prevention and control of diseases;

[0007] Fourth, existing technical methods for assessing the impact of heavy pollution on human health mainly consider the impact of air pollutants on human mortality, and lack consideration of the impact on disease. However, the most direct and easiest impact of heavy pollution on human health is disease.

[0008] Due to the above-mentioned limitations in the methods for mapping out the spectrum of sensitive diseases related to heavy pollution, the existing research methods are not suitable for the actual local conditions and cannot support the comprehensive and scientific mapping out of the spectrum of sensitive diseases related to heavy air pollution.

[0009] In the prior art, an episode method based on a single severe pollution event was proposed to study excess medical visits related to smog in the North China Plain in January 2013. This technology can only target a single severe pollution event, and the types of diseases studied are relatively coarse, so as to draw a spectrum of diseases sensitive to severe pollution.

[0010] The specific method of evaluating excessive visits for heavy pollution by this technology is as follows:

[0011] S1: Select a heavy pollution research period and set the same month and day of the adjacent year as the control period;

[0012] S2: Calculate the ratio (RR) of the visit rate between the heavy pollution period and the control period.

[0013] However, this method is only applicable to a certain severe pollution incident in a certain area; without building a model, possible confounding factors such as temperature and humidity are not well controlled; the diseases studied are only large-scale systems and cannot be subdivided into types, making it impossible to draw a sensitive disease spectrum.

[0014] In summary, there is an urgent need for a technical solution that can overcome the above-mentioned defects, support comprehensive and scientific mapping of the spectrum of diseases sensitive to severe atmospheric pollution based on actual conditions. Summary of the invention

[0015] In order to solve the problems existing in the prior art, the present invention proposes a method and device for drawing a spectrum of diseases sensitive to severe atmospheric pollution. The present invention identifies multiple historical severe pollution events that distinguish concentrations and durations, builds a model to quantitatively analyze the chronic exposure-response relationship between severe pollution and different types of diseases, and then couples the disease burden calculation model to rank the death or medical treatment burden related to severe pollution events for all diseases, and finally draws a spectrum of diseases sensitive to severe atmospheric pollution, providing strong technical support for weather pollution and disease warning.

[0016] In a first aspect of an embodiment of the present invention, a method for drawing a spectrum of diseases sensitive to severe air pollution is proposed, comprising:

[0017] Collect historical atmospheric environmental exposure data and population health data;

[0018] Based on the historical atmospheric environmental exposure data, identify multiple historical heavy pollution events distinguishing concentrations and durations;

[0019] Calculate a comprehensive heavy pollution exposure score based on the heavy pollution events described;

[0020] Based on the heavy pollution events and population health data, the fitting model was used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases;

[0021] Based on the chronic exposure-response relationship between the heavy pollution and different diseases and the comprehensive score of heavy pollution exposure, the disease burden related to heavy pollution is calculated by coupling the disease burden;

[0022] Rank the burden of diseases related to heavy pollution and draw a spectrum of sensitive diseases.

[0023] In a second aspect of an embodiment of the present invention, a device for drawing a spectrum of diseases sensitive to severe atmospheric pollution is provided, comprising:

[0024] Data collection module, used to collect historical atmospheric environmental exposure data and population health data;

[0025] A heavy pollution event identification module, used to identify multiple heavy pollution events in history that distinguish concentrations and durations based on the historical atmospheric environment exposure data;

[0026] A heavy pollution scoring module, used to calculate a comprehensive heavy pollution exposure score based on the heavy pollution event;

[0027] A chronic exposure-response relationship analysis module is used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases using a fitting model based on the heavy pollution events and population health data;

[0028] A calculation module, for calculating the disease burden related to heavy pollution by coupling the disease burden according to the chronic exposure-response relationship between the heavy pollution and different diseases and the comprehensive score of heavy pollution exposure;

[0029] A drawing module is used to rank the burden of diseases related to heavy pollution and draw the spectrum of sensitive diseases.

[0030] In a third aspect of an embodiment of the present invention, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements a method for drawing a spectrum of diseases sensitive to severe atmospheric pollution when executing the computer program.

[0031] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a method for drawing a spectrum of diseases sensitive to severe atmospheric pollution is implemented.

[0032] In a fifth aspect of an embodiment of the present invention, a computer program product is proposed. The computer program product includes a computer program, and when the computer program is executed by a processor, a method for drawing a spectrum of diseases sensitive to severe atmospheric pollution is implemented.

[0033] The method and device for drawing a spectrum of diseases sensitive to severe atmospheric pollution proposed in the present invention include a data collection module for collecting historical atmospheric environmental exposure data and human health data; a severe pollution event identification module for identifying multiple severe pollution events that distinguish between concentrations and durations in history based on the historical atmospheric environmental exposure data; a severe pollution scoring module for calculating a comprehensive severe pollution exposure score based on the severe pollution events; a chronic exposure-response relationship analysis module for quantitatively analyzing the chronic exposure-response relationship between severe pollution and different types of diseases using a fitting model based on the severe pollution events and human health data; a calculation module for calculating the severe pollution-related disease burden by coupling the disease burden based on the chronic exposure-response relationship between severe pollution and different types of diseases and the severe pollution exposure comprehensive score; and a drawing module for sorting the severe pollution-related disease burden and drawing a spectrum of sensitive diseases. The technology for mapping diseases sensitive to severe atmospheric pollution implemented by the overall solution can identify multiple severe pollution events in history, and thus derive the chronic exposure-response relationship between severe pollution events of different concentration levels and durations and specific disease outcomes through model fitting, providing evidence for further formulating and revising standards and establishing an early warning system. In addition, the present invention is coupled with a disease burden model to map a spectrum of sensitive diseases, which can provide scientific advice for responses such as the allocation and deployment of medical staff when severe pollution weather occurs. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 It is a flow chart of a method for drawing a spectrum of diseases sensitive to severe air pollution according to an embodiment of the present invention.

[0036] Figure 2 It is a schematic diagram of a process for collecting historical atmospheric environment exposure data and population health data according to an embodiment of the present invention.

[0037] Figure 3 It is a flowchart of identifying multiple heavy pollution events with different concentrations and durations in history according to an embodiment of the present invention.

[0038] Figure 4 It is a schematic diagram of a process for analyzing chronic exposure-response relationship according to an embodiment of the present invention.

[0039] Figure 5 It is a schematic diagram of the architecture of a device for drawing a spectrum of diseases sensitive to severe air pollution according to an embodiment of the present invention.

[0040] Figure 6It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0042] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0043] According to the implementation mode of the present invention, a method and device for drawing a spectrum of diseases sensitive to severe atmospheric pollution are proposed, which relates to the field of computer data processing technology. It can mainly process big data to realize Internet data services such as big data resource services, database and cloud database services; the present invention adopts cloud computing software, a new generation of massive information intelligent search software, data mining software, and cloud fusion application operation support platform software to realize information services and data atmospheric data processing, and realize the drawing of a spectrum of diseases sensitive to severe atmospheric pollution. The present invention focuses on the chronic effects of severe atmospheric pollution, can identify multiple severe pollution events in history, and quantitatively calculate the chronic exposure-response relationship of different types of severe pollution events to the outcomes of specific diseases, couple the disease burden model, and finally draw a spectrum of diseases sensitive to severe atmospheric pollution by ranking the disease burden of specific diseases. The comprehensive scoring method for severe pollution exposure proposed in the overall scheme takes into account the identification methods of multiple severe pollution events of different concentrations and durations in history, and the method for drawing a spectrum of sensitive diseases, which provides strong technical support for the drawing of a spectrum of diseases sensitive to severe atmospheric pollution.

[0044] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0045] Figure 1 FIG. 1 is a flow chart of a method for drawing a spectrum of diseases sensitive to severe atmospheric pollution according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0046] S101, collect historical atmospheric environmental exposure data and population health data;

[0047] S102, identifying multiple historical heavy pollution events distinguishing concentrations and durations according to the historical atmospheric environment exposure data;

[0048] S103, calculating a comprehensive score of heavy pollution exposure according to the heavy pollution event;

[0049] S104, based on the heavy pollution events and population health data, using a fitting model to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different types of diseases;

[0050] S105, calculating the disease burden related to heavy pollution by coupling the disease burden based on the chronic exposure-response relationship between the heavy pollution and the diseases of different diseases and the comprehensive score of heavy pollution exposure;

[0051] S106, rank the burden of diseases related to heavy pollution and draw a spectrum of sensitive diseases.

[0052] In order to explain more clearly the method of drawing the spectrum of diseases sensitive to severe air pollution, each step will be explained in detail below.

[0053] In one embodiment, for S101, historical atmospheric environment exposure data and population health data are collected, such as Figure 2 As shown, the detailed method is:

[0054] S101-1, determining a target time range, wherein a first time period is selected as the target time range according to the feasibility of data collection;

[0055] Specifically, based on the feasibility of data collection, try to choose a relatively recent time period as the target time range. It is recommended to use nearly 5 or 10 years as the target time range to determine the starting time of the target time range.

[0056] S101-2: Collect PM2.5 data in the target area by county / city within the target time range. 2.5 , daily / hourly average data of O3, NO2, SO2, CO, temperature and humidity;

[0057] Specifically, if the data is hourly, it is processed as the daily average level.

[0058] S101-3, within the target time frame, collect medical case information of the entire population or the preset target population, which at least includes the medical diseases, prescription drugs, length of residence in the area, age, gender, race, and marital status; and within the target time frame, collect death case information of the entire medical population or the preset target population, which at least includes the disease causing death.

[0059] Specifically, the medical case information of the entire population (male / female and all age groups) or special target populations within the target time range is collected, including medical diseases (including ICD codes), prescription drugs, length of residence in the area, age, gender, race, marital status, etc.; the death case information of the entire medical population (male / female and all age groups) or special target populations within the target time range is collected, including information such as the disease caused by death (including ICD codes).

[0060] In actual application scenarios, taking a certain region as an example, the target time range is determined to be the past 10 years, namely 2013-2023, so the starting time is January 1, 2013.

[0061] Collect air pollution data from 35 monitoring stations in all 16 districts of the region during the target time period. The data can be obtained from the air quality network. Calculate PM using hourly data from the monitoring stations. 2.5 The daily average levels of , O3, NO2, SO2 and CO, daily temperature and relative humidity were obtained from the Meteorological Data Network.

[0062] The records of hospital admissions for cardiovascular diseases in the region during the target time period were collected, including the International Classification of Diseases, 10th Revision (ICD-10): I00-I99 information, age, gender, race, marital status, prescription drugs, etc. All death case records in Beijing during the same period were collected, including information such as the ICD-10 code of the cause of death.

[0063] In one embodiment, for S102, based on the historical atmospheric environment exposure data, multiple historical heavy pollution events distinguishing concentration and duration are identified, such as Figure 3 As shown, the specific method is:

[0064] S102-1, select a key pollutant in the atmosphere as the key pollutant in the definition of a severe pollution event, and set a certain number of concentration classification values ​​based on the severe air pollution standards and actual conditions;

[0065] Specifically, 1 to 2 concentration division values ​​may be set.

[0066] S102-2, based on the concentration classification value, divide each day in the study period into no severe pollution event, severe pollution event, and extremely severe pollution event;

[0067] S102-3, classify heavy pollution events or extremely heavy pollution events according to the number of days of continuous pollution.

[0068] Specifically, the number of days of continuous pollution can be divided into 1 day, 2 days, 3 days and more than 3 days.

[0069] Specifically, taking O3 as an example, in order to clarify the different impacts of severe and extremely severe O3 pollution events that last for different days, three definitions are used to identify severe and extremely severe O3 pollution events:

[0070] Definition 1, O3 concentration 60-99 μg / m 3 A severe O3 pollution event lasting for 1 day or more is considered an O3 severe pollution event, with an O3 concentration of ≥100 μg / m 3 An O3 pollution event lasting for 1 day or more is considered an extremely severe O3 pollution event.

[0071] Definition 2: O3 concentration ≥ 60 μg / m 3 Lasts for two days or more and does not reach ≥100 μg / m for two consecutive days 3 For severe O3 pollution events (60-99 μg / m 3 Lasts for two days or more to represent this category), O3 concentration ≥ 100μg / m 3 If it lasts for two days or more, it is PM 2.5 Very serious pollution incident.

[0072] Definition 3: O3 concentration ≥ 60 μg / m 3 Lasts for three days or more and does not reach ≥100 μg / m for three consecutive days 3 For severe O3 pollution events (60-99 μg / m 3 Lasts for three days or more to represent this category), O3 concentration ≥ 100μg / m 3 An O3 pollution event lasting for more than three days is considered an extremely severe O3 pollution event.

[0073] In one embodiment, for S103, calculating a comprehensive score of heavy pollution exposure according to the heavy pollution event includes:

[0074] Under the defined definition of heavy pollution events, the number of days of exposure to heavy pollution events / extremely heavy pollution events of the target population each year from the start time to death or the end of the target time is calculated, and the comprehensive score of heavy pollution exposure each year is calculated using the following formula:

[0075] Score = D h +D e ×5; (1)

[0076] In the formula, Score is the comprehensive score of heavy pollution exposure in a certain year;

[0077] D h It is the number of days of heavy pollution exposure in a year from the start time to the end of death or target time;

[0078] D e It is the number of days of exposure to extremely severe pollution in a year from the start time to the end of death or target time.

[0079] The population with medical records between January 1, 2013 and December 31, 2023 was selected as the target population. Death information was matched for each subject in the target population, and those who died within one year after enrollment were excluded. The number of days of exposure to heavy pollution / very heavy pollution events was calculated for each subject each year after enrollment, and the annual heavy pollution exposure score was calculated according to formula (1).

[0080] In one embodiment, for S104, based on the heavy pollution events and population health data, a fitting model is used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different types of diseases, referring to Figure 4 , the specific method is:

[0081] S104-1, adopting a cohort study design, the target time range starts at the time when all target populations begin to be enrolled, and the target time range ends at the end of the cohort follow-up;

[0082] S104-2, a time-varying COX proportional hazard model was used to quantitatively analyze the chronic exposure-response relationship. The model controlled covariates such as gender, age, and medical history. The chronic exposure-response relationship of heavy pollution exposure to death was obtained by fitting the model. Among them, the model took into account the lag of heavy pollution exposure and obtained the chronic exposure-response relationship with a lag of 1 year, 2 years, and 3 years after heavy pollution exposure. Through stratified analysis, the sensitivity of different specific diseases to heavy pollution events was obtained.

[0083] Specifically, a cohort design and time-varying COX model were used to quantitatively calculate the mortality risk associated with different O3 heavy pollution comprehensive scores. Using R software, the dependent variable introduced a death column (0 = no death, 1 = death), the independent variable was the O3 heavy pollution comprehensive score, and the covariate controlled gender, age, and medical history. The adjusted β value and 95% CI (confidence level) were calculated.

[0084] In one embodiment, for S105, according to the chronic exposure-response relationship between the heavy pollution and the diseases of different diseases and the comprehensive score of heavy pollution exposure, the disease burden related to heavy pollution is calculated by coupling the disease burden, including:

[0085] The disease burden for a certain year is calculated using the following formula:

[0086] BD=(β×Score)×M;(2)

[0087] In the formula, BD is the excess burden of death from a certain disease caused by severe or extremely severe pollution in a certain year;

[0088] β is the coefficient of increased risk of death for every increase of 1 in the comprehensive exposure score to severe pollution;

[0089] Score is the comprehensive score of heavy pollution exposure in a certain year;

[0090] M is the average number of deaths per year from a certain disease during the study period;

[0091] The following formula is used to calculate the average annual disease burden within the target time frame:

[0092] ABD=∑BD / N;(3)

[0093] Where ABD is the average annual excess burden of death from a certain disease caused by severe or extremely severe pollution during the study period;

[0094] ∑BD is the accumulation of BD during the study period;

[0095] N is the number of years in the study period.

[0096] Specifically, the estimated β from Definition 1 (severe or extremely severe O3 pollution events lasting one day or longer), the total number of deaths from cardiovascular disease (or specific diseases) in a certain year within the target time range (representing normal conditions), and the comprehensive score of O3 heavy pollution exposure in a certain year are used to calculate the average annual excess number of deaths from heavy air pollution through formula (2) and formula (3). In one embodiment, for S106, the burden of heavy pollution-related diseases is ranked and a spectrum of sensitive diseases is drawn, including:

[0097] Sort the average annual excess deaths of different specific diseases from high to low, screen diseases with a burden of excess deaths related to heavy pollution, and draw a spectrum of sensitive diseases.

[0098] It should be noted that, although the operations of the method of the present invention are described in a specific order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0099] After introducing the method of the exemplary embodiment of the present invention, next, refer to Figure 5 A device for drawing a spectrum of diseases sensitive to severe air pollution according to an exemplary embodiment of the present invention is introduced.

[0100] The implementation of the device for drawing the spectrum of diseases sensitive to severe atmospheric pollution can refer to the implementation of the above method, and the repeated parts will not be repeated. The terms "module" or "unit" used below can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0101] Based on the same inventive concept, the present invention also proposes a device for drawing a spectrum of diseases sensitive to severe atmospheric pollution, such as Figure 5As shown, the device comprises:

[0102] Data collection module 510, used to collect historical atmospheric environment exposure data and population health data;

[0103] A heavy pollution event identification module 520 is used to identify a plurality of historical heavy pollution events distinguishing concentration and duration according to the historical atmospheric environment exposure data;

[0104] A heavy pollution scoring module 530 is used to calculate a comprehensive heavy pollution exposure score according to the heavy pollution event;

[0105] The chronic exposure-response relationship analysis module 540 is used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases by using a fitting model according to the heavy pollution events and population health data;

[0106] A heavy pollution-related disease burden calculation module 550 is used to calculate the heavy pollution-related disease burden by coupling the disease burden according to the chronic exposure-response relationship between the heavy pollution and the diseases of different diseases and the comprehensive score of heavy pollution exposure;

[0107] The drawing module 560 is used to sort the disease burden related to heavy pollution and draw a spectrum of sensitive diseases.

[0108] It should be noted that although several modules of the device for drawing the spectrum of diseases sensitive to severe atmospheric pollution are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules described above can be concretized in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules for concretization.

[0109] In one embodiment, the data collection module 510 collects historical atmospheric environment exposure data and population health data, including:

[0110] Determine the target time range, wherein the first time period is selected as the target time range according to the feasibility of data collection;

[0111] Collect PM2.5 in the target area by county / city within the target time range. 2.5 , daily / hourly average data of O3, NO2, SO2, CO, temperature and humidity;

[0112] Within the target time frame, information on medical visits of the entire population or the preset target population will be collected, which will at least include the diseases visited, prescribed drugs, length of residence in the area, age, gender, race, and marital status; and within the target time frame, information on death cases of the entire population or the preset target population will be collected, which will at least include the disease causing death.

[0113] In one embodiment, the heavy pollution event identification module 520 calculates a heavy pollution exposure comprehensive score according to the heavy pollution event, including:

[0114] Under the defined definition of heavy pollution events, the number of days of exposure to heavy pollution events / extremely heavy pollution events of the target population each year from the start time to death or the end of the target time is calculated, and the comprehensive score of heavy pollution exposure each year is calculated using the following formula:

[0115] Score = D h +D e ×5;

[0116] In the formula, Score is the comprehensive score of heavy pollution exposure in a certain year;

[0117] D h It is the number of days of heavy pollution exposure in a year from the start time to the end of death or target time;

[0118] D e It is the number of days of exposure to extremely severe pollution in a year from the start time to the end of death or target time.

[0119] In one embodiment, the heavy pollution scoring module 530 identifies multiple heavy pollution events in history by distinguishing concentration and duration based on the historical atmospheric environment exposure data, including:

[0120] Select a key pollutant in the atmosphere as the key pollutant in the definition of a severe pollution event, and set a certain number of concentration division values ​​based on severe air pollution standards and actual conditions;

[0121] Based on the concentration classification value, each day in the study period is divided into no severe pollution events, severe pollution events, and extremely severe pollution events;

[0122] Severe pollution incidents and extremely severe pollution incidents are divided according to the number of days of continuous pollution.

[0123] In one embodiment, the chronic exposure-response relationship analysis module 540 uses a fitting model to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases based on the heavy pollution events and population health data, including:

[0124] A cohort study design was adopted, with the start time of the target time range being the start time of enrollment of all target populations, and the end time of the target time range being the end time of the cohort follow-up;

[0125] The time-varying COX proportional hazard model was used to quantitatively analyze the chronic exposure-response relationship. The model controlled covariates such as gender, age, and medical history. The chronic exposure-response relationship of heavy pollution exposure to death was obtained by fitting the model. Among them, the model took into account the lag of heavy pollution exposure and obtained the chronic exposure-response relationship with a lag of 1 year, 2 years, and 3 years. Through stratified analysis, the sensitivity of different specific diseases to heavy pollution events was obtained.

[0126] In one embodiment, the heavy pollution-related disease burden calculation module 550 calculates the heavy pollution-related disease burden by coupling the disease burden according to the chronic exposure-response relationship between the heavy pollution and the diseases of different diseases and the comprehensive score of heavy pollution exposure, including:

[0127] The disease burden for a certain year is calculated using the following formula:

[0128] BD = (β × Score) × M;

[0129] In the formula, BD is the excess burden of death from a certain disease caused by severe or extremely severe pollution in a certain year;

[0130] β is the coefficient of increased risk of death for every increase of 1 in the comprehensive exposure score to severe pollution;

[0131] Score is the comprehensive score of heavy pollution exposure in a certain year;

[0132] M is the average number of deaths per year from a certain disease during the study period;

[0133] The following formula is used to calculate the average annual disease burden within the target time frame:

[0134] ABD=∑BD / N;

[0135] Where ABD is the average annual excess burden of death from a certain disease caused by severe or extremely severe pollution during the study period;

[0136] ∑BD is the accumulation of BD during the study period;

[0137] N is the number of years in the study period.

[0138] In one embodiment, the drawing module 560 ranks the burden of diseases related to heavy pollution and draws a spectrum of sensitive diseases, including:

[0139] Sort the average annual excess deaths of different specific diseases from high to low, screen diseases with a burden of excess deaths related to heavy pollution, and draw a spectrum of sensitive diseases.

[0140] Based on the above invention concept, Figure 6As shown, the present invention also proposes a computer device 600, including a memory 610, a processor 620, and a computer program 630 stored in the memory 610 and executable on the processor 620, wherein the processor 620 implements the aforementioned method for drawing a spectrum of diseases sensitive to severe atmospheric pollution when executing the computer program 630.

[0141] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the aforementioned method for drawing the spectrum of diseases sensitive to severe atmospheric pollution.

[0142] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements a method for drawing a spectrum of diseases sensitive to severe atmospheric pollution.

[0143] The method and device for drawing a spectrum of diseases sensitive to severe atmospheric pollution proposed in the present invention include a data collection module for collecting historical atmospheric environmental exposure data and human health data; a severe pollution event identification module for identifying multiple severe pollution events that distinguish between concentrations and durations in history based on the historical atmospheric environmental exposure data; a severe pollution scoring module for calculating a comprehensive severe pollution exposure score based on the severe pollution events; a chronic exposure-response relationship analysis module for quantitatively analyzing the chronic exposure-response relationship between severe pollution and different types of diseases using a fitting model based on the severe pollution events and human health data; a calculation module for calculating the severe pollution-related disease burden by coupling the disease burden based on the chronic exposure-response relationship between severe pollution and different types of diseases and the severe pollution exposure comprehensive score; and a drawing module for sorting the severe pollution-related disease burden and drawing a spectrum of sensitive diseases. The technology for mapping diseases sensitive to severe atmospheric pollution implemented by the overall solution can identify multiple severe pollution events in history, and thus derive the chronic exposure-response relationship between severe pollution events of different concentration levels and durations and specific disease outcomes through model fitting, providing evidence for further formulating and revising standards and establishing an early warning system. In addition, the present invention is coupled with a disease burden model to map a spectrum of sensitive diseases, which can provide scientific advice for responses such as the allocation and deployment of medical staff when severe pollution weather occurs.

[0144] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of laws and regulations.

[0145] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] The present invention is described with reference to flowcharts and / or block diagrams of methods and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0147] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0149] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for drawing a spectrum of diseases sensitive to severe atmospheric pollution, characterized in that: include: Collect historical atmospheric environmental exposure data and population health data; Based on the historical atmospheric environmental exposure data, identify multiple historical heavy pollution events distinguishing concentrations and durations; Calculate a comprehensive heavy pollution exposure score based on the heavy pollution events described; Based on the heavy pollution events and population health data, the fitting model was used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases; Based on the chronic exposure-response relationship between the heavy pollution and different diseases and the comprehensive score of heavy pollution exposure, the disease burden related to heavy pollution is calculated by coupling the disease burden; Rank the burden of diseases related to heavy pollution and draw a spectrum of sensitive diseases.

2. The method according to claim 1, characterized in that Collect historical atmospheric environmental exposure data and population health data, including: Determine the target time range, wherein the first time period is selected as the target time range according to the feasibility of data collection; Collect PM2.5 in the target area by county / city within the target time range. 2.5 , daily / hourly average data of O3, NO2, SO2, CO, temperature and humidity; Within the target time frame, information on medical visits of the entire population or the preset target population will be collected, which will at least include the diseases visited, prescribed drugs, length of residence in the area, age, gender, race, and marital status; and within the target time frame, information on death cases of the entire population or the preset target population will be collected, which will at least include the disease causing death.

3. The method according to claim 1, characterized in that The comprehensive score of heavy pollution exposure is calculated based on the heavy pollution incidents, including: Under the defined definition of heavy pollution events, the number of days of exposure to heavy pollution events / extremely heavy pollution events of the target population each year from the start time to death or the end of the target time is calculated, and the comprehensive score of heavy pollution exposure each year is calculated using the following formula: Score=D h +D e ×5; In the formula, Score is the comprehensive score of heavy pollution exposure in a certain year; D h It is the number of days of heavy pollution exposure in a year from the start time to the end of death or target time; D e It is the number of days of exposure to extremely severe pollution in a year from the start time to the end of death or target time.

4. The method according to claim 1, characterized in that: Based on the historical atmospheric environmental exposure data, multiple historical heavy pollution events with different concentrations and durations were identified, including: Select a key pollutant in the atmosphere as the key pollutant in the definition of a severe pollution event, and set a certain number of concentration division values ​​based on severe air pollution standards and actual conditions; Based on the concentration classification value, each day in the study period is divided into no severe pollution events, severe pollution events, and extremely severe pollution events; Severe pollution incidents and extremely severe pollution incidents are divided according to the number of days of continuous pollution.

5. The method according to claim 1, characterized in that: Based on the heavy pollution events and population health data, a fitting model was used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different types of diseases, including: A cohort study design was adopted, with the start time of the target time range being the start time of enrollment of all target populations, and the end time of the target time range being the end time of the cohort follow-up; The time-varying COX proportional hazard model was used to quantitatively analyze the chronic exposure-response relationship. The model controlled covariates such as gender, age, and medical history. The chronic exposure-response relationship of heavy pollution exposure to death was obtained by fitting the model. Among them, the model took into account the lag of heavy pollution exposure and obtained the chronic exposure-response relationship with a lag of 1 year, 2 years, and 3 years. Through stratified analysis, the sensitivity of different specific diseases to heavy pollution events was obtained.

6. The method according to claim 1, characterized in that Based on the chronic exposure-response relationship between the heavy pollution and different diseases and the comprehensive score of heavy pollution exposure, the disease burden related to heavy pollution is calculated by coupling the disease burden, including: The disease burden for a certain year is calculated using the following formula: BD = (β × Score) × M; In the formula, BD is the excess burden of death from a certain disease caused by severe or extremely severe pollution in a certain year; β is the coefficient of increased risk of death for every increase of 1 in the comprehensive exposure score to severe pollution; Score is the comprehensive score of heavy pollution exposure in a certain year; M is the average number of deaths per year from a certain disease during the study period; The following formula is used to calculate the average annual disease burden within the target time frame: ABD=ΣBD / N; Where ABD is the average annual excess burden of death from a certain disease caused by severe or extremely severe pollution during the study period; ∑BD is the accumulation of BD during the study period; N is the number of years in the study period.

7. The method according to claim 1, characterized in that Ranking the burden of diseases related to heavy pollution and mapping out the spectrum of sensitive diseases, including: Sort the average annual excess deaths of different specific diseases from high to low, screen diseases with a burden of excess deaths related to heavy pollution, and draw a spectrum of sensitive diseases.

8. A device for drawing a spectrum of diseases sensitive to severe atmospheric pollution, characterized in that: include: Data collection module, used to collect historical atmospheric environmental exposure data and population health data; A heavy pollution event identification module, used to identify multiple heavy pollution events in history that distinguish concentrations and durations based on the historical atmospheric environment exposure data; A heavy pollution scoring module, used to calculate a comprehensive heavy pollution exposure score based on the heavy pollution event; A chronic exposure-response relationship analysis module is used to quantitatively analyze the chronic exposure-response relationship between heavy pollution and different diseases using a fitting model based on the heavy pollution events and population health data; A heavy pollution-related disease burden calculation module is used to calculate the heavy pollution-related disease burden by coupling the disease burden based on the chronic exposure-response relationship between the heavy pollution and different diseases and the heavy pollution exposure comprehensive score; A drawing module is used to rank the burden of diseases related to heavy pollution and draw the spectrum of sensitive diseases.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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