Multi-dimensional analysis control method for informatization system

Abstract

The invention relates to the technical field of data analysis, and discloses a multi-dimensional analysis control method for an informatization system, and the method comprises the steps: displaying the spatial distribution of a definite case and a suspected case in a key monitoring region; dividing the key monitoring area into a plurality of sub-areas, respectively constructing a judgment time sequence of each sub-area, and carrying out risk sorting on the sub-areas according to the parameter number of the judgment time sequences; sequencing the parameters in each judgment time sequence from first to second according to time to obtain a case number with the earliest judgment time, and drawing a contact personnel network diagram according to the contact chain; carrying out risk numbering on the non-definite cases and the non-suspected cases according to the contact personnel network diagram, and adjusting a risk sequence according to the risk numbering number of the sub-regions; and adjusting the risk sequence of the sub-regions according to the environmental parameters and the disinfection times to obtain a final risk sequence of the sub-regions. According to the invention, accurate monitoring and dynamic adjustment of epidemic situations of infectious diseases are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and more particularly, to a multi-dimensional analysis and control method for an information system. Background Art

[0003] In recent years, the rapid development of information technology has provided new solutions for infectious disease prevention and control. With the help of advanced means such as big data analysis, geographic information system (GIS) technology, Internet of Things devices, sensors, and artificial intelligence, the accuracy and efficiency of epidemic monitoring have been significantly improved. However, existing infectious disease information systems mainly focus on static monitoring, lacking in-depth analysis and dynamic adjustment of multi-dimensional data during the epidemic process.

[0004] Therefore, it is necessary to provide a multi-dimensional analysis and control method for an information system to solve the problem that existing infectious disease information systems lack in-depth analysis and dynamic adjustment of multi-dimensional epidemic data. Summary of the Invention

[0005] In view of this, the present invention proposes a multi-dimensional analysis and control method for an information system, aiming to solve the problem that existing infectious disease information systems lack in-depth analysis and dynamic adjustment of multi-dimensional epidemic data.

[0006] The present invention proposes a multi-dimensional analysis and control method for an information system, including:

[0007] Obtain the geographical location information of confirmed cases and suspected cases, divide key monitoring areas according to the geographical location information, and use GIS technology to display the spatial distribution of confirmed cases and suspected cases in the key monitoring areas;

[0008] Divide the key monitoring areas into several sub-areas, number the sub-areas, number the confirmed cases and suspected cases in the sub-areas, collect the determination times of the confirmed cases and suspected cases, respectively construct the determination time series of each sub-area, and rank the sub-areas according to the number of parameters in the determination time series;

[0009] Sort the parameters in each determination time series in chronological order, compare the first parameters in each determination time series to obtain the case number with the earliest determination time, collect the close contacts of this case to form a contact chain, and draw a contact person network diagram according to the contact chain;

[0010] Assign risk numbers to non-confirmed cases and non-suspected cases according to the contact person network diagram, determine whether to adjust the sub-area risk ranking according to the number of people with risk numbers in the sub-area, and if it is determined that adjustment is needed, adjust the risk ranking according to the number of people with risk numbers in the sub-area;

[0011] Collect the environmental parameters of each sub-region, and determine whether to perform a secondary adjustment on the risk ranking of the sub-region according to the environmental parameters. If it is determined to perform a secondary adjustment, adjust the risk ranking of the sub-region according to the environmental parameters and the number of disinfection times to obtain the final risk ranking of the sub-region; wherein, the environmental parameters include temperature parameters and light intensity.

[0012] Further, when obtaining the geographical location information of confirmed cases and suspected cases and dividing the key monitoring areas according to the geographical location information, it includes:

[0013] Obtain the geographical location information of confirmed cases and suspected cases, and visually display the case distribution of each confirmed case and suspected case on the map;

[0014] Connect the geographical locations of the outermost confirmed cases and suspected cases on the map to obtain a preliminary high-risk area;

[0015] Set a safety distance, and expand the outer edge of the preliminary high-risk area outward to the safety distance to obtain a high-risk area.

[0016] Further, when using GIS technology to display the spatial distribution of confirmed cases and suspected cases in the key monitoring area, it includes:

[0017] Utilize GIS technology to mark the geographical locations of each confirmed case and suspected case on the map, distinguish and mark according to confirmed cases and suspected cases, and display the longitude and latitude coordinates of confirmed cases and suspected cases at the corresponding positions on the map;

[0018] Real-time update the longitude and latitude coordinates of confirmed cases and suspected cases on the map.

[0019] Further, when dividing the key monitoring area into several sub-regions, numbering the sub-regions, and numbering the confirmed cases and suspected cases in the sub-regions, it includes:

[0020] Evenly divide the key monitoring area into multiple sub-regions according to the area, and number the sub-regions in the same direction sequence;

[0021] Number the confirmed cases and suspected cases in the sub-regions in the same direction sequence according to the longitude and latitude coordinates.

[0022] Further, when collecting the determination times of the confirmed cases and suspected cases, respectively constructing the determination time series of each sub-region, and performing risk ranking on the sub-regions according to the number of parameters of the determination time series, it includes:

[0023] Construct a judgment time series \(A_i=(q_1,q_2,\cdots,q_n,y_1,y_2,\cdots,y_n)\) for each sub-region, where \(A_i\) represents the \(i\)-th sub-region, \(q_j\) (\(j = 1,2,\cdots,n\)) represents the judgment time of the confirmed case numbered \(j\), and \(y_k\) (\(k = 1,2,\cdots,n\)) represents the judgment time of the suspected case numbered \(k\).

[0024] According to the number of parameters of the judgment time series, rank the risks of the corresponding sub-regions from high to low. The sub-region corresponding to the judgment time series with the largest number of parameters has the highest risk.

[0025] Further, when risk-numbering non-confirmed cases and non-suspected cases according to the contact personnel network diagram and judging whether to adjust the risk ranking of the sub-region according to the number of people with risk numbers in the sub-region, it includes:

[0026] Set the risk tolerance number of people. If the number of people with risk numbers in the sub-region is less than the risk tolerance number of people, do not adjust the risk ranking of the sub-region.

[0027] If the number of people with risk numbers in the sub-region is greater than or equal to the risk tolerance number of people, adjust the risk ranking of the sub-region.

[0028] Further, when it is judged that adjustment is needed and the risk ranking is adjusted according to the number of people with risk numbers in the sub-region, it includes:

[0029] Calculate the equivalent number of people in each sub-region. The equivalent number of people = the number of people with risk numbers in the sub-region / 2.

[0030] Calculate the sum of the equivalent number of people in the sub-region and the number of parameters of the judgment time series, and re-rank the sub-regions from high to low according to the sum values of each sub-region.

[0031] Further, when collecting the environmental parameters of each sub-region and judging whether to make a secondary adjustment to the risk ranking of the sub-region according to the environmental parameters, it includes:

[0032] Set the number of days of collection, and calculate the average daily temperature and average daily light intensity of the sub-region within the collection days.

[0033] Set the minimum temperature and the minimum light intensity. If the average daily temperature is less than or equal to the minimum temperature, and the average daily light intensity is less than or equal to the minimum light intensity, then judge to make a secondary adjustment to the risk ranking of the sub-region.

[0034] Otherwise, judge not to make a secondary adjustment to the risk ranking of the sub-region.

[0035] Further, when it is determined to perform secondary adjustment and the risk ranking of the sub-regions is adjusted according to the environmental parameters and the number of disinfections to obtain the final risk ranking of the sub-regions, it includes:

[0036] Collect the number of disinfections of each sub-region within the collection days, calculate the average daily disinfection times of the collection days, calculate the adjustment value according to the average daily temperature, average daily light intensity and average daily disinfection times, and adjust the risk ranking of the sub-regions according to the adjustment value;

[0037] Set a standard adjustment value, and calculate the adjustment value through the following formula:

[0038] T = T0(1 + w1 + w2 + w3);

[0039] In the above formula, T represents the adjustment value, T0 represents the standard adjustment value, w1 represents the average daily temperature adjustment coefficient, w2 represents the average daily light intensity adjustment coefficient, w3 represents the average daily disinfection times adjustment coefficient, where the value ranges of w1, w2 and w3 are all 0 - 0.5.

[0040] Further, when it is determined to perform secondary adjustment and the risk ranking of the sub-regions is adjusted according to the environmental parameters and the number of disinfections to obtain the final risk ranking of the sub-regions, it also includes:

[0041] Set a first adjustment value and a second adjustment value, where the first adjustment value is less than the second adjustment value;

[0042] If the adjustment value is less than the first adjustment value, then advance the risk ranking of the sub-region by one position;

[0043] If the adjustment value is greater than or equal to the first adjustment value and less than or equal to the second adjustment value, then advance the risk ranking of the sub-region by two positions;

[0044] If the adjustment value is greater than the second adjustment value, then advance the risk ranking of the sub-region by three positions.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows: By comprehensively considering geographical location, case time series, contact chain analysis, and environmental factors, the present invention realizes precise monitoring and dynamic adjustment of infectious disease epidemics. First, the GIS technology is used to display the spatial distribution of confirmed and suspected cases, which can intuitively identify high-risk areas of the epidemic, thereby providing a scientific basis for epidemic prevention and control. By dividing the key monitoring areas into multiple sub-areas and numbering them, the risk assessment can be refined, and differential management can be implemented according to the epidemic situation in different sub-areas. Further, the analysis of the determination time series of cases and the contact chain helps to track close contacts and form a personnel network diagram, providing support for the tracking of the source of infection and the formulation of prevention and control strategies. At the same time, according to the environmental parameters and the number of disinfections, a secondary risk ranking adjustment is carried out, which can further optimize the risk assessment results, timely adjust the epidemic prevention and control measures, and improve the prevention and control effect. Through this dynamic adjustment mechanism, the changes in the epidemic can be responded to in real time, ensuring the accuracy and efficiency of the prevention and control measures. In addition, through multi-dimensional risk ranking, refined management of different regions and personnel can be carried out, thereby effectively suppressing the spread of the epidemic and ensuring public health safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0047] Figure 1 It is a flowchart of a multi-dimensional analysis and control method for an information system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0049] In some embodiments of the present application, referring to Figure 1 as shown, this embodiment provides a multi-dimensional analysis and control method for an information system, including the following steps:

[0050] S100. Obtain the geographical location information of confirmed cases and suspected cases, divide the key monitoring areas according to the geographical location information, and use GIS technology to display the spatial distribution of confirmed cases and suspected cases in the key monitoring areas;

[0051] S200. Divide the key monitoring areas into several sub-areas, number the sub-areas, number the confirmed cases and suspected cases in the sub-areas, collect the determination time of the confirmed cases and suspected cases, respectively construct the determination time series of each sub-area, and rank the risks of the sub-areas according to the number of parameters in the determination time series;

[0052] S300. Sort the parameters in each determination time series in chronological order, compare the first parameters in each determination time series to obtain the case number with the earliest determination time, collect the close contacts of this case to form a contact chain, and draw a contact personnel network diagram according to the contact chain;

[0053] S400. Assign risk numbers to non-confirmed cases and non-suspected cases according to the contact personnel network diagram, judge whether to adjust the risk ranking of the sub-areas according to the number of people with risk numbers in the sub-areas, and if it is judged that adjustment is needed, adjust the risk ranking according to the number of people with risk numbers in the sub-areas;

[0054] S500. Collect the environmental parameters of each sub-area, judge whether to make a secondary adjustment to the risk ranking of the sub-areas according to the environmental parameters, and if it is judged to make a secondary adjustment, adjust the risk ranking of the sub-areas according to the environmental parameters and the number of disinfection times to obtain the final risk ranking of the sub-areas; wherein, the environmental parameters include temperature parameters and light intensity.

[0055] It can be understood that the present invention realizes the precise monitoring and dynamic adjustment of the infectious disease epidemic situation by comprehensively considering geographical location, case time series, contact chain analysis and environmental factors. First of all, using GIS technology to display the spatial distribution of confirmed and suspected cases can visually identify high-risk areas of the epidemic, thus providing a scientific basis for epidemic prevention and control. By dividing the key monitoring areas into multiple sub-areas and numbering them, the risk assessment can be refined, and differential management can be implemented for the epidemic situations in different sub-areas. Further, the analysis of the determination time series of cases and the contact chain helps to track close contacts and form a personnel network diagram, providing support for the tracking of the source of infection and the formulation of prevention and control strategies. At the same time, the secondary risk ranking adjustment based on environmental parameters and the number of disinfection times can further optimize the risk assessment results, timely adjust the epidemic prevention and control measures, and improve the prevention and control effect. Through this dynamic adjustment mechanism, it is possible to respond to the changes in the epidemic situation in real time, ensure the accuracy and efficiency of prevention and control measures. In addition, through multi-dimensional risk ranking, refined management can be carried out for different regions and personnel, thereby effectively suppressing the spread of the epidemic and ensuring public health safety.

[0056] Specifically, the area can be a cabin, and the area number can be the cabin number, so as to count the cabin information. Combining the case number and the risk number can facilitate querying the statistical quantity of cabin cases.

[0057] In some embodiments of the present application, when obtaining the geographical location information of confirmed cases and suspected cases and dividing the key monitoring areas according to the geographical location information, it includes:

[0058] Obtain the geographical location information of confirmed cases and suspected cases, and visually display the case distribution of each confirmed case and suspected case on the map;

[0059] Connect the geographical locations of the outermost confirmed cases and suspected cases on the map to obtain a preliminary high-risk area;

[0060] Set a safety distance, and expand the outer edge of the preliminary high-risk area outward to the safety distance to obtain a high-risk area.

[0061] It can be understood that by obtaining the geographical location information of confirmed cases and suspected cases and visually displaying them on the map, the spatial distribution of cases can be intuitively presented, helping to quickly identify high-incidence areas of the epidemic. Connecting the geographical locations of confirmed cases and suspected cases and determining the preliminary high-risk area helps to identify possible sources of epidemic spread and provides a basis for subsequent prevention and control measures. By setting a safety distance and expanding the preliminary high-risk area to the safe area, the further spread of the epidemic can be prevented in advance, ensuring that prevention and control measures cover a wider range of potential risk areas. This method makes epidemic monitoring more accurate and flexible, helps to timely adjust resources and emergency response measures, thereby effectively reducing the risk of epidemic spread and ensuring public health and safety.

[0062] In some embodiments of the present application, when using GIS technology to display the spatial distribution of confirmed cases and suspected cases in key monitoring areas, it includes:

[0063] Using GIS technology, mark the geographical location of each confirmed case and suspected case on the map, and according to the distinction between confirmed cases and suspected cases, display the longitude and latitude coordinates of confirmed cases and suspected cases at the corresponding positions on the map;

[0064] Real-time update the longitude and latitude coordinates of confirmed cases and suspected cases on the map.

[0065] It is understandable that using GIS technology to display the spatial distribution of confirmed cases and suspected cases in key monitoring areas has significant benefits. First of all, GIS technology can visually mark the geographical location information of each confirmed case and suspected case on the map, and distinguish between confirmed cases and suspected cases through different markings, which helps to quickly identify the specific location of the epidemic and potential high-risk areas. This visualization method allows public health personnel and decision-makers to view the distribution of cases at a glance, timely grasp the epidemic situation, and provide accurate data support for formulating targeted prevention and control measures. Secondly, by updating the longitude and latitude coordinates of cases in real time, GIS technology can ensure that the epidemic monitoring system always reflects the latest case data, avoiding the failure of prevention and control measures or misallocation of resources caused by information lag. The real-time update function enables monitoring personnel to keep abreast of the development trend of the epidemic at any time, especially in the initial stage of an outbreak, quickly locate the aggregation areas of confirmed and suspected cases, and take timely measures such as isolation and disinfection to prevent the spread of the epidemic. In short, using GIS technology for spatial distribution display not only improves the efficiency of epidemic monitoring, but also provides powerful technical support for public health management, helping to ensure public health and safety.

[0066] In some embodiments of the present application, when dividing the key monitoring area into several sub-areas, numbering the sub-areas, and numbering the confirmed cases and suspected cases in the sub-areas, it includes:

[0067] Dividing the key monitoring area into multiple sub-areas evenly according to the area, and numbering the sub-areas in sequence in the same direction;

[0068] Numbering the confirmed cases and suspected cases in the sub-areas in sequence in the same direction according to the longitude and latitude coordinates.

[0069] It is understandable that dividing the key monitoring area into multiple uniform sub - regions and numbering each sub - region has significant management and analysis advantages. First of all, uniformly dividing the sub - regions can ensure the comprehensiveness and balance of epidemic monitoring within the region, avoiding monitoring blind spots or uneven resource allocation caused by some areas being too concentrated or too dispersed. This method can ensure that each sub - region has equal importance in monitoring and prevention and control, thus providing data support for refined epidemic prevention and control measures. Secondly, numbering the sub - regions and case numbers in the same direction sequence can form a standardized data structure in the system, facilitating subsequent data management and rapid retrieval. Whether analyzing the time series of cases or tracing close contacts, this standardized numbering method can greatly improve the integration and operability of information. In addition, the unity of the numbering system facilitates subsequent automated analysis, reducing the complexity and potential errors of human intervention. Numbering the confirmed cases and suspected cases within the sub - region in the order of longitude and latitude coordinates makes the spatial distribution of case data clearer, helping to track the transmission path of cases and determine potential high - risk areas. This method can support the accurate positioning of cases and suspected cases, thereby improving the speed and accuracy of the prevention and control response. Generally speaking, uniformly dividing the sub - regions and numbering them provides strong data support for the precise management and real - time adjustment of epidemic prevention and control, helping to identify risks in a timely manner and implement targeted measures.

[0070] In some embodiments of the present application, when collecting the determination times of confirmed cases and suspected cases, respectively constructing the determination time series of each sub - region, and performing risk ranking on the sub - regions according to the number of parameters of the determination time series, it includes:

[0071] Construct a determination time series Ai=(q1, q2,..., qn, y1, y2,..., yn) with the sub - region as the unit, where Ai represents the i - th sub - region, qj (j = 1, 2,..., n) represents the determination time of the confirmed case numbered j, and yk (k = 1, 2,..., n) represents the determination time of the suspected case numbered k;

[0072] According to the number of parameters of the determination time series, perform risk ranking on the sub - regions corresponding to the determination time series from high to low, and the sub - region corresponding to the determination time series with the largest number of parameters has the highest risk.

[0073] It is understandable that by constructing a judgment time series for each sub-region and ranking the risks according to the judgment times of confirmed cases and suspected cases in the series, the epidemic risks of each sub-region can be effectively quantified and evaluated. Taking the judgment times of confirmed cases and suspected cases in each sub-region as components of the time series not only helps to accurately track the occurrence order of cases but also reveals the potential trend of the spread of the epidemic. Specifically, the judgment times of confirmed cases and suspected cases reflect the time context of the development of the epidemic. The earlier the judgment time of a case, the more likely it indicates that the epidemic in that region has spread for some time and the higher the risk. Ranking the sub-regions according to the number of parameters in the judgment time series can achieve accurate assessment of epidemic risks. Ranking the sub-regions from high to low in terms of risk helps prevention and control personnel to prioritize high-risk regions, timely adjust resource allocation and prevention and control strategies, and thus more effectively prevent the spread of the epidemic. In addition, this method can also provide a specific time frame for decision-makers to help formulate more scientific prevention and control plans and ensure a quick response in a short time. Therefore, through the construction and ranking of the judgment time series, strong data support can be provided for the refined management and dynamic prevention and control of the epidemic.

[0074] In some embodiments of the present application, when risk numbers are assigned to non-confirmed cases and non-suspected cases according to the contact personnel network diagram and it is determined whether to adjust the risk ranking of the sub-region based on the number of people with risk numbers in the sub-region, it includes:

[0075] Set a risk tolerance number. If the number of people with risk numbers in the sub-region is less than the risk tolerance number, the risk ranking of the sub-region is not adjusted;

[0076] If the number of people with risk numbers in the sub-region is greater than or equal to the risk tolerance number, the risk ranking of the sub-region is adjusted.

[0077] It is understandable that setting the risk tolerance number and judging whether to adjust the risk ranking according to the number of people with risk numbers in the sub-region can effectively avoid overreaction or unnecessary adjustments, ensuring the accuracy and rationality of prevention and control measures. By setting the risk tolerance number, when the number of people with risk numbers in the sub-region is small, it indicates that the potential risk in this region is relatively low. At this time, there is no need to adjust the risk ranking, avoiding resource waste and management chaos. Such a setting helps to maintain the stability of the epidemic prevention and control and ensure that resources are concentrated in truly high-risk areas. On the other hand, when the number of people with risk numbers in the sub-region reaches or exceeds the set risk tolerance number, it indicates that the risk in this region is high and there may be a hidden danger of transmission and spread. Therefore, it is necessary to adjust the risk ranking in a timely manner. This dynamic adjustment method can help prevention and control personnel identify potential threats of the epidemic in a timely manner and respond quickly, ensuring that high-risk areas are given priority attention, so as to allocate prevention and control resources more scientifically. Generally speaking, through reasonable setting and adjustment methods of the risk tolerance number, the efficiency and accuracy of epidemic prevention and control can be improved, ensuring the effectiveness and rationality of measures.

[0078] In some embodiments of the present application, when it is determined that adjustment is needed and the risk ranking is adjusted according to the number of people with risk numbers in the sub-region, it includes:

[0079] Calculate the equivalent number of people in each sub-region, where the equivalent number of people = the number of people with risk numbers in the sub-region / 2;

[0080] Calculate the sum value of the equivalent number of people in the sub-region and the number of parameters in the determination time series, and re-rank the sub-regions from high to low according to the sum values of each sub-region from more to less.

[0081] It is understandable that by calculating the "equivalent number of people" in each sub-region and combining the number of parameters in the determination time series to adjust the risk ranking, the epidemic risks of each sub-region can be evaluated more scientifically. The calculation method of the equivalent number of people uses half of the number of people with risk numbers as a reference. This setting makes the risk assessment more balanced. At the same time, the combination of the equivalent number of people and the number of parameters in the determination time series provides a comprehensive risk assessment index. Through this comprehensive ranking method, the risk levels of each sub-region can be ranked more accurately, ensuring that high-risk areas are given priority attention and timely adjusting prevention and control resources and measures. Based on the comprehensive assessment of the equivalent number of people and the determination time series, the risk ranking can be dynamically adjusted, thus providing a scientific basis for prevention and control decisions. This method can reduce human bias, improve the rationality and scientificity of risk ranking, and further optimize the epidemic prevention and control methods and resource allocation.

[0082] In some embodiments of the present application, when collecting the environmental parameters of each sub-region and judging whether to make a secondary adjustment to the risk ranking of the sub-region, it includes:

[0083] Set the number of days for data collection, and calculate the average daily temperature and average daily light intensity of the sub-region within the number of days for data collection;

[0084] Set the minimum temperature and the minimum light intensity. If the average daily temperature is less than or equal to the minimum temperature and the average daily light intensity is less than or equal to the minimum light intensity, then it is determined that the risk ranking of the sub-region is adjusted twice;

[0085] Otherwise, it is determined that the risk ranking of the sub-region is not adjusted twice.

[0086] It can be understood that by collecting the environmental parameters of each sub-region, such as the average daily temperature and the average daily light intensity, and judging whether to perform a secondary risk ranking adjustment according to the set minimum temperature and minimum light intensity, the epidemic risk can be evaluated more accurately in combination with environmental factors. Environmental parameters have an important impact on virus transmission. For example, low temperature and weak light conditions may provide favorable conditions for virus survival and transmission. Therefore, in this case, a secondary adjustment of the risk ranking helps to identify potential high-risk areas in a timely manner. This dynamic adjustment method can adjust the prevention and control methods according to the actual environmental changes, improve the response ability, and avoid missing the prevention and control opportunity due to changes in environmental conditions. In addition, setting the minimum values of temperature and light intensity as the judgment basis avoids excessive sensitivity to fluctuations in environmental factors, ensuring the rationality and stability of the risk ranking adjustment. This method reduces the interference of human judgment and enhances the scientific nature of risk assessment. Through the real-time monitoring and secondary adjustment of environmental parameters, it can ensure that the epidemic prevention and control measures match the actual situation, further improve the prevention and control efficiency, and reduce the possibility of epidemic spread.

[0087] In some embodiments of the present application, if it is determined to perform a secondary adjustment, when adjusting the risk ranking of the sub-region according to the environmental parameters and the number of disinfection times to obtain the final risk ranking of the sub-region, it includes:

[0088] Collect the number of disinfection times of each sub-region within the number of days for data collection, calculate the average daily disinfection times of the number of days for data collection, calculate the adjustment value according to the average daily temperature, average daily light intensity and average daily disinfection times, and adjust the risk ranking of the sub-region according to the adjustment value;

[0089] Set the standard adjustment value, and calculate the adjustment value through the following formula:

[0090] T = T0(1 + w1 + w2 + w3);

[0091] In the above formula, T represents the adjustment value, T0 represents the standard adjustment value, w1 represents the average daily temperature adjustment coefficient, w2 represents the average daily light intensity adjustment coefficient, w3 represents the average daily disinfection times adjustment coefficient, where the value ranges of w1, w2 and w3 are all 0 - 0.5.

[0092] It is understandable that by combining environmental parameters and the number of disinfections for secondary risk ranking adjustment, a more comprehensive and accurate risk assessment can be achieved. The number of disinfections, as an important factor in controlling the spread of the epidemic, can effectively reduce the survival and spread of the virus, especially in high-risk areas. Calculating the average daily number of disinfections and considering it together with environmental parameters helps to dynamically evaluate the actual risk level of sub-regions. This method not only improves the accuracy of epidemic prevention and control but also can flexibly respond to changes under different environmental and disinfection conditions. Using standard adjustment values and adjustment coefficients further refines the risk ranking. By setting the adjustment coefficient, the influence degree of different factors on the risk ranking can be controlled, avoiding the over-influence of a single factor on the ranking result. In addition, the calculation formula of the adjustment value is flexible and can be adjusted according to the actual situation to ensure that the risk assessment of each sub-region always matches the current environmental conditions. This comprehensive adjustment mechanism helps to allocate prevention and control resources more efficiently and improve the response speed and accuracy of epidemic prevention and control.

[0093] In some embodiments of the present application, when it is determined to perform secondary adjustment and the risk ranking of the sub-region is adjusted according to the environmental parameters and the number of disinfections to obtain the final risk ranking of the sub-region, it further includes:

[0094] Set a first adjustment value and a second adjustment value, where the first adjustment value is less than the second adjustment value;

[0095] If the adjustment value is less than the first adjustment value, advance the risk ranking of the sub-region by one position;

[0096] If the adjustment value is greater than or equal to the first adjustment value and less than or equal to the second adjustment value, advance the risk ranking of the sub-region by two positions;

[0097] If the adjustment value is greater than the second adjustment value, advance the risk ranking of the sub-region by three positions.

[0098] It is understandable that by setting the first adjustment value and the second adjustment value and flexibly adjusting the risk ranking according to the size of the adjustment value, the epidemic risk of the sub-region can be more accurately reflected. This method ensures that regions with different risk levels can be adjusted in a timely manner according to the actual situation by gradually increasing the risk ranking, avoiding over-reaction or under-reaction in prevention and control. For example, when the adjustment value is less than the first adjustment value, it indicates a lower risk and only a small adjustment is needed; while when the adjustment value is close to or exceeds the second adjustment value, it indicates a higher risk and more stringent prevention and control measures need to be taken to improve the risk ranking. This hierarchical adjustment mechanism has high flexibility and adaptability and can respond in a timely manner according to different environmental changes and prevention and control requirements to ensure the efficient allocation of prevention and control resources. At the same time, the clear adjustment criteria (such as advancing by one position, two positions or three positions) avoid errors caused by subjective judgment, enhance the scientificity and fairness of risk assessment, help to optimize epidemic prevention and control strategies, and improve the overall prevention and control effect.

[0099] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can 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.) that contain computer-usable program code.

[0100] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0101] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: still can modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A multi-dimensional analysis and control method for an information system, characterized in that: include: Obtain geographic location information of confirmed cases and suspected cases, divide key monitoring areas according to the geographic location information, and use GIS technology to display the spatial distribution of confirmed cases and suspected cases in the key monitoring areas; Divide the key monitoring area into several sub-areas, number the sub-areas, number the confirmed cases and suspected cases in the sub-areas, collect the determination time of the confirmed cases and suspected cases, respectively construct the determination time series of each sub-area, and rank the sub-areas by risk according to the number of parameters of the determination time series; Sort the parameters in each of the determination time series from earliest to latest according to time, compare the first parameter in each determination time series, obtain the case number with the earliest determination time, collect the close contacts of the case to form a contact chain, and draw a contact person network diagram based on the contact chain; According to the contact person network diagram, non-confirmed cases and non-suspected cases are risk-numbered, and the risk ranking of the sub-region is determined based on the number of people with risk numbers in the sub-region. If it is determined that adjustment is required, the risk ranking is adjusted based on the number of people with risk numbers in the sub-region; Collect environmental parameters of each sub-area, and determine whether to make a secondary adjustment to the risk ranking of the sub-area based on the environmental parameters. If it is determined that a secondary adjustment is required, adjust the risk ranking of the sub-area based on the environmental parameters and the number of disinfections to obtain a final sub-area risk ranking; wherein the environmental parameters include temperature parameters and light intensity.

2. The multi-dimensional analysis control method for an information system according to claim 1, characterized in that: The obtaining of geographical location information of confirmed cases and suspected cases and dividing key monitoring areas according to the geographical location information includes: Obtain the geographic location information of confirmed cases and suspected cases, and visualize the case distribution of each confirmed case and suspected case on the map; Connect the geographical locations of the confirmed cases and suspected cases at the outermost edge of the map to obtain the high-risk initial area; Set a safety distance and expand the outer edge of the high-risk initial area outward to the safety distance to obtain a high-risk area.

3. The multi-dimensional analysis control method for an information system according to claim 2, characterized in that: Use GIS technology to display the spatial distribution of confirmed cases and suspected cases in the key monitoring areas, including: Using GIS technology, the geographical location of each confirmed case and suspected case is marked on the map, and the latitude and longitude coordinates of the confirmed cases and suspected cases are displayed at the corresponding positions on the map; The latitude and longitude coordinates of confirmed and suspected cases are updated in real time on the map.

4. The multi-dimensional analysis control method for an information system according to claim 3, characterized in that: The step of dividing the key monitoring area into a plurality of sub-areas, numbering the sub-areas, and numbering the confirmed cases and suspected cases in the sub-areas includes: The key monitoring area is evenly divided into a plurality of sub-areas according to the area, and the sub-areas are numbered in the same direction order; Confirmed cases and suspected cases in the sub-areas are numbered sequentially in the same direction according to their latitude and longitude coordinates.

5. The multi-dimensional analysis control method for an information system according to claim 4, characterized in that: The collecting of the determination time of the confirmed cases and the suspected cases, respectively constructing a determination time series for each sub-region, and ranking the sub-regions by risk according to the number of parameters of the determination time series, includes: Construct the judgment time series Ai=(q1, q2, …, qn, y1, y2, …, yn) in sub-region units, where Ai represents the i-th sub-region, qj (j=1, 2, …, n) represents the judgment time of the j-th confirmed case, and yk (k=1, 2, …, n) represents the judgment time of the k-th suspected case; According to the number of parameters of the determination time series, the sub-regions corresponding to the determination time series are ranked from high to low in risk, and the sub-region corresponding to the determination time series with the largest number of parameters has the highest risk.

6. The multi-dimensional analysis control method for an information system according to claim 5, characterized in that: The step of assigning risk numbers to non-confirmed cases and non-suspected cases according to the contact person network diagram, and determining whether to adjust the sub-region risk ranking according to the number of risk numbered people in the sub-region, includes: The risk tolerance number is set. If the number of risk numbered people in the sub-area is less than the risk tolerance number, the risk ranking of the sub-area will not be adjusted; If the number of people with risk numbers in the sub-area is greater than or equal to the number of people with risk tolerance, the risk ranking of the sub-area is adjusted.

7. The multi-dimensional analysis control method for an information system according to claim 6, characterized in that: If it is determined that adjustment is needed, the risk ranking is adjusted according to the number of people with sub-region risk numbers, including: Calculate the equivalent number of people in each sub-region, equivalent number of people = number of people with risk codes in the sub-region / 2; Calculate the sum of the equivalent number of people in the sub-region and the number of parameters for determining the time series, and re-rank the sub-regions from high to low risk based on the sum of the sub-regions from large to small.

8. The multi-dimensional analysis control method for an information system according to claim 7, characterized in that: The collecting of environmental parameters of each sub-area and determining whether to make a secondary adjustment to the risk ranking of the sub-area according to the environmental parameters include: Set the number of days for collection and calculate the average daily temperature and average sunlight intensity of the sub-area within the number of days for collection; Set a minimum temperature value and a minimum light intensity value. If the average daily temperature is less than or equal to the minimum temperature value, and the average daily light intensity is less than or equal to the minimum light intensity value, then determine to make a secondary adjustment to the risk ranking of the sub-area. Otherwise, it is determined that no secondary adjustment is to be made to the risk ranking of the sub-region.

9. The multi-dimensional analysis control method for an information system according to claim 8, characterized in that: If it is determined that a secondary adjustment is to be made, the risk ranking of the sub-areas is adjusted according to the environmental parameters and the number of disinfection times to obtain the final sub-area risk ranking, including: Collect the number of disinfection times of each sub-area within the collected days, calculate the average daily disinfection times of the collected days, calculate the adjustment value according to the average daily temperature, average sunlight intensity and average daily disinfection times, and adjust the risk ranking of the sub-area according to the adjustment value; Set the standard adjustment value, which is calculated by the following formula: T = T0 (1 + w1 + w2 + w3); In the above formula, T represents the adjustment value, T0 represents the standard adjustment value, w1 represents the average daily temperature adjustment coefficient, w2 represents the average daylight intensity adjustment coefficient, and w3 represents the average daily disinfection times adjustment coefficient. The value ranges of w1, w2 and w3 are all 0-0.

5.

10. The multi-dimensional analysis control method for an information system according to claim 9, characterized in that: If it is determined that a secondary adjustment is to be made, the risk ranking of the sub-areas is adjusted according to the environmental parameters and the number of disinfection times to obtain the final sub-area risk ranking, and the following is also included: Setting a first adjustment value and a second adjustment value, wherein the first adjustment value is smaller than the second adjustment value; If the adjustment value is less than the first adjustment value, the risk ranking of the sub-region is advanced by one rank; If the adjustment value is greater than or equal to the first adjustment value, and less than or equal to the second adjustment value, the risk ranking of the sub-region is advanced by two ranks; If the adjustment value is greater than the second adjustment value, the risk ranking of the sub-region is advanced by three ranks.

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