CN112885482A - Epidemic situation prevention method for student returning school - Google Patents
Epidemic situation prevention method for student returning school Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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Abstract
The invention relates to an epidemic situation prevention method for student returning school, which comprises the following steps: 1) constructing an epidemic situation big data geographic spatial database, a distributed student basic information database and a student daily condition database, wherein the student daily condition database comprises location information and health condition information; 2) constructing basic information of a correction scheme; 3) judging the epidemic situation of the location of each student according to the epidemic situation big data geospatial database and the location information, and acquiring a student list without infection risk according to the student daily condition database; thus, the batch returning and correcting schemes are formulated according to the basic information of the distributed student basic information database and the returning and correcting schemes; 4) and the students return to the school according to the school returning scheme. Compared with the prior art, the method and the system have the advantages that interactive analysis is carried out on epidemic situation big data and personal information reported by students in daily life, the school return risk of the students is obtained, a peak-staggering school return scheme is generated, and the efficiency, the safety and the scientificity of school return work are considered.
Description
Technical Field
The invention relates to the field of epidemic situation prevention, in particular to an epidemic situation prevention method for student returning school.
Background
For colleges and universities, the primary problem facing colleges and universities under the epidemic situation background is that the colleges and universities gradually promote safe and orderly school return of students under the epidemic situation prevention and control normalization. At present, the school returning modes of most colleges and universities are simple schemes of student application and college approval, schools cannot effectively master the school returning time and the infected risk of students, the condition that a large number of students return to schools collectively in the same time period is easily caused, the safety condition of the students cannot be ensured, and the risk of the gathering and spreading of epidemic situations exists. Therefore, under the multiple pressure of teaching requirements of students in lower grades, graduation procedure handling requirements of students in graduation grades and new-born entrance, epidemic situation prevention is urgently needed in colleges and universities.
Disclosure of Invention
The invention aims to provide an epidemic situation prevention method for student returning school, which aims to overcome the defects that the prior art has the condition that a large number of students return school collectively in the same time period, the safety condition of the students cannot be ensured, and the risk of the gathering and the propagation of the epidemic situation exists.
The purpose of the invention can be realized by the following technical scheme:
an epidemic situation prevention method for student returning school comprises the following steps:
the method comprises the steps of constructing a comprehensive information big data platform: acquiring national epidemic situation data and constructing an epidemic situation big data geographic space database; acquiring personal information daily reported by students, and constructing a daily condition database of the students, wherein the personal information daily reported by the students comprises location information and health condition information;
acquiring a student list without infection risk: according to the location information and the health condition information in the epidemic situation big data geospatial database and the student daily condition database, acquiring a student list without infection risk through a preset decision index;
a step of generating a correction scheme: generating a returning and correcting scheme according to the student list without the infection risk;
the method comprises the following steps: and the students return to the school according to the school returning scheme.
Further, the method for generating the return-to-school scheme further comprises the step of constructing basic information of the return-to-school scheme: constructing basic information of the returning and correcting scheme, wherein the basic information comprises the batch number and the name of the returning and correcting scheme and the maximum returning and correcting number of people in each batch;
the step of constructing the comprehensive information big data platform further comprises the steps of obtaining basic data of students and constructing a distributed student basic information database;
the generating steps of the correction scheme are as follows: and generating a batch of returning and correcting schemes according to the non-infection risk student list, the distributed student basic information database and the basic information of the returning and correcting schemes.
Further, in the step of constructing the basic information of the return-proofreading scheme, the return-proofreading scheme in batches is formulated by adopting a preset double strategy of the return-proofreading security risk and the return-proofreading priority, and the double strategy of the return-proofreading security risk and the return-proofreading priority is constructed based on the return-proofreading security risk strategy and the return-proofreading priority strategy.
Further, the school returning priority strategy comprises the screening of information of the location of the students, the grade of the students, the specialty, the school district and the dormitory building.
Further, the method for generating the returning and correcting scheme further comprises the steps of increasing and decreasing the returning and correcting scheme: issuing the school returning schemes obtained in the school returning scheme generating step to students and colleges, obtaining declaration information, and adding or deleting the school returning schemes;
the declaration information comprises personal health condition change information, position change information, contact information with high-risk groups and return-to-school intention information.
Further, the acquisition of the list of students without infection risk comprises the following steps:
and loading the location information of the students and the spatial position distribution information of the epidemic situation cases in the epidemic situation big data geospatial database into a pre-established cellular automaton to obtain the students contacting with the epidemic situation cases as the students with infection risks, and other students as the students without infection risks, thereby obtaining the student list without infection risks.
Further, the student daily condition database and the distributed student basic information database are both distributed index data structures.
Further, the decision index includes: whether the student continuously checks the card in the isolation period, whether the student lives overseas, whether the student changes the position and whether the student has confirmed cases in the activity range or not.
Further, in the step of constructing the comprehensive information big data platform, the national epidemic situation data is acquired through a web crawler technology.
Further, data cross comparison, similarity matching and data fusion are carried out on the national epidemic situation data acquired through the web crawler technology, and the epidemic situation big data geospatial database is constructed.
Compared with the prior art, the invention has the following advantages:
(1) firstly, judging the epidemic situation of the location of each student through an epidemic situation big data geospatial database and the location information of the student every day; then, a student list without infection risk is further judged through a student daily condition database, so that batch returning and school schemes are formulated according to basic information of the returning and school schemes, and the method is scientific, reasonable, safe and reliable in flow; the college return-to-school scheme generation method provided by the invention can be applied to scientific management and risk assessment in the college return-to-school process, intelligently realizes the batch peak-shifting return-to-school scheme designation and ensures the return-to-school and recollection work.
(2) In the step of constructing the comprehensive information big data platform, a data structure is organized in a distributed index mode, so that the efficiency of data query is improved, and the searching and updating of mass student information are facilitated;
(3) the epidemic situation prevention method for student returning school provided by the invention fully uses the big data of the epidemic situation as an important data source for scheme formulation. The method comprises the steps of obtaining case statistical data and position point data of 2880 counties, county-level cities and single-row planning areas (economic development areas and the like) in China on websites such as a clove garden, Tencent and Baidu and information publishing platforms such as micro blogs and public numbers of governments in various regions through a network crawler technology, then carrying out intelligent analysis on epidemic situation data, solving related problems such as data loss, inconsistent data formats and inconsistent statistical calibers through data cross comparison, similar matching and data fusion, improving the automation level of epidemic situation data processing, and further ensuring the accuracy of the epidemic situation data. The construction and maintenance of refined epidemic situation big data ensure the accuracy and real-time of epidemic situation and risk judgment, effectively ensure the assessment of the school return risks of students, and improve the safety of the school return process from the source.
(4) The college returning scheme generation method for epidemic situation prevention and control fully considers basic information of student residence places, grades, dormitories, school zones and the like, automatically generates batch college returning student schemes, and gives consideration to actual requirements of students and colleges on the premise of safety, order and peak-shifting returning, so that the scientificity and the safety of the returning schemes are guaranteed. Compared with the unordered school return under the current general epidemic situation background, the method for generating the school return scheme provided by the invention has the advantages of clear thought, reliable scheme and good universality and generalizability.
(5) By means of a geographic information technology and a spatial big data processing technology, massive epidemic situation data and personal information (such as health states, position changes (infected risks) and the like) daily declared by students can be deeply mined, personal and epidemic situation related data are interactively analyzed, return and school risk information of personnel is obtained, and a peak-load return and school scheme is scientifically generated according to school arrangement and return and school priority. By the method, a school returning scheme is designated, the efficiency, the safety and the scientificity of school returning work are considered, the risk of epidemic situations can be reduced to the minimum, and the actual requirements of students in colleges and universities can be fully met.
Drawings
FIG. 1 is a flow chart of a method of generating a rework scenario of the present invention;
FIG. 2 is a diagram of a visual geospatial epidemic database in accordance with the present invention;
FIG. 3 is a diagram of the arrangement of batches of the rework scenario proposed by the present invention;
FIG. 4 is a diagram of a student list screening method for a school return scheme proposed by the present invention;
FIG. 5 is a graph of the results of the proposed recalibration scheme of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Example 1
The embodiment provides an epidemic situation prevention method for student returning school, which comprises the following steps:
the method comprises the steps of constructing a comprehensive information big data platform: acquiring national epidemic situation data and constructing an epidemic situation big data geographic space database; acquiring basic data of students and constructing a distributed student basic information database; acquiring personal information daily reported by students, and constructing a daily condition database of the students, wherein the personal information daily reported by the students comprises location information and health condition information;
and a construction step of basic information of the correction scheme: constructing basic information of a correction scheme;
a step of generating a correction scheme: according to location information in the epidemic situation big data geographic space database and the student daily condition database, the epidemic situation of the location of each student is judged;
acquiring a student list without infection risk according to epidemic situation situations of places of students and a student daily condition database;
according to a student list without infection risk, a distributed student basic information database and basic information of a returning and correcting scheme, making a returning and correcting scheme in batches;
the method comprises the following steps: and the students return to the school according to the school returning scheme.
The student daily condition database and the distributed student basic information database are both distributed index data structures.
The steps are described in detail below.
1. Generating a correction scheme
In the step of generating the returning school scheme, a student list without infection risk is obtained through a preset decision index, wherein the decision index comprises: whether the student 14 continuously checks the card, whether the student lives overseas in the health condition within 14 days, whether the student lives in the overseas, the position change condition and whether the student has confirmed diagnosis cases in the activity range.
The acquisition of the student list without infection risk comprises the following steps:
and loading the location information of the students and the spatial position distribution information of the epidemic case in the epidemic situation big data geospatial database into a pre-established cellular automaton to obtain the students contacting with the epidemic case as the students with infection risks.
Further, new students with infection risks are obtained according to health conditions within 14 days, whether the students 14 continuously punch cards, whether the students live overseas, position change conditions and whether the confirmed diagnosis case indexes exist in the range of activity; and other students are used as the students without infection risks, so that a list of the students without infection risks is obtained.
In the step of constructing the basic information of the return-proofreading scheme, a preset double strategy of the return-proofreading security risk and the return-proofreading priority is adopted to formulate the return-proofreading scheme in batches, and the double strategy of the return-proofreading security risk and the return-proofreading priority is constructed based on the return-proofreading security risk strategy and the return-proofreading priority strategy.
The school returning priority strategy comprises the screening of information of the location of students, the grade of students, the specialty, the school district and the dormitory building.
2. Building steps of comprehensive information big data platform
In the step of constructing the comprehensive information big data platform, national epidemic situation data is obtained through a web crawler technology.
And carrying out data cross comparison, similarity matching and data fusion on the national epidemic situation data acquired by the web crawler technology to construct an epidemic situation big data geographic spatial database.
3. Increase and decrease steps of correction scheme
The method for generating the return correction scheme further comprises the steps of increasing and decreasing the return correction scheme: and (4) issuing the returning and correcting scheme obtained in the returning and correcting scheme generating step to students and colleges, obtaining declaration information, and adding or deleting the returning and correcting scheme.
The declaration information includes personal health condition change information, position change information, contact information with high risk group, and return intention information.
4. Return correction scheme evaluation step
The method for generating the return-to-school scheme further comprises the step of evaluating the return-to-school scheme: and evaluating the returning and correcting scheme to obtain an executable returning and correcting scheme for actual returning and correcting arrangement.
The embodiment also provides a device for formulating an epidemic situation prevention and control-oriented school return scheme, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the epidemic situation prevention method for student school return as described above.
The detailed description of the specific implementation process is as follows:
as shown in fig. 1, the epidemic situation prevention method for student returning school of the present embodiment is a method for student returning school, which performs planning as a whole and makes a scientific and reasonable batch peak-shifting returning school scheme meeting the reality, so as to be used for student returning school, and the method includes the following steps:
1) a large comprehensive student information data platform of a return school scheme is established, and the inquiry and update of student information and the generation, arrangement and export of the return school scheme are efficiently and conveniently realized;
2) newly establishing an estimated returning and correcting scheme, and setting basic information of the returning and correcting scheme, including the number and name of batches to be returned and the maximum number of persons to be returned and corrected in each batch;
3) combining epidemic situation big data and student personal information, and automatically generating batch peak-staggering batch school student list according to actual requirements;
4) according to the requirements and actual conditions of students, intelligently auditing the declaration information of the students, and performing addition or deletion of a back-checking list after studying and judging the system safety;
5) and carrying out intelligent evaluation on the final correction scheme, and storing, issuing and confirming the scheme after the final correction scheme passes the evaluation.
The step 1) is specifically as follows:
11) acquiring case statistical data and position point data of 2880 counties, county-level cities and single-row planning areas (economic development areas and the like) in China on websites such as a syringomy park, Tencent and Baidu websites and information publishing platforms such as micro blogs and public numbers of governments in various regions by using a web crawler technology, constructing an epidemic situation big data geographic space database, and performing daily maintenance and updating on the database;
12) constructing a distributed student basic information database, and inputting basic information of students, including school numbers, names, colleges, school areas, dormitories and whether the students return to school or not;
13) personal information reported by students in daily life is imported and processed, such as locations and health conditions, and the daily conditions of the students are updated in real time and used as basic information for risk analysis of the return school;
14) a data structure is organized in a distributed index mode, so that the efficiency of data query is improved, and the searching and updating of massive student information are facilitated;
the step 2) is specifically as follows:
21) newly establishing a pre-estimated returning and correcting scheme, and setting the starting and ending time, the name, the batch number and the maximum returning and correcting number of each batch of the returning and correcting scheme according to the policy and the requirements of the colleges and universities;
the step 3) is specifically as follows:
31) big data analysis is carried out on the national city and county level epidemic situations, and the situation of the epidemic situation of the student location is accurately researched and judged according to the spatial position distribution of the diagnosed cases and the spatial position database of the student;
32) according to the daily reported information of students, judging the risk of returning and correcting by taking whether the students 14 continuously punch cards, the health condition in 14 days, whether the students live overseas, the position change condition, whether the students have confirmed cases in the activity range and whether the students stay in key areas as decision indexes, and accurately obtaining a list of persons without infection risk;
33) and comprehensively screening out the student lists meeting the conditions through double strategies of the school returning safety risk and the school returning priority, and automatically generating the school returning student lists of each batch. The school returning priority strategy comprises fine screening of information such as the distance of the location of the students, the grade of the students, the specialty, the school district and the dormitory building, and therefore overall arrangement of the school and individual school returning requirements of the students are considered.
The step 4) is specifically as follows:
41) issuing a preliminary school returning scheme to students and various colleges, then intelligently checking declaration information submitted by the students, such as personal health condition change, position change, contact with high-risk groups and the like, and automatically deleting and adjusting the school returning scheme;
42) and adjusting a returning school scheme according to the willingness and actual conditions of students, auditing newly added returning school applications of the students, analyzing the returning school risk by one person, and adding the students to the returning school batch after the students pass the auditing.
The step 5) is specifically as follows:
51) and carrying out intelligent evaluation on the final returning and correcting scheme, re-analyzing the safety and feasibility of the scheme according to the final returning and correcting time, the number of persons returning and correcting and the personnel risk information of each batch, storing, issuing and confirming the scheme after the scheme is passed, and putting the scheme into an actual returning and correcting arrangement as an executable returning and correcting scheme.
The practical specific embodiment of the method of the embodiment is as follows:
a) the refined epidemic situation big data provided by the invention obtains the epidemic situation big data of 2880 county-level areas in the country through a crawler technology, constructs an accurate national epidemic situation database and updates the database in real time, thereby realizing the spatial distribution analysis of nationwide confirmed cases and suspected cases. According to the result of the spatial analysis, different spatial regions are divided into high-risk, medium-risk, low-risk and safe regions by referring to the spatial distribution density of confirmed and suspected cases, so that the risk evaluation of spatial positions is realized. As shown in fig. 2;
b) the setting and generating mode of the invention for the student return-school scheme is shown in figure 3. And setting the starting and ending time, the name, the batch number and the maximum number of the colleges in each batch of the college returning schemes according to the policy and the requirements of the colleges and universities.
c) The generation mode of the student return school scheme list is shown in figure 4. Whether the students 14 continuously punch cards, whether the students live overseas in 14 days, whether the students change the position, whether confirmed cases exist in the activity range or not and whether the students stay in the key area are selected as decision indexes, and the students meeting the conditions are comprehensively screened out through the double strategies of the safety risk of the returning school and the priority of the returning school and are added to the returning school list of the batch;
d) issuing a preliminary school returning scheme to students and various colleges, then intelligently checking declaration information submitted by the students, such as personal health condition change, position change, contact with high-risk groups and the like, and automatically deleting and adjusting the school returning scheme;
e) and adjusting a returning school scheme according to the willingness and actual conditions of students, auditing newly added returning school applications of the students, analyzing the returning school risk by one person, and adding the students to the returning school batch after the students pass the auditing.
f) And intelligently evaluating the final returning and correcting scheme, re-analyzing the safety and feasibility of the scheme according to the final returning and correcting time, the number of returning and correcting people and the personnel risk information of each batch, storing, issuing and confirming the scheme after the scheme is passed, putting the scheme into an actual returning and correcting arrangement as an executable returning and correcting scheme, wherein the finally issued returning and correcting scheme is shown in figure 5.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. An epidemic situation prevention method for student returning school is characterized by comprising the following steps:
the method comprises the steps of constructing a comprehensive information big data platform: acquiring national epidemic situation data and constructing an epidemic situation big data geographic space database; acquiring personal information daily reported by students, and constructing a daily condition database of the students, wherein the personal information daily reported by the students comprises location information and health condition information;
acquiring a student list without infection risk: according to the location information and the health condition information in the epidemic situation big data geospatial database and the student daily condition database, acquiring a student list without infection risk through a preset decision index;
a step of generating a correction scheme: generating a returning and correcting scheme according to the student list without the infection risk;
the method comprises the following steps: and the students return to the school according to the school returning scheme.
2. The epidemic prevention method for student's college-returning according to claim 1, wherein the method for generating the college-returning plan further comprises the steps of constructing basic information of the college-returning plan: constructing basic information of the returning and correcting scheme, wherein the basic information comprises the batch number and the name of the returning and correcting scheme and the maximum returning and correcting number of people in each batch;
the step of constructing the comprehensive information big data platform further comprises the steps of obtaining basic data of students and constructing a distributed student basic information database;
the generating steps of the correction scheme are as follows: and generating a batch of returning and correcting schemes according to the non-infection risk student list, the distributed student basic information database and the basic information of the returning and correcting schemes.
3. The epidemic situation prevention method for student's college refund, according to claim 2, characterized in that in the college refund scheme generating step, the college refund scheme of the sub-batch is formulated by adopting a preset double strategy of safety risk of refund and priority of refund, and the double strategy of safety risk of refund and priority of refund is constructed based on the safety risk strategy of refund and priority of refund.
4. The epidemic prevention method for student's return school according to claim 3, wherein the priority strategy for the return school includes screening of information about the location of the student, the grade of the student, the specialty, the school zone, and the dormitory building.
5. The epidemic prevention method for student's college entrance according to claim 1, wherein the method for generating the college entrance plan further comprises the steps of increasing and decreasing the college entrance plan: issuing the school returning schemes obtained in the school returning scheme generating step to students and colleges, obtaining declaration information, and adding or deleting the school returning schemes;
the declaration information comprises personal health condition change information, position change information, contact information with high-risk groups and return-to-school intention information.
6. The method as claimed in claim 1, wherein the obtaining of the list of students without infection risk comprises the following steps:
and loading the location information of the students and the spatial position distribution information of the epidemic situation cases in the epidemic situation big data geospatial database into a pre-established cellular automaton to obtain the students contacting with the epidemic situation cases as the students with infection risks, and other students as the students without infection risks, thereby obtaining the student list without infection risks.
7. The method as claimed in claim 1, wherein the student daily status database and the distributed student basic information database are distributed indexed data structures.
8. The method of claim 1, wherein the decision index comprises: whether the student continuously checks the card in the isolation period, whether the student lives overseas, whether the student changes the position and whether the student has confirmed cases in the activity range or not.
9. The epidemic prevention method for student's college entrance according to claim 1, wherein in the step of constructing the comprehensive information big data platform, the national epidemic data is obtained by web crawler technology.
10. The epidemic prevention method for student's college refuge according to claim 9, characterized in that the said national epidemic data obtained by web crawler technology is cross-compared, similar matched and fused to construct the said epidemic big data geospatial database.
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