CN114974491A - Early warning method and device for number of cases, electronic equipment and computer readable medium - Google Patents
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Abstract
The disclosure relates to a case quantity early warning method, a case quantity early warning device, electronic equipment and a computer readable medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring case information of all target cases in a target area in a historical time period, wherein the case information comprises attack time and target positions; obtaining the statistical number of cases corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case; determining each scanning central point in the target area, and respectively scanning by using different scanning windows according to each scanning central point to obtain the scanning number of cases in each statistical time period in the scanning range corresponding to each scanning window; and determining a case quantity early warning area in the target area according to the case quantity scanned in the scanning range corresponding to each scanning window. The early warning of the number of cases is carried out by using a space scanning strategy, so that the space sensitivity and the early warning accuracy can be improved.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method, an apparatus, an electronic device, and a computer-readable medium for early warning of a number of cases.
Background
To cope with the needs of public health emergencies, monitoring studies on the number of various disease cases are increasingly important. An effective and feasible monitoring method can provide basis for public health personnel to adopt an effective prevention and control strategy.
At present, data in various disease monitoring processes are all based on data of a human reporting system, the reporting system is greatly influenced by subjective judgment, and the data has delay, so that the monitoring accuracy is influenced, and the purpose of monitoring in time cannot be achieved.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure provides a method, a device, an electronic device and a computer readable medium for early warning of the number of cases, so as to improve spatial sensitivity and early warning accuracy of monitoring the number of cases to at least a certain extent.
According to a first aspect of the present disclosure, there is provided a method for warning of a number of cases, comprising:
acquiring case information corresponding to all target cases in a target area in a historical time period, wherein the case information comprises the attack time and the target position of the target case;
obtaining the statistical number of cases corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case;
determining each scanning central point in the target area, and respectively scanning by using different scanning windows according to each scanning central point to obtain the case scanning number of each statistical time period in the scanning range corresponding to each scanning window;
and determining a case quantity early warning area in the target area according to the case quantity scanned in each statistical time period in the scanning range corresponding to each scanning window.
In an exemplary embodiment of the present disclosure, the obtaining the number of cases scanned in each statistical time period within a scanning range corresponding to each scanning window by respectively scanning with different scanning windows according to each scanning center point includes:
obtaining corresponding position information according to the target position, wherein the position information comprises longitude data and latitude data corresponding to the target position;
for each scanning central point in the target area, determining a corresponding scanning range according to different scanning windows respectively;
and obtaining the case scanning number of each statistical time period in the scanning range corresponding to each scanning window according to the position information and the case statistical number corresponding to each target position.
In an exemplary embodiment of the present disclosure, the determining, for each scanning central point in the target region, a corresponding scanning range according to different scanning windows respectively includes:
and respectively taking each scanning central point in the target area as a circle center, and determining a scanning range corresponding to each scanning window according to a plurality of different preset radius values.
In an exemplary embodiment of the present disclosure, the determining each scan center point within the target region includes:
and determining each scanning central point in the target area according to a preset longitude moving distance and a preset latitude moving distance.
In an exemplary embodiment of the present disclosure, the determining, according to the number of cases scanned in each statistical time period within the scanning range corresponding to each scanning window, a case number early warning area within the target area includes:
obtaining the number of cases in the current early warning time period and the number of cases in a plurality of associated time periods associated with the early warning time period according to the number of cases scanned in each statistical time period in the scanning range corresponding to the scanning window;
determining early warning threshold indexes corresponding to the early warning time periods according to the number of cases in each associated time period;
and when the number of cases in the early warning time period is greater than or equal to the early warning threshold index corresponding to the early warning time period, determining the scanning range corresponding to the scanning window as a case number early warning area.
In an exemplary embodiment of the present disclosure, the determining an early warning threshold indicator corresponding to the early warning time period according to the number of cases in each of the associated time periods includes:
and determining early warning threshold indexes corresponding to the early warning time periods according to the percentile of the number of the cases corresponding to each associated time period.
In an exemplary embodiment of the present disclosure, the method further comprises:
after the target area scanning is finished, drawing all the case quantity early warning areas in the target area on a map.
According to a second aspect of the present disclosure, there is provided an early warning device of a number of cases, comprising:
the system comprises a case information acquisition module, a case information acquisition module and a case information processing module, wherein the case information acquisition module is used for acquiring case information corresponding to all target cases in a target area in a historical time period, and the case information comprises the attack time and the target position of the target cases;
the case quantity determining module is used for obtaining the case statistical quantity corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case;
a case quantity scanning module, configured to determine each scanning center point in the target area, and scan the case statistical quantities corresponding to the target positions in a scanning range using different scanning windows according to each scanning center point, to obtain the case scanning quantities of the statistical time periods in the scanning range corresponding to each scanning window;
and the early warning area determining module is used for determining a case quantity early warning area in the target area according to the case scanning quantity of each statistical time period in the scanning range corresponding to each scanning window.
According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of warning of the number of cases of any of the above via execution of the executable instructions.
According to a fourth aspect of the present disclosure, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the method of warning of the number of cases as set forth in any one of the above.
The exemplary embodiments of the present disclosure may have the following advantageous effects:
in the case quantity early warning method according to the exemplary embodiment of the present disclosure, the attack time and the position corresponding to all target cases in a target area in a historical time period are obtained, the number of cases corresponding to each target position in each statistical time period is counted, then, a scanning window is used to perform scanning based on each scanning center point in the target area, so as to obtain the number of case scans in each statistical time period in different scanning ranges, and finally, the case quantity early warning area in the target area is determined according to the number of case scans in each statistical time period in the scanning range corresponding to each scanning window. According to the early warning method for the number of cases in the disclosed example embodiment, on one hand, real-time and accurate scanning monitoring is carried out based on a spatial scanning strategy, monitoring sensitivity is improved through dynamic scanning, and early warning accuracy is improved by adding spatial information in the case number monitoring process, so that the situation that accurate early warning cannot be sent according to the actual number of cases when the number of cases is small and the cases are distributed in different hospitals is avoided; on the other hand, by determining the case quantity early warning area in the target area, a possible disease propagation area can be provided while early warning, and a basis is provided for public health personnel to adopt an effective prevention and treatment strategy.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 shows a flow diagram of an early warning method of the number of cases of an example embodiment of the present disclosure;
FIG. 2 schematically shows statistical data obtained after merging the number of cases within the same day according to geographical location;
fig. 3 illustrates a flowchart of scanning a case statistics amount corresponding to each target location using a scanning window according to an exemplary embodiment of the disclosure;
FIG. 4 illustrates a schematic view of scanning a target area using a scanning window in accordance with one embodiment of the present disclosure;
fig. 5 shows a flow diagram of determining a case quantity early warning area within a target area according to an example embodiment of the present disclosure;
FIG. 6 schematically illustrates a line graph of the number of cases and the pre-warning threshold indicator for a current pre-warning time period, according to one embodiment of the present disclosure;
FIG. 7 illustrates a schematic diagram of a case quantity pre-warning area within a target area, in accordance with one embodiment of the present disclosure;
FIG. 8 shows a flow diagram of a method for case number pre-warning in accordance with one embodiment of the present disclosure;
fig. 9 illustrates a block diagram of an early warning apparatus of the number of cases of an exemplary embodiment of the present disclosure;
FIG. 10 illustrates a schematic diagram of a computer system suitable for use with the electronic device implementing embodiments of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
In some related embodiments, the monitoring of the number of cases is based on a disease diagnosis based monitoring system. After the doctor or the monitoring center confirms to diagnose the relevant cases, the cases are reported through the reporting system, then the monitoring system integrates the reported data, and the early warning calculation is carried out by adopting relevant algorithms such as control charts and the like. The control chart is a tool chart with control boundaries used for analyzing and judging whether the process is in a stable state, is a functional chart for distinguishing normal fluctuation and abnormal fluctuation, and is a statistical tool in field quality management. However, the reporting system is greatly affected by subjective judgment, and data has delay, which not only affects the monitoring accuracy, but also fails to achieve the purpose of monitoring in time.
In view of this, the present exemplary embodiment first provides an early warning method for the number of cases, so as to solve the problems that the monitoring system in the related embodiments is greatly affected by subjective judgment, and data reporting has a delay, so that the monitoring accuracy is affected, and the like. Referring to fig. 1, the method for warning the number of cases may include the steps of:
step S110, acquiring case information corresponding to all target cases in a target area in a historical time period, wherein the case information comprises the attack time and the target position of the target case.
And S120, obtaining the statistical number of the cases corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case.
And S130, determining each scanning central point in the target area, and respectively scanning by using different scanning windows according to each scanning central point to obtain the scanning number of cases in each statistical time period in the scanning range corresponding to each scanning window.
And S140, determining a case quantity early warning area in the target area according to the case scanning quantity of each statistical time period in the scanning range corresponding to each scanning window.
In the case quantity early warning method according to the exemplary embodiment of the present disclosure, the attack time and the position corresponding to all target cases in a target area in a historical time period are obtained, the number of cases corresponding to each target position in each statistical time period is counted, then, a scanning window is used to perform scanning based on each scanning center point in the target area, so as to obtain the number of case scans in each statistical time period in different scanning ranges, and finally, the case quantity early warning area in the target area is determined according to the number of case scans in each statistical time period in the scanning range corresponding to each scanning window. According to the early warning method for the number of cases in the disclosed example embodiment, on one hand, real-time and accurate scanning monitoring is carried out based on a spatial scanning strategy, monitoring sensitivity is improved through dynamic scanning, and early warning accuracy is improved by adding spatial information in the case number monitoring process, so that the situation that accurate early warning cannot be sent according to the actual number of cases when the number of cases is small and the cases are distributed in different hospitals is avoided; on the other hand, by determining the case quantity early warning area in the target area, a possible disease propagation area can be provided while early warning is carried out, and a basis is provided for public health personnel to adopt an effective prevention and treatment strategy.
The above steps of the present exemplary embodiment will be described in more detail with reference to fig. 2 to 7.
In step S110, case information corresponding to all target cases in the target area in the historical time period is acquired, wherein the case information includes the onset time and the target position of the target case.
In this example embodiment, the target area refers to an area to be monitored, such as a city, and the historical time period may be, for example, approximately 3 years or approximately 5 years. The target case refers to a case having specific symptoms such as fever, diarrhea, etc., or belonging to the same diagnosis type.
In the process of monitoring the number of cases, firstly, a data source for monitoring needs to be acquired, and specifically, information of cases having specific symptoms or belonging to the same diagnosis type in emergency outpatient services of all hospitals in a target area can be acquired, including the onset time of the cases and the target position, wherein the target position can be, for example, the address of the target case. Data with a historical time period of up to 5 years may be recalled in the time dimension.
For the target locations corresponding to all target cases, such as address information, a mapping software API (Application Programming Interface) may be used to convert into corresponding location information, such as latitude and longitude data. For example, after transformation, the geographical position of a certain case is [ 116.663585, 40.670384 ], and the onset time of the case is as [ 2021-03-12 ].
In step S120, a statistical number of cases corresponding to each target position in each statistical time period of the historical time period is obtained based on the onset time and the target position of the target case.
In this exemplary embodiment, the case counts with the same target position may be combined based on each statistical time period, so as to obtain the case statistical number corresponding to each target position in each statistical time period of the historical time period. For example, each day in the historical time period may be taken as a statistical time period, the counts of cases with the same geographic location on the same day may be combined, and the final data format may be as shown in fig. 2, where the 4-column data includes longitude, latitude, the number of cases, and date.
In step S130, each scanning center point in the target region is determined, and different scanning windows are respectively used for scanning according to each scanning center point, so as to obtain the number of cases scanned in each statistical time period in the scanning range corresponding to each scanning window.
In this exemplary embodiment, the target area may be scanned and monitored based on a spatial scanning strategy, specifically, scanning may be performed at different spatial positions with different size scanning windows. The case scanning number refers to the sum of the case statistical numbers of all target positions in a scanning window obtained by scanning all target positions in the scanning window.
In this exemplary embodiment, as shown in fig. 3, scanning is performed by using different scanning windows according to each scanning center point, so as to obtain the number of cases scanned in each statistical time period within the scanning range corresponding to each scanning window, which may specifically include the following steps:
and S310, obtaining corresponding position information according to the target position, wherein the position information comprises longitude data and latitude data corresponding to the target position.
For target locations corresponding to all target cases, such as address information, a mapping software API may be used to convert them into corresponding location information, such as latitude and longitude data.
And S320, determining a corresponding scanning range for each scanning central point in the target area according to different scanning windows.
In this exemplary embodiment, each scan center point in the target area may be determined according to a preset longitude movement distance and a preset latitude movement distance. Specifically, based on the scanning center point movement strategy, the scanning is performed in a grid manner in longitude and latitude, and the scanning is performed according to a preset longitude movement distance and a preset latitude movement distance, for example, the longitude movement distance is 0.2, and the latitude movement distance is 0.1, until all target areas are scanned.
And assuming that the scanning window is in a circular shape, respectively taking each scanning central point in the target area as a circle center, and determining a scanning range corresponding to each scanning window according to a plurality of different preset radius values. The radius of the scanning window is set as a parameter r, the size of the radius is changed at the same scanning central point to carry out statistical calculation and monitoring, and the maximum value of the radius is set, such as 5 kilometers. For example, for each scan center point in the target area, 1 km, 2 km, 3 km, 4 km, and 5 km are radius values, respectively, corresponding to 5 different scan ranges. In addition, the spatial scanning window may have other shapes, such as a square shape, and is not particularly limited in this exemplary embodiment.
And S330, obtaining the case scanning number of each statistical time period in the scanning range corresponding to each scanning window according to the position information corresponding to each target position and the case statistical number.
After the scanning range corresponding to each scanning window is determined, counting the number of case scans in each counting time period in each scanning window according to the position information corresponding to each target position and the number of case statistics, and obtaining a time sequence in the scanning window. For example, the total number of cases per day for approximately 5 years per scan window is counted.
Fig. 4 shows a schematic diagram of scanning a target area using scanning windows, in which different scanning windows 402 are respectively used for each scanning center point in the target area within a map range of the target area 401, and the number of cases in each statistical time period within each scanning window is scanned, according to an embodiment of the present disclosure.
In step S140, a case quantity early warning area in the target area is determined according to the number of case scans in each statistical time period within the scanning range corresponding to each scanning window.
In this exemplary embodiment, an MPM (moving percentile metric) algorithm may be used to monitor and calculate the number of cases scanned in each statistical time period within the scanning range corresponding to each scanning window. As shown in fig. 5, determining a case quantity early warning area in a target area according to the number of case scans in each statistical time period in the scanning range corresponding to each scanning window may specifically include the following steps:
step 510, obtaining the number of cases in the current early warning time period and the number of cases in a plurality of associated time periods associated with the early warning time period according to the number of cases scanned in each statistical time period in the scanning range corresponding to the scanning window.
In this example embodiment, the current warning time period may be, for example, 7 days including the current monitoring date, and the plurality of associated time periods associated with the warning time period may be, for example, historical contemporaneous time periods of each year and two weeks before and after the previous warning time period. For example, the number of case scans in each statistical time period within the scanning range corresponding to the scanning window is as follows:
in the table, the number of scanned cases per day from 1 month to 1 day in 2008 to 2011 is calculated, and assuming that 1 month to 21 days in 2011 is the current monitoring date, 15 days to 21 days in 2011 are the current early warning time periods, and the number of cases in the current early warning time period, namely 7 days from 1 month to 15 days in 2011 to 21 days, is summed up to obtain the number of cases in the current early warning time period. The plurality of related time periods related to the early warning time period are historical contemporaneous time periods of the previous 3 years and time periods of two weeks before and after, and the number of cases in the time periods is respectively summed up to obtain the following time period statistical table:
and S520, determining early warning threshold indexes corresponding to early warning time periods according to the number of cases in each associated time period.
In this example embodiment, the early warning threshold indicator corresponding to the early warning time period may be determined according to the percentile of the number of cases corresponding to each associated time period, and the percentile of the current data and the percentile of the data in the historical associated time period may be compared. For example, according to the data in the time period statistical table, the percentiles of the number of cases corresponding to each associated time period are obtained as follows:
| P50 | P60 | P70 | P80 | P90 |
| 25 | 27 | 27 | 29 | 33 |
P50-P90 are different early warning threshold indicators, and can be selected and set according to actual conditions.
And S530, when the number of cases in the early warning time period is greater than or equal to the early warning threshold index corresponding to the early warning time period, determining the scanning range corresponding to the scanning window as a case number early warning area.
Assuming that an early warning threshold index corresponding to the early warning time period is P80, namely 80% quantile of data in the historical association time period, when the number of cases in the early warning time period is greater than or equal to the early warning threshold index, determining a scanning range corresponding to a scanning window as a case number early warning area. During monitoring, each scanning window needs to be calculated once, and if the value in each scanning window exceeds a corresponding threshold value, early warning is carried out.
After moving step by step according to the time window, a line graph of the number of cases and the warning threshold index of the current warning period as shown in fig. 6 can be obtained.
The monitoring and warning algorithm may be replaced by a cumulant sum (cumulant sum), an ARIMA (differential Integrated Moving Autoregressive model), and other algorithms, which are not specifically limited in this exemplary embodiment.
In this exemplary embodiment, after the scanning of the target area is finished, all the case quantity early warning areas in the target area may be further plotted on the map. For example, the geographic information system mapping technology can be used to display all case quantity early warning areas in the target area on a map, so as to realize result visualization.
And respectively calculating an early warning index threshold value for each scanning window, if the early warning index threshold value exceeds the threshold value, early warning is carried out, and the area and the geographic position of the scanning window are recorded. After all scanning of the target area is completed, integrating all results to perform GIS (Geographic Information System) drawing, taking the scanning center point as an early warning center point according to longitude and latitude Information of the scanning center point corresponding to the scanning window and the radius of the scanning window, and displaying the position and the area of the early warning point on a map so as to facilitate checking by a worker. As shown in fig. 7, the drawn warning map displays a case quantity warning area 702 in a target area 701. Meanwhile, each early warning area can be displayed to be different colors according to the number of cases in different early warning areas, so that the early warning effect is improved.
Fig. 8 is a complete flowchart of a method for warning the number of cases in an embodiment of the present disclosure, which is an example of the above steps in the present exemplary embodiment, and the specific steps in the flowchart are as follows:
and step S810, acquiring the case information in the target area within five years, wherein the case information comprises the morbidity time and the address information of all cases.
And S820, acquiring geographic longitude and latitude data corresponding to the case.
And converting the address information of the case into corresponding longitude and latitude data by using a map software API.
And S830, dynamically adjusting the size of a scanning window to perform space scanning, and performing early warning calculation on the time dimension of a scanning space by combining a monitoring early warning algorithm.
And carrying out space scanning based on preset parameters such as longitude moving distance, latitude moving distance, scanning window radius and the like, and carrying out early warning calculation on the time dimension of a scanning space by combining monitoring and early warning algorithms such as a moving percentile method and the like.
And S840, multipoint monitoring and early warning.
And carrying out GIS data drawing according to the early warning calculation result, and displaying the early warning area on a map of the target area. By combining the dynamic space scanning method with the traditional monitoring and early warning algorithm, the monitoring space sensitivity and the early warning accuracy are improved.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Further, the disclosure also provides an early warning device for the number of cases. Referring to fig. 9, the warning apparatus of the number of cases may include a case information acquisition module 910, a case number determination module 920, a case number scanning module 930, and a warning area determination module 940. Wherein:
the case information acquiring module 910 may be configured to acquire case information corresponding to all target cases in a target area in a historical time period, where the case information includes a disease time and a target position of the target case;
the number-of-cases determining module 920 may be configured to obtain, according to the attack time and the target location of the target case, a number of cases counted corresponding to each target location in each statistical time period of the historical time periods;
the case quantity scanning module 930 may be configured to determine each scanning center point in the target area, and perform scanning using different scanning windows according to each scanning center point, to obtain the number of case scans in each statistical time period within the scanning range corresponding to each scanning window;
the early warning region determining module 940 may be configured to determine a case number early warning region in the target region according to the number of case scans in each statistical time period within the scanning range corresponding to each scanning window.
In some exemplary embodiments of the present disclosure, the case number scanning module 930 may include a location information determining unit, a scanning range determining unit, and a case number scanning determining unit. Wherein:
the position information determining unit may be configured to obtain corresponding position information according to the target position, where the position information includes longitude data and latitude data corresponding to the target position;
the scanning range determining unit may be configured to determine, for each scanning central point in the target area, a corresponding scanning range according to different scanning windows respectively;
the case scan number determining unit may be configured to obtain the case scan number of each statistical time period within the scanning range corresponding to each scanning window according to the location information and the case statistical number corresponding to each target location.
In some exemplary embodiments of the present disclosure, the scanning range determining unit may be specifically configured to respectively use each scanning center point in the target area as a center of a circle, and determine the scanning range corresponding to each scanning window according to a plurality of different preset radius values.
In some exemplary embodiments of the present disclosure, the warning apparatus for the number of cases provided by the present disclosure may further include a scan center point determining module, which may be configured to determine each scan center point in the target area according to preset longitude and latitude movement distances.
In some exemplary embodiments of the present disclosure, the early warning region determination module 940 may include a number of cases determination unit, a threshold index determination unit, and an early warning region determination unit. Wherein:
the case quantity determining unit may be configured to obtain, according to the number of cases scanned in each statistical time period within the scanning range corresponding to the scanning window, the number of cases in the current early warning time period and the number of cases in a plurality of associated time periods associated with the early warning time period;
the threshold index determining unit may be configured to determine an early warning threshold index corresponding to the early warning time period according to the number of cases in each associated time period;
the early warning area determining unit may be configured to determine a scanning range corresponding to the scanning window as a case number early warning area when the number of cases in the early warning time period is greater than or equal to an early warning threshold index corresponding to the early warning time period.
In some exemplary embodiments of the present disclosure, the threshold index determining unit may be specifically configured to determine the early warning threshold index corresponding to the early warning time period according to the percentile of the number of cases corresponding to each associated time period.
In some exemplary embodiments of the present disclosure, the warning device for the number of cases provided by the present disclosure may further include a warning area display module, which may be configured to draw all warning areas for the number of cases in the target area on the map after the target area is scanned.
The details of each module/unit in the above-mentioned warning device for number of cases have already been described in detail in the corresponding method embodiment section, and are not described herein again.
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device to implement an embodiment of the invention.
It should be noted that the computer system 1000 of the electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiment of the present invention.
As shown in fig. 10, the computer system 1000 includes a Central Processing Unit (CPU)1001 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for system operation are also stored. The CPU 1001, ROM 1002, and RAM 1003 are connected to each other via a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.
In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. When the computer program is executed by a Central Processing Unit (CPU)1001, various functions defined in the system of the present application are executed.
It should be noted that the computer readable media shown in the present disclosure may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method as described in the embodiments above.
It should be noted that although in the above detailed description several modules of the device for action execution are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module, in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. An early warning method for the number of cases, comprising:
acquiring case information corresponding to all target cases in a target area in a historical time period, wherein the case information comprises the attack time and the target position of the target case;
obtaining the statistical number of cases corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case;
determining each scanning central point in the target area, and respectively scanning by using different scanning windows according to each scanning central point to obtain the case scanning number of each statistical time period in the scanning range corresponding to each scanning window;
and determining a case quantity early warning area in the target area according to the case quantity scanned in each statistical time period in the scanning range corresponding to each scanning window.
2. The method for warning of the number of cases according to claim 1, wherein the step of obtaining the number of cases scanned in each statistical time period within the scanning range corresponding to each scanning window by scanning with different scanning windows according to each scanning center point comprises:
obtaining corresponding position information according to the target position, wherein the position information comprises longitude data and latitude data corresponding to the target position;
for each scanning central point in the target area, determining a corresponding scanning range according to different scanning windows respectively;
and obtaining the case scanning number of each statistical time period in the scanning range corresponding to each scanning window according to the position information and the case statistical number corresponding to each target position.
3. The method for warning of the number of cases according to claim 2, wherein the determining, for each scan center point in the target area, a corresponding scan range according to different scan windows comprises:
and respectively taking each scanning central point in the target area as a circle center, and determining a scanning range corresponding to each scanning window according to a plurality of different preset radius values.
4. The method for warning about the number of cases as set forth in claim 1, wherein the determining each scan center point in the target area comprises:
and determining each scanning central point in the target area according to a preset longitude moving distance and a preset latitude moving distance.
5. The method for early warning of the number of cases according to claim 1, wherein the determining the number of cases early warning area in the target area according to the number of cases scanned in each statistical time period within the scanning range corresponding to each scanning window comprises:
obtaining the number of cases in the current early warning time period and the number of cases in a plurality of associated time periods associated with the early warning time period according to the number of cases scanned in each statistical time period in the scanning range corresponding to the scanning window;
determining early warning threshold indexes corresponding to the early warning time periods according to the number of cases in each associated time period;
and when the number of cases in the early warning time period is greater than or equal to the early warning threshold index corresponding to the early warning time period, determining the scanning range corresponding to the scanning window as a case number early warning area.
6. The method for early warning of the number of cases according to claim 5, wherein the determining an early warning threshold indicator corresponding to the early warning time period according to the number of cases in each of the associated time periods comprises:
and determining early warning threshold indexes corresponding to the early warning time periods according to the percentile of the number of the cases corresponding to each associated time period.
7. The method for warning about the number of cases according to claim 1, further comprising:
after the target area scanning is finished, drawing all the case quantity early warning areas in the target area on a map.
8. An early warning device of a number of cases, comprising:
the system comprises a case information acquisition module, a case information acquisition module and a case information processing module, wherein the case information acquisition module is used for acquiring case information corresponding to all target cases in a target area in a historical time period, and the case information comprises the attack time and the target position of the target cases;
the case quantity determining module is used for obtaining the case statistical quantity corresponding to each target position in each statistical time period of the historical time periods according to the attack time and the target position of the target case;
a case quantity scanning module, configured to determine each scanning center point in the target area, and scan the case statistical quantities corresponding to the target positions in a scanning range using different scanning windows according to each scanning center point, to obtain the case scanning quantities of the statistical time periods in the scanning range corresponding to each scanning window;
and the early warning area determining module is used for determining a case number early warning area in the target area according to the case scanning number of each statistical time period in the scanning range corresponding to each scanning window.
9. An electronic device, comprising:
a processor; and
a memory for storing one or more programs which, when executed by the processor, cause the processor to implement the method of warning of the number of cases according to any one of claims 1 to 7.
10. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method of warning of the number of cases according to any one of claims 1 to 7.
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