Apparatus, method and program for determining optimal collection size of a collection test method for the diagnosis of infectious diseases

Abstract

An electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to the present invention comprises: a memory storing a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooled size based on the prevalence rate of the infectious disease and the number of subjects in the pooled test method; and a processor that sets the prevalence rate and the number of subjects in the test count calculation function and determines the pooled size as the optimal aggregation size such that the test count calculation function with the prevalence rate and the number of subjects set calculates the minimum total number of tests, wherein the pooled size may be the number of samples collected from subjects in the pooled test step that are pooled into one pooled group.

Description

Technology Field

[0001] The present invention relates to an electronic device, method, and computer program for determining the optimal aggregation size of a pooled test method for the diagnosis of infectious diseases. More specifically, the invention relates to an electronic device, method, and computer program for determining the optimal aggregation size of a pooled test method for the diagnosis of infectious diseases, which can induce an efficient pooled test method by determining the minimum pooled size as the optimal pooled size through a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, for each pooled size based on the prevalence rate of the infectious disease and the number of subjects in the pooled test method. Background Technology

[0003] Molecular diagnostics is a representative in vitro diagnostic method that detects the cause of a disease or the presence of infection by detecting nucleic acids (DNA, RNA, or their variants) from disease-causing bacteria, viruses, and other pathogens. The molecular diagnostic process consists of a pretreatment step to obtain pure nucleic acids, a gene amplification step using Polymerase Chain Reaction (PCR), and a diagnostic step involving analysis. Among these, the pretreatment step is the process of extracting nucleic acids containing target genes from biological samples to secure the target genes intended for gene amplification.

[0004] Such pretreatment processes consume a significant amount of time due to steps such as mixing samples with various reagents and handling residues. Furthermore, since these procedures are carried out in laboratories equipped with necessary equipment (such as centrifuges), samples collected from patients, including blood, must be transported to the laboratory. However, as infectious diseases like COVID-19 have recently shown a rapid rate of infection leading to a surge in patients, rapid diagnosis and follow-up measures are required above all else. In other words, rapid diagnosis at the scene is essential.

[0005] Meanwhile, the sample pretreatment process requires mixing samples with various reagents, necessitating specialized personnel with relevant expertise. However, in situations where the number of patients surges, there is a severe shortage of skilled professionals to handle the situation, which causes the molecular diagnostic process to take a long time. To address this issue, pooled testing methods have been introduced, in which multiple samples are combined into a single sample and individual retests are performed on the remaining samples if the result is positive. However, problems are arising, such as a decrease in testing speed, as the number of tests increases depending on the number of samples mixed. Prior art literature

[0007] Korean Registered Patent No. 10-2560947 The problem to be solved

[0008] The objective of the present invention is to provide an electronic device, method, and computer program for determining the optimal aggregate size of a pooled test method for diagnosing an infectious disease, which can induce an efficient pooled test method by determining the minimum aggregate size as the optimal aggregate size through a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the prevalence rate of the infectious disease and the number of subjects in the pooled test method, based on the pooled test size.

[0009] The objects of the present invention are not limited to those mentioned above, and other unmentioned objects and advantages of the present invention may be understood from the following description and will be more clearly understood by the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims. means of solving the problem

[0011] An electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to the present invention comprises: a memory storing a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooled size based on the prevalence rate of the infectious disease and the number of subjects in the pooled test method; and a processor that sets the prevalence rate and the number of subjects in the test count calculation function and determines the pooled size as the optimal aggregation size such that the test count calculation function with the prevalence rate and the number of subjects set calculates the minimum total number of tests, wherein the pooled size may be the number of samples collected from subjects in the pooled test step that are pooled into one pooled group.

[0012] The processor can determine the optimal aggregation size using the test count calculation function, which calculates the total test count by summing the first test count, which is the number of diagnostic tests performed in the aggregate inspection step, and the second test count, which is the number of diagnostic tests performed in the individual inspection step according to the result of the aggregate inspection step.

[0013] The above test count calculation function can calculate the first test count according to the aggregation size using the set number of test subjects, calculate the expected value for a test result diagnosed as positive when the diagnostic test is performed the first test count in the aggregation test stage using the prevalence rate and the first test count, and calculate the second test count using the expected value and the aggregation size.

[0014] The above function for calculating the number of checks can be expressed by the following mathematical formula.

[0016] <Mathematical Formula>

[0018] Here, E(R) is the total number of tests, N1 is the number of the first test, N2 is the number of the second test, and N is the number of test subjects, and is the expected value, g is the pool size, and p' is the probability that the test result of a diagnostic test for any one pool group will be diagnosed as positive according to the prevalence.

[0019] The memory may store a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooling size based on either the prevalence rate of the infectious disease or the positivity rate of the infectious disease and the number of subjects in the pooled test method.

[0020] The processor includes, when the prevalence rate is not obtained, a processor that sets the positive rate and the number of subjects in the test count calculation function and determines the aggregation size as the optimal aggregation size such that the test count calculation function with the positive rate and the number of subjects set calculates the minimum total number of tests; and the processor compares the regional positive rate, which is the positive rate of the infectious disease in the region where the aggregation test method is performed, with the national positive rate, which is the positive rate of the infectious disease nationwide, and determines the positive rate set in the test count calculation function as either the regional positive rate or the national positive rate based on the comparison result, and the aggregation size may be the number of samples collected from subjects in the aggregation test step that are aggregated into one aggregation group.

[0021] The processor includes a processor that, when the prevalence rate is not obtained, sets the positive rate and the number of subjects in the test count calculation function, and determines the aggregation size as the optimal aggregation size such that the test count calculation function with the positive rate and the number of subjects set calculates the minimum total test count; wherein the processor determines whether the change value of the regional positive rate, which is the positive rate of the infectious disease in the region where the aggregate testing method is performed, exceeds a reference change value, and based on the result of the determination, determines the positive rate set in the test count calculation function as either the first regional positive rate, which is the regional positive rate during a first past period from the time of performance of the aggregate testing method, or the second regional positive rate, which is the regional positive rate during a second past period from the time of performance, wherein the first past period is shorter than the second past period, and the aggregation size may be the number of samples aggregated into one aggregation group among the samples collected from subjects in the aggregate testing step.

[0022] A method for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to the present invention comprises: a step in which a processor sets the prevalence rate and the number of subjects in a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooled test size based on the prevalence rate of the infectious disease and the number of subjects in the pooled test method; and a step in which the processor determines the pooled size as the optimal aggregation size such that the test count calculation function, in which the prevalence rate and the number of subjects are set, calculates the minimum total number of tests; wherein the pooled size may be the number of specimens collected from subjects in the pooled test step that are pooled into one pooled group.

[0023] The above determining step may include a step in which the processor determines the optimal aggregation size using a test count calculation function that calculates the total test count by summing the first test count, which is the number of diagnostic tests performed in the aggregate test step, and the second test count, which is the number of diagnostic tests performed in the individual test step according to the result of the aggregate test step.

[0024] The above test count calculation function can calculate the first test count according to the aggregation size using the set number of test subjects, calculate the expected value for a test result diagnosed as positive when the diagnostic test is performed the first test count in the aggregation test stage using the prevalence rate and the first test count, and calculate the second test count using the expected value and the aggregation size.

[0025] The above function for calculating the number of checks can be expressed by the following mathematical formula 2.

[0026] <Mathematical Formula>

[0027] Here, E(R) is the total number of tests, N1 is the number of the first test, N2 is the number of the second test, and N is the number of test subjects, and is the expected value, g is the pool size, and p' is the probability that the test result of a diagnostic test for any one pool group will be diagnosed as positive according to the prevalence.

[0029] A computer program according to the present invention may be stored on a computer-readable recording medium to enable a method for extracting tinnitus characteristics based on the measurement of the narrowband minimum masking according to the present invention described above. Effects of the invention

[0031] An efficient pooled testing method can be derived by determining the minimum pooling size as the optimal pooling size through a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled testing step and the individual testing step included in the pooled testing method according to the present invention, based on the prevalence rate of infectious diseases and the number of subjects in the pooled testing method, according to the pooled testing method. Brief explanation of the drawing

[0033] FIG. 1 is a conceptual diagram of an electronic device and an external device for determining the optimal aggregate size of an aggregate test method for diagnosing infectious diseases according to one embodiment of the present invention. FIG. 2 is a block diagram of an electronic device for determining the optimal aggregate size of an aggregate test method for diagnosing infectious diseases according to one embodiment of the present invention. FIG. 3 is a diagram illustrating a pooled test method to which an electronic device for determining the optimal pooling size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention is applied. Figure 4 is a graph showing the optimal aggregation size by prevalence rate determined by an electronic device for determining the optimal aggregation size of an aggregation test method for diagnosing infectious diseases according to one embodiment of the present invention. FIG. 5 is a diagram showing a screen in which an electronic device for determining the optimal aggregate size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention outputs the optimal aggregate size. FIG. 6 is a flowchart of a method for determining the optimal aggregate size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention. Specific details for implementing the invention

[0034] Hereinafter, various embodiments of the present invention are described with reference to the accompanying drawings. However, this is not intended to limit the present invention to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives of the embodiments of the present invention. In connection with the description of the drawings, similar reference numerals may be used for similar components.

[0035] In this document, expressions such as "have," "can have," "include," or "can include" refer to the existence of the relevant feature (e.g., numerical values, functions, actions, or components, etc.) and do not exclude the existence of additional features.

[0036] In this document, expressions such as “A or B”, “at least one of A or / and B”, or “one or more of A or / and B” may include all possible combinations of items listed together. For example, “A or B”, “at least one of A and B”, or “at least one of A or B” may refer to cases including (1) at least one A, (2) at least one B, or (3) both at least one A and at least one B.

[0037] Expressions such as "first," "second," "first," or "second" used in this document may modify various components regardless of order and / or importance, and are used merely to distinguish one component from another without limiting such components. For example, the first user device and the second user device may represent different user devices regardless of order or importance. For example, without departing from the scope of rights set forth in this document, the first component may be named the second component, and similarly, the second component may be renamed the first component.

[0038] When it is stated that a certain component (e.g., a first component) is "(operatively or communicatively) coupled with / to" or "connected to" another component (e.g., a second component), it should be understood that said certain component is directly connected to said other component or may be connected through said other component (e.g., a third component). On the other hand, when it is stated that a certain component (e.g., a first component) is "directly connected" or "directly connected" to said other component (e.g., a second component), it may be understood that no other component (e.g., a third component) exists between said certain component and said other component.

[0039] As used in this document, the expression "configured to" may be replaced, depending on the context, with, for example, "suitable for," "having the capacity to," "designed to," "adapted to," "made to," or "capable of." The term "configured to" does not necessarily mean "specifically designed to" in hardware. Instead, in some situations, the expression "device configured to" may mean that the device is "capable of" in conjunction with other devices or components. For example, the phrase “a control unit configured (or set) to perform A, B, and C” may mean a dedicated processor for performing said operations (e.g., an embedded processor), or a generic-purpose processor (e.g., a CPU or an application processor) capable of performing said operations by executing one or more software programs stored in memory.

[0040] In particular, in this specification, the “~device” may include one or more of a Central Processing Unit (CPU), an Application Processor (AP), and a Communication Processor (CP).

[0041] In this specification, “~device” refers to any type of hardware device comprising at least one processor, and may be understood to include software configurations operating on said hardware device according to the embodiments. For example, “~device” may be understood to include smartphones, tablet PCs, desktops, laptops, and user clients and applications running on each of these devices, but is not limited thereto.

[0042] The terms used in this document are used merely to describe specific embodiments and are not intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by those skilled in the art described in this document. Terms used in this document that are defined in general dictionaries may be interpreted as having the same or similar meaning as they have in the context of the relevant technology, and are not to be interpreted in an ideal or overly formal sense unless explicitly defined in this document. In some cases, even terms defined in this document may not be interpreted to exclude the embodiments of this document.

[0043] FIG. 1 is a conceptual diagram of an electronic device and an external device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention, FIG. 2 is a block diagram of an electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention, and FIG. 3 is a diagram for explaining a pooled test method to which an electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention is applied.

[0044] Referring to FIGS. 1 to 3, an electronic device (100) for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention can determine the optimal aggregation size to minimize the total number of tests performed when the prevalence rate and the number of test subjects are determined, through a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooled size, based on the prevalence rate of the infectious disease and the number of test subjects in the pooled test method.

[0045] Here, the pooled testing method may be a diagnostic testing method for infectious diseases consisting of a sample collection step, a pooled testing step, and an individual testing step, as illustrated in FIG. 3.

[0046] Specifically, during the sample collection stage, samples can be collected from each of the multiple subjects who visited the testing center.

[0047] Subsequently, in the pooled testing stage, specimens collected from each of the multiple subjects are pooled and mixed in a pooled size to form a pooled group, and then a diagnostic test for an infectious disease can be performed on each of the multiple pooled groups.

[0048] Subsequently, in the individual testing stage, diagnostic tests are performed individually on each specimen collected in the pooled group in which the diagnostic test result in the pooled testing stage was diagnosed as positive, thereby identifying test subjects infected with an infectious disease.

[0049] An electronic device (100) for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease according to one embodiment of the present invention can optimally determine the aggregation size, which is the number of specimens collected from test subjects and aggregated into one aggregation group, in the pooled test step of the pooled test method described above.

[0050] To this end, an electronic device (100) for determining the optimal aggregate size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention may include a processor (140), a display unit (150), an input unit (120), a communication unit (110), and a memory (130).

[0051] The communication unit (110) can receive various information and data from an external device (200) that is necessary for the electronic device (100) determining the optimal aggregation size of the aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention to determine the optimal aggregation size.

[0052] Specifically, the communication unit (110) can receive the prevalence rate of infectious diseases and the number of subjects subject to the pooled testing method from an external device (200).

[0053] Here, the external device (200) may be one or more of the servers of a local health center managing infectious diseases and a health authority.

[0054] The input unit (120) can receive various information and data necessary for the electronic device (100) for determining the optimal aggregation size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention to determine the optimal aggregation size.

[0055] Specifically, the input unit (120) can receive input from the user regarding the prevalence rate of infectious diseases and the number of subjects subject to the pooled testing method.

[0056] To this end, the input unit (120) may be equipped with one or more of a mouse device, a keyboard device, a tablet device, and a touch module.

[0057] Previously, the prevalence rate of infectious diseases and the number of subjects received by the communication unit (110) or the prevalence rate of infectious diseases and the number of subjects entered by the input unit (120) can be set in the test count calculation function by the processor (140).

[0058] A detailed explanation regarding this will be provided later.

[0059] Memory (130) can store a function to calculate the number of checks.

[0060] Here, the test count calculation function may be a function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test stage and the individual test stage included in the pooled test method, according to the pooling size based on the prevalence of the infectious disease and the number of subjects in the pooled test method.

[0061] In other words, the test count calculation function may be a function that calculates the total number of tests based on the aggregation size, given that the prevalence rate of the infectious disease and the number of subjects in the pooled test method are fixed.

[0062] Specifically, the function for calculating the number of tests can calculate the total number of tests by summing the first number of tests, which is the number of diagnostic tests performed in the aggregated test stage, and the second number of tests, which is the number of diagnostic tests performed in the individual test stage based on the results of the aggregated test stage.

[0063] At this time, the test count calculation function can calculate the first test count according to the aggregate size using the number of test subjects.

[0064] In addition, the test count calculation function can calculate the expected value of a test result diagnosed as positive when a diagnostic test is performed the first number of times at the pooled test stage using the prevalence rate and the first number of tests, and can calculate the second number of tests using the expected value and the pooling size.

[0065] Such a function for calculating the number of checks can be expressed by the following mathematical formula 1.

[0067] <Mathematical Formula 1>

[0068]

[0069] Here, E(R) is the total number of tests, N1 is the number of the first test, N2 is the number of the second test, and N is the number of test subjects, and is the expected value, g is the pool size, and p' is the probability that the test result of a diagnostic test for any one pool group will be diagnosed as positive according to the prevalence.

[0071] That is, the processor (140) inputs the prevalence rate of the infectious disease and the number of subjects received by the communication unit (110) or the prevalence rate of the infectious disease and the number of subjects input by the input unit (120) into a test count calculation function and sets the total number of tests, which is the output value of the test count calculation function that is calculated differently as the aggregation size is changed, into an optimal aggregation size such that the minimum total number of tests is calculated as the output value.

[0072] Figure 4 is a graph showing the optimal aggregation size by prevalence rate determined by an electronic device for determining the optimal aggregation size of an aggregation test method for diagnosing infectious diseases according to one embodiment of the present invention.

[0073] Referring to FIG. 4, the processor (140) can predetermine the optimal aggregation size by using a test count calculation function set by setting the number of test subjects to “100,000” and changing the prevalence rate from “0%” to “100%”.

[0074] Meanwhile, the processor (140) compares the total number of inspections according to the determined optimal aggregation size with the number of subjects, and if the total number of inspections according to the determined optimal aggregation size exceeds the number of subjects, it may decide not to perform the aggregation inspection method.

[0075] Meanwhile, the memory (130) can store a function to calculate the number of inspections according to another embodiment.

[0076] Here, the function for calculating the number of tests according to another embodiment may be a function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test stage and the individual test stage included in the pooled test method, by pooling size based on the positivity rate of the infectious disease and the number of subjects in the pooled test method.

[0077] That is, the test count calculation function according to another embodiment may be a function that calculates the total number of tests by aggregate size based on the positivity rate and the number of subjects, rather than the prevalence rate, compared to the test count calculation function according to one embodiment.

[0078] At this time, the processor (140) according to another embodiment can determine the optimal aggregate size by using a test count calculation function according to another embodiment, which is a function that calculates the total number of tests based on the positive rate and the number of test subjects in each aggregate size when the prevalence rate is not obtained due to the initial transmission stage of the infectious disease.

[0079] Specifically, in the case where the prevalence rate is not obtained and only the positivity rate is obtained due to the initial transmission stage of the infectious disease, the processor (140) according to another embodiment can set the positivity rate and the number of test subjects in the test count calculation function according to another embodiment.

[0080] Subsequently, the processor (140) according to another embodiment can determine the optimal aggregation size such that the test count calculation function according to another embodiment, in which the positive rate and the number of test subjects are set, calculates the minimum total number of tests.

[0081] At this time, the processor (140) according to another embodiment compares the regional positive rate, which is the positive rate of infectious disease in the region where the aggregate testing method is performed, with the national positive rate, which is the positive rate of infectious disease in the country, and based on the comparison result, can determine the positive rate set in the test count calculation function according to another embodiment as either the regional positive rate or the national positive rate.

[0082] Specifically, the processor (140) according to another embodiment may set the regional positive rate to the positive rate set in the test count calculation function according to another embodiment if the regional positive rate is smaller than the national positive rate.

[0083] Conversely, if the regional positive rate is greater than the national positive rate, the processor (140) according to another embodiment may set the national positive rate to the positive rate set in the test count calculation function according to another embodiment.

[0084] Additionally, when the processor (140) according to another embodiment determines the positive rate set in the test count calculation function according to another embodiment as the regional positive rate, it determines whether the change value of the regional positive rate exceeds a reference change value, and based on the result of the determination, the positive rate (regional positive rate) set in the test count calculation function according to another embodiment may be determined as either the first regional positive rate, which is the regional positive rate during the first past period from the time of execution when the aggregated test method is performed, or the second regional positive rate, which is the regional positive rate during the second past period from the time of execution.

[0085] Specifically, the processor (140) according to another embodiment may set the first regional positive rate to the positive rate set in the test count calculation function according to another embodiment when the change value of the regional positive rate exceeds the reference change value.

[0086] Conversely, the processor (140) according to another embodiment may set the second regional positive rate to the positive rate set in the test count calculation function according to another embodiment if the change value of the regional positive rate is less than or equal to the reference change value.

[0087] Here, the first past period may be shorter than the second past period.

[0088] That is, if the change in the positive rate is large, the positive rate of a short past period can be set by inputting it into a test count calculation function according to another embodiment, and if the change in the positive rate is small, the positive rate of a long past period can be set by inputting it into a test count calculation function according to another embodiment.

[0089] FIG. 5 is a diagram showing a screen in which an electronic device for determining the optimal aggregate size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention outputs the optimal aggregate size.

[0090] Referring to FIG. 5, the processor (140) can control the display unit (150) so that the determined optimal aggregation size is displayed on the screen.

[0091] At this time, the processor (140) can control the display unit (150) so that the prevalence rate, the number of subjects, etc., along with the determined optimal aggregation size, are displayed on the screen.

[0092] Through this, inspectors at the testing center can perform the aggregate testing method by checking the optimal aggregate size displayed on the screen.

[0093] To this end, the display unit (150) may be equipped with a display module.

[0094] The processor (140) can perform the operation of each of the components described above and may include one or more cores (not shown) and a graphics processing unit (not shown) and / or a connection channel (e.g., a bus, etc.) for transmitting and receiving signals with other components.

[0095] The processor (140) may be configured to perform the operation of each of the components described above by executing one or more instructions stored in memory (130).

[0096] The memory (130) can store programs (one or more instructions) for processing and controlling the processor (140). The programs stored in the memory (130) can be divided into multiple modules according to their function.

[0097] The memory (130) can store data, information, and signals to perform the functions described above.

[0098] FIG. 6 is a flowchart of a method for determining the optimal aggregate size of an aggregate test method for diagnosing an infectious disease according to one embodiment of the present invention.

[0099] Referring to Fig. 6, in step S1, the processor obtains the prevalence of the infectious disease and the number of subjects subject to the pooled testing method.

[0100] Subsequently, in step S2, the processor sets the prevalence rate and the number of subjects in a test count calculation function that calculates the total number of tests—which is the total number of diagnostic tests performed in the pooled test stage and individual test stage included in the pooled test method—based on the prevalence rate of the infectious disease and the number of subjects in the pooled test method, according to the pooling size.

[0101] Finally, in step S3, the processor determines the optimal aggregation size such that the test count calculation function, with the prevalence rate and the number of test subjects set, calculates the minimum total number of tests.

[0102] The present invention has been described above with reference to preferred embodiments. Those skilled in the art will understand that the present invention can be implemented in modified forms without departing from the essential characteristics of the invention. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the invention is defined by the claims, not by the foregoing description, and all variations within the scope of the claims should be interpreted as being included in the invention.

[0103] As described above, although the present invention has been explained by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs. Explanation of the symbols

[0105] 100: Electronic device for determining the optimal pool size of a pooled test method for the diagnosis of infectious diseases 110 : Processor 120 : Output section 130 : Display unit 140 : Input section 150 : Communications Department 160 : Storage section

Claims

Claim 1 An electronic device for determining the optimal pooling size of a pooled test method for the diagnosis of an infectious disease, comprising: a memory storing a test count calculation function that calculates the total number of tests, which is the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method, according to the pooling size based on either the prevalence rate of the infectious disease and the positivity rate of the infectious disease and the number of subjects of the pooled test method; and, when the prevalence rate is obtained, a processor sets the prevalence rate and the number of subjects in the test count calculation function, and determines the aggregation size as the optimal aggregation size such that the test count calculation function with the prevalence rate and the number of subjects set calculates the minimum total number of tests; wherein the aggregation size is the number of samples collected from subjects in the aggregation test step that are aggregated into one aggregation group; and, when the positivity rate is obtained and the prevalence rate is not obtained, the processor sets the positivity rate and the number of subjects in the test count calculation function, and determines the aggregation size as the optimal aggregation size such that the test count calculation function with the positivity rate and the number of subjects set calculates the minimum total number of tests; and, when the positivity rate is obtained and the prevalence rate is not obtained, the processor compares the magnitude between the regional positivity rate, which is the positivity rate of the infectious disease in the region where the aggregation test method is performed, and the national positivity rate, which is the positivity rate of the infectious disease nationwide, and if the regional positivity rate is smaller than the national positivity rate, the test count calculation The positive rate set in the function is determined as the regional positive rate, and if the regional positive rate is greater than the national positive rate, the positive rate set in the test count calculation function is determined as the national positive rate, and when the processor determines the positive rate set in the test count calculation function as the regional positive rate, it determines whether the change value of the regional positive rate exceeds a reference change value.An electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease, characterized in that if the change value of the region positive rate exceeds the reference change value, the positive rate set in the test count calculation function is determined as the first region positive rate, which is the region positive rate during the first past period from the time of execution when the pooled test method is performed; if the change value of the region positive rate is less than or equal to the reference change value, the positive rate set in the test count calculation function is determined as the second region positive rate, which is the region positive rate during the second past period from the time of execution, wherein the first past period is shorter than the second past period; and the processor compares the total number of tests according to the determined optimal aggregation size with the number of subjects, and if the total number of tests according to the determined optimal aggregation size exceeds the number of subjects, it is determined not to perform the pooled test method. Claim 2 An electronic device for determining the optimal aggregation size of a aggregate test method for diagnosing an infectious disease, characterized in that, in claim 1, the processor determines the optimal aggregation size using a test count calculation function that calculates the total test count by summing the first test count, which is the number of diagnostic tests performed in the aggregate test step, and the second test count, which is the number of diagnostic tests performed in the individual test step according to the result of the aggregate test step. Claim 3 An electronic device for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease, characterized in that, in paragraph 2, the test count calculation function calculates the first test count according to the aggregation size using the set number of test subjects, calculates an expected value for a test result diagnosed as positive when the diagnostic test is performed the first test count using the set prevalence rate or the set positive rate and the first test count, and calculates the second test count using the expected value and the aggregation size. Claim 4 An electronic device for determining the optimal aggregate size of an aggregate test method for diagnosing infectious diseases, characterized in that, in paragraph 3, the function for calculating the number of tests is expressed by the following mathematical formula. Here, E(R) is the total number of tests, N1 is the number of the first test, N2 is the number of the second test, and N is the number of test subjects, and is the expected value, g is the pool size, and p' is the probability that the result of a diagnostic test for any one pool group will be diagnosed as positive according to the prevalence or positivity rate. Claim 5 A method for determining the optimal pool size of a pooled test method for the diagnosis of an infectious disease comprises: a step in which a processor sets the prevalence rate and the positivity rate of the infectious disease and the number of subjects in a test count calculation function, which calculates the total number of diagnostic tests performed in the pooled test step and the individual test step included in the pooled test method based on the pool size and the number of subjects in the pooled test method, wherein the total number of tests is the total number of tests performed in each pooled test step and the pooled test method; and the step of setting the prevalence rate and the positivity rate and the number of subjects is further comprising the step in which, if the prevalence rate is obtained, the processor sets the prevalence rate and the number of subjects in the test count calculation function; and the method for determining the optimal pool size of a pooled test method for the diagnosis of an infectious disease further comprises the step in which the processor determines the pool size as the optimal pool size such that the test count calculation function, in which the prevalence rate and the number of subjects are set, calculates the minimum total number of tests; wherein the pool size is the pool In the testing stage, the number of specimens collected from test subjects is collected into one pool of specimens, and the step of setting either the prevalence rate and the positivity rate and the number of test subjects further includes the step of the processor setting the positivity rate and the number of test subjects in the test count calculation function when the positivity rate is obtained and the prevalence rate is not obtained; and the method for determining the optimal pooling size of a pooled testing method for the diagnosis of an infectious disease includes the step of determining the pooling size as the optimal pooling size such that the test count calculation function, in which the positivity rate and the number of test subjects are set, calculates the minimum total number of tests.The step of further including the positive rate and the number of subjects in the test count calculation function is as follows: when the positive rate is obtained and the prevalence rate is not obtained, the processor compares the regional positive rate, which is the positive rate of the infectious disease in the region where the pooled testing method is performed, with the national positive rate, which is the positive rate of the infectious disease nationwide; if the regional positive rate is smaller than the national positive rate, the processor determines the positive rate set in the test count calculation function as the regional positive rate; and if the regional positive rate is larger than the national positive rate, the processor determines the positive rate set in the test count calculation function as the national positive rate. The method for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease further comprises the step of: when the processor determines the positive rate set in the test count calculation function as the regional positive rate, determining whether the change value of the regional positive rate exceeds a reference change value; if the change value of the regional positive rate exceeds the reference change value, determining the positive rate set in the test count calculation function as the first regional positive rate, which is the regional positive rate during a first past period from the time of execution when the pooled test method is performed; and if the change value of the regional positive rate is less than or equal to the reference change value, determining the positive rate set in the test count calculation function as the second regional positive rate, which is the regional positive rate during a second past period from the time of execution when the pooled test method is performed; wherein the first past period is shorter than the second past period. The method further comprises the step of the processor comparing the total number of tests according to the determined optimal aggregation size with the number of subjects, and determining not to perform the pooled test method if the total number of tests according to the determined optimal aggregation size exceeds the number of subjects. A method for determining the optimal aggregate size of an aggregate test method for the diagnosis of infectious diseases, characterized by: Claim 6 A method for determining the optimal aggregation size of a pooled test method for diagnosing an infectious disease, characterized in that, in claim 5, the determining step comprises the step of the processor determining the optimal aggregation size using the test count calculation function, which calculates the total test count by summing the first test count, which is the number of diagnostic tests performed in the pooled test step, and the second test count, which is the number of diagnostic tests performed in the individual test step according to the result of the pooled test step. Claim 7 A method for determining the optimal aggregation size of a pooled testing method for the diagnosis of an infectious disease, wherein, in claim 6, the function for calculating the number of tests calculates the first number of tests according to the aggregation size using the set number of subjects, calculates the expected value for a test result diagnosed as positive when the diagnostic test is performed the first number of tests using the set prevalence rate or the set positivity rate and the first number of tests, and calculates the second number of tests using the expected value and the aggregation size. Claim 8 A method for determining the optimal aggregate size of an aggregate testing method for the diagnosis of an infectious disease, characterized in that, in claim 7, the function for calculating the number of tests is expressed by the following mathematical formula. Here, E(R) is the total number of tests, N1 is the number of the first test, N2 is the number of the second test, and N is the number of test subjects, and is the expected value, g is the pool size, and p' is the probability that the result of a diagnostic test for any one pool group will be diagnosed as positive according to the prevalence or positivity rate. Claim 9 A computer program stored on a computer-readable recording medium that is combined with a computer, which is hardware, to enable the execution of a method according to any one of claims 5 through 8. Claim 10 delete Claim 11 delete

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