Test server, communication terminal, test system, and test method

Abstract

A test server includes: a communication unit that communicates with a plurality of communication terminals via a network, the plurality of communication terminals each being connectable to a test device capable of executing a test on the presence or absence of a disease and each being capable of inputting a diagnosis on the presence or absence of the disease, the diagnosis being related to the test and made by a doctor; and a control unit that acquires at least one of a result of the test and the diagnosis as a test information item from each of the plurality of communication terminals via the communication unit, causes a storage unit to store the plurality of acquired test information items therein, performs statistical processing on the plurality of stored test information items, and causes the communication unit to return a result of the statistical processing according to a demand given from each of the communication terminals before the doctor makes a diagnosis.

1 . A prevalence rate prediction method for infectious disease, comprising:
 communicating with a plurality of communication terminals via a network, wherein
 each of the plurality of communication terminals is connected to a test device, wherein the test device is configured to execute a test on one of a presence or an absence of the infectious disease, and 
 each of the plurality of communication terminals inputs a diagnosis on the one of the presence or the absence of the infectious disease; 
   acquiring a plurality of test information from the plurality of communication terminals, wherein each of the plurality of test information comprises at least one of a result of the test or a result of the diagnosis;   controlling a storage device to store the acquired plurality of test information;   performing statistical process on the stored plurality of test information, wherein at least one of a result of the statistical process is a current prevalence rate;   outputting the result of the statistical process based on a demand given from each of the plurality of communication terminals before doctor's diagnosis; and   predicting a future prevalence rate based on the current prevalence rate and a prevalence rate that is before a specific period.   
     
     
         2 . The prevalence rate prediction method according to  claim 1 , wherein
 the result of the statistical process is at least one of a positive predictive value or a negative predictive value, and   the result of the statistical process is outputted based on:
 a number of at least one first test information of the plurality of test information in which the result of the test and the result of the diagnosis are positive; 
 a number of at least one second test information of the plurality of test information in which the result of the test is negative and the result of the diagnosis is positive; 
 a number of at least one third test information of the plurality of test information in which the result of the test is positive and the result of the diagnosis is negative; and 
 a number of at least one fourth test information of the plurality of test information in which the result of the test and the result of the diagnosis are negative. 
   
     
     
         3 . The prevalence rate prediction method according to  claim 1 , further comprising calculating a change rate of a future prevalence rate per unit time based on the current prevalence rate and the prevalence rate that is before the specific period. 
     
     
         4 . The prevalence rate prediction method according to  claim 1 , further comprising providing a warning information to a user based on the future prevalence rate, wherein the warning information corresponds to information of future infection spread. 
     
     
         5 . The prevalence rate prediction method according to  claim 4 , wherein the warning information is provided based on the predicted future prevalence rate exceeds a specific threshold value. 
     
     
         6 . The prevalence rate prediction method according to  claim 1 , further comprising correcting the current prevalence rate based on at least one of patient attribute information, terminal attribute information, or location information. 
     
     
         7 . The prevalence rate prediction method according to  claim 6 , further comprising:
 performing weighting based on at least one of the patient attribute information, the terminal attribute information, or the location information; and   correcting the current prevalence rate based on the performed weighting.   
     
     
         8 . The prevalence rate prediction method according to  claim 6 , further comprising:
 performing narrowing down of target data based on at least one of the patient attribute information, the terminal attribute information, or the location information; and   correcting the current prevalence rate based on the performed narrowing down of the target data.   
     
     
         9 . The prevalence rate prediction method according to  claim 6 , wherein the patient attribute information includes at least one of medical interview information, medication information, previous disease, physical information, lifestyle habits information, genotype, microbial flora of patients, or race. 
     
     
         10 . The prevalence rate prediction method according to  claim 6 , wherein the terminal attribute information includes region information that is associated with a test terminal. 
     
     
         11 . The prevalence rate prediction method according to  claim 10 , further comprising estimating the current prevalence rate based on a distance between the current position of the test terminal and the position that is associated with execution of the test, wherein the terminal attribute information includes a current position of the test terminal and a position that is associated with execution of the test. 
     
     
         12 . The prevalence rate prediction method according to  claim 10 , further comprising
 acquiring an immunization penetration rate in an administrative district, wherein a communication terminal of the plurality of communication terminals is associated with the administrative district; and   correcting the current prevalence rate based on the acquired immunization penetration rate.   
     
     
         13 . The prevalence rate prediction method according to  claim 6 , wherein
 the location information includes information of first region information in which the test is not implemented and information of at least one second region in which the test is implemented, and   the at least one second region is different from the first region.   
     
     
         14 . The prevalence rate prediction method according to  claim 13 , further comprising
 estimating the current prevalence rate in the first region based on a plurality of prevalence rates and a factor having an influence on infection between each of the at least one second region and the first region, wherein
 the plurality of prevalence rates is associated with the at least one second region, and 
 the plurality of prevalence rates is different from the current prevalence rate, future prevalence rate, and the prevalence rate that is before the specific period. 
   
     
     
         15 . The prevalence rate prediction method according to  claim 1 , wherein the result of the test is associated with execution of various types of tests. 
     
     
         16 . The prevalence rate prediction method for infectious according to  claim 1 , further comprising calculating a positive rate of the stored plurality of test information instead of the current prevalence rate. 
     
     
         17 . The prevalence rate prediction method according to  claim 1 , further comprising:
 evaluating effectiveness of the test based on a positive predictive value;   transmitting an evaluation result of effectiveness of the test to each of the plurality of communication terminals; and   causing each of the plurality of communication terminals to output a message of one of recommendation or non-recommendation for the test.   
     
     
         18 . The prevalence rate prediction method according to  claim 1 , acquiring the plurality of stored test information from the test device. 
     
     
         19 . A test server to predict a prevalence rate of infectious disease, comprising: circuitry configured to:
 communicate with a plurality of communication terminals via a network, wherein
 each of the plurality of communication terminals is connected to a test device, wherein the test device is configured to execute a test on one of a presence or an absence of the infectious disease, and 
 each of the plurality of communication terminals inputs a diagnosis on the one of the presence or the absence of the infectious disease; 
   acquire a plurality of test information from the plurality of communication terminals, wherein each of the plurality of test information comprises at least one of a result of the test or a result of the diagnosis;   control a storage device to store the acquired plurality of test information;   perform statistical process on the stored plurality of test information, wherein at least one of a result of the statistical process is a current prevalence rate;   output the result of the statistical process based on a demand given from each of the plurality of communication terminals before doctor's diagnosis; and   predict a future prevalence rate based on the current prevalence rate and a prevalence rate that is before a specific period.   
     
     
         20 . A test system to predict a prevalence rate of infectious disease, comprising
 a test device that executes a test on one of a presence or an absence of a disease; and   a test server that comprises circuitry configured to:
 communicate with a plurality of communication terminals via a network, wherein
 each of the plurality of communication terminals is connected to a test device, wherein the test device is configured to execute a test on one of a presence or an absence of the infectious disease, and 
 each of the plurality of communication terminals inputs a diagnosis on the one of the presence or the absence of the infectious disease; 
 
 acquire a plurality of test information from the plurality of communication terminals, wherein each of the plurality of test information comprises at least one of a result of the test or a result of the diagnosis; 
 control a storage device to store the acquired plurality of test information; 
 perform statistical process on the stored plurality of test information, wherein at least one of a result of the statistical process is a current prevalence rate; 
 output the result of the statistical process based on a demand given from each of the plurality of communication terminals before doctor's diagnosis; and 
 predict a future prevalence rate based on the current prevalence rate and a prevalence rate that is before a specific period.