Contact tracing analytics

• US 10,251,610 B2
• Filed: 01/26/2016
• Issued: 04/09/2019
• Est. Priority Date: 01/26/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Parthasarathy, Kanagavalli, Pillai, Saritha S., Rojo, Marianne B., Sethumadhavan, Kishore, Syarif, Ronny, Tandiono, Helen
• Primary Examiner(s): Small, Naomi J
• Application Number:
  US15/006,214
• Publication Number:
  US 20170209102A1
• Time in Patent Office: 1,169 Days
• Field of Search: 34053911
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records

Abstract

Contact tracing during an event is provided. Community interaction information for one or more clusters is determined. The community interaction information for a cluster correlates times and physical locations of one or more individuals within an area corresponding to the cluster. It is determined that a first individual has traveled from a first area corresponding to a first cluster to a second area corresponding to a second cluster. The determination is based, at least in part, on correlated times and physical locations of the first individual. One or more at-risk individuals is identified based, at least in part, on the community interaction information of the second cluster.

Claims

1. A method for contact tracing during an event, the method comprising:

connecting, by one or more processors, a plurality of disparate sources of information to an algorithm, wherein the plurality of disparate sources of information comprise;

(i) different data formats containing at least data describing body temperature readings corresponding to a plurality of individuals, data describing a plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the plurality of individuals, and data describing a plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the plurality of individuals; and

(ii) interaction data which proliferates into a large data set;

converting, by one or more processors, the plurality of disparate sources of information into a common format amenable for analytics by the algorithm, wherein the algorithm sends the large data set to a data repository;

determining, by one or more processors, community interaction information for one or more clusters within the common format, wherein the community interaction information for a cluster correlates times and physical locations of one or more individuals within an area corresponding to the cluster;

performing, by one or more processors, the analytics on the plurality of disparate sources of information converted to the common format, in order to determine that a first individual has traveled from a first area corresponding to a first cluster to a second area corresponding to a second cluster, wherein the determination is based, at least in part, on correlated times and physical locations of the first individual; and

predicting, by one or more processors, one or more at-risk individuals by generating a list of the one or more at-risk individuals, as contained within the large data set in the data repository, based at least in part on;

the performed analytics which;

(i) account for dynamic events associated with the first cluster and the second cluster, wherein the dynamic events include a plurality of seamless interactions within the first cluster and the second cluster and between the first cluster and the second cluster, and (ii) derive discrete data from the plurality of disparate sources of information,

the community interaction information of the second cluster,

the data describing the plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the at-risk individuals among the plurality of individuals, and

the data describing the plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the at-risk individuals among the plurality of individuals.

2. The method of claim 1, wherein determining the community interaction information for the one or more clusters further comprises:

obtaining, by one or more processors, medical information associated with the one or more individuals within the area of the one or more clusters, wherein the obtained medical information may be modified based on the performed analytics; and

obtaining, by one or more processors, risk information associated with the area to which the one or more clusters correspond to, wherein the obtained risk information may be modified based on the performed analytics.

3. The method of claim 2, wherein obtaining medical information associated with the one or more individuals comprises:

obtaining, by one or more processors, patient information from a registration device containing an infrared scanner, wherein the patient information includes body temperatures determined by the infrared scanner for the one or more individuals; and

obtaining, by one or more processors, information associated with the one or more individuals via one or more environmental sensors including at least a mobile communications device and an imaging device.

4. The method of claim 1, wherein performing the analytics on the disparate sources of information, comprises:

optimizing, by one or more processors, the community interaction information for the one or more clusters by grouping data within a defined category wherein disparate sources of the community interaction information are converted into a common data format for further optimization, newly acquired information is received, a first set of the community interaction information is excluded from further optimization, and a second set of the community interaction information is included for further optimization;

indexing, by one or more processors, the data within the defined category utilizing an identifier for at least one individual wherein the optimized data is contained within the identifier, the identifier is searchable, and newly acquired information is received;

creating, by one or more processors, a profile based on the optimized and indexed data within the defined category; and

identifying, by one or more processors, the one or more at-risk individuals based, at least in part, on the profile and the optimized and indexed data.

5. The method of claim 1, further comprising:

in response to determining that the first individual has traveled from the first area to the second area, compiling, by one or more processors, community interaction information associated with the first individual from the first cluster and the second cluster.

6. The method of claim 1, wherein identifying the one or more at-risk individuals further comprises:

performing, by one or more processors, contact tracing at different cluster levels; and

extracting, by one or more processers, data from different cluster levels to obtain contact information of the one or more at-risk individuals.

7. The method of claim 6, further comprising:

providing, by one or more processors, to a user at least one name or contact information for at least one of the one or more at-risk individuals.

8. A computer program product for contact tracing during an event, the computer program product comprising:

a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising;

program instructions to connect a plurality of disparate sources of information to an algorithm, wherein the plurality of disparate sources of information comprise;

(i) different data formats containing at least data describing body temperature readings corresponding to a plurality of individuals, data describing a plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the plurality of individuals, and data describing a plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the plurality of individuals; and

(ii) interaction data which proliferates into a large data set;

program instructions to convert the plurality of disparate sources of information into a common format amenable for analytics by the algorithm, wherein the algorithm stores the large data set, wherein the algorithm sends the large data set to a data repository;

program instructions to determine community interaction information for one or more clusters within the common format, wherein the community interaction information for a cluster correlates times and physical locations of one or more individuals within an area corresponding to the cluster;

program instructions to perform analytics on the plurality of disparate sources of information converted to the common format, in order to determine that a first individual has traveled from a first area corresponding to a first cluster to a second area corresponding to a second cluster, wherein the determination is based, at least in part, on correlated times and physical locations of the first individual; and

program instructions to predict one or more at-risk individuals by generating a list of the one or more at-risk individuals, as contained within the large data set in the data repository, based at least in part on;

the performed analytics which;

(i) account for dynamic events associated with the first cluster and the second cluster, wherein the dynamic events include a plurality of seamless interactions within the first cluster and the second cluster and between the first cluster and the second cluster, and (ii) derive discrete data from the plurality of disparate sources of information,

the community interaction information of the second cluster;

the data describing the plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the at-risk individuals among the plurality of individuals, and

the data describing the plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the at-risk individuals among the plurality of individuals.

9. The computer program product of claim 8, wherein the program instructions to determine the community interaction information for the one or more clusters further comprise:

program instructions to obtain medical information associated with the one or more individuals within the area of the one or more clusters, wherein the obtained medical information may be modified based on the performed analytics; and

program instructions to obtain risk information associated with the area to which the one or more clusters correspond to, wherein the obtained risk information may be modified based on the performed analytics.

10. The computer program product of claim 9, wherein the program instructions to obtaining medical information associated with the one or more individuals, comprise:

program instructions to obtain patient information from a registration device containing an infrared scanner, wherein the patient information includes body temperatures determined by the infrared scanner for the one or more individuals; and

program instructions to obtain information associated with the one or more individuals via one or more environmental sensors including at least a mobile communications device and an imaging device.

11. The computer program product of claim 8, wherein program instructions to perform the analytics on the disparate sources of information, further comprise:

program instructions to optimize the community interaction information for the one or more clusters by grouping data within a defined category wherein disparate sources of the community interaction information are converted into a common data format for further optimization, newly acquired information is received, a first set of the community interaction information is excluded from further optimization, and a second set of the community interaction information is included for further optimization;

program instructions to index the data within the defined category utilizing an identifier for at least one individual wherein the optimized data is contained within the identifier, the identifier is searchable, and newly acquired information is received;

program instructions to create a profile based on the optimized and indexed data within the defined category; and

program instructions to identify the one or more at-risk individuals based, at least in part, on the profile and the optimized and indexed data.

12. The computer program product of claim 8, wherein the program instructions further comprise:

program instructions to, in response to determining that the first individual has traveled from the first area to the second area, compile community interaction information associated with the first individual from the first cluster and the second cluster.

13. The computer program product of claim 8, wherein the program instructions to identify the one or more at-risk individuals further comprise:

program instructions to perform contact tracing at different cluster levels; and

program instructions to extract data from different cluster levels to obtain contact information of the one or more at-risk individuals.

14. The computer program product of claim 13, wherein the program instructions further comprise:

program instructions to provide to a user at least one name or contact information for at least one of the one or more at-risk individuals.

15. A computer system for contact tracing during an event, the computer system comprising:

one or more computer processors;

one or more computer readable storage media;

program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to connect a plurality of disparate sources of information to an algorithm, wherein the plurality of disparate sources of information comprise;

(i) different data formats containing at least data describing body temperature readings corresponding to a plurality of individuals, data describing a plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the plurality of individuals, and data describing a plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the plurality of individuals; and

(ii) interaction data which proliferates into a large data set;

program instructions to convert the plurality of disparate sources of information into a common format amenable for analytics by the algorithm, wherein the algorithm stores the large data set, wherein the algorithm sends the large data set to a data repository;

program instructions to determine community interaction information for one or more clusters within the common format, wherein the community interaction information for a cluster correlates times and physical locations of one or more individuals within an area corresponding to the cluster;

program instructions to perform analytics on the plurality of disparate sources of information converted to the common format, in order to determine that a first individual has traveled from a first area corresponding to a first cluster to a second area corresponding to a second cluster, wherein the determination is based, at least in part, on correlated times and physical locations of the first individual; and

program instructions to predict one or more at-risk individuals by generating a list of the one or more at-risk individuals, as contained within the large data set in the data repository, based at least in part on;

the performed analytics which;

(i) account for dynamic events associated with the first cluster and the second cluster, wherein the dynamic events include a plurality of seamless interactions within the first cluster and the second cluster and between the first cluster and the second cluster, and (ii) derive discrete data from the plurality of disparate sources of information,

the community interaction information of the second cluster;

the data describing the plurality of travel itineraries of destinations traveled with respectively associated traveled dates and times corresponding to each of the at-risk individuals among the plurality of individuals, and

the data describing the plurality of travel itineraries of destinations scheduled for travel with respectively associated scheduled travel dates and times corresponding to each of the at-risk individuals among the plurality of individuals.

16. The computer system of claim 15, wherein the program instructions to determine the community interaction information for the one or more clusters further comprise:

program instructions to obtain medical information associated with the one or more individuals within the area of the one or more clusters, wherein the obtained medical information may be modified based on the performed analytics; and

program instructions to obtain risk information associated with the area to which the one or more clusters correspond to, wherein the obtained risk information may be modified based on the performed analytics.

17. The computer system of claim 16, wherein the program instructions to obtain medical information associated with the one or more individuals, comprise:

program instructions to obtain patient information from a registration device, wherein the patient information includes body temperatures of the one or more individuals; and

program instructions to obtain information associated with the one or more individuals via one or more environmental sensors including at least a mobile communications device and an imaging device.

18. The computer system of claim 15, wherein program instructions to perform the analytics on the disparate sources of information, further comprise:

program instructions to optimize the community interaction information for the one or more clusters by grouping data within a defined category wherein disparate sources of the community interaction information are converted into a common data format for further optimization, newly acquired information is received, a first set of the community interaction information is excluded from further optimization, and a second set of the community interaction information is included for further optimization;

program instructions to index the data within the defined category utilizing an identifier for at least one individual wherein the optimized data is contained within the identifier, the identifier is searchable, and newly acquired information is received;

program instructions to create a profile based on the optimized and indexed data within the defined category; and

program instructions to identify the one or more at-risk individuals based, at least in part, on the profile and the optimized and indexed data.

19. The computer system of claim 15, wherein the program instructions to identify the one or more at-risk individuals further comprise:

program instructions to perform contact tracing at different cluster levels; and

program instructions to extract data from different cluster levels to obtain contact information of the one or more at-risk individuals.

20. The computer system of claim 19, wherein the program instructions further comprise:

program instructions to provide to a user at least one name or contact information for at least one of the one or more at-risk individuals.