System and method for analyzing and controlling epidemics

• US 9,141,762 B2
• Filed: 12/13/2011
• Issued: 09/22/2015
• Est. Priority Date: 12/15/2010
• Status: Active Grant

• Current Assignee: Biocell EPI Limited
• Original Assignee: Hayim Shaul, Michal Lev, Ran Balicer, Ron Lev
• Inventors: Lev, Michal, Shaul, Hayim, Lev, Ron, Balicer, Ran
• Primary Examiner(s): Eng, George
• Assistant Examiner(s): HAMMONDS, MARCUS C
• Application Number:
  US13/993,186
• Publication Number:
  US 20130275160A1
• Time in Patent Office: 1,379 Days
• Field of Search: 4554561-457, 455/412.2, 4554041-4042, 4554141-4144
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
• CPC Class Codes: G16H 70/60 relating to pathologies
• CPC Class Codes: H04M 2203/2094 Proximity
• CPC Class Codes: H04M 3/22 Arrangements for supervision, monitoring or testing
• CPC Class Codes: H04M 3/42357 where the information is provided to a monitoring entity such as a potential calling party or a call processing server
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds

Abstract

A method for analyzing and controlling epidemics in which an initiating signal is received indicative of a list of newly classified carriers of an infectious disease from an authorized health authority. Location data is received for a mobile device and a mobility pattern derived from the received location data is compared with a mobility pattern of first users to determine occurrence of a proximity event, during which one of the first users was spaced from a given carrier less than a predetermined distance. The proximity event is ranked in terms of the likelihood that the given carrier was involved in the transmission of the disease during the proximity event. If the ranking of the proximity event is higher than a predetermined level, the process is repeated for the first user participating in the proximity event and for second users. Corrective action information is then transmitted.

Claims

1. A method for analyzing and controlling epidemics, comprising the steps of:

a) receiving an initiating signal which is indicative of a list of newly classified carriers of an infectious disease from an authorized health authority;

b) extracting location data and interaction data for mobile devices belonging to said newly classified carriers using Call Detail Records (CDRs) that are continuously collected and stored for all mobile device users;

c) comparing a mobility pattern and interpersonal interaction pattern derived from said extracted location data and interaction data for each newly classified carrier of the newly classified carriers with a mobility pattern and an interpersonal interaction pattern of a plurality of mobile device users to determine encounters and occurrence of one or more proximity events, wherein during the one or more proximity events at least one first user of said plurality of mobile device users was within a predetermined distance of at least one of the newly classified carriers or social interactions occurred between said at least one first user and said at least one of the newly classified carriers;

d) ranking said one or more proximity events in terms of the likelihood that said at least one of the newly classified carriers was involved in transmission of said infectious disease during said one or more proximity events, based on at least one of an interaction duration or a pre-encounter event;

e) repeating steps c) and d) for the at least one first user participating in said one or more proximity events and at least one second user of the plurality of mobile device users when the ranking of said one or more proximity events is higher than a predetermined level;

f) finding a group of users from the plurality of mobile device users that have been infected and/or having the highest probability to be infected, without being symptomatic, based on the ranking;

g) transmitting corrective action information to control spreading of said infectious disease; and

h) transmitting forensic analysis information, in response to the number of mobile device users in said group of users and identification information of mobile device users participating in said one or more proximity events where said ranking is higher than said predetermined level.

2. The method according to claim 1, wherein the location and interaction data is extracted from consumer proprietary network information which is collected by data network service providers during transmission of a communication link.

3. The method according to claim 2, wherein the data network is a cellular network and the consumer proprietary network information is a call detail record of the call detail records.

4. The method according to claim 2, wherein the data network is a WiFi network or a WiMAX network.

5. The method according to claim 1, wherein the location and interaction data is generated by a location identifying component provided with the mobile device.

6. The method according to claim 5, wherein the location identifying component is a subscriber identity module (SIM) application.

7. The method according to claim 1, wherein the one or more proximity events is ranked higher than the predetermined level when the pre-encounter event involving the at least one first user and the at least one of the newly classified carriers preceded the one or more proximity events.

8. The method according to claim 7, wherein the pre-encounter event is the transmission of a communication link between the at least one first user and the at least one of the newly classified carriers within a predetermined time prior to the one or more proximity events.

9. The method according to claim 7, wherein the pre-encounter event is ingress of the at least one first user and the at least one of the newly classified carriers into a common vehicle.

10. The method according to claim 1, wherein the one or more proximity events is ranked higher than the predetermined level when the one or more proximity events continues for more than a predetermined duration.

11. The method according to claim 9, wherein the one or more proximity events is ranked higher than the predetermined level when an average proximity between the at least one first user and the at least one of the newly classified carriers within the vehicle is less than a predetermined value.

12. The method according to claim 1, wherein the initiating signal is also indicative of policy rules or of disease information, type and characteristics.

13. The method according to claim 1, wherein the corrective action signal is indicative of infected locations and infected people.

14. The method according to claim 1, further comprising the steps of:

a) classifying the at least one first user as a potential carrier when the ranking of said one or more proximity events is higher than a predetermined level; and

b) determining an extent of an epidemic distribution in response to a known number of carriers and potential carriers and in response to epidemic source information.

15. A system for determining interpersonal interaction patterns during a period of distress, comprising:

a) a health authority server for transmitting an initiating signal which is indicative of a list of selected mobile device users carrying an infectious disease;

b) a plurality of mobile devices each accessed by a different mobile device user of a plurality of mobile device users and having a unique hardware identifier;

c) a component for generating location data and interaction data for each of said plurality of mobile devices, using Call Detail Records (CDRs) that are continuously collected and stored for all mobile device users; and

d) a processing device for extracting said location data and interaction data associated with the mobile devices of said selected mobile device users of the plurality of mobile device known to require assistance during a period of distress and for generating from said location data and interaction data a mobility pattern and interpersonal interaction pattern for said selected mobile device users, wherein said processing device is operable to;

i. determine encounters and occurrence of one or more proximity events, by means of said mobility pattern and interpersonal interaction pattern, between at least one of said selected mobile device users and at least one corresponding additional mobile device user of the plurality of mobile device users, wherein during the one or more proximity events said at least one corresponding additional mobile device user was within a predetermined distance of said at least one of the selected mobile device users or social interactions occurred between said at least one corresponding additional mobile device user and said at least one of the selected mobile device users;

ii. rank said one or more proximity events in terms of the likelihood that, during said one or more proximity events, said at least one corresponding additional mobile device user was in need of said assistance, based on at least one of an interaction duration or a pre-encounter event;

iii) repeat steps i, and ii, for said at least one corresponding additional mobile device and at least one second corresponding mobile device user of the plurality of mobile device users when the ranking of said one or more proximity events is higher than a predetermined level;

iv. find a group of users of the plurality of mobile device users that have been infected and/or having the highest probability to be infected, without being symptomatic, based on the ranking;

v. classify said at least one corresponding additional mobile device user as one or more potential beneficiaries of said assistance when said one or more proximity events was ranked higher than said predetermined level; and

vi. transmit a corrective action signal to an authority to indicate the nature or scope of assistance that is required for said selected mobile device users and the one or more potential beneficiaries;

vii. transmit forensic analysis information, in response to the number of users in said group of users and identification information of mobile device users participating in said one or more proximity events where said ranking is higher than said predetermined level.

16. The system according to claim 15, wherein the selected mobile device users is a carrier of an infectious disease, the assistance is receiving a vaccine for said disease, and the one or more potential beneficiaries are potential carriers of said disease.

17. The system according to claim 16, further comprising transmitting the initiating signal which is indicative of a list of newly classified carriers of said disease to the processing device.

18. The system according to claim 17 wherein the health authority server is operable to receive a defining signal from an authorized health entity to indicate that someone has been diagnosed as being a carrier of the infectious disease.

19. The system according to claim 16, wherein the processing device comprises an evaluation module for determining the ranking of one or more proximity events and a potential carrier database which stores identifying information of all classified potential carriers.

20. The system according to claim 19, wherein the evaluation module is operable to assign a ranking higher than the predetermined level upon determining that the pre-encounter event involving the at least one corresponding additional user and the at least one selected mobile device user preceded the one or more proximity events,

involving the at least one first user and the at least one of the newly classified carriers preceded the one or more proximity events.

21. The system according to claim 16, wherein the initiating signal is indicative of information selected from the group consisting of characteristics of the disease, known ways of transmitting the disease, probability of disease transmission after being within an infectable range, time of disease incubation after having been transmitted to another person, health authority policy rules regarding what type of vaccination is required and quarantine rules, carrier identification, and information regarding known infected locations.

22. The system according to claim 15, wherein the location generating component is stored in each of the plurality of mobile devices.

23. The system according to claim 15, wherein the location generating component is stored in a data network service provider center and is operable to provide consumer proprietary network information associated with each of the plurality of mobile devices which is collected during transmission of a communication link therewith.

24. The system according to claim 15, wherein the corrective action signal is indicative of information selected from the group consisting of real-time or near to real-time epidemic status information, epidemic distribution information, epidemic source information, risk information, strategy decisions, graphic probability maps, post processing information, and identity of the first carrier of the disease.

25. The system according to claim 15, wherein the at least one selected mobile device user is a trapped person, the assistance is being rescued from a fallen building site, and the one or more potential beneficiaries is a potentially trapped user.