IP Library Granted Patent US 12,308,128
Granted Patent B2
US 12,308,128 · App. 16/936,278 · Granted May 20, 2025

Health data aggregation and outbreak modeling

Inventors: Pardis Sabeti (Cambridge, MA); Andres Colubri (Cambridge, MA); Todd Brown (Cambridge, MA)
Assignees: The Broad Institute, Inc.; President and Fellows of Harvard College
G16H50/80G06N7/01G16H50/50G16H50/70H04W4/023H04W4/80
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Quick Facts
Patent No.
US 12,308,128
App. No.
16/936,278
Filed
Jul 22, 2020
Granted
May 20, 2025
Kind
B2
Art Unit
3682
USPC
705/2
Abstract

The technology uses aggregated health data and outbreak models to conduct differential diagnosis and provide risk assessments that indicate a likelihood of contracting COVID-19. A healthcare organization server provides COVID-19 diagnostic kits and health applications to participating computing devices that log user health data and registers contacts with other participating users via wireless interactions. The organization compares received data with data received from computing devices from a plurality of other users and identifies common occurrences. The server creates an outbreak model of a geographic region based on the data. The server communicates a determined likelihood of contracting COVID-19 of the user to the user computing device. The server provides the outbreak model to the user, healthcare workers, or others for use in responding to the outbreak.

Claims (46)

1. A computer-implemented method to use aggregated data to provide a population informed assessment of infection in real-time, comprising:

by one or more computing systems:

transmitting, in real-time, from a user computing device associated with a user by way of a wireless communication technology to the one or more computing systems, a first input, the first input is a communication of user data, the user data comprising medical history of the user, a current symptoms profile, diagnostic results, location history, and social network connectivity;

transmitting, in real-time, from a plurality of computing devices associated with a plurality of other users by way of a wireless communication technology to the one or more computing systems, a second input, the second input is a communication comprising medical history, a current symptoms profile, diagnostic results, location history, and social network connectivity of each of the plurality of other users;

processing, in real-time, by way of the one or more computing systems, the first input and the second input with a population Partially Observed Markov Process (POMP)-based model of a disease event;

generating, in real-time, by way of the one or more computing systems, a connectivity score, the connectivity score being based at least in part on the location history of the user, a number of social media connections of the user with a sub-set of other users, and a type of contagion to which the user may have been exposed;

generating, in real-time, by way of the one or more computing systems, a population informed risk of infection of the user based at least in part on the connectivity score and common attributes and from the population POMP-based model of a disease event, a health status of a geographic region of the user based on the population POMP-based model, and diagnostics and/or treatment based on the population informed risk of infection of the user; and

transmitting to the user in real-time by way of a push notification, the population informed risk of infection, the health status of a geographic region, and the diagnostics and/or treatment by way of the wireless communication technology from the one or more computing systems to the user computing device.

2. The computer-implemented method of claim 1 , wherein the population model determines a rate of infectivity for COVID-19.

3. The computer-implemented method of claim 1 , wherein the model is generated via a machine-learning function.

4. The computer-implemented method of claim 1 , wherein the user data further comprises user attributes comprising contact information, dwelling, place of employment, school of enrollment, or a combination thereof.

5. The computer-implemented method of claim 1 , wherein

user data further comprises health data comprising a genetic profile.

6. The computer-implemented method of claim 1 , wherein the health data comprises a partial or whole genomic sequence of a SARS-Cov-2 isolated from the user.

7. The computer-implemented method of claim 6 where the partial or whole genomic sequence is used to determine a pathogen transmission chain.

8. The computer-implemented method of claim 1 , further comprising, by the user computing device:

registering contact of the user computing device to proximate user computer devices of participating users; and

transmitting registered contacts to the one or more computing systems.

9. The computer-implemented method of claim 1 , wherein transmitting further comprises communicating a status of a user to the user computing device to display to the user in real-time by way of the notification technology.

10. The computer-implemented method of claim 8 , wherein the user computing device broadcasts a location and identity periodically or continuously.

11. The computer-implemented method of claim 10 , wherein the user computing device broadcasts via Bluetooth technology and transmits contact data between the user and plurality of other users periodically or continuously by way of the Bluetooth technology.

12. The computer-implemented method of claim 1 , wherein identification of the sub-set of users is based on one or more of location data of the user computing device and contact data from the user computing device.

13. The computer-implemented method of claim 8 , wherein identification of the sub-set of users is based at least in part on a list of contacts from one or more of a contact application and a social media application.

14. The computer-implemented method of claim 8 , further comprising simulation of response to one or more simulated actions to be taken by a user.

15. The computer-implemented method of claim 14 , wherein the simulated actions comprise quarantining and/or treatment.

16. The computer-implemented method of claim 14 , further comprising simulation of response to one or more simulated actions to be taken by one or more users of a population.

17. The computer-implemented method of claim 1 , further comprising displaying, by the user computing device, a map illustrating areas in which a contagious illness is prevalent.

18. The computer-implemented method of claim 1 , wherein the user data is input into the user computing device via an application operating on the user computing device.

19. A system to use aggregated health data and outbreak models to provide risk assessments to user computing devices in real-time, the system comprising:

a diagnostic kit, comprising:

components sufficient to allow a user to be tested to determine if the user has contracted an infectious disease;

a storage device; and

a processor communicatively coupled to the storage device, wherein the processor executes application code instructions that are stored in the storage device to cause the system to:

transmit, in real-time from a user computing device associated with a user by way of a wireless communication technology, a first input, the first input is a communication of user data, the user data comprising medical history of the user, a current symptoms profile, diagnostic results, location history, and social network connectivity;

transmit, from a plurality of computing devices associated with a plurality of other users by way of a wireless communication technology, a second input, the second input is a communication comprising medical history, a current symptoms profile, diagnostic results, location history, and social network connectivity of each of the plurality of other users;

process, in real-time, the first input and the second input with a population Partially Observed Markov Process (POMP)-based model of a disease event;

generate, in real-time, a connectivity score, the connectivity score being based at least in part on the location history of the user, a number of social media connections of the user with a sub-set of other users, and a type of contagion to which the user may have been exposed;

generate, in real-time, a real time population informed risk of infection of the user based at least in part on the connectivity score and common attributes and from the population POMP-based model of a disease event, a real time health status of a geographic region of the user based on the population POMP-based model, and diagnostics and/or treatment based on the population informed risk of infection of the user; and

transmit to the user in real-time by way of one or more push notifications, the population informed risk of infection, the health status of a geographic region, and the diagnostics and/or treatment by way of the wireless communication technology to the user computing device.

20. The system of claim 19 , wherein the population model determines a rate of infectivity for COVID-19.

21. The system of claim 19 , wherein the population model is generated via a machine-learning function.

22. The system of claim 19 , wherein the user data further comprises user attributes comprising contact information, dwelling, place of employment, school of enrollment, or a combination thereof.

23. The system of claim 19 , wherein user data further comprises health data comprising a genetic profile.

24. The system of claim 19 , further comprising simulation of response to one or more simulated actions to be taken by one or more user(s) in a population.

25. The method of claim 1 , wherein the notification technology comprises of a push notification.

26. The system of claim 19 , wherein the notification technology comprises of a push notification.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 8, 2021
From: COLUBRI, ANDRES
To: THE BROAD INSTITUTE, INC.
Reel/Frame 055864/0343 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 6, 2021
From: BROWN, TODD
To: THE BROAD INSTITUTE, INC.
Reel/Frame 054836/0121 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2020
From: SABETI, PARDIS
To: HOWARD HUGHES MEDICAL INSTITUTE
Reel/Frame 053894/0064 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2020
From: PARDIS SABETI, FOR HERSELF AND AS AGENT OF HOWARD HUGHES MEDICAL INSTITUTE
To: PRESIDENT AND FELLOWS OF HARVARD COLLEGE
Reel/Frame 053894/0074 →
Continuity (3)
Provisional Application 62877754 · Jul 23, 2019
Provisional Application 62877773 · Jul 23, 2019
Related Publication 20210050116A1 · Feb 18, 2021
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