Privacy-Preserving Movement Analytics for Multi-Pathogen Risk Scoring
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Solution Overview
Problem
Existing pandemic-surveillance systems fail to provide privacy-friendly, actionable insights for individuals and organizations to reduce infection and death rates during pandemics, leading to a conflict between minimizing virus spread and maintaining economic activity.
Innovation Solution
Implementing a suite of technologies including a mobile app for personal risk indexing, SaaS for workplace safety, and DaaS for public health policy, which provide dynamic risk assessments and behavior modification suggestions to guide movement decisions, reducing infection and death rates while allowing economic activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pandemic surveillance systems collect detailed movement data to track virus spread, then infection tracking accuracy is improved, but privacy protection deteriorates
Solution Approach 1:
The patent extracts only the essential epidemiological features from movement data (geolocation paths, time stamps, duration at locations) while deliberately excluding personally identifiable information. This allows infection tracking to proceed with sufficient accuracy for public health purposes while removing the privacy-violating elements of the data.
Solution Approach 2:
The patent applies different data processing qualities to different aspects of movement data. Aggregated statistical data is maintained in detailed form for epidemiological analysis, while individual-level data is anonymized or removed. This local differentiation allows simultaneous achievement of tracking accuracy and privacy protection in different data contexts.
2Object-affected harmful factors
If strict movement restrictions are implemented to reduce virus spread, then infection rates are reduced, but economic activity deteriorates
Solution Approach 1:
The patent implements dynamic risk assessment that continuously updates movement recommendations based on current epidemiological conditions, location-specific transmission rates, and real-time movement data. This allows restrictions to be adjusted dynamically - stricter in high-risk areas and times, more permissive in low-risk contexts - thereby reducing infections while preserving economic activity where safe.
Solution Approach 2:
The patent applies different movement restriction recommendations to different geographic locations based on local epidemiological conditions. High-risk locations receive stricter guidance while low-risk locations maintain normal activity levels. This spatial differentiation allows infection reduction in critical areas without broadly suppressing economic activity across all regions.
3Measurement precision
If comprehensive movement data is collected to assess infection risk, then risk assessment accuracy is improved, but data security requirements deteriorate
Solution Approach 1:
The patent extracts and retains only the epidemiologically relevant features of movement data (geographic paths, temporal patterns, duration metrics) while removing or anonymizing identifiers that would compromise security. This extraction maintains risk assessment accuracy by preserving transmission-risk patterns while eliminating the security vulnerabilities associated with storing comprehensive personal data.
Data Source
AI summary
Provided is a process, including: obtaining movement transactions without having server-side access to information by which the members of the population undergoing the changes in geolocation indicated by the movement transactions can be identified, either personally or pseudonymously; obtaining for movement transactions corresponding to a designated window of time, geographic-pathogen-risk scores of starting geolocations that include the starting geographic positions; updating for the movement transactions corresponding to the designated window of time, geographic-pathogen-risk scores of the ending geolocations based on both geographic-pathogen-risk scores of the starting geolocations involved in movement transactions ending at the ending geolocations and rates of traffic at the ending geolocations indicated by movement transactions ending or starting at the ending geolocations.