Controlling compartmental flows in epidemiological modeling based on mobility data

US11948694B2 · kind B2 · utility

Inventors

• Vishrawas Gopalakrishnan · Cambridge, US
• Sayali Navalekar · Westford, US
• James H. Kaufman · San Jose, US
• Simone Bianco · San Francisco, US
• Kun Hu · Santa Clara, US
• Ajay A. Deshpande · White Plains, US
• Sarah Kefayati · San Francisco, US
• Ujwal Reddy Moramganti · Ashburn, US
• George Sirbu · Saline, US
• Xuan Liu · Yorktown Heights, US
• Raman Srinivasan · Plano, US
• Pan Ding · New York, US

Key dates

• Filing date: May 12, 2021
• Grant date: Apr 2, 2024
• Expiry date: Feb 1, 2042

Classification

• Technology area (CPC Y): Emerging Cross-Sectional Technologies
• CPC primary: Y02A90/10
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Mechanisms are provided for compartmental epidemiological computer modeling based on mobility data. Machine learning training of an isolation rate prediction computer model is performed to generate a trained isolation rate prediction model that predicts an isolation rate of a biological population. Isolation data is received which comprises data indicating a measure of mobility of the biological population. The trained isolation rate prediction model is executed on input features extracted from the isolation data to generate a predicted isolation rate. A compartmental epidemiological computer model, comprising a plurality of compartments representing states of a population with regard to an infectious disease, is executed to simulate a progression of the infectious disease and flows of portions of the population from between compartments in the compartmental epidemiological computer model are controlled based on the predicted isolation rate.