Hyperlocal Risk Monitoring and Pandemic Preparedness

Hyperlocal Risk Monitoring and Pandemic Preparedness through Privacy-Enhanced Mobility and Social Interactions Analysis

Table of Contents

Description

This project develops a framework for hyperlocal risk monitoring and data-driven decision-making for pandemic preparedness. Such hyperlocal awareness can help governments and response officials at all levels with policy-making, e.g., opening in-person or online; closing or partially shutting down businesses; proactively reallocating medical supplies and medical workforces to more vulnerable areas, enabling better preparation and readiness for disease outbreaks. It can also benefit community members’ decision-making, e.g., avoiding high-risk areas. We use fine-grained mobility and social interactions data to better model infection spread. Furthermore, we use privacy-enhanced monitoring techniques to protect users’ privacy.



  • Shaham, Sina and Ghinita, Gabriel and Shahabi, Cyrus Models and mechanisms for spatial data fairness, Proceedings of the VLDB Endowment, v.16, 2022.

  • Shaham, Sina and Ghinita, Gabriel and Shahabi, Cyrus Differentially-Private Publication of Origin-Destination Matrices with Intermediate Stops, Proceedings of the 25th International Conference on Extending Database Technology (EDBT), 2022.

  • Rambhatla, Sirisha and Zeighami, Sepanta and Shahabi, Kameron and Shahabi, Cyrus and Liu, Yan Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data, ACM Transactions on Spatial Algorithms and Systems, v.8, 2022.

  • Wang, Chenyu and Lin, Zongyu and Yang, Xiaochen and Sun, Jiao and Yue, Mingxuan and Shahabi, Cyrus HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting, Proceedings of the AAAI Conference on Artificial Intelligence, v.36, 2022.

  • Zaidi, Abbas and Ahuja, Ritesh and Shahabi, Cyrus Differentially Private Occupancy Monitoring from WiFi Access Points, 23rd IEEE International Conference on Mobile Data Management (MDM), 2022.

  • Zeighami, Sepanta and Shahabi, Cyrus and Krumm, John Estimating Spread of Contact-Based Contagions in a Population Through Sub-Sampling, Proceedings of the VLDB Endowment, v.14, 2021.


Software Artifacts


People


Students

Sepanta Zeighami

CS PhD Student, USC

Ritesh Ahuja

Graduated Aug/2022

Kameron Shahabi

CS Undergrad. Student, USC


Colaborators

John Krumm

Viterbi School of Engineering, USC

Gabriel Ghinita

CSE, Hamad Bin Khalifa University

Sina Shaham

CS PhD Student, USC


Principal Investigator

Cyrus Shahabi

Viterbi School of Engineering, USC


Sponsors