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Privacy and Ethics in Pandemic Data Collection and Processing


  • The Institute for Computational and Experimental Research in Mathematics (ICERM) 121 South Main Street Providence, RI, 02903 United States (map)

[workshop]

In January of 2023, over 50 experts in the field(s) of public health, epidemiology, simulation modeling, cryptography, and bioethics came together in Providence, Rhode Island for the first in a series of workshops sponsored by the Center for Mobility Analysis for Pandemic Prevention Strategies (MAPPS) at Brown University. This event was co-hosted by Brown University’s NSF-funded Institute for Computational and Experimental Research in Mathematics (ICERM).


The goal(s) of the workshop were to:

  1. Develop a state-of-the-art approach to collect and analyze human mobility and social mixing data that can inform real-time pandemic responses while balancing benefits, risks and harms.

  2. Develop a protocol for the MAPPING@Brown exercise; and

  3. Identify and initiate new collaborations that can support an application in response to the forthcoming U.S. National Science Foundation (NSF) Predictive Intelligence for Pandemic Prevention (PIPP) Phase II Center Grants solicitation.

The four-day workshop ran from January 17th – 20th, 2023 and included five keynote speakers, three state of the science presentations, five small-group breakout sessions, and one panel discussion with MAPPS investigators. The workshop aimed to build on collective knowledge and deliver the following outcomes:

  • Data: Prioritized list of data needs for measuring movement and social mixing during the MAPPING@Brown study.

  • Privacy and ethics: Concrete approaches to managing the ethical issues that arise from collecting, managing, analyzing, and sharing mobility and social mixing data.

  • Technical execution: Outline of the technical approaches to use and share potentially sensitive data responsibly.

  • Modeling: Proposed MAPPING@Brown modeling and simulation scenarios that might enable us to, predict, prevent, and mitigate future pandemics.

  • Data sharing: Identification of techniques for using multi-party computation to securely analyze mobility and social mixing datasets from multiple institutions or mobile devices at once.

The workshop steering committee included all six MAPPS PIs as well as Betsy Stubblefield Loucks (Associate Director of Research Strategy in the Office of the Vice President of Research), Peyton Luiz (MAPPS Project Manager), Jason Gantenberg (Research Scientist in the Department of Health Services, Policy & Practice and Assistant Professor of Practice in Epidemiology), and Aditya Khanna (Assistant Professor in the Department of Behavioral and Social Sciences). 

For complete information on workshop proceedings, recommendations, agenda, and attendees please refer to the Workshop Summary Report.

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November 10

Mobility Analysis for Pandemic Prevention Strategies (MAPPS): Using mobility and social network data to predict and prevent future pandemics

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January 31

COVID Information Commons: Mobility Analysis for Pandemic Prevention Strategies (MAPPS) by Mark Lurie