MIT Covid-19 Response System (MCRS) FAQ
The MIT Quest for Intelligence and Lincoln Lab are collaborating to model the effects of the return to campus, primarily focusing on the near term with the research ramp-up. In response to a charge from Vice Chancellor for Undergraduate and Graduate Education Ian Waitz and Vice President for Research Maria Zuber, the Quest and Lincoln Lab are building the MIT Covid-19 Response System (MCRS), designed to answer the following questions:
- What are the current and predicted population densities in different buildings across campus at different timepoints in the future?
- What is the current and predicted flow of people at entrance points across campus at different timepoints in the future?
- What locations represent potential hotspots of increased risk?
- What are the predicted risks of infection in different demographics on campus?
We anticipate the system will be used to answer additional questions over time by MIT’s senior administration.
No, the MCRS system is meant to meet an operational need at MIT. We do not plan to conduct research with this data and are focusing on answering operational questions for MIT.
We are currently using de-identified portions of:
- The IS&T-managed Covid Access dataset, specifically a one-way encryption of each individual’s Kerberos ID, along with eligibility-to-return criteria, type of commute, number of hours, building numbers, assigned cores and schedule.
- The daily records of the badge readers, de-identified using the same one-way encryption of the Kerberos IDs.
- GIS campus layouts.
- The floor plans that principal investigators submitted to inform the initial phase of the research ramp-up process.
As we build out the system, we may need additional datasets. We will keep this page updated as new datasets are requested and approved.
The encryption of the IDs means we cannot tell who is who. Furthermore, we will not know who any specific piece of data is associated with, but we need to know how many people are where, and how often they are there.
We will use these records to build models of how the overall MIT population functions on campus. Knowing the aggregate behavior of people allows us to make predictions of the density of people in buildings and shared facilities, which allows us to model the risk of increased infections.
We have experience in creating synthetic datasets via simulation that have population-level statistics that match the individual data, but where the records in the synthetic datasets do not correspond to any given individual. These synthetic datasets can be more broadly shared without risk of revealing the behavior of any individual.
There are four potential actions MIT might take based on the datasets:
- Increase or decrease constraints on building access.
- Adapt testing strategies for individuals who have access to specific buildings on campus.
- Increase or decrease custodial services.
- Increase communications regarding the importance of social distancing, personal protective equipment, and other protocols.
Following MIT’s policy on Privacy and Disclosure of Information, even for de-identified data, we will tightly restrict access to the individual records. Only specific and identified engineers in the Quest for Intelligence and Lincoln Lab will have access to the data, and for specific purposes. The data is protected by access control with access audits provided by a partner cloud service provider. All personnel with access to the data are registered with the Legal, Ethical, Equity Committee for Campus Planning (LEE).
We will follow the LEE’s guidelines, which call for deleting all human-sourced data collected as part of MCRS projects or operations after the data are no longer operationally relevant. We assume that the overall sunset period for all data will be at most 12 months. If the data must be retained for longer, we will re-apply to LEE.
We will retain no more than four weeks’ worth of badge reader records. We believe this will give us sufficient data to build models of the day-to-day building entry flow while retaining no more data than necessary.
Different data sets have different oversight bodies. LEE reviews and approves all requests for data, and reviews and approves the uses of the system by senior administration. Data provided by IS&T are reviewed and approved by the IT Governance Committee.
Yes. While the data collected will be de-identified, the system includes an opt-out option. When completing the acknowledgement form in the Covid Pass app (available to those authorized for on-campus access), you may opt out of data collection. New and existing users of Covid Pass may opt out of data collection at any time by resubmitting the acknowledgement form.