Campus Coronavirus Response

Colleges can provide much-needed support for strained hospitals

As the growing number of coronavirus cases continues to strain limited hospital resources, college campuses with largely vacated dormitories are in a unique position to provide additional beds and facilities to hospitals. Dorms can be repurposed as alternative sites to house recovering patients and offer temporary lodging to medical personnel, coordinated through hospital systems.

At the MGGG Redistricting Lab, we usually study gerrymandering. But with the same geodata and math modeling skills, we can build a simple model that connects hospitals to nearby college campuses.

Let’s take a look at Massachusetts.

Mapping hospital–university flows in MA

  • size is proportional to number of beds
  • Hospitals
  • Colleges
  • Loading map... JavaScript must be enabled

    Think we should adjust which colleges and hospitals are included? Provide feedback here.

    What are you seeing in these maps?

    This is a mathematical model and mapping tool intended to lend quantitative support to a qualitative point: available dorm capacity can have a significant impact as the nation mobilizes infrastructure for COVID-19 treatment. (See Nation at a Glance below for a visualization showing all 50 states.)

    Our model flows people from hospitals to universities in a way that accounts for bed capacity and minimizes travel time. Here are the separate populations that can be transferred from hospitals to colleges:

    • Medical personnel who need a place to sleep without exposing their families and home communities to risk
    • Hospital patients with non-COVID conditions
    • Hospital patients recovering from COVID

    By freeing beds, this alliance allows hospitals to convert more beds to critical care and provides support for front-line medical workers and other first responders.

    How to use this model

    We anticipate several uses for this model in keeping with its design.

    • Priority campuses. You can sort the campuses in order of utilization (last column in the Data Table) to glean a priority order for mobilizing the campus response.
    • Underserved areas. Planners can look at regions of the state with long travel times to decide where other building types or new emergency facilities will best complement the campus response.
    • Well-matched hospitals. Universities can set the mapping tool to reflect their own available dorm capacity, then receive an indication of which hospitals they are best suited to support.

    Precise model output depends critically on the quality of input data and assumptions, and the need for speed and generality makes those very approximate in this case. Therefore the applications identified above are better supported by the model than relying on detailed assignment numbers of patients and medical staff.

    Data Tables

    College City Number of dorm beds Hospital staff assigned by the model Patients assigned by the model Utilization (%)

    Hospitals included in the model City Number of beds

    Model assumptions and data sources

    The current model only includes flows of medical personnel and non-COVID patients. This is not a predictive model. We are working to sync up with other models of projected COVID demand on hospitals and will add recovering COVID patients at that time.

    Share of dorm capacity that is available for hospital use is left as a parameter in the model, considering that the three types of populations will have to be housed separately and in suitable facilities. The mathematical formulation is described here, and data sourcing is found here. See our GitHub repo for full details of model structure and parameters.

    We thank Michael Apkon of Tufts Medical Center, Assaad Sayah of Cambridge Health Alliance, Dawn Brantley of the Massachusetts Emergency Management Agency, and Ozlem Ergun of Northeastern University for helpful discussions about model uses and design.

    Other states (beta)


    New York

    Caveat: this is based on national-level datasets.
    Contact us here if you would like access to detailed modeling for your state.

    In the news

    About us

    MGGG Redistricting Lab is a research team of the Tisch College of Civic Life at Tufts University. We are grateful for the major support of the National Science Foundation through the Convergence Accelerator award OIA-1937095, Network Science of Census Data.

    This project is a team effort of the MGGG Redistricting Lab with critical collaboration from Parker Rule, Olivia Walch, and Austin Buchanan.

    The Nation at a Glance

    Forty-nine out of fifty states have more dormitory beds than hospital beds, based on DHS datasets. Toggle the bubbles column to sort by the dorm-to-hospital ratio.

    State Dorm-to-Hospital Bed Ratio Total Dorm Capacity Total Hospital Beds