Covid Analytics

Analytics for a better world project

This project connects to SDG 3, Good Health and Well-Being.


The Research project is led by Professor Dimitris Bertsimas of MIT. Several collaborators, students and partners work on this large effort.

View the full team.



The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at a steep economic price. We design analytical tools to support these decisions and combat the pandemic. Specifically, we propose a comprehensive data-driven approach to understand the clinical characteristics of COVID-19, predict its mortality, forecast its evolution, and ultimately alleviate its impact. By leveraging cohort-level clinical data, patient-level hospital data, and census-level epidemiological data, we develop an integrated four-step approach, combining descriptive, predictive and prescriptive analytics. First, we aggregate hundreds of clinical studies into the most comprehensive database on COVID-19 to paint a new macroscopic picture of the disease. Second, we build personalized calculators to predict the risk of infection and mortality as a function of demographics, symptoms, comorbidities, and lab values. Third, we develop a novel epidemiological model to project the pandemic’s spread and inform social distancing policies. Fourth, we propose an optimization model to re-allocate ventilators and alleviate shortages. Our results have been used at the clinical level by several hospitals to triage patients, guide care management, plan ICU capacity, and re-distribute ventilators. At the policy level, they are currently supporting safe back-to-work policies at a major institution and equitable vaccine distribution planning at a major pharmaceutical company, and have been integrated into the US Center for Disease Control’s pandemic forecast.

A critical tool for COVID-19 planning is charting out the progression of the pandemic across the United States and the world. They have developed a new epidemiological model called DELPHI, which forecasts infections, hospitalizations, and deaths. You can think of our model as a standard SEIR model with additional features specific to the COVID-19 pandemic, like under-detection and differentiated government intervention.




View the project and ongoing research on the Covid Analytics Project Website.