Maia Majumder

[1] Her Ph.D. thesis focused on modeling disease transmission dynamics during real-world outbreaks, taking into account that there is heterogeneity within populations, so some individuals are more likely than others to transmit an infection.

[2] While at Massachusetts Institute of Technology, Majumder joined HealthMap, a team of researchers, epidemiologists, and software developers at Boston Children's Hospital that utilizes freely available electronic data to perform real-time disease outbreak monitoring and surveillance.

In 2019, Majumder was appointed a faculty member at Harvard Medical School and Boston Children's Hospital's Computational Health Informatics Program (CHIP).

[13][14] The analysis utilized publicly available data from cases of the infection in Wuhan, China between December 1, 2019 and January 26, 2020 and estimated the R0 is somewhere between 2.0 and 3.1, making COVID-19 more contagious that the seasonal flu.

[16] She notes that in order to get an accurate view of COVID-19's fatality, we must first know how many people have actually been infected—a number that is unclear due to limited COVID-19 testing and the need to survey populations for who may have antibodies for the virus, but only experienced a mild infection.