covid19_datathon

This repo holds files for a group project for MIT's COVID-19 week long part time Datathon. Our team focused on disparities in health outcomes from COVID-19, specifically:

* How complete is COVID-19 mortality data by race in the USA?

* What socioeconomic factors contribute most to racial disparities in mortality from COVID-19?

Please see the README within the eda folder for a description of our approach and findings.

TEAM:

• Team members: Kristin Mussar, Megan O’Rorke, Bing Han & Timothy Sokphat
• Mentors: Michael Williams from PACE Healthcare Capital & Lauren Chambers from ACLU

CONTRIBUTION FOCUS AREAS:

• Data analysis & visualization of disparity factors: Kristin Mussar (eda folder, files starting with "KM")
• Data analysis & visualization of missing race data: Megan O’Rorke (eda/eda_race_coverage_map.ipynb & images folder)
• Literature review: Bing Han (see prior research in slides PDF)
• Presentation deck: Timothy Sokphat (see slides PDF)

DATA SOURCES:

• COVID Racial Data Tracker
• CDC Death Distributions among Minorities
• COVID-19 Community Vulnerability Index (CCVI)
• Johns Hopkins Racial Data Transparency

BROADER DATATHON CONTEXT:

The MIT COVID19-Datathon is an effort to understand the impact of COVID-19 across 5 areas:

• Measuring the Impact of Policies around COVID-19
• Misinformation during the Pandemic
• Disparities in Health Outcomes from COVID-19
• Epidemiology of COVID-19
• Megacity Pandemic Response in NYC

There are ~400 participants across 5 tracks in teams of 3-7 participants. The datathon organiziers describe the disparities in health outcomes area of research as follows: COVID-19 is not the “great equalizer” that some may claim it to be, with preliminary data from the United States and other jurisdictions indicating that the burden of the pandemic is falling disproportionately upon certain marginalized groups. In this track, the goal is to perform data-driven analyses to characterize and understand the nature and magnitude of these disparities, as well as their structural and policy determinants. We will be analyzing datasets related to the prevalence of COVID-19 among different populations, the outcomes of cases in those populations, and structural determinants such as socio-economic status and food security.

For more information visit https://covid19challenge.mit.edu/datathon/