COVID Dashboard Tracks Pandemic in New York City
Thanks to effective public health measures, the COVID-19 outbreak is now much less severe in New York City than it was in the spring, although upwards of 100 people still test positive every day. As businesses and schools reopen, however, there is a chance that the coronavirus could reassert itself.
To see the latest information on COVID-19 in the five boroughs, visit the NYC Neighborhoods COVID-19 Dashboard, which tracks daily cases, deaths, and testing for every New York City neighborhood. Developed by Qixuan Chen, associate professor of biostatistics at Columbia Mailman School, and several students, the tool uses data from the New York City Department of Health and Mental Hygiene to provide visualizations of distributions and trends on cases, hospitalizations, and deaths, along with demographic information, including age, sex, and race/ethnicity, as well as neighborhood characteristics, including demographics and disease burden. A projection feature has also been added as a resource.
The Dashboard shows that on September 8 there were 14 new cases diagnosed in the Flushing/Murray Hill neighborhood of Queens, the most cases citywide. Nearby Corona, Queens, which has seen the most deaths from COVID-19 of any neighborhood, reported 5 new cases. Many other neighborhoods reported no cases. Across the city, the pandemic has disproportionately affected older adults, men, and communities of color.
“We built this tool to give policymakers and the general public the ability to get timely information about COVID-19 in New York City—information which may prove important as schools reopen,” says Chen. “It also allows researchers to study the disparate impact of COVID-19 on vulnerable populations or neighborhoods.”
Additional COVID-19 Dashboards and Projections
The Demographics by State COVID-19 Reporting (DSCovR) Dashboard is an interactive tool developed by Shing Lee and colleagues to track and visualize state level demographics and time trends for COVID-19 cases, deaths and policies in the U.S., as well as, cases and deaths internationally.
Yuanjia Wang and colleagues created a model to forecast the COVID-19 pandemic in the U.S.; she posts daily forecasts on GitHub. Weekly forecasts produced with researchers at the University of North Carolina Chapel Hill are part of the COVID-19 ensemble modeling hub used by the U.S. Centers for Disease Control and Prevention (CDC). The CDC publishes these aggregate forecasts online.
Data modelers Jeffrey Shaman and Sen Pei publish national COVID-19 projections on GitHub which provide the basis for weekly maps and data visualizations created in collaboration with Charles Branas and Andrew Rundle. The modeling team is advising and providing projections to the White House Coronavirus Task Force, the CDC, New York City, and various state governments. They have published several research papers, including on asymptomatic transmission, estimated number of lives lost to delayed response, and how to avoid infections stemming from a hurricane evacuation.
Wan Yang developed a model to project COVID-19 cases in New York City. Weekly are published on Github and shared with the New York City Department of Health and Mental Hygiene. She has published papers on the potential impact of reopening schools and COVID fatality risk.
Our team of professors, scientists and researchers have been hard at work to help officials control the COVID-19 pandemic, both in New York and nationwide. Read up on our research and projects for a full list of contributions from the Mailman faculty.