COVID-19 Roundup: At-Risk Counties, Individualism, the New Normal & More
As the COVID-19 pandemic sweeps the globe, big data and AI have emerged as crucial tools for everything from diagnosis and epidemiology to therapeutic and vaccine development. Here, we collect the latest news in how big data is fighting back against COVID-19.
Researchers from data startup Akai Kaeru have teamed up with Stony Brook University to develop a machine learning tool to identify the U.S. counties most at risk for deaths from the COVID-19 pandemic. Using a massive dataset covering all 3,000+ counties, the researchers identified problem counties based on factors like poverty, rurality, low education, sleep deprivation and more. To read more, click here.
Using data from a variety of sources, researchers from Sandia National Laboratories have developed a model that forecasts new cases up to ten days into the future with high accuracy. The model, which is an evolution of a model developed in the late 2000s for tracking influenza-like illnesses, has been able to accurately predict the trajectory of cases since April. To read more, click here.
The COVID-19 Open Research Dataset (CORD-19) comprises over 150,000 academic articles related to COVID-19, which resulted in a challenge for developers to use AI to help researchers sift through that deluge of data. Qlik has now answered that call with a modified version of its Qlik Sense platform to enable intuitive keyword searching and automatically updated document databases. To learn more, click here.
The U.S. is home to 4% of the world’s population, but more than a quarter of its COVID-19 cases. Researchers from the University of Virginia and the University of British Columbia explored the link between this poor response and historic levels of individualism (approximated through time spent on the American frontier) at a county level, finding a strong relationship between the two factors. To read more, click here.
Data virtualization solution provider AtScale has released new datasets and a Tableau workbook with prebuilt dashboards for its COVID-19 Cloud OLAP Insight Model. The model analyzes datasets from a variety of sources to provide users with insights on economic shifts, mobility data, case numbers, airport traffic, and the relationships between those factors. To read more, click here.
The CoronaSurveys project aims to estimate the total number of cases using a simple survey with just a handful of questions. The project has now expanded to cover 150 countries in 60 languages, allowing researchers to obtain estimates that researchers claim are close to the most accurate data on the incidence of COVID-19 worldwide. To read more, click here.
Business intelligence firm Domo has updated its free, interactive COVID-19 Global Tracker with data from the National Paycheck Protection Program, allowing users to interact with data from the $500 billion loan program through a number of lenses. Domo’s, which was launched in March, updates every ten minutes with data from a variety of sources covering the health-related and social aspects of COVID-19. To read more, click here.
Do you know about big data applications for COVID-19 that should be featured on this list? If so, send us an email at [email protected]. We look forward to hearing from you.