Local Data Save Lives From COVID-19

In terms of slowing the coronavirus’ rate of spread, we know that social distancing is working. However, the go-to preventative measure has left nursing homes in a vulnerable front-line position.

As of April 24, 2020, nearly 10,000 coronavirus deaths in America were connected to nursing home residents or caregivers.

Routine temperature checks have been the customary approach to early-detection of COVID-19 in residents, but this method may identify the virus when it’s too late.

By collecting local data on those with confirmed cases of COVID-19 and using smart tech, nursing homes can buy more time.

From March 23-30, 2020, coronavirus cases across long-term care patients in America spiked by 172%. The Life Care Center of Kirkland in Seattle, Washington was one of the first U.S. epicenters of the outbreak.

There, more than ⅔ of residents have tested positive for COVID-19, and nearly 40 residents have died from the virus. Altogether, at least 2,300 long-term care facilities in America have reported cases of coronavirus.

Specific to New Jersey, nearly 400 long-term facilities have been affected by an outbreak, resulting over 1,500 deaths. Several health experts across America have criticized lack of testing and data collecting. Health experts believe these tools are vital to developing new strategies to combat the virus.

If predictive models are built solely on macro data, we may miss vital differences in an epidemic’s spread.

Geographic location, socioeconomics, and cultural customs/behaviors are all data factors that must be taken into account for solutions to COVID-19 to be discovered.

Doing so can inform us of the virus’ risk factors, societal and environmental context, severity, and method of spread.

Saying this, there are many ways post-acute facilities can collect data while simultaneously monitoring for early warning signs of COVID-19. UC San Francisco is studying 2,000 healthcare workers using Oura Ring.

The technological ring measures the wearer’s temperature, heart rate, respiration rate, and more. Oura Ring tracks symptoms through the finger to determine algorithms to predict many illnesses.

UC San Francisco’s immediate goal in this study is to detect early onset symptoms of COVID-19. Furthermore, smart thermometers can be used to track the spread of COVID-19.

The Kinsa smart thermometer has been consistently predicting the spread of COVID-19 – accurately forecasting 2-3 weeks ahead of the Centers for Disease and Control and Prevention (CDC).

Here’s how it works: anonymized data is used to track fevers across the country, pulling from 162,000 readings per day across 500,000 thermometers.

Kinsa also has adapted algorithms to detect fevers that are inconsistent with typical flu spread patterns. Altogether, this allows the smart thermometer to identify likely clusters of coronavirus.

However, you don’t have to be a data scientist to contribute to the data pool – you can help from home. Folding@home lets you share your unused computer power to aid research into potential cures for COVID-19 and other diseases.

The answer to COVID-19 is in data, and many early-detection methods are too late. Read more on the ways data can save lives in the infographic below.

Local Data Save Lives From COVID-19