Around 30 researchers from four Finnish institutions (i.e., Aalto University, Finnish Meteorological Institute, VTT Technical Research Centre of Finland and University of Helsinki) investigated how far aerosol particles are being spread from one’s cough, sneeze and talk into his/her surrounding environment.

How quickly does virus spread?

With the help of a supercomputer and 3D visualization, the research consortium created a simulation showcasing a person who coughs within an aisle bounded by shelves in a supermarket/ grocery store with standard ventilation. They aimed to model how airborne aerosol particles smaller than 20 micrometers are typically emitted and found that an aerosol cloud will be formed as soon as a cough, sneeze or talk takes place.

It will then take a couple of minutes for the cloud to dilute and disperse from its point of origin to its immediate vicinity. Researchers believe someone who is infected with coronavirus or influenza A may cough and walk away but he or she will leave behind small aerosol particles carrying the viruses (i.e., usually less than 15 micrometers for coronavirus and less than five micrometers for influenza A) that linger and move along in the air rather than sink to the ground. Eventually, some of these aerosol particles may find themselves in someone else’s respiratory tracts.

As such, it’s suggested to avoid “nodal points” or busy public indoor spaces and to keep a mindful physical distance from others when one is feeling unwell. This preliminary result also recommends one to keep good hand hygiene and to cover his or her mouth with sleeve or tissue for cough and sneeze. Earlier, a separate study also confirmed masks to be an effective way of preventing the spread of coronavirus and influenza viruses from symptomatic individuals.

How can smartwatches help?

It appears that face masks and gloves may be the new form of “wearables” we need to get used to in the midst of the ongoing Covid-19 pandemic. At the same time, a group of researchers from the University of Michigan and Duke University found that by examining healthcare data from smartwatches, particularly evidence indicating interrupted sleep, would forecast whether a person is likely to be down with flu, 24 hours before it turned contagious.

The research team employed a machine learning algorithm that was trained with data obtained from medical wristbands to extrapolate the sleep patterns of 25 participants who were intentionally exposed to a strain of flu virus. Seven participants were found to have interrupted sleep 24 hours before they developed flu symptoms and began infecting others. The pre-print study is currently undergoing a second round of review by IEEE Transactions on Biomedical Engineering. Although its main focus is on flu, researchers believe it may also be applicable to other infections, including coronavirus.

The ongoing Covid-19 pandemic had requested individuals experiencing symptoms to self-isolate until they are tested negative. Even if smartwatches are not able to diagnose who is down with Covid-19, this study may guide individuals when to begin self-isolation.

As the leading author Alfred O. Hero, John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering said, “as we get more data from the populations wearing smartwatches through this pandemic, our predictive models will be refined. We imagine that these refined models could be used to generate an early warning signal and even potentially enable the prediction of asymptomatic spreading without tests”.

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Author Bio

Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.