Data Analytics and Privacy in the Time of COVID-19 Posted on : Apr 21 - 2020

Attempting to track and mitigate the impacts of a global pandemic is proving to be like looking for the proverbial needle in a stack of other needles. Fortunately, we have made huge strides recently in data identification, collection and integration and new tools and processes (including Artificial Intelligence) have improved the speed and precision needed to reveal the critical insights. Thanks to these technological innovations, data analytics is playing a pivotal role in mankind’s battle against COVID-19.

Some memorable examples of these valuable data driven insights:

· Kaggle, the data scientist community website, has posted a comprehensive dataset on COVID-19 infections, deaths and recoveries, as well as a collection of scientific papers on COVID-19 and related viral diseases. Data scientists around the globe have been analyzing this data to look for insights that can help stop the disease. The Kaggle community’s findings to date include observations about risk factors, symptoms, seasonality, virus persistence, the incubation period and diagnostics that provide health researchers with valuable corroborative data.

· Researchers are using Google search trends to predict regions where COVID-19 outbreaks are about to occur. As the virus incubates in a given region, local citizens begin to observe symptoms such as loss of smell, joint aches and a dry cough. Those people often turn to Google to search for more information on their health. By tracking regionally aggregated Google searches, the researchers can predict areas where the disease is spreading, even in the absence of medical testing. They were also able to determine a previously unidentified COVID-19 symptom based on Google search patterns: eye pain.

· Google and Apple have teamed up to create a contact-tracing smartphone app that can determine who has been in contact with an infected person, while still preserving privacy for the individual. Suppose a government requires its citizens to install the app, or requires its cellular carriers to automatically install the app. As a smartphone’s owner moves around, the app connects with nearby smartphones via Bluetooth radio, which has a range of around 30 feet, and stores the nearby phones’ IDs in the local smartphone storage, rather than a central server. When someone tests positive for the virus, their smartphone ID is broadcast to each smartphone’s app, which can then compare it with the data stored locally in the smartphone. Thus, the app can determine whether that smartphone owner came in contact with the infected person and should therefore also be quarantined. The smartphone owner is alerted and can make the necessary lifestyle adjustments, and the app can report the diagnosis back to the medical authorities who can act to enforce the quarantine, without ever revealing any citizen’s detailed location information. View More