Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.
Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’
Bernard Marr ist ein weltbekannter Futurist, Influencer und Vordenker in den Bereichen Wirtschaft und Technologie mit einer Leidenschaft für den Einsatz von Technologie zum Wohle der Menschheit. Er ist Bestsellerautor von 20 Büchern, schreibt eine regelmäßige Kolumne für Forbes und berät und coacht viele der weltweit bekanntesten Organisationen. Er hat über 2 Millionen Social-Media-Follower, 1 Million Newsletter-Abonnenten und wurde von LinkedIn als einer der Top-5-Business-Influencer der Welt und von Xing als Top Mind 2021 ausgezeichnet.
Bernards neueste Bücher sind ‘Künstliche Intelligenz im Unternehmen: Innovative Anwendungen in 50 Erfolgreichen Unternehmen’
The Vital Role Of Big Data In The Fight Against Coronavirus
2 July 2021
One of the advantages we have today in the fight against coronavirus that wasn’t as sophisticated in the SARS outbreak of 2003 is big data and the high level of technology available. China tapped into big data, machine learning, and other digital tools as the virus spread through the nation in order to track and contain the outbreak. The lessons learnt there have continued to spread across the world as other countries fight the spread of the virus and use digital technology to develop real-time forecasts and arm healthcare professionals and government decision-makers with intel they can use to predict the impact of the coronavirus.
China’s Surveillance Infrastructure Used to Track Exposed People
China’s surveillance culture became useful in the country’s response to COVID-19. Thermal scanners were installed in train stations to detect elevated body temperatures—a potential sign of infection. If a high temperature was detected, then the person was detained by health officials to undergo coronavirus testing. If the coronavirus test came back positive, authorities would alert every other passenger who may have been exposed to the virus so they could quarantine themselves. This notification was enabled because of the country’s transportation rules that require every passenger who travels on public transport to use their real names and government-issued ID cards.
China has millions of security cameras that are used to track citizens movements in addition to spotting crimes. This helped authorities discover people who weren’t compliant with quarantine orders. If a person was supposed to be in quarantine, but cameras tracked them outside their homes, authorities would be called. Mobile phone data was also used to track movements.
The Chinese government also rolled out a Close Contact Detector app that alerted users if they were in contact with someone who had the virus. Travel verification reports produced by telecom providers could list all the cities visited by a user in the last 14 days to determine if quarantine was recommended based on their locations. By integrating the data collected by China’s surveillance system, the country was able to find ways to fight the spread of the coronavirus.
Mobile App for Contact Tracing
In Europe and America, privacy considerations for citizens are of bigger concern than they are in China, yet medical researchers and bioethics experts understand the power of technology to support contact tracing in a pandemic. Oxford University’s Big Data Institute worked with government officials to explain the benefits of a mobile app that could provide valuable data for an integrated coronavirus control strategy. Since nearly half of all coronavirus transmissions occur before symptoms occur, speed and effectiveness to alert people that may have been exposed are paramount during a pandemic such as coronavirus. A mobile app that harnesses 21st-century technology can accelerate the notification process while maintaining ethics to slow the rate of contagion.
Tech innovators had already worked on solutions to effectively monitor and track the spread of flu. FluPhone was introduced in 2011, but the app wasn’t highly adopted, which limited its usefulness. Other app solutions are in the works from a variety of organisations that aim to give people a tool to self-identify their health status and symptoms. Along with all the challenges coronavirus has us facing, it’s also providing essential learning experiences for data science in healthcare.
In the United States, the government is in conversation with tech giants such as Facebook, Google, and others to determine what’s possible—and ethical—in terms of using location data from Americans’ smartphones to track movements and understand patterns.
Official Dashboards Track the Virus and Outbreak Analytics
Another tool that has been helpful for private citizens, government policy-makers and healthcare professionals to see the progression of contagion and to inform models of how invasive this virus will be are dashboards from entities such as the World Health Organisation that provide real-time stats. The dashboard I have been watching is this one. These dashboards pull in data from around the world to show confirmed cases and deaths from coronavirus and locations. This comprehensive data set can then be used to create models and predict hotspots for the disease so that decisions can be made about stay-at-home orders and to help healthcare systems prepare for a surge of cases.
Outbreak analytics takes all available data, including the number of confirmed cases, deaths, tracing contacts of infected people, population densities, maps, traveller flow, and more, and then processes it through machine learning to create models of the disease. These models represent the best predictions regarding peak infection rates and outcomes.
Big Data Analytics and Successes in Taiwan
As coronavirus spread in China, it was assumed that Taiwan would be heavily hit in part because of its proximity to China, the regular flights that went from the island to China each day, and how many Taiwanese citizens work in China. However, Taiwan used technology and a robust pandemic plan created after the 2003 SARS outbreak to minimise the virus impact on its land.
Part of their strategy integrated the national health insurance database with data from its immigration and customs database. By centralising the data in this way, when faced with coronavirus, they were able to get real-time alerts regarding who might be infected based on symptoms and travel history. In addition to this, they had QR code scanning and online reporting of travel and health symptoms that helped them classify travellers infection risks and a toll-free hotline for citizens to report suspicious symptoms. Officials took immediate action from the minute WHO broadcast information about a pneumonia of unknown cause in China on Dec. 31, 2019. This was the first reported case of coronavirus, and Taiwan’s quick response and use of technology are the likely reasons they have a lower rate of infection than others despite their proximity to China.
Technology is vital in the fight against coronavirus and future pandemics. In addition to being able to support modelling efforts and predicting the flow of a pandemic, big data, machine learning, and other technology can quickly and effectively analyse data to help humans on the frontlines figure out the best preparation and response to this and future pandemics.