Updated: Feb 20
Ever since its first confirmed case in December 2019, the 2019 Novel Coronavirus (also known as the Wuhan virus, 2019-nCoV, or COVID-19) has been compared to another strain of coronavirus: the SARS (Severe Acute Respiratory Syndrome) related Coronavirus. While they have similarities - both are coronaviruses that originated from bats and transmitted to humans via consumption - humankind has taken the lessons from the 2003 SARS outbreak to heart and applied them in the fight against the 2019 Novel Coronavirus.
One of these lessons is the use of technology in healthcare. During the SARS outbreak, authorities were unable to fully harness the power of technology because of the shortage of data needed to feed artificial intelligence systems; such systems were also not as powerful as they are now.
However, our ability to use technology to our benefit has increased vastly in the last few years. The power of technology - especially those related to data science and analytics - has also been apparent in the coronavirus outbreak response over the last few months. In the age of social media and improved data analytics technologies, authorities have a vast amount of data needed to make accurate predictions and data-based insights to quickly and effectively respond to the outbreak.
For instance, data is collected then visualised to easily monitor the spread of the coronavirus. Governments across the globe can then use this to make data-driven decisions to slow the spread of the virus, be it by screening, implementing quarantines, or restricting entry of passengers travelling from these hotspots.
Such maps can also allow the public to better understand the spread and seek medical attention if needed. For instance, a map of confirmed 2019-nCoV cases in Singapore visualises the spread and includes verified details of each individual case, such as their citizenship, place of residence and recently visited areas. The public can then easily monitor the spread, keep up-to-date on new cases, and take the necessary measures (e.g. self-quarantine) if they came into indirect contact with confirmed cases.
Similarly, artificial intelligence (AI) is being used to predict the next hotspot for outbreaks. Health surveillance platforms use big data analytics to process information from news reports and social media to accurately predict virus outbreak patterns. These are then further analysed by epidemiologists then sent to governments, businesses, and public health organizations; the same platform predicted the 2019-nCoV outbreak and informed its clients almost a week before any announcements by the World Health Organisation.
Together, these technologies can be used to make crucial decisions in the face of resource limitations. Where are medical professionals needed most? Where should important Personal Protective Equipment (like masks, sanitisers and thermometers) be sent to first? What can we do to prevent and contain the spread of the 2019 Novel Coronavirus and other diseases? With the help of data analytics technologies, authorities can make quick decisions in time-sensitive situations and thus, effectively and swiftly prevent the further spread of the 2019 Novel Coronavirus and other diseases.
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