For what it’s worth, COVID19 has taught us a number of things. Things that we probably already knew, but hadn’t really put into perspective. One of these important lessons is the value of data, and its ability to change the outcome of anything – including a worldwide viral pandemic. Quite frankly, this is not the first time the world has seen something like this. Maybe not on this scale, but as far as viral pandemics go, it was merely 16 years ago when the SAARS outbreak dominated international media. What did not exist at that time, however, was the level of technology in the way of machine learning and big data that countries such as China have now. This has allowed them the opportunity to develop real-time forecasts while equipping healthcare professionals and decision-makers in the government with actionable intel that can be used to predict the impact of COVID19.
Using surveillance for contact tracing
China’s use of big data through surveillance in contact tracing has been an invaluable tool for slowing down the spread of the disease. As controversial as it may be, China’s high level of citizen surveillance meant that thermal scanners placed in high traffic areas such as public transport stations allowed for law enforcement to detect and detain individuals with elevated body temperatures. Those who tested positive were quarantined, while surveillance footage was used to identify and contact those who may have come in contact with an infected person. The mandatory use of government-issued identification made the process even easier.
The widespread use of surveillance (originally designed to spot crime) helped authorities identify defaulters who broke quarantine orders as well. If a person was supposed to be placed in mandatory home quarantine, but cameras found them to be non-compliant, the local authorities would be called in. Mobile phone data was also used to track their movements.
Effective use of smartphone applications
Here in India, the Government’s attempt at contact tracing through its app, Aarogya Setu has not gone according to plan. What was initially seen as convenient way for people to get verified updates on the pandemic, while at the same time reporting their own symptoms and getting notified of infected individuals around them, was instead met with backlash. Privacy concerns became the key reason why many people refused to download and install the app after the application was hacked into and exposed. This prompted the government to make the code open source by publishing it to GitHub.
In China, however, these concerns are fairly non-existent. A “Close Contact Detector” app became a mandatory install, which 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 2 weeks 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.
Dashboards from reliable sources
Organisations such as WHO (World Health Organization) track various diseases that have the potential to lead to pandemics. The use of big data to track the spread of COVID19 was evident from day one on detailed dashboards published on their website. The interactive dashboard has been using big data collated in realtime to display accurate readouts of COID19 numbers in every city across the world. The dashboard also generated detailed reports that can be downloaded and used for various applications.
The use of these dashboards is instrumental in predicting 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.
Taiwan is a case study in the use of Big Data
As COVID19 took a toll on China, it was only obvious that Taiwan would be next given its proximity to China. However, given its experience with SAARS in 2003, and the systems it put in place then, Taiwan showed effective use of data and analysis to minimise the risk and impact of the virus on the island. Part of their strategy combined the national health insurance database with information from its immigration and customs database. By unifying the data in this way, when faced with coronavirus, they were able to get real-time warnings regarding who might be infected based on symptoms and travel history.
The use of technology is vital in the current fight against coronavirus. But this is just a model for how the world will handle all 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 analyze data to help those on the frontlines figure out the best preparation and response to this and future pandemics.