Using AI and Data Science to Combat Health Pandemics
— April 8, 2020
By Anindya Ghose
The pace at which firms have innovated to collect and process real time data is simply astonishing. Tech firms in Asia have developed mobile apps to help people check if they have taken the same flight or train as confirmed virus patients. Government officials have used such data to track down individuals who may have been exposed, screen them, and if necessary, quarantine them. Baidu used infrared and AI-powered facial recognition to screen people at airports and railway stations for fever. Machine-learning programs have analyzed social media posts and search engine query data to predict the size and speed of the outbreak in different part of China. Chinese firms are using drones and robots to perform contactless delivery and to spray disinfectants in public areas. Google’s DeepMind is using deep learning to find new information about the structure of proteins associated with Covid-19, which in turn can provide important clues to the coronavirus vaccine formula.
Thus, today’s pandemic response can be different in part due to advances in data collection and harnessing that data through AI algorithms. It is notable that a small Canadian AI startup BlueDot spotted Covid-19 nine days before the WHO alerted people to the emergence of this coronavirus. Scientists have used real-time maps and sophisticated forecasting algorithms from epidemiology to predict the number of infected people who left Wuhan and track the spread of the novel coronavirus by analyzing air traffic patterns across China.
Read the full BrandEquity article.
Anindya Ghose is Heinz Riehl Professor of Business