A multi-disciplinary team of researchers, entrepreneurs, and policy makers announced an AI-based project, nicknamed “Eva,” that uses data to support decision-making by the Greek government as it reopens the tourist industry vital to its economy amid the worldwide COVID-19 pandemic.
Vishal Gupta and Kimon Drakopoulos from the Marshall School of Business at the University of Southern California; Hamsa Bastani from the Wharton School at the University of Pennsylvania; Jon Vlachogiannis, founder of AgentRisk; and the Greek government came together earlier this summer to build the machine-learning platforms.
Son of New York-based Dr. Jagdish Gupta, a veteran AAPI leader and a current member of its BOT, Vishal Gupta is an Assistant Professor of Data Sciences and Operations, developing new algorithmic approaches to data-driven decision-making in settings where data and/or resources are scarce, with applications in healthcare, revenue management and business analytics.
Greece is home to approximately 11 million people, but it has welcomed more than 33 million visitors annually in recent years, with tourism accounting for close to 20% of the country’s employment.
Gupta, Bastani, and Drakopoulos collaboratively developed Eva’s underlying algorithms, emphasizing learning from real-time data, and wrote its implementation. Vlachogiannis is the software architect of the machine learning pipeline, which allows seamless and secure access to anonymized data from disparate Greek government databases in near real-time. Recently, Drakopoulos has been embedded with Greek public health and policy leaders, overseeing Eva’s deployment and liaising with the rest of the team as they continue to tailor Eva to Greece’s unique circumstance.
“One of the most exciting elements of Eva is its ability to learn, improve and evolve. Adapting in real-time is crucial in this pandemic, where the situation on the ground can change dramatically in a day or two,” said Gupta.
“The AI system developed by Bastani, Drakopoulos, Gupta, and Vlachogiannis has been an asset both for preparing the opening of the country to visitors from all over the world, as well as for allowing flexibility in decision making regarding our COVID-19 strategy,” said Nikos Hardalias, Greece’s Civil Protection and Deputy Minister for Crisis Management, who heads the COVID-19 Response Taskforce for the country.
“Tourism is vital to the Greek economy and in times of a pandemic controlling the flow of visitors is extremely delicate both operationally and from a public health point of view,” continued Hardalias. “The developed solution has allowed the Greek Government to make crucial decisions with confidence due to the ability to continuously monitor the epidemiological characteristics of all countries that we accept visitors from. It is great to see how science can complement our national response to this challenge in keeping the local population and our visitors safe.”
Eva combines real-time testing data with information from a simple form that visitors complete 24 hours before arrival to build a risk profile for each visitor. Based on that profile, Eva suggests which visitors should be tested for COVID-19 on arrival and which can safely be admitted without testing. Crucially, Eva uses past data and optimization to simultaneously improve its own risk predictions while also identifying sick visitors before they enter the country, all subject to Greece’s current COVID-19 testing capacity.
How it works
The system provides several benefits for travelers and decision makers by leveraging data to enhance public safety:
- Efficiency: With as many as 40,000 people per day arriving at points of entry around the country, Greece cannot test everyone who might bring coronavirus into the country. Using data to assess risk factors focuses testing on the riskiest travelers, enhancing public health and safety while responsibly allocating valuable testing resources.
- Convenience: A streamlined operations including the pre-arrival form, expedited testing, and seamlessly connected databases minimizes disruptions to travelers. Most travelers are not subject to additional screening, and, those who are, are usually on their way to enjoying Greece within 24 hours without wasting valuable vacation time.
- Responsiveness: By leveraging real-time data to allocate resources, Eva’s analytics support rapid decision-making, allowing policy-makers to quickly respond to unexpected super-spreader events or flare-ups.
“For me, this is about not only applying my work in data science to help the people of Greece,” said Drakopoulos, “but also the people of the world who love to travel and worry about the safety of doing so.”
Bastani added, “New testing results are continuously incorporated into the dynamic learning algorithm, giving Eva a distinct advantage over static COVID-19 screening policies. This is an exciting step forward in evidence-based policy-making.”
No screening procedure can possibly find every infected visitor. Eva dovetails with Greece’s existing contact-tracing system to catch anyone who slips through the cracks. Overall, Eva’s risk-profiles, test allocations and other data analytics form a real-time dashboard, visually representing the latest information to the Greek Government to inform decision-making.
“In addition to a day of hope for those who love travel and long for a path out of the pandemic, this is also a huge day for data science, machine learning and algorithmic support for good governance,” said Vlachogiannis.
Kimon Drakopoulos is an assistant professor of data sciences and operations, whose research focuses on epidemics modeling, social networks, and information economics.
Consistently ranked among the nation’s premier schools, USC Marshall is internationally recognized for its emphasis on entrepreneurship and innovation, social responsibility and path-breaking research. Located in the heart of Los Angeles, one of the world’s leading business centers and the U.S. gateway to the Pacific Rim, Marshall offers its 6,000-plus undergraduate and graduate students a unique world view and impressive global experiential opportunities. For more information, visit www.marshall.usc.edu.
Vishal Gupta, an Assistant Professor of Data Sciences and Operations at USC Marshall and an Affiliate Faculty at the USC Center for AI and Society, currently serving as an Associate Editor for Management Science in the “Big Data Analytics” department.
Before joining USC, Vishal completed his B.A. in Mathematics and Philosophy from Yale University, graduating Magna Cum Laude with honors, and completed Part III of the Mathematics Tripos at the University of Cambridge with distinction. He then spent four years working as a “quant” in finance at Barclays Capital focusing on commodities modeling, derivatives pricing, and risk management. Eventually, realizing how much he missed working towards a larger mission of impact, Vishal left the private sector to complete his Ph.D. in Operations Research at MIT in 2014 under Prof. Dimitris Bertsimas.
Vishal’s research focuses on data-driven decision-making and optimization, particularly in settings where data are scarce. Such settings are common in applications that center on personalization/customization and adapting to changing environments in real-time. Consequently, Vishal’s research spans a wide variety of areas including risk and revenue management, education, healthcare, and business analytics. He has received a number of recognitions for his work including Finalist for the Pierskalla Best Paper competition, Finalist for the Service Science Best Paper competition, and Finalist for the George Nicholson Best Student Paper competition.