Faced with limited resources in a pandemic, Greece turned to machine-learning software to decide which sorts of travelers to test for COVID-19 as they arrived in the country.
The system in question used reinforcement learning, specifically multi-armed bandit algorithms, to identify which potentially infected, asymptomatic passengers were worth testing and putting into quarantine if necessary. It also was able to produce up-to-date statistics on infections for officials to analyze, such as early signs of the emergence of COVID-19 hot spots abroad, we're told.
Nicknamed Eva, the software was put to use at all 40 of Greece's entry points from August 6 to November 1 last year. Incoming travelers were asked to fill out a questionnaire detailing the country and region they were coming from as well as their age and gender. Based on these characteristics, Eva selected whether they should be tested for COVID-19 upon arrival. At its peak, Eva was apparently processing between roughly 30,000 and 55,000 forms a day, each form representing a household, and about 10 to 20 per cent of households were tested.