| Paper ID | SS-4.6 |
| Paper Title |
OPTIMAL QUESTIONNAIRES FOR SCREENING OF STRATEGIC AGENTS |
| Authors |
Anuj Vora, Ankur Kulkarni, Indian Institute of Technology, Bombay, India |
| Session | SS-4: Data Science Methods for COVID-19 |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Special Sessions: Data Science Methods for COVID-19 |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
During the COVID-19 pandemic the health authorities at airports and train stations try to screen and identify the travellers possibly exposed to the virus. However, many individuals avoid getting tested and hence may misreport their travel history. This is a challenge for the health authorities who wish to ascertain the truly susceptible cases in spite of this strategic misreporting. We investigate the problem of questioning travellers to classify them for further testing when the travellers are strategic or are unwilling to reveal their travel histories. We show there are fundamental limits to how many travel histories the health authorities can recover. |
