Sensor-Based Fuzzy Inference of COVID-19 Transmission Risk in Cruise Ships.
Journal:
Studies in health technology and informatics
PMID:
39176844
Abstract
Cruise ships are densely populated ecosystems where infectious diseases can spread rapidly. Hence, early detection of infected individuals and risk assessment (RA) of the disease transmissibility are critical. Recent studies have investigated the long-term assessment of transmission risk on cruise ships; however, short-term approaches are limited by data unavailability. To this end, this work proposes a novel short-term knowledge-based method for RA of disease transmission based on fuzzy rules. These rules are constructed using knowledge elicited from domain experts. In contrast to previous approaches, the proposed method considers data captured by several sensors and the ship information system, according to a recently proposed smart ship design. Evaluation with agent-based simulations confirms the effectiveness of the proposed method across various cases.