MONCOVID-19: Technologies for Monitoring COVID-19 Epidemiological Development

The overall goal of this initiative is to establish a baseline for new technologies and analytical tools that may support epidemiological observational studies with monitoring capabilities of COVID-19 in a high-risk environment e.g. hospitals to protect healthcare workers from transmission, and to create a safe working environment without contaminated areas, surfaces and objects. The recent findings from Centers for Disease Control and Prevention, UCLA and Princeton University show that the coronavirus can remain active in the air for up to 3 hours, on copper surfaces up to 4 hours, on paper surfaces up to 24 hours and up to two to three days on plastic and stainless steel surfaces. This requires urgent actions to develop technologies and techniques, which can be deployed in healthcare centres to identify potentially infected areas. It is very important to emphasize that this system is not intended for medical diagnosis, as this requires examination of symptoms on a patient and should validated by physical and laboratory tests together with a doctor’s assessment.

This research project aims to explore the potential and limitations of using a VIS-IR spectroscopic system to measure spectral characteristics in e.g. hospital environments and support epidemiological observations on contamination risk as well as supporting infection prevention and control. The effective application of the proposed methodology may be able to support monitoring infectiousness and support preventing the transmission events. With respect to the eight immediate research actions of WHO in February 2020, this project is focusing on action 4, 5 and 8 to support the epidemiological studies. The consortium consists of technical partners and collaborators (NORCE, NEO, Telops) for hyperspectral imaging, computer vision and machine learning, medical experts (UiB, Haukeland university hospital) for influenza, and viral infections and international labs for clinical analysis.