Modelling the Impact of Robotics on Infectious Spread Among Healthcare Workers

The Coronavirus disease 2019 (Covid-19) pandemic has brought the world to a standstill. Healthcare systems are critical to maintain during pandemics, however, providing service to sick patients has posed a hazard to frontline healthcare workers (HCW) and particularly those caring for elderly patients. Various approaches are investigated to improve safety for HCW and patients. One promising avenue is the use of robots. Here, we model infectious spread based on real spatio-temporal precise personal interactions from a geriatric unit and test different scenarios of robotic integration. We find a significant mitigation of contamination rates when robots specifically replace a moderate fraction of high-risk healthcare workers, who have a high number of contacts with patients and other HCW. While the impact of robotic integration is significant across a range of reproductive number R0, the largest effect is seen when R0 is slightly above its critical value. Our analysis suggests that a moderate-sized robotic integration can represent an effective measure to significantly reduce the spread of pathogens with Covid-19 transmission characteristics in a small hospital unit.RV thanks the financial support from the Estonian Center of Excellence in IT (EXCITE) funded by the European Regional Development Fund, through the research grant TK148. This research was funded by “la Caixa” Foundation’s Social Research Call 2021 under the project code SR20-00386 to VME, and by grants from the Heidi Demetriades Foundation, the ETH Zurich Foundation, and the Henan Provincial People’s Hospital Outstanding Talents Founding Grant Project to AZ.Peer reviewe