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Modelling the Impact of Robotics on Infectious Spread Among Healthcare Workers.
Vicente, Raul; Mohamed, Youssef; Eguíluz, Victor M; Zemmar, Emal; Bayer, Patrick; Neimat, Joseph S; Hernesniemi, Juha; Nelson, Bradley J; Zemmar, Ajmal.
  • Vicente R; Department of Neurosurgery, Henan Provincial People's Hospital, Henan University People's Hospital, Henan University School of Medicine, Zhengzhou, China.
  • Mohamed Y; Institute of Computer Science, University of Tartu, Tartu, Estonia.
  • Eguíluz VM; Institute of Computer Science, University of Tartu, Tartu, Estonia.
  • Zemmar E; Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Palma de Mallorca, Spain.
  • Bayer P; Department of Neurosurgery, University of Louisville, School of Medicine, Louisville, KY, United States.
  • Neimat JS; Department of Neurosurgery, University of Louisville, School of Medicine, Louisville, KY, United States.
  • Hernesniemi J; Department of Neurosurgery, University of Louisville, School of Medicine, Louisville, KY, United States.
  • Nelson BJ; Department of Neurosurgery, Henan Provincial People's Hospital, Henan University People's Hospital, Henan University School of Medicine, Zhengzhou, China.
  • Zemmar A; Multi-Scale Robotics Laboratory, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland.
Front Robot AI ; 8: 652685, 2021.
Article in English | MEDLINE | ID: covidwho-1266693
Semantic information from SemMedBD (by NLM)
1. Communicable Diseases PROCESS_OF Health Personnel
Subject
Communicable Diseases
Predicate
PROCESS_OF
Object
Health Personnel
2. Illness (finding) PROCESS_OF Patients
Subject
Illness (finding)
Predicate
PROCESS_OF
Object
Patients
3. American College of Cardiology/American Heart Association Lesion Complexity Score C PROCESS_OF Health Personnel
Subject
American College of Cardiology/American Heart Association Lesion Complexity Score C
Predicate
PROCESS_OF
Object
Health Personnel
4. Hospital Units LOCATION_OF Analysis
Subject
Hospital Units
Predicate
LOCATION_OF
Object
Analysis
5. Communicable Diseases PROCESS_OF Health Personnel
Subject
Communicable Diseases
Predicate
PROCESS_OF
Object
Health Personnel
6. Illness (finding) PROCESS_OF Patients
Subject
Illness (finding)
Predicate
PROCESS_OF
Object
Patients
7. American College of Cardiology/American Heart Association Lesion Complexity Score C PROCESS_OF Health Personnel
Subject
American College of Cardiology/American Heart Association Lesion Complexity Score C
Predicate
PROCESS_OF
Object
Health Personnel
8. Hospital Units LOCATION_OF Analysis
Subject
Hospital Units
Predicate
LOCATION_OF
Object
Analysis
ABSTRACT
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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Front Robot AI Year: 2021 Document Type: Article Affiliation country: Frobt.2021.652685

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Front Robot AI Year: 2021 Document Type: Article Affiliation country: Frobt.2021.652685