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10.1088/1752-7163/ac1721

http://scihub22266oqcxt.onion/10.1088/1752-7163/ac1721
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34293732!ä!34293732

suck abstract from ncbi


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pmid34293732      J+Breath+Res 2021 ; 15 (4): ä
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  • A perspective on hospital-acquired (nosocomial) infection control of COVID-19: usefulness of spatial separation between wards and airborne isolation unit #MMPMID34293732
  • Mimura K; Oka H; Sawano M
  • J Breath Res 2021[Jul]; 15 (4): ä PMID34293732show ga
  • The coronavirus disease 2019 (COVID-19) pandemic has imposed a considerable burden on hospitals and healthcare workers (HCWs) worldwide, increasing the risk of outbreaks and nosocomial transmission to 'non-COVID-19' patients, who represent the highest-risk population in terms of mortality, and HCWs. Since HCWs are at the interface between hospitals on the one hand and the community on the other, they are potential reservoirs, carriers, or victims of severe acute respiratory syndrome coronavirus 2 cross-transmission. In addition, there has been a paradigm shift in the management of viral respiratory outbreaks, such as the widespread testing of patients and HCWs, including asymptomatic individuals. In hospitals, there is a risk of aerosol transmission in poorly ventilated spaces, and when performing aerosol-producing procedures, it is imperative to take measures against aerosol transmission. In particular, spatial separation of the inpatient ward for non-COVID-19 patients from that designated for patients with suspected or confirmed COVID-19 as well as negative-pressure isolation on the floor of the ward, using an airborne infection isolation device could help prevent nosocomial infection.
  • |*Hospitals[MESH]
  • |*Infection Control/methods/statistics & numerical data[MESH]
  • |*Physical Distancing[MESH]
  • |*Ventilation/methods/statistics & numerical data[MESH]
  • |Aerosols[MESH]
  • |COVID-19 Testing[MESH]
  • |COVID-19/diagnosis/epidemiology/*prevention & control/transmission[MESH]
  • |Cross Infection/diagnosis/epidemiology/*prevention & control/transmission[MESH]
  • |Health Personnel/*statistics & numerical data[MESH]
  • |Humans[MESH]


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