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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20179929

RESUMO

BackgroundDevelopment of strategies for mitigating the severity of COVID-19 is now a top global public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions such as social distancing, self-isolation, tracing and quarantine, wearing facial masks/ personal protective equipment. MethodsWe developed an individual-based model for COVID-19 transmission among healthcare workers in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan in a Bayesian framework. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. ResultsWe estimated that work-related stress increases susceptibility to COVID-19 infection among healthcare workers by 52% (90% Credible Interval (CrI): 16.4% - 93.0%). The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. A strict quarantine policy with the isolation of symptomatic cases and a high fraction of pre-symptomatic/ asymptomatic cases (via contact tracing or high test rate), could only prolong outbreak duration with minimal impact on the outbreak size. Our results indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. ConclusionsOur analysis shows that a COVID-19 outbreak in a hospitals non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20047159

RESUMO

BackgroundThere had been a preliminary occurrence of human-to-human transmissions between healthcare workers (HCWs), but risk factors in the susceptibility for COVID-19, and infection patterns among HCWs have largely remained unknown. MethodsRetrospective data collection on demographics, lifestyles, contact status with infected subjects for 118 HCWs (include 12 COVID-19 HCWs) from a single-center. Sleep quality and working pressure were evaluated by Pittsburgh Sleep Quality Index (PSQI) and The Nurse Stress Index (NSI), respectively. Follow-up duration was from Dec 25, 2019, to Feb 15, 2020. Risk factors and transmission models of COVID-19 among HCWs were analyzed and constructed. FindingsA high proportion of COVID-19 HCWs had engaged in night shift-work (75.0% vs. 40.6%) and felt they were working under pressure (66.7% vs. 32.1%) than uninfected HCWs. COVID-19 HCWs had higher total scores of PSQI and NSI than uninfected HCWs. Furthermore, these scores were both positively associated with COVID-19 risk. An individual-based model (IBM) estimated the outbreak duration among HCWs in a non-typical COVID-19 ward at 62-80 days and the basic reproduction number R0 =1.27 [1.06, 1.61]. By reducing the average contact rate per HCW by a 1.35 factor and susceptibility by a 1.40 factor, we can avoid an outbreak of the basic case among HCWs. InterpretationPoor sleep quality and high working pressure were positively associated with high risks of COVID-19. A novel IBM of COVID-19 transmission is suitable for simulating different outbreak patterns in a hospital setting. FundingFundamental Research Funds for the Central Universities

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