ABSTRACT
Objective: To estimate the latent period and incubation period of Omicron variant infections and analyze associated factors. Methods: From January 1 to June 30, 2022, 467 infections and 335 symptomatic infections in five local Omicron variant outbreaks in China were selected as the study subjects. The latent period and incubation period were estimated by using log-normal distribution and gamma distribution models, and the associated factors were analyzed by using the accelerated failure time model (AFT). Results: The median (Q1, Q3) age of 467 Omicron infections including 253 males (54.18%) was 26 (20, 39) years old. There were 132 asymptomatic infections (28.27%) and 335 (71.73%) symptomatic infections. The mean latent period of 467 Omicron infections was 2.65 (95%CI: 2.53-2.78) days, and 98% of infections were positive for nucleic acid test within 6.37 (95%CI: 5.86-6.82) days after infection. The mean incubation period of 335 symptomatic infections was 3.40 (95%CI: 3.25-3.57) days, and 97% of them developed clinical symptoms within 6.80 (95%CI: 6.34-7.22) days after infection. The results of the AFT model analysis showed that compared with the group aged 18-49 years old, the latent period [exp(ß)=1.36 (95%CI: 1.16-1.60), P<0.001] and incubation period [exp(ß)=1.24 (95%CI: 1.07-1.45), P=0.006] of infections aged 0-17 years old were prolonged. The latent period [exp(ß)=1.38 (95%CI: 1.17-1.63), P<0.001] and the incubation period [exp(ß)=1.26 (95%CI: 1.06-1.48), P=0.007] of infections aged 50 years old and above were also prolonged. Conclusion: The latent period and incubation period of most Omicron infections are within 7 days, and age may be a influencing factor of the latent period and incubation period.
Subject(s)
COVID-19 , Male , Humans , Adult , Adolescent , Young Adult , Middle Aged , Infant, Newborn , Infant , Child, Preschool , Child , SARS-CoV-2 , Infectious Disease Incubation Period , Asymptomatic InfectionsABSTRACT
As a non-thermal food processing technology, Electron beam (E-beam) irradiation has been used to enhance microbial safety by deactivating unwanted spoilage and pathogenic microorganisms in food industry. This study evaluated the effects of E-beam irradiation at doses killing SARS-COV-2 on qualities and sensory attributes. The results showed that irradiation caused little effect on the proximate composition, amino acid content, texture, and sensory attributes (P > 0.05). However, E-beam increased TBARS (Thiobarbituric acid reactive substances) and lowered vitamin E content in dose-dependently. Irradiation up to 10 kGy significantly decreased unsaturated fatty acid (UFA) content and inhibited the increase in TVB-N (The total volatile basic nitrogen) while reducing cohesiveness and chewiness (P < 0.05). E-beam irradiation with 7–10 kGy caused greater ΔE values (ΔE > 5) via the significant increase of b*, accompanied by big visual difference in shrimp (P < 0.05). A dose of 4 kGy E-beam irradiation was recommended without altering its physicochemical properties and sensory attributes. © 2023 Elsevier Ltd
ABSTRACT
Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.