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The coronavirus disease of 2019 (COVID-19) is a pandemic. To characterize its disease transmissibility, we propose a Bayesian change point detection model using daily actively infectious cases. Our model builds on a Bayesian Poisson segmented regression model that can 1) capture the epidemiological dynamics under the changing conditions caused by external or internal factors; 2) provide uncertainty estimates of both the number and locations of change points; and 3) adjust any explanatory time-varying covariates. Our model can be used to evaluate public health interventions, identify latent events associated with spreading rates, and yield better short-term forecasts.
RESUMO
The outbreak of the 2019 Novel Coronavirus (SARS-CoV-2) rapidly spread from Wuhan, China to more than 150 countries, areas, or territories, causing staggering numbers of infections and deaths. In this study, bioinformatics analyses were performed on 5,568 complete genomes of SARS-CoV-2 virus to predict the T cell and B cell immunogenic epitopes of all viral proteins, which formed a systematic immune vulnerability landscape of SARS-CoV-2. The immune vulnerability and genetic variation profiles of SARS-CoV were compared with those of SARS-CoV and MERS-CoV. In addition, a web portal was developed to broadly share the data and results as a resource for the research community. Using this resource, we showed that genetic variations in SARS-CoV-2 are associated with loss of B cell immunogenicity, an increase in CD4+ T cell immunogenicity, and a minimum loss in CD8+ T cell immunogenicity, indicating the existence of a curious correlation between SARS-CoV-2 genetic evolutions and the immunity pressure from the host. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic/vaccine development and mechanistic research.
RESUMO
Objective To investigate antibiotic resistance and Staphylococcal cassette chromosome mec (SCC-mec) genotype of methicillin-resistant Staphylococcus aureus (MRSA)in Dalian Area .Methods Antimicrobial susceptibility of MRSA was detected by Kirby-Bauer method and SCCmec genotype by multiple PCR method .Results 38 strains of MRSA were all multidrug-resistant strains ,but susceptible to vancomycin and chloramphenicol .The most common SCCmec genotype was type Ⅱ (86 .84% ) ,type Ⅲwas in the second place(10 .53% ) ,and unidentified type accounted for 2 .6% .Conclusion MRSA strains in Dalian area are charac-terized by multidrug resistance ,type Ⅱ is the most common SCCmec genotype .
