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Background: To analyse clinical characteristics, antibiotic susceptibility, and risk factors for mortality in paediatric invasive pneumococcal disease (IPD) in Beijing.Methods: Paediatric IPD patients in our hospital were retrospectively collected from 2012 to 2017. Clinical manifestations, laboratory tests, antimicrobial susceptibility and serotype of isolates, and risk factors for mortality of IPD were analysed.Results: Overall, 186 IPD cases were enrolled. The major manifestations were meningitis (76), pneumonia with bacteraemia (60), bacteraemia without focus (21), and pneumonia with empyaema (22). Of 72 cases with underlying diseases, leukaemia (18.0%), congenital heart disease (15.3%), primary immunodeficiency disease (12.5%), nephrotic syndrome (12.5%), and cerebrospinal fluid leakage (12.5%) were most common. In total 96.9% of isolates would have been covered by the pneumococcal conjugate vaccine (PCV13), including 19F (32.8%), 19A (23.4%), 4 (17.2%), and 23F (9.4%). Nonsusceptibility rates of penicillin, cefotaxime, and cefepime among nonmeningitis patients increased between 2012 and 2017; The mortality rate was 21.5%. Meningitis, respiratory failure, multiple organ failure, and white blood cell count < 4000 cells/μL were independent risk factors for mortality.Conclusion: Meningitis was the most common clinical manifestation of IPD, and was frequently associated with death. Strains in the PCV13 vaccine would cover most of the cases, and so wider use of PCV13 should be considered. [ABSTRACT FROM AUTHOR]

The calculation and analysis of subway network capacity is one of the core issues of network operation. This paper focuses on this topic and proposes a passenger-oriented network capacity calculation method. First, subway network capacity is defined as maximum passenger demand that the network can serve under certain level of service requirement. Next, a method to calculate network capacity based on pressure test and simulation experiment is proposed. The key steps of this method such as level of service estimation and passenger demand loading in this method are studied. And then a mesoscopic model and simulation system of subway system are built as method implementation platform. Finally, Beijing subway network is taken as the case study to calculate and analyze network capacity in different level of service requirement during peak hours. It is found out that transfer stations are the bottlenecks that constrain network capacity, and congestion usually performs clustering characteristics taking transfer stations as centers. [ABSTRACT FROM AUTHOR]