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In this study, we performed a single-centered study of 307 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected patients. It was found that co-infection of SARS-CoV-2 and influenza virus was common during COVID-19 outbreak. And patients coinfected with SARS-CoV-2 and influenza B virus have a higher risk of developing poor outcomes so a detection of both viruses was recommended during COVID-19 outbreak.

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This study pools household travel and built environment data from 15 diverse US regions to produce travel models with more external validity than any to date. It uses a large number of consistently defined built environmental variables to predict five household travel outcomes – car trips, walk trips, bike trips, transit trips and vehicle miles travelled (VMT). It employs multilevel modelling to account for the dependence of households in the same region on shared regional characteristics and estimates ‘hurdle’ models to account for the excess number of zero values in the distributions of dependent variables such as household transit trips. It tests built environment variables for three different buffer widths around household locations to see which scale best explains travel behaviour. The resulting models are appropriate for post-processing outputs of conventional travel demand models, and for sketch planning applications in traffic impact analysis, climate action planning and health impact assessment.

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