ABSTRACT
The COVID-19 pandemic and antipandemic policies have significantly impacted highway transportation. Many studies have been conducted to quantify these impacts. However, quantitative analysis of the impacts on province-wide traffic in developing countries, such as China, is still inadequate. This paper tried to fill this gap by proposing equations to quantify the traffic variations of overall province-wide traffic and to analyze the intercity bus traffic variation and intercity bus usage, applying the K-means cluster method to conduct the analysis of traffic reductions in regions with different levels of economic development, and using the hypothesis testing for traffic recovery analysis. It is found that passenger vehicle traffic and truck traffic dropped by 59.67% and 68.19% during the outbreak, respectively. The intercity bus traffic on highways declined by 59.8% to 98.6%, and the intercity bus usage dropped by 55.6% on average. For traffic reductions in different regions, the higher the GDP per capita was, the more the traffic was affected by the pandemic. In regions with lower GDP per capita, traffic variations were minor. It is also found that the passenger vehicle traffic went through four stages in 99 days: the Decline Stage, Rapid Recovery Stage, Slow Recovery Stage, and Normal Stage, while truck traffic only experienced the Decline Stage, Rapid Recovery Stage, and Normal Stage and took 51 days to recover to the Normal Stage. In the Rapid Recovery Stage, the recovery rates were 15.6% and 12.9% per week for passenger vehicle traffic and truck traffic, respectively, and the recovery rate was only 2.1% for passenger vehicle traffic in the Slow Recovery Stage. Despite the recovery of traffic volumes, neither passenger-kilometers nor tonne-kilometers of freight in 2020 reached the same level as in 2019. These findings help the understanding of the pandemic’s impacts on highway traffic for researchers and can provide valuable references for decision-makers to develop antipandemic policies.
ABSTRACT
The efficient induction and long-term persistence of pathogen-specific memory CD8 T cells are pivotal to rapidly curb the reinfection. Recent studies indicated that long-noncoding RNAs expression is highly cell- and stage-specific during T cell development and differentiation, suggesting their potential roles in T cell programs. However, the key lncRNAs playing crucial roles in memory CD8 T cell establishment remain to be clarified. Through CD8 T cell subsets profiling of lncRNAs, this study found a key lncRNA-Snhg1 with the conserved naivehi-effectorlo-memoryhi expression pattern in CD8 T cells of both mice and human, that can promote memory formation while impeding effector CD8 in acute viral infection. Further, Snhg1 was found interacting with the conserved vesicle trafficking protein Vps13D to promote IL-7Rα membrane location specifically. With the deep mechanism probing, the results show Snhg1-Vps13D regulated IL-7 signaling with its dual effects in memory CD8 generation, which not just because of the sustaining role of STAT5-BCL-2 axis for memory survival, but more through the STAT3-TCF1-Blimp1 axis for transcriptional launch program of memory differentiation. Moreover, we performed further study with finding a similar high-low-high expression pattern of human SNHG1/VPS13D/IL7R/TCF7 in CD8 T cell subsets from PBMC samples of the convalescent COVID-19 patients. The central role of Snhg1-Vps13D-IL-7R-TCF1 axis in memory CD8 establishment makes it a potential target for improving the vaccination effects to control the ongoing pandemic.