Social media insights into spatio-temporal emotional responses to COVID-19 crisis.

The Coronavirus pandemic has presented multifaceted challenges in urban emotional well-being and mental health management. Our study presents a spatio-temporal sentiment mining (STSM) framework to address these challenges, focusing on the space-time geography and environmental psychology. This framework analyzes the distribution and trends of 6 categories of public sentiments in Shanghai during the COVID-19 crisis, considering the potential urban spatial influencing factors. The research specifically draws on social media data temporally coinciding with the spread of COVID-19 and the pre-trained language model RoBERTa-wwm-ext to classify public sentiment, in order to characterize the distribution and trends of dominant urban sentiment under the influence of epidemic at different phases. The interactions between urban geospatial features and sentiments are further modelled and explained using LightGBM algorithm and SHapley Additive exPlanations (SHAP) technique. The experimental findings reveal the subtle yet dynamic impact of the urban environment on the long-term spatial variation and trends of public sentiment under the epidemic, with green spaces and socio-economic status emerging as significant factors. Regions with higher permanent population consumption demonstrated more positive sentiments, underscoring the significance of socio-economic factors in urban planning and public health policy. This research offers the most extensive analysis to date on the influence of urban characteristics on public sentiment during Shanghai's epidemic life cycle also lays the groundwork for applying the STSM framework in future crises beyond COVID-19.

Modeling the complete spatiotemporal spread of the COVID-19 epidemic in mainland China.

OBJECTIVES: The novel coronavirus (COVID-19) epidemic is reaching its final phase in China. The epidemic data are available for a complete assessment of epidemiological parameters in all regions and time periods. METHODS: This study aims to present a spatiotemporal epidemic model based on spatially stratified heterogeneity (SSH) to simulate the epidemic spread. A susceptible-exposed/latent-infected-removed (SEIR) model was constructed for each SSH-identified stratum (each administrative city) to estimate the spatiotemporal epidemiological parameters of the outbreak. RESULTS: We estimated that the mean latent and removed periods were 5.40 and 2.13 days, respectively. There was an average of 1.72 latent or infected persons per 10,000 Wuhan travelers to other locations until January 20th, 2020. The space-time basic reproduction number (R0) estimates indicate an initial value between 2 and 3.5 in most cities on this date. The mean period for R0 estimates to decrease to 80%, and 50% of initial values in cities were an average of 14.73 and 19.62 days, respectively. CONCLUSIONS: Our model estimates the complete spatiotemporal epidemiological characteristics of the outbreak in a space-time domain. These findings will help enhance a comprehensive understanding of the outbreak and inform the strategies of prevention and control in other countries worldwide.

First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: an early exploratory study incorporating location-based service data of mobile devices.

OBJECTIVES: The outbreak of atypical pneumonia caused by the novel coronavirus (COVID-19) has currently become a global concern. The generations of the epidemic spread are not well known, yet these are critical parameters to facilitate an understanding of the epidemic. A seafood wholesale market and Wuhan city, China, were recognized as the primary and secondary epidemic sources. Human movements nationwide from the two epidemic sources revealed the characteristics of the first-generation and second-generation spreads of the COVID-19 epidemic, as well as the potential third-generation spread. METHODS: We used spatiotemporal data of COVID-19 cases in mainland China and two categories of location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics. RESULTS: Two categories of device trajectories had generally significant correlations and determinant powers of the epidemic spread. Bothr and q statistics decreased with distance from the epidemic sources and their associations changed with time. At the beginning of the epidemic, the mixed first-generation and second-generation spreads appeared in most cities with confirmed cases. They strongly interacted to enhance the epidemic in Hubei province and the trend was also significant in the provinces adjacent to Hubei. The third-generation spread started in Wuhan from January 17-20, 2020, and in Hubei from January 23-24. No obvious third-generation spread was detected outside Hubei. CONCLUSIONS: The findings provide important foundations to quantify the effect of human movement on epidemic spread and inform ongoing control strategies. The spatiotemporal association between the epidemic spread and human movements from the primary and secondary epidemic sources indicates a transfer from second to third generations of the infection. Urgent control measures include preventing the potential third-generation spread in mainland China, eliminating it in Hubei, and reducing the interaction influence of first-generation and second-generation spreads.

A Chinese Herbal Formulation, Xiao-Er-An-Shen Decoction, Attenuates Tourette Syndrome, Possibly by Reversing Abnormal Changes in Neurotransmitter Levels and Enhancing Antioxidant Status in Mouse Brain.

Xiao-Er-An-Shen Decoction (XEASD) has been used clinically for the treatment of Tourette syndrome (TS) in children for more than 20 years in mainland China. The biochemical mechanism underlying the therapeutic action produced by XEASD treatment against TS remains unknown. However, a previous study has shown that pre-incubation of PC12 neuronal cells with XEASD can induce neurite outgrowth and protect against oxidative stress. In the present study, using a mouse model of TS induced by 3,3'-iminodipropionitrile (IDPN), stereotypy scoring, and locomotor activity were assessed. Levels of neurotransmitters including glutamate, aspartate, and gamma-aminobutyric acid (GABA) in brain tissue as well as plasma cyclic adenosine monophosphate (cAMP) were measured using assay kits. The ratio of reduced glutathione (GSH)/oxidized glutathione (GSSG) and Mn-superoxide dismutase (MnSOD) activity in brain mitochondrial fractions as well as mitochondrial glutathione reductase and cytosolic γ-glutamylcysteine activities were also examined. The phosphorylation of cAMP-responsive element binding protein (CREB) in brain tissue was measured by Western blot analysis. XEASD treatment was found to significantly ameliorate the severity of behavioral symptoms in affected mice, as evidenced by decreases in the stereotypy score and locomotor activity. The beneficial effect of XEASD was accompanied by the reversal of abnormal levels of GABA, glutamate, and aspartate, in brain tissue of IDPN-challenged mice. In addition, XEASD treatment increased plasma cyclic adenosine monophosphate (cAMP) levels and activated the phosphorylation of CREB in brain tissue of TS mice. Furthermore, XEASD treatment was found to enhance the antioxidant status of brain tissue in affected mice, as evidenced by increases in the GSH/GSSG ratio and the activity of MnSOD in brain mitochondrial fractions. Taken together, these experimental results will hopefully provide insight into the pharmacological basis for the beneficial effects of XEASD in children suffering from TS.