Public sector's misinformation debunking during the public health campaign: a case of Hong Kong.

For a public health campaign to succeed, the public sector is expected to debunk the misinformation transparently and vividly and guide the citizens. The present study focuses on COVID-19 vaccine misinformation in Hong Kong, a non-Western society with a developed economy and sufficient vaccine supply but high vaccine hesitancy. Inspired by the Health Belief Model (HBM) and research on source transparency and the use of visuals in the debunking, the present study examines the COVID-19 vaccine misinformation debunking messages published by the official social media and online channels of the public sector of Hong Kong (n = 126) over 18 months (1 November 2020 to 20 April 2022) during the COVID-19 vaccination campaign. Results showed that the most frequently occurring misinformation themes were misleading claims about the risks and side effects of vaccination, followed by (non-)effectiveness of the vaccines and the (un)-necessity of vaccination. Among the HBM constructs, barriers and benefits of vaccination were mentioned the most, while self-efficacy was the least addressed. Compared with the early stage of the vaccination campaign, an increasing number of posts contained susceptibility, severity or cues to action. Most debunking statements did not disclose any external sources. The public sector actively used illustrations, with affective illustrations outnumbering cognitive ones. Suggestions for improving the quality of misinformation debunking during public health campaigns are discussed.

Cross-regional analysis of the association between human mobility and COVID-19 infection in Southeast Asia during the transitional period of "living with COVID-19”

Background In response to COVID-19, Southeast Asian (SEA) countries had imposed stringent lockdowns and restrictions to mitigate the pandemic ever since 2019. Because of a gradually boosting vaccination rate along with a strong demand for economic recovery, many governments have shifted the intervention strategy from restrictions to "Living with COVID-19” where people gradually resumed their normal activities since the second half of the year 2021. Noticeably, timelines for enacting the loosened strategy varied across Southeast Asian countries, which resulted in different patterns of human mobility across space and time. This thus presents an opportunity to study the relationship between mobility and the number of infection cases across regions, which could provide support for ongoing interventions in terms of effectiveness. Objective This study aimed to investigate the association between human mobility and COVID-19 infections across space and time during the transition period of shifting strategies from restrictions to normal living in Southeast Asia. Our research results have significant implications for evidence-based policymaking at the present of the COVID-19 pandemic and other public health issues. Methods We aggregated weekly average human mobility data derived from the Facebook origin and destination Movement dataset. and weekly average new cases of COVID-19 at the district level from 01-Jun-2021 to 26-Dec-2021 (a total of 30 weeks). We mapped the spatiotemporal dynamics of human mobility and COVID-19 cases across countries in SEA. We further adopted the Geographically and Temporally Weighted Regression model to identify the spatiotemporal variations of the association between human mobility and COVID-19 infections over 30 weeks. Our model also controls for socioeconomic status, vaccination, and stringency of intervention to better identify the impact of human mobility on COVID-19 spread. Results The percentage of districts that presented a statistically significant association between human mobility and COVID-19 infections generally decreased from 96.15% in week 1 to 90.38% in week 30, indicating a gradual disconnection between human mobility and COVID-19 spread. Over the study period, the average coefficients in 7 SEA countries increased, decreased, and finally kept stable. The association between human mobility and COVID-19 spread also presents spatial heterogeneity where higher coefficients were mainly concentrated in districts of Indonesia from week 1 to week 10 (ranging from 0.336 to 0.826), while lower coefficients were mainly located in districts of Vietnam (ranging from 0.044 to 0.130). From week 10 to week 25, higher coefficients were mainly observed in Singapore, Malaysia, Brunei, north Indonesia, and several districts of the Philippines. Despite the association showing a general weakening trend over time, significant positive coefficients were observed in Singapore, Malaysia, western Indonesia, and the Philippines, with the relatively highest coefficients observed in the Philippines in week 30 (ranging from 0.101 to 0.139). Conclusions The loosening interventions in response to COVID-19 in SEA countries during the second half of 2021 led to diverse changes in human mobility over time, which may result in the COVID-19 infection dynamics. This study investigated the association between mobility and infections at the regional level during the special transitional period. Our study has important implications for public policy interventions, especially at the later stage of a public health crisis.

Cross-regional analysis of the association between human mobility and COVID-19 infection in Southeast Asia during the transitional period of "living with COVID-19".

BACKGROUND: In response to COVID-19, Southeast Asian (SEA) countries had imposed stringent lockdowns and restrictions to mitigate the pandemic ever since 2019. Because of a gradually boosting vaccination rate along with a strong demand for economic recovery, many governments have shifted the intervention strategy from restrictions to "Living with COVID-19" where people gradually resumed their normal activities since the second half of the year 2021. Noticeably, timelines for enacting the loosened strategy varied across Southeast Asian countries, which resulted in different patterns of human mobility across space and time. This thus presents an opportunity to study the relationship between mobility and the number of infection cases across regions, which could provide support for ongoing interventions in terms of effectiveness. OBJECTIVE: This study aimed to investigate the association between human mobility and COVID-19 infections across space and time during the transition period of shifting strategies from restrictions to normal living in Southeast Asia. Our research results have significant implications for evidence-based policymaking at the present of the COVID-19 pandemic and other public health issues. METHODS: We aggregated weekly average human mobility data derived from the Facebook origin and destination Movement dataset. and weekly average new cases of COVID-19 at the district level from 01-Jun-2021 to 26-Dec-2021 (a total of 30 weeks). We mapped the spatiotemporal dynamics of human mobility and COVID-19 cases across countries in SEA. We further adopted the Geographically and Temporally Weighted Regression model to identify the spatiotemporal variations of the association between human mobility and COVID-19 infections over 30 weeks. Our model also controls for socioeconomic status, vaccination, and stringency of intervention to better identify the impact of human mobility on COVID-19 spread. RESULTS: The percentage of districts that presented a statistically significant association between human mobility and COVID-19 infections generally decreased from 96.15% in week 1 to 90.38% in week 30, indicating a gradual disconnection between human mobility and COVID-19 spread. Over the study period, the average coefficients in 7 SEA countries increased, decreased, and finally kept stable. The association between human mobility and COVID-19 spread also presents spatial heterogeneity where higher coefficients were mainly concentrated in districts of Indonesia from week 1 to week 10 (ranging from 0.336 to 0.826), while lower coefficients were mainly located in districts of Vietnam (ranging from 0.044 to 0.130). From week 10 to week 25, higher coefficients were mainly observed in Singapore, Malaysia, Brunei, north Indonesia, and several districts of the Philippines. Despite the association showing a general weakening trend over time, significant positive coefficients were observed in Singapore, Malaysia, western Indonesia, and the Philippines, with the relatively highest coefficients observed in the Philippines in week 30 (ranging from 0.101 to 0.139). CONCLUSIONS: The loosening interventions in response to COVID-19 in SEA countries during the second half of 2021 led to diverse changes in human mobility over time, which may result in the COVID-19 infection dynamics. This study investigated the association between mobility and infections at the regional level during the special transitional period. Our study has important implications for public policy interventions, especially at the later stage of a public health crisis.

Non-clinical safety evaluation of prophylactic mRNA vaccine:general principles and concerns

Messenger RNA（mRNA） vaccine, with antigen-encoded mRNA packaged in delivery vehicles, performs its functions via antigen translation and specific immune response. mRNA vaccines have proven their protective effects and safety in the ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2（SARS-CoV-2）. The World Health Organization issued guidelines specifically for prophylactic mRNA vaccines in 2021, which provide important guidance for non-clinical research on mRNA vaccines. Furthermore, some unusual adverse reactions, such as cerebrovascular disease, embolic stroke, transient cerebral ischemia, deep vein thrombosis, myocarditis（pericarditis） and allergic reactions, have been also found in clinical trials and applications of mRNA vaccines, which deserves attention in non-clinical studies.

News from Messenger? A Cross-National Comparative Study of News Media's Audience Engagement Strategies via Facebook Messenger Chatbots

As an emerging audience engagement channel for news organizations, news chatbots can interact with and attract audiences in a conversational manner. The present study applies the comparative digital journalism frameworks and examines how society-level factors-such as media systems and information communication technology's development-explain chatbot implementation on social media platforms. We surveyed 365 news organizations across 38 countries or regions and inspected their Facebook Messenger accounts with a mixed-methods approach. We found that less than half of the surveyed news organizations implemented Messenger, and only 67 Messengers were responsive-i.e. able to produce at least one response. We used the walkthrough method to interact with the Messengers with 22 pre-defined search queries on information seeking and navigation related to COVID-19. Then we used qualitative content analysis to examine the contents generated by the Messengers. Some Messengers are out of service or could only provide limited services (e.g. generating templated responses or closed-ended options). The Messengers in different news organizations demonstrated great variations in their capacity to understand the queries and interact with the audiences and reparative strategies to handle search failure. We proposed a three-category typology of news chatbots and offered practical and constructive suggestions for news organizations.

Synergism of TNF-α and IFN-ß triggers human airway epithelial cells death by apoptosis and pyroptosis.

Cytokine release syndrome, also called cytokine storm, could cause lung tissue damage, acute respiratory distress syndrome (ARDS) and even death during SARS-CoV-2 infection. However, the underlying mechanisms of cytokine storm still remain unknown. Among these cytokines, the function of TNF-α and type I IFNs especially deserved further investigation. Here, we first found that TNF-α and IFN-ß synergistically induced human airway epithelial cells BEAS-2B death. Mechanistically, the combination of TNF-α and IFN-ß led to the activation of caspase-8 and caspase-3, which initiated BEAS-2B apoptosis. The activated caspase-8 and caspase-3 could further induce the cleavage and activation of gasdermin D (GSDMD) and gasdermin E (GSDME), which finally resulted in pro-inflammatory pyroptosis. The knock-down of caspase-8 and caspase-3 could effectively block the activation of GSDMD and GSDME, and then the death of BEAS-2B induced by TNF-α and IFN-ß. In addition, pan-caspase inhibitor Z-VAD-FMK (ZVAD) and necrosulfonamide (NSA) could inhibit BEAS-2B death induced by TNF-α and IFN-ß. Overall, our work revealed one possible mechanism that cytokine storm causes airway epithelial cells (AECs) damage and ARDS. These results indicated that blocking TNF-α and IFN-ß-mediated AECs death may be a potential target to treat related viral infectious diseases, such as COVID-19.

Insights on the possibility of SARS-CoV-2 transmission through the eyes.

A novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCOV), causing coronavirus disease 2019 (COVID-19), has rapidly spread to most countries and regions worldwide since it broke out at the end of 2019. Epidemic of the virus produces a tremendous pressure on the global health systems. With progressive insight into SARS-CoV-2, the role of eye tissue has attracted wide attention in the spread of COVID-19. Whether SARS-CoV-2 can enter the human body through eyes and cause infection? The fact that unprotected exposure of the eyes to 2019-nCoV might have allowed the virus to infect the body implies that 2019-nCOV can invade eye tissue and set foot in organism. Facing the severe challenge of preventing spread of the COVID-19, combined with the high-risk environment of ophthalmology, it is crucial to investigate ocular tropism of coronavirus. This paper explores the possibility of coronavirus transmission through the eye from aspects of probable mechanisms, clinical cases, detection of coronavirus; and puts forward precautions for ophthalmologists and nurses. Consequently, this review reveals our understanding of ocular tropism of coronavirus and contributes to determining risk of ocular transmission, raising awareness of necessary eye protection among medical workers and reducing further prevalence of SARS-CoV-2.

The Long-Term Effect of COVID-19 Disease Severity on Risk of Diabetes Incidence and the Near 1-Year Follow-Up Outcomes among Postdischarge Patients in Wuhan.

We assessed the nearly 1-year health consequences following discharge and related risk factors of COVID-19 infection and further explored the long-term effect of COVID-19 disease severity on the risk of diabetes incidence. This prospective study included 248 COVID-19 patients discharged from Wuhan Hospital of Traditional Chinese Medicine who were followed up between 1 March and 10 June 2021. Logistic regression models were used to evaluate risk factors. The top ten symptoms were shortness of breath (30.3%), sore or dry throat (25.7%), cough (23.2%), expectoration (23.2%), body pain (22.3%), chest tightness (20.8%), palpitations (17.8%), sleep difficulties (17.0%), fatigue (16.6%), and anxiety (15.3%). Hypertension was associated with fatigue (OR = 2.51, 95% CI: 1.08, 5.80), shortness of breath (OR = 2.34, 95% CI: 1.16, 4.69), palpitations (OR = 2.82, 95% CI: 1.26, 6.31), expectoration (OR = 2.08, 95% CI: 1.01, 4.30), and sore or dry throat (OR = 2.71, 95% CI: 1.30, 5.65). Diabetes was associated with palpitations (OR = 3.22, 95% CI: 1.18, 8.81). Critical illness was associated with an increased risk of diabetes incidence after discharge (OR = 2.90, 95% CI: 1.07, 7.88), which seemed more evident in males. Long COVID-19 symptoms were common at 1-year postdischarge; hypertension and diabetes could be projected as potential risk factors. We are among the first researchers to find that critical illness is associated with incident diabetes after discharge.

Evaluation of online game-based and traditional teaching methods in cephalometric landmarks identifications.

INTRODUCTION: Orthodontic students need to accurately identify cephalometric landmarks to perform cephalometric measurements, which is the prerequisite to proper orthodontic diagnosis and treatment. To provide insights into future cephalometric education, we compared the performance of different methods that can be used in tracing practice, including a novel online game-based method, the cephalometric training module of Uceph (version 948; Uceph, Chengdu, China). METHODS: A total of 45 first-year orthodontic graduate students were divided into 3 groups to receive different kinds of cephalometric training (module group, practicing with the cephalometric training module of Uceph; teaching group, practicing under the teacher's guidance; self-training group, practicing with traced cephalogram as reference). After training with 4 cephalograms, students completed 2 test samples in which the tracing accuracy and time were recorded and a questionnaire concerning their feelings. RESULTS: Both the teaching and module group offered performance advantages on increasing the tracing accuracy and speed of students. The module group provided a better performance on improving tracing accuracy than the teaching group. Students in the module group showed improved concentration, interest, satisfaction toward the teaching method and confidence of correctly identifying landmarks than self-training group, and enhanced interest than students in the teaching group. CONCLUSIONS: The shooting game-based cephalometric training module of Uceph has demonstrated better performance than traditional face-to-face teaching and self-learning, proving to be a viable online tool to train cephalometric tracing, especially during the coronavirus disease 2019 pandemic.

Structure Based Affinity Maturation and Characterizing of SARS-CoV Antibody CR3022 against SARS-CoV-2 by Computational and Experimental Approaches.

The COVID-19 epidemic is raging around the world. Neutralizing antibodies are powerful tools for the prevention and treatment of SARS-CoV-2 infection. Antibody CR3022, a SARS-CoV neutralizing antibody, was found to cross-react with SARS-CoV-2, but its affinity was lower than that of its binding with SARS-CoV, which greatly limited the further development of CR3022 against SARS-CoV-2. Therefore, it is necessary to improve its affinity to SARS-CoV-2 in vitro. In this study, the structure-based molecular simulations were utilized to virtually mutate the possible key residues in the complementarity-determining regions (CDRs) of the CR3022 antibody. According to the criteria of mutation energy, the mutation sites that have the potential to impact the antibody affinity were then selected. Then optimized CR3022 mutants with the enhanced affinity were further identified and verified by enzyme-linked immunosorbent assay (ELISA), surface plasma resonance (SPR) and autoimmune reactivity experiments. Finally, molecular dynamics (MD) simulation and binding free energy calculation (MM/PBSA) were performed on the wild-type CR3022 and its two double-site mutants to understand in more detail the contribution of these sites to the higher affinity. It was found that the binding affinity of the CR3022 antibody could be significantly enhanced more than ten times after the introduction of the S103F/Y mutation in HCDR-3 and the S33R mutation in LCDR-1. The additional hydrogen-bonding, hydrophobic interactions, as well as salt-bridges formed between the modified double-site mutated antibody and SARS-CoV-2 RBD were identified. The computational and experimental results clearly demonstrated that the affinity of the modified antibody has been greatly enhanced. This study indicates that CR3022 as a neutralizing antibody recognizing the conserved region of RBD against SARS-CoV with cross-reactivity with SARS-CoV-2, a different member in a large family of coronaviruses, could be improved by the computational and experimental approaches which provided insights for developing antibody drugs against SARS-CoV-2.

Masked Face Detection Algorithm in the Dense Crowd Based on Federated Learning

Wearing masks is an effective and simple method to prevent the spread of the COVID-19 pandemic in public places, such as train stations, classrooms, and streets. It is of positive significance to urge people to wear masks with computer vision technology. However, the existing detection methods are mainly for simple scenes, and facial missing detection is prone to occur in dense crowds with different scales and occlusions. Moreover, the data obtained by surveillance cameras in public places are difficult to be collected for centralized training, due to the privacy of individuals. In order to solve these problems, a cascaded network is proposed: the first level is the Dilation RetinaNet Face Location (DRFL) Network, which contains Enhanced Receptive Field Context (ERFC) module with the dilation convolution, aiming to reduce network parameters and locate faces of different scales. In order to adapt to embedded camera devices, the second level is the SRNet20 network, which is created by Neural Architecture Search (NAS). Due to privacy protection, it is difficult for surveillance video to share in practice, so our SRNet20 network is trained in federated learning. Meanwhile, we have made a masked face dataset containing about 20,000 images. Finally, the experiments highlight that the detection mAP of the face location is 90.6% on the Wider Face dataset, and the classification mAP of the masked face classification is 98.5% on the dataset we made, which means our cascaded network can detect masked faces in dense crowd scenes well.

Corrigendum: Multicenter Analysis of Liver Injury Patterns and Mortality in COVID-19.

[This corrects the article DOI: 10.3389/fmed.2020.584342.].

Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19.

With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that scenarios with digital contact tracing and quick isolation intervention can reduce the infectious population by 92.11% compared to those without contact tracing. By further restricting the inbound population with a 10,000 daily quota and applying moderate-to-strong community nonpharmacological interventions (NPIs), the average daily confirmed cases in the forecast period of 60 days can be well controlled at around 9 per day (95% CI: 7-12). Two main policy recommendations are drawn from the study. First, digital contact tracing would be an effective countermeasure for reducing local virus spread, especially when it is applied along with a moderate level of vaccination coverage. Second, implementing a daily quota on inbound travelers and restrictive community NPIs would further keep the local infection under control. This study offers scientific evidence and prospective guidance for developing and instituting plans to lift mandatory border control policies in preparing for the global economic recovery.

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic.

The impact of Coronavirus Disease 2019 (COVID-19) on cause-specific mortality has been investigated on a global scale. However, less is known about the excess all-cause mortality and air pollution-human activity responses. This study estimated the weekly excess all-cause mortality during COVID-19 and evaluated the impacts of air pollution and human activities on mortality variations during the 10th to 52nd weeks of 2020 among sixteen countries. A SARIMA model was adopted to estimate the mortality benchmark based on short-term mortality during 2015-2019 and calculate excess mortality. A quasi-likelihood Poisson-based GAM model was further applied for air pollution/human activity response evaluation, namely ground-level NO2 and PM2.5 and the visit frequencies of parks and workplaces. The findings showed that, compared with COVID-19 mortality (i.e., cause-specific mortality), excess all-cause mortality changed from -26.52% to 373.60% during the 10th to 52nd weeks across the sixteen countries examined, revealing higher excess all-cause mortality than COVID-19 mortality in most countries. For the impact of air pollution and human activities, the average country-level relative risk showed that one unit increase in weekly NO2, PM2.5, park visits and workplace visits was associated with approximately 1.54% increase and 0.19%, 0.23%, and 0.23% decrease in excess all-cause mortality, respectively. Moreover, compared with the impact on COVID-19 mortality, the relative risks of weekly NO2 and PM2.5 were lower, and the relative risks of weekly park and workplace visits were higher for excess all-cause mortality. These results suggest that the estimation based on excess all-cause mortality reduced the potential impact of air pollution and enhanced the influence of human activities compared with the estimation based on COVID-19 mortality.

Yearly and Daily Relationship Assessment between Air Pollution and Early-Stage COVID-19 Incidence: Evidence from 231 Countries and Regions

The novel coronavirus disease 2019 (COVID-19) has caused significantly changes in worldwide environmental and socioeconomics, especially in the early stage. Previous research has found that air pollution is potentially affected by these unprecedented changes and it affects COVID-19 infections. This study aims to explore the non-linear association between yearly and daily global air pollution and the confirmed cases of COVID-19. The concentrations of tropospheric air pollution (CO, NO2, O3, and SO2) and the daily confirmed cases between 23 January 2020 and 31 May 2020 were collected at the global scale. The yearly discrepancies of air pollutions and daily air pollution are associated with total and daily confirmed cases, respectively, based on the generalized additive model. We observed that there are significant spatially and temporally non-stationary variations between air pollution and confirmed cases of COVID-19. For the yearly assessment, the number of confirmed cases is associated with the positive fluctuation of CO, O3, and SO2 discrepancies, while the increasing NO2 discrepancies leads to the significant peak of confirmed cases variation. For the daily assessment, among the selected countries, positive linear or non-linear relationships are found between CO and SO2 concentrations and the daily confirmed cases, whereas NO2 concentrations are negatively correlated with the daily confirmed cases;variations in the ascending/declining associations are identified from the relationship of the O3-confirmed cases. The findings indicate that the non-linear relationships between global air pollution and the confirmed cases of COVID-19 are varied, which implicates the needs as well as the incorporation of our findings in the risk monitoring of public health on local, regional, and global scales.

Effects of urban functional fragmentation on nitrogen dioxide (NO2) variation with anthropogenic-emission restriction in China.

Urban functional fragmentation plays an important role in assessing Nitrogen Dioxide (NO2) emissions and variations. While the mediated impact of anthropogenic-emission restriction has not been comprehensively discussed, the lockdown response to the novel coronavirus disease 2019 (COVID-19) provides an unprecedented opportunity to meet this goal. This study proposes a new idea to explore the effects of urban functional fragmentation on NO2 variation with anthropogenic-emission restriction in China. First, NO2 variations are quantified by an Autoregressive Integrated Moving Average with external variables-Dynamic Time Warping (SARIMAX-DTW)-based model. Then, urban functional fragmentation indices including industrial/public Edge Density (ED) and Landscape Shape Index (LSI), urban functional Aggregation Index (AI) and Number of Patches (NP) are developed. Finally, the mediated impacts of anthropogenic-emission restriction are assessed by evaluating the fragmentation-NO2 variation association before and during the lockdown during COVID-19. The findings reveal negative effects of industrial ED, public LSI, urban functional AI and NP and positive effects of public ED and industrial LSI on NO2 variation based on the restricted anthropogenic emissions. By comparing the association analysis before and during lockdown, the mediated impact of anthropogenic-emission restriction is revealed to partially increase the effect of industrial ED, industrial LSI, public LSI, urban functional AI and NP and decrease the effect of public ED on NO2 variation. This study provides scientific findings for redesigning the urban environment in related to the urban functional configuration to mitigating the air pollution, ultimately developing sustainable societies.

How source-level and message-level factors influence journalists’ social media visibility during a public health crisis

Social media has become a channel through which journalists distribute their work, reach audiences and gain visibility. Informed by the frameworks of journalistic branding, the heuristic-systematic model, and hypertextual elements, the present study examines the extent to which the source factor (journalists? branding on social media profiles) and message factors (communication styles and hypertextual elements) influence visibility (i.e. the popularity of the account and the number of favourites and retweets of the posts). We analysed the Twitter profiles of 98 health journalists from seven major media organizations in the US and conducted a manual content analysis of a representative sample of their public tweets (n?=?3982) published during the Covid-19 pandemic. In contrast to expectations, branding contributed little to any indicators of visibility, and profiles with institutional branding had fewer followers. Both affective messages and rational messages received more likes and retweets than messages without these elements. Tweets containing images or news-related hyperlinks received more retweets, whereas the number of @mentions in a tweet was negatively related to visibility. Journalists from traditional media, those who tweeted more often, and those with more followers had higher levels of visibility.

Association between NO2 concentrations and spatial configuration: a study of the impacts of COVID-19 lockdowns in 54 US cities

The massive lockdown of global cities during the COVID-19 pandemic is substantially improving the atmospheric environment, which for the first time, urban mobility is virtually reduced to zero, and it is then possible to establish a baseline for air quality. By comparing these values with pre-COVID-19 data, it is possible to infer the likely effect of urban mobility and spatial configuration on the air quality. In the present study, a time-series prediction model is enhanced to estimate the nationwide NO2 concentrations before and during the lockdown measures in the United States, and 54 cities are included in the study. The prediction generates a notable NO2 difference between the observations if the lockdown is not considered, and the changes in urban mobility can explain the difference. It is found that the changes in urban mobility associated with various road textures have a significant impact on NO2 dispersion in different types of climates.