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The political dimension of crisis communication remains understudied in public administration. We defined the politicization of government crisis communication as the employment of politics-oriented communication strategies in crisis messaging. We further examined the state-level politicization occurring during COVID-19 and its influence on public engagement and policy compliance. We applied machine learning algorithms to analyze 43,642 Twitter messages posted by fifty US state governors, assessing the extent to which these governors politicized crisis communication. We compiled data from multiple sources to explore the influence of communication politicization on public engagement and compliance behaviors. While most governors showed major concerns regarding reputation and blame, their level of politicization and selection of communication strategies varied. Increased levels of communication politicization discouraged the public's online engagement and policy compliance. Excessive levels of political consideration could undermine the legitimacy and effectiveness of government crisis communication, and thus an examination of their relationship was essential.
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The resumption of production after the "suspension” caused by the COVID-19 has emerged as an urgent problem for many enterprises and the government. The resumption of production is actually a dynamic evolution problem from 0 to 1 (100%). This paper constructs a general game model and a dynamic replication system for the resumption of production and government support, and gives theorems for the construction of the model. It analyzes the evolution mechanism and scenario conditions for the convergence of enterprise strategies to the "resumption of production” strategy, takes the resumption of production of hog farmers as an example to carry out a study on the regulation of countermeasures to resume hog production, and explores systemic countermeasures and suggestions for the rapid convergence of farmers' strategies to the "resumption of work and production” strategy. The study found that the production resuming behavior system dynamics evolution game regulation model provides a systematic model and method for the study of resumption countermeasures, a general regulation model for the resumption ratio from 0 to 1 (100%), and a systematic idea, method and model for exploring the "precise strategy” system to promote the rapid resumption of production. © 2023, Science Press (China). All rights reserved.
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Objective: To investigate how well do the middle school students in Wuhan know and perform COVID-19 prevention behaviors during the epidemic, and to identify the influencing factors that impact the wellness of students' performance on mask-wearing, hand washing, and other health-related behaviors. Method: We surveyed 21 middle schools in Wuhan using a self-developed questionnaire, evaluated the students' prevention behaviors, and used logistic regression to identify the influencing factors. Results: We investigated 6 858 students with an average age of (14. 5±1. 5) years, including 3 584 male students (accounting for 52. 3%). Grade, parents' education, and submission time are significantly related to the wellness of the three types of health behaviors (P<0. 05). Junior high school students showed a better performance in handwashing and other health-related behaviors than senior high school students (P<0. 05). Parents' education showed a significant impact on students' prevention behaviors in all aspects (P<0. 05). Conclusion: Enhancement is needed for the education of prevention behaviors among middle school students. Schools should pay more attention to students whose parents are of the lower level of education. © 2023 Editorial Board of Medical Journal of Wuhan University. All rights reserved.
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One Health is an upgrade and optimization of health concepts, which recognizes the integrated health of the human-animal-environment. It emphasizes the use of interdisciplinary collaboration, multi-sectoral coordination, and multi-organizational One Health approaches to solve scientific questions. The surveillance and early warning system is the basis of public health emergency prevention and control. The COVID-19 pandemic and the emerging infectious disease (EID) have put great challenges on the existing surveillance and early warning systems worldwide. Guided by the concept of One Health, we attempt to build a new pattern of integrated surveillance and early warning system for EID. We will detail the system including the One Health-based organizational structure, zoonotic and environmental science surveillance network, EID reporting process, and support and guarantee from education and policy. The integrated surveillance and early warning system for EID constructed here has practical and application prospects, and will provide guidance for the prevention and control of COVID-19 and the possible EID in the future.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.
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Teleconferencing technology has been widely used in the context of the covid-19 pandemic. However, local and remote participants always have a poorer experience of hybrid discussion for various reasons in the leaderless group discussions with mixed online and offline members. In this paper, this phenomenon is explored through an early pilot study. We found problems with the lack of presence of remote participants in hybrid discussion sessions, as well as unclear information about the status of members. To solve such problems, we've designed a social robot called SNOTBOX. The bot indicates the participation status (marginalized or not) of the remote participant using "Buzzo" and the remote participant's desire to be heard through a "Eureka". We used both representations to attract the attention of local participants as a way to enhance the presence of remote participants in the conference. SNOTBOX is easy to produce and allows for DIY customization, and also supports multi-participant online discussions. © 2023 IEEE Computer Society. All rights reserved.
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The recent COVID-19 pandemic has raised concerns about individual resilience in the face of adversity. The abundant research suggested that artificial intelligence (AI) can help organizations handle changes during this challenging period. However, little empirical research has explored whether the presence of AI enhances individual resilience against adversities. Drawing on the reciprocal determinism theory, this study considers the formation of two typical post-adoption behaviors and their subsequent results in individual resilience. The structural equation modeling shows that AI factors (usability and sociability) and personal factors (self-efficacy) determine usage behaviors (routine and infusion use), in turn affecting individual resilience. The OLS results suggest the right half of the U-shaped relationships between infusion use and resilience. Two-step fsQCA offers three configurations resulting in high resilience under the different presence of AI factors and also suggests the roles of user behaviors. The study provides new theoretical enlightenment for the impact of digital service technology on individuals and enriches the existing literature on the usage of digital service technology. The findings provide practical implications for practitioners to design AI products better to improve smart service experience. © 2023 Elsevier Ltd
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FRET is ascribed to the spectral overlapping of upconversion luminescence and the absorption of AuNPs. This experiment enables early-stage coronavirus detection. The results show a sensitivity of 100 fM for the detection of COVID-19 DNA. © 2022 The Author(s)
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FRET is ascribed to the spectral overlapping of upconversion luminescence and the absorption of AuNPs. This experiment enables early-stage coronavirus detection. The results show a sensitivity of 100 fM for the detection of COVID-19 DNA. © 2022 The Author(s)
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The emergence of new business ecosystem such as virtual economy and digital economy has transformed traditional economic thinking and brought new opportunities for the development. Today, the global economy is gradually recovering from the COVID-19 pandemic, but the coexistence and collision of real-world and online activities still exist, so by analyzing the experience of using individuals, the trust of the community, and the conflict and integration between the two, it may provide a good business ecosystem for Metaverse Era. © 2022 IEEE.
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Under the influence of COVID-19, intercity ride-sharing has become more and more popular due to its relatively little contact and low price and has gradually become one of the important ways of intercity transportation. The ride-sharing platform provides functions of information interaction among passengers and drivers, allocating the transportation tasks and recommending the optimal route planning. Existing ride-sharing platforms fail to take user's personalized needs into account when assigning tasks, and users have low satisfaction with the planned routes. This paper designs an allocation algorithm (Allocation Algorithm 4 Inter-city Carpool) for intercity carpool and proposes a pricing function related to the detour distance and user's satisfaction, so as to ensure the optimal benefits for ride-sharing platforms and drivers, as well as the optimal passenger satisfaction. The AA4IC algorithm is proved to be incentive compatible and budget balanced theoretically, and the effectiveness of allocation scheme generation and path planning is verified by experiments. When the algorithm is iterated 1000 times, the time is less than 200 s, and the task assignment under the optimal user satisfaction can be achieved. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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One Health is an upgrade and optimization of health concepts, which recognizes the integrated health of the human-animal-environment. It emphasizes the use of interdisciplinary collaboration, multi-sectoral coordination, and multi-organizational One Health approaches to solve scientific questions. The surveillance and early warning system is the basis of public health emergency prevention and control. The COVID-19 pandemic and the emerging infectious disease (EID) have put great challenges on the existing surveillance and early warning systems worldwide. Guided by the concept of One Health, we attempt to build a new pattern of integrated surveillance and early warning system for EID. We will detail the system including the One Health-based organizational structure, zoonotic and environmental science surveillance network, EID reporting process, and support and guarantee from education and policy. The integrated surveillance and early warning system for EID constructed here has practical and application prospects, and will provide guidance for the prevention and control of COVID-19 and the possible EID in the future. © 2022, National Institute of Parasitic Diseases. All rights reserved.
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Background: Kidney transplant recipients (KTR) have a diminished response to SARS-CoV-2 vaccination in comparison to immunocompetent individuals. Deeper understanding of the antibody response in KTRs following third-dose vaccination would enable identification of those who remain unprotected against Omicron and require additional treatment strategies. Method(s): We profiled antibody responses in KTRs pre-and at one and three months post-third-dose SARS-CoV2 mRNA-based vaccine. Anti-spike and anti-RBD IgG levels were determined by ELISA. Neutralization against wild-type, Beta, Delta and Omicron (BA.1) variants was determined using a SARS-CoV-2 spike pseudotyped lentivirus assay. Result(s): 44 KTRs were analysed at 1 and 3 months (n=26) post-third-dose. At one month, the proportion of participants with a robust antibody response had increased significantly from baseline, but Omicron-specific neutralizing antibodies were detected in just 45% of KTRs. Median anti-spike and anti-RBD antibody levels declined at 3 months, but the proportion of KTRs with a robust antibody response was unchanged. 38.5% KTRs maintained Omicron-specific neutralization at 3 months. No clinical variables were significantly associated with detectable Omicron neutralizing antibodies, but anti-RBD titres appeared to identify those with Omicron-specific neutralizing capacity. Conclusion(s): Over 50% of KTRs lack an Omicron-specific neutralization response 1 month following a third mRNA-vaccine dose. Among responders, binding and neutralizing antibody responses were well preserved at 3 months. Anti-RBD antibody titres may be a useful identifier of patients with detectable Omicron neutralizing antibody response.
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Objective: To explore the effect of vaccination on viral negative conversion of children with COVID-19. Methods: A retrospective cohort study was conducted. A cohort of 189 children aged 3-14 years with COVID-19 admitted to Renji Hospital (South branch) of Shanghai Jiao Tong University School of Medicine from April 7th to May 19th 2022 was enrolled in the study. According to the vaccination status, the infected children were divided into an unvaccinated group and a vaccinated group. Age, gender, severity, clinical manifestations, and laboratory tests, etc. were compared between groups, by rank sum test or chi-square test. The effects of vaccination on viral negative conversion were analyzed by a Cox mixed-effects regression model. Additionally, a questionnaire survey was conducted among the parents of unvaccinated children to analyze the reasons for not being vaccinated. Results: A total of 189 children aged 3-14 years were enrolled, including 95 males (50.3%) and 94 females (49.7%), aged 5.7 (4.1,8.6) years. There were 117 cases (61.9%) in the unvaccinated group and 72 cases (38.1%) in the vaccinated group. The age of the vaccinated group was higher than that of the unvaccinated group (8.8 (6.8, 10.6) vs. 4.5 (3.6, 5.9) years, Z=9.45, P<0.001). No significant differences were found in clinical manifestations, disease severity, and laboratory results between groups (all P>0.05), except for the occurrence rate of cough symptoms, which was significantly higher in the vaccinated group than in the non-vaccinated group (68.1% (49/72) vs. 50.4% (59/117),χ2=5.67, P=0.017). The Kaplan-Meier survival curve and Cox mixed-effects regression model showed that the time to the viral negative conversion was significantly shorter in the vaccinated group compared with the unvaccinated group (8 (7, 10) vs. 11 (9, 12) d, Z=5.20, P<0.001; adjusted HR=2.19 (95%CI 1.62-2.97)). For questionnaire survey on the reasons for not receiving a vaccination, 115 questionnaires were distributed and 112 valid questionnaires (97.4%) were collected. The main reasons for not being vaccinated were that parents thought that their children were not in the range of appropriate age for vaccination (51 cases, 45.5%) and children were in special physical conditions (47 cases, 42.0%). Conclusion: Vaccination can effectively shorten the negative conversion time of children with COVID-19 and targeted programs should be developed to increase eligible children's vaccination rate for SARS-CoV-2 vaccination.
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COVID-19 , Vaccines , Child , Female , Male , Humans , COVID-19/prevention & control , COVID-19 Vaccines , Retrospective Studies , SARS-CoV-2 , China/epidemiologyABSTRACT
Background The coronavirus disease 2019 (COVID-19) has affected approximately 2 million individuals worldwide;however, data regarding fatal cases have been limited. Objective To report the clinical features of 162 fatal cases of COVID-19 from 5 hospitals in Wuhan between December 30, 2019 and March 12, 2020. Methods The demographic data, signs and symptoms, clinical course, comorbidities, laboratory findings, computed tomographic (CT) scans, treatments, and complications of the patients with fatal cases were retrieved from electronic medical records. Results The median patient age was 69.5 (interquartile range: 63.0-77.25) years, and 80% of the patients were over 61 years. A total of 112 (69.1%) patients were men. Hypertension (45.1%) was the most common comorbidity, while 59 (36.4%) patients had no comorbidity. At admission, 131 (81.9%) patients had severe or critical COVID-19, whereas 39 (18.1%) patients with hypertension or chronic lung disease had moderate COVID-19. In total, 126 (77.8%) patients received antiviral treatment, while 132(81.5%) patients received glucocorticoid treatment. A total of 116 (71.6%) patients were admitted to the intensive care unit (ICU), and 137 (85.1%) patients received mechanical ventilation. Most patients received mechanical ventilation before ICU admission. Approximately 93.2% of the patients developed respiratory failure or acute respiratory distress syndrome. There were no significant differences in the inhospital survival time among the hospitals (P=0.14). Conclusion Young patients with moderate COVID-19 without comorbidity at admission could also develop fatal outcomes. The in-hospital survival time of the fatal cases was similar among the hospitals of different levels in Wuhan. © Wolters Kluwer Health, Inc. All rights reserved.
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With the proposal of "carbon peak" and "carbon neutralization", Liquefied Natural Gas (LNG) has gradually garnered the attention of energy market as a clean and low-carbon energy. In this context, it is of great significance to analyze the evolution mode of the LNG maritime transport network, so as to master the dynamic of global energy pattern and the status of China's import trade. In this paper, the evolution trend of the global LNG maritime transport network from 2018 to 2020 is explored based on the ship trajectory data and complex network theory. Meanwhile, according to China's trade status, LNG import sources, distribution of main import ports, and the inflow status of the top three import ports in China are analyzed. The results show that: (1) From 2018 to 2020, the global LNG maritime transport network expanded with a "scale-free" characteristic. The "breadth" and "depth" of node connections in the backbone network are increasing, and there is a risk that global LNG trade will become monopolistic;(2) The countries along the "Belt and Road Initiative" actively participated in trade. The numbers of import ports and import voyages in Central and North America, South and Southeast Asia have significantly increased, and in particular, Sabetta and Bonny ranked the top eight globally according to their export volume;(3) The average shortest path length of the network is increasing year by year from 2018 to 2020, and the new mode of "transshipment port" business is gradually emerging. By 2020, 21 transshipment ports have participated in LNG trade, and the United States occupies the dominant position in global transshipment;(4) In recent three years, China's LNG import scale has developed rapidly, and the flow direction of the maritime transport network tends to be diversified. However, Australia is still the main LNG source for China. In terms of import volume, the ports of Tianjin, Shenzhen, and Yung'an rank the top three in China, and the pressure to reduce carbon emissions has prompted the economically developed regions to build terminals and increase imports. © 2022, Science Press. All right reserved.
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Understanding how interurban movements can modify the spatial distribution of the population is important for transport planning but is also a fundamental ingredient for epidemic modeling. We illustrate this on vacation trips for all transportation modes in China during the Lunar New Year and compare the results for 2019 with the ones for 2020 where travel bans were applied for mitigating the spread of a novel coronavirus (COVID-19). We first show that inter-urban travel flows are broadly distributed and display both large temporal and spatial fluctuations, making their modeling very difficult. When flows are larger, they appear to be more dispersed over a larger number of origins and destinations, creating de facto hubs that can spread an epidemic at a large scale. These movements quickly induce (in about a week for this case) a very strong population concentration in a small set of cities. We characterize quantitatively the return to the initial distribution by defining a pendular ratio which allows us to show that this dynamics is in general very slow and even stopped for the 2020 Lunar New Year due to travel restrictions. Travel restrictions obviously limit the spread of the diseases between different cities, but have thus the counter-effect of keeping high concentration in a small set of cities, a priori favoring intra-city spread, unless individual contacts are strongly limited. These results shed some light on the statistics of interurban movements and how they modify the national distribution of populations, a crucial ingredient for devising effective control strategies at a national level. Copyright © 2022 Ye, Hu, Ji and Barthelemy.
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Background: The impact of immunosuppressants on COVID-19 vaccination response and durability in patients with immune-mediated infammatory diseases (IMID) is yet to be fully characterized. Humoral response may be attenuated in these patients especially those on B cell depleting therapy and higher doses of corticosteroids, but data regarding other immunosuppressants are scarce. Objectives: We aimed to investigate antibody and T cell responses and durability to SARS-CoV-2 mRNA vaccines (BNT162b and/or mRNA 1273) in IMID patients on immunomodulatory maintenance therapy other than B-cell depleting therapy and corticosteroids. Methods: This prospective observational cohort study examined the immuno-genicity of SARS-CoV-2 mRNA vaccines in adult patients with IMIDs (psoriatic arthritis, psoriasis, infammatory bowel disease and rheumatoid arthritis) with or without maintenance immunosuppressive therapies (anti-TNF, methotrexate/azathioprine [MTX/AZA], anti-TNF + MTX/AZA, anti IL12/23, anti-IL-17, anti-IL23) compared to healthy controls. Automated ELISA for IgGs to spike trimer, spike receptor binding domain (RBD) and the nucleocapsid (NP) and T-cell release of 9 cytokines (IFNg, IL2, IL4, IL17A, TNF) and cytotoxic molecules (sFasL, GzmA, GzmB, Perforinin) in cell culture supernatants following stimulation with spike or NP peptide arrays were conducted at 4 time points: T1=pre vaccination, T2=me-dian 26 days after dose 1, T3=median 16 days after dose 2 and T4=median 106 days after dose 2. Neutralization assays against four SARS-CoV-2 variants (wild type, delta, beta and gamma) were conducted at T3. Results: We followed 150 subjects: 26 healthy controls and 124 IMID patients: 9 untreated, 44 on anti-TNF, 16 on anti-TNF with MTX/AZA, 10 on anti-IL23, 28 on anti-IL12/23, 9 on anti-IL17, 8 on MTX/AZA (Table 1). Most patients mounted antibody and T cell responses with increases from dose 1 to dose 2 (100% sero-conversion at T3) and some decline by T4, with variability within groups. Antibody levels and neutralization efficacy was lower in anti-TNFgroups (anti-TNF, anti-TNF + MTX/AZA) compared to controls and waned by T4 (Figure 1). T cell responses were not consistently different between groups. Pooled data showed a higher antibody response to mRNA-1273 compared to BNT162b. Conclusion: Following 2 doses of mRNA vaccination there is 100% seroconver-sion in IMID patients on maintenance therapy. Antibody levels and neutralization efficacy in anti-TNF group are lower than controls, and wane substantially by 3 months after dose 2. These fndings highlight the need for third dose in patients undergoing treatment with anti-TNF therapy and continued monitoring of immunity in these patient groups, taking into consideration newer variants and additional vaccine doses.
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Objective To analyze the molecular epidemiological characteristics of the Corona virus disease 2019 (COVID‑19) cases in Shijiazhuang, which can reveal the origin of the outbreak and provide a scientific basis for COVID‑19 prevention and control. Methods From January 2 to January 8, 2021, a total of 404 samples from 170 COVID‑19 cases were collected from the Shijiazhuang Fifth Hospital. The consensus sequence of 2019 novel Coronavirus(2019‑nCoV) was obtained through multiplex polymerase chain reaction‑based sequencing. The sequences of 170 COVID‑19 cases were analyzed by the PANGOLIN, and the data were statistically analyzed by T‑test. Results Among the 404 COVID‑19 samples, a total of 356 samples obtained high quality genome sequences (>95%, 100×sequencing depth). The whole genome sequences of 170 COVID‑19 cases were obtained by eliminating repeated samples. All 170 sequences were recognized as lineage B1.1 using PANGOLIN. The number of single nucleotide polymorphism arrange from 18-22 and most of the single nucleotide polymorphism were synonymous variants. All of 170 genomes could be classified into 48 sub‑groups and most of the genomes were classified into 2 sub‑groups (66 and 31, respectively). Conclusions All cases in this study are likely originated from one imported case. The viruses have spread in the community for a long time and have mutated during the community transmission.
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Objective: To investigate the infection rate in close contacts of COVID-19 patients before and after the last negative nucleic acid test, evaluate the effect of dynamic nucleic acid test in determining the infectivity of COVID-19 patients. Methods: Dynamic nucleic acid test results of COVID-19 cases were collected in a retrospective cohort study. COVID-19 cases with negative nucleic acid test results before their first positive nucleic acid tests were selected as study subjects. Close contacts of the index cases and the secondary close contacts were kept isolation for medical observation to assess their risk of infection. Results: This study included 89 confirmed cases from two local COVID-19 epidemics in Ningbo. A total of 5 609 close contacts were surveyed, the overall infection rate was 0.20%. No close contacts of the COVID-19 cases before the last negative nucleic acid test were infected, and the infection rate in the close contacts of the COVID-19 cases after the last negative nucleic acid test was 1.33%, all of these close contacts lived together with the index cases. No secondary close contacts were infected. Conclusion: COVID-19 patient becomes infectious after the last nucleic acid is negative, and has no infectivity before the last nucleic acid negative.
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COVID-19 , Epidemics , Nucleic Acids , COVID-19/epidemiology , Humans , Retrospective Studies , SARS-CoV-2ABSTRACT
Drawing on recent research on robust governance, we conceptualize robust crisis communication as a dynamic process centered on evolving public communication demands. We propose a three-dimensional measurement for empirically examining the robustness of government crisis communication in the context of the COVID-19 pandemic. We collected 43,642 Twitter messages posted by 50 state governors in the United States from January 1 to June 30, 2020. We applied machine learning algorithms to code the voluminous Twitter data based on messaging topics, sentiments, and interactions. This study found an overall low level of robustness in the governors' crisis communication. Governors most frequently posted reputation management tweets, followed by tweets about the government's handling of the pandemic. This research presents empirical evidence for the heavy influence of politics on governors' crisis communication strategies and highlights the need to understand and build robust crisis communication.