Non-randomized evaluation of hospitalization after a prescription for nirmatrelvir/ritonavir versus molnupiravir in high-risk COVID-19 outpatients.

OBJECTIVES: To assess and compare subsequent hospital admissions within 30 days for patients after receiving a prescription for either oral nirmatrelvir/ritonavir or oral molnupiravir. METHODS: We conducted a retrospective review of 3207 high-risk, non-hospitalized adult COVID-19 patients who received a prescription for molnupiravir (n = 209) or nirmatrelvir/ritonavir (n = 2998) at an academic medical centre in New York City from April to December 2022. Variables including age, vaccination status, high-risk conditions and demographic factors were pulled from the electronic medical record. We used multivariable logistic regression to adjust for potential confounding variables. RESULTS: All-cause 30 day hospitalization was not significantly different between patients who received nirmatrelvir/ritonavir compared with molnupiravir (1.4% versus 1.9%, P value = 0.55). The association between COVID-related hospitalization and medication was also not significant (0.7%versus 0.5%, P value = 0.99). Patients who received molnupiravir were more likely to have more underlying high-risk conditions. After adjusting for potential confounders, the odds of all-cause hospitalizations were not significantly different between patients who received nirmatrelvir/ritonavir compared with molnupiravir (OR = 1.16, 95% CI: 0.4-3.3, P value = 0.79). CONCLUSIONS: These data provide additional evidence to support molnupiravir as a suitable alternative when other COVID-19 antivirals cannot be given.

Real-time updating of dynamic social networks for COVID-19 vaccination strategies.

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

Robotics Innovation for the Elderly [From the Editor's Desk]

As I write this editorial, it is the beginning of 2023. I would like to wish you and your loved ones a happy and healthy new year. We hope that 2023 will be a better year. Year 2022 was difficult for those in the war zone and those who struggled with policies on the COVID-19 pandemic. While the pandemic is at the back of most people's minds in many countries, as China abruptly abandoned its zero-COVID policy, hospitals in China became overcrowded very quickly, and the health-care system has faced a major stress test since December 2022. Sadly, among the most vulnerable populations, older adults were hit badly and could not get needed help in time, which led to many deaths. We need to take care of the elderly and work on robotics innovations to assist them.

Real-time updating of dynamic social networks for COVID-19 vaccination strategies

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

How information processing and risk/benefit perception affect COVID-19 vaccination intention of users in online health communities.

Objective: To investigate the relationship among information processing, risk/benefit perception and the COVID-19 vaccination intention of OHCs users with the heuristic-systematic model (HSM). Methods: This study conducted a cross-sectional questionnaire via an online survey among Chinese adults. A structural equation model (SEM) was used to examine the research hypotheses. Results: Systematic information processing positively influenced benefit perception, and heuristic information processing positively influenced risk perception. Benefit perception had a significant positive effect on users' vaccination intention. Risk perception had a negative impact on vaccination intention. Findings revealed that differences in information processing methods affect users' perceptions of risk and benefit, which decide their vaccination intention. Conclusion: Online health communities can provide more systematic cues and users should process information systematically to increase their perceived benefits, consequently increase their willingness to receive COVID-19 vaccine.

COVID-19 vaccination hesitancy and safety among adult people with epilepsy in eastern China.

OBJECTIVE: This study assesses the hesitancy and safety of vaccination administration for the novel 2019 Coronavirus Disease (COVID-19) among adult people with epilepsy (PWE). METHODS: We recruited adult PWE who visited the outpatient epilepsy clinic from August 2021 to February 2022. We administered a structured questionnaire and a face-to-face interview regarding demographic factors, epilepsy characteristics, and relevant vaccine issues to all patients. Factors related to receiving a vaccine and epilepsy-related events after vaccination were then analyzed. RESULTS: A total of 501 PWE were surveyed; 288 were unvaccinated and 213 were vaccinated. Patients without jobs (OR: 0.59; 95% CI: 0.37-0.95, p = 0.03) were less likely to receive the vaccine compared to students or those with jobs. Other factors associated with vaccination were a higher number of anti-seizure medications (OR: 0.72; 95% CI: 0.55-0.95, p = 0.02) and a lower pre-vaccine seizure frequency (OR: 2.21; 95% CI: 1.06-4.59, p = 0.03). Of the 213 vaccinated patients, 10 (4.70%) reported at least one local and/or systemic side effect. Most patients (92.50%) did not report worse seizures within one month of vaccination. Poor ASM adherence (OR: 15.06; 95% CI: 1.75-129.87, p = 0.01) and fatigue/stimulant drinks such as caffeine (OR: 50.59; 95% CI: 7.57-337.94, p < 0.01) were significantly associated with seizure worsening within one month of receiving the COVID-19 vaccination. CONCLUSION: Almost two-fifths of patients with adult PWE have received a COVID-19 vaccine. Attention should be paid to educating epilepsy patients without jobs on the significance and safety of the vaccine. There was a low risk of seizure worsening in the short term after vaccination in PWE.

Analysis of public reactions to the novel Coronavirus (COVID-19) outbreak on Twitter

PurposeThe novel Coronavirus (COVID-19) pandemic, which started in late December 2019, has spread to more than 200 countries. As no vaccine is yet available for this pandemic, government and health agencies are taking draconian steps to contain it. This pandemic is also trending on social media, particularly on Twitter. The purpose of this study is to explore and analyze the general public reactions to the COVID-19 outbreak on Twitter.Design/methodology/approachThis study conducts a thematic analysis of COVID-19 tweets through VOSviewer to examine people's reactions related to the COVID-19 outbreak in the world. Moreover, sequential pattern mining (SPM) techniques are used to find frequent words/patterns and their relationship in tweets.FindingsSeven clusters (themes) were found through VOSviewer: Cluster 1 (green): public sentiments about COVID-19 in the USA. Cluster 2 (red): public sentiments about COVID-19 in Italy and Iran and a vaccine, Cluster 3 (purple): public sentiments about doomsday and science credibility. Cluster 4 (blue): public sentiments about COVID-19 in India. Cluster 5 (yellow): public sentiments about COVID-19's emergence. Cluster 6 (light blue): public sentiments about COVID-19 in the Philippines. Cluster 7 (orange): Public sentiments about COVID-19 US Intelligence Report. The most frequent words/patterns discovered with SPM were "COVID-19,” "Coronavirus,” "Chinese virus” and the most frequent and high confidence sequential rules were related to "Coronavirus, testing, lockdown, China and Wuhan.”Research limitations/implicationsThe methodology can be used to analyze the opinions/thoughts of the general public on Twitter and to categorize them accordingly. Moreover, the categories (generated by VOSviewer) can be correlated with the results obtained with pattern mining techniques.Social implicationsThis study has a significant socio-economic impact as Twitter offers content posting and sharing to billions of users worldwide.Originality/valueAccording to the authors' best knowledge, this may be the first study to carry out a thematic analysis of COVID-19 tweets at a glance and mining the tweets with SPM to investigate how people reacted to the COVID-19 outbreak on Twitter.

Neutralization against SARS-CoV-2 Delta/Omicron variants and B cell response after inactivated vaccination among COVID-19 convalescents.

Emerging SARS-CoV-2 variants have made COVID-19 convalescents susceptible to re-infection and have raised concern about the efficacy of inactivated vaccination in neutralization against emerging variants and antigen-specific B cell response. To this end, a study on a long-term cohort of 208 participants who have recovered from COVID-19 was conducted, and the participants were followed up at 3.3 (Visit 1), 9.2 (Visit 2), and 18.5 (Visit 3) months after SARS-CoV-2 infection. They were classified into three groups (no-vaccination (n = 54), one-dose (n = 62), and two-dose (n = 92) groups) on the basis of the administration of inactivated vaccination. The neutralizing antibody (NAb) titers against the wild-type virus continued to decrease in the no-vaccination group, but they rose significantly in the one-dose and two-dose groups, with the highest NAb titers being observed in the two-dose group at Visit 3. The NAb titers against the Delta variant for the no-vaccination, one-dose, and two-dose groups decreased by 3.3, 1.9, and 2.3 folds relative to the wild-type virus, respectively, and those against the Omicron variant decreased by 7.0, 4.0, and 3.8 folds, respectively. Similarly, the responses of SARS-CoV-2 RBD-specific B cells and memory B cells were boosted by the second vaccine dose. Results showed that the convalescents benefited from the administration of the inactivated vaccine (one or two doses), which enhanced neutralization against highly mutated SARS-CoV-2 variants and memory B cell responses. Two doses of inactivated vaccine among COVID-19 convalescents are therefore recommended for the prevention of the COVID-19 pandemic, and vaccination guidelines and policies need to be updated.

Humans and the Environment [From the Editor’s Desk]

The COVID-19 pandemic has changed a lot of things, one of which is human behavior. For me, I found a new hobby of hiking during the first year of the pandemic. I hiked in dozens of state parks around me during the fall and winter seasons, some of which I did not even know existed before the pandemic. I felt relieved both physically and mentally after the weekend hiking trips, and it was helpful for me to reduce the Zoom fatigue built up during work days.

Expanding the scope and visibility of ambulatory stewardship programs with novel coronavirus disease 2019 (COVID-19) therapeutics

Antimicrobial stewardship programs (ASPs) can be expanded to the outpatient setting to serve as a first line of defense against coronavirus disease 19 (COVID-19) hospitalizations and to reduce the burden on emergency departments and acute-care hospitals. Given the numerous emergency use authorizations of monoclonal antibodies and oral antivirals, ASPs possess the expertise and leadership to direct ambulatory COVID-19 initiatives and transform it into a predominantly outpatient illness. In this review, we summarize the critical role and benefits of an ASP-championed ambulatory COVID-19 therapeutics program.

Long-term outcomes of COVID-19 convalescents: An 18.5-month longitudinal study in Wuhan.

OBJECTIVES: This study aimed to describe the full scope of long-term outcomes and the ongoing pathophysiological alterations among COVID-19 survivors. METHODS: We established a longitudinal cohort of 208 COVID-19 convalescents and followed them at 3.3 (interquartile range [IQR]: 1.3, 4.4, visit 1), 9.2 (IQR: 9.0, 9.6, visit 2), and 18.5 (IQR: 18.2, 19.1, visit 3) months after infection, respectively. Serial changes in multiple physical and psychological outcomes were comprehensively characterized. We, in addition, explored the potential risk factors of SARS-CoV-2 antibody response and sequelae symptoms. RESULTS: We observed continuous improvement of sequelae symptoms, lung function, chest computed tomography (CT), 6-minute walk test, and the Borg dyspnea scale, whereas sequelae symptoms (at least one) and abnormal chest CT patterns still existed in 45.2% and about 30% of participants at 18.5 months, respectively. Anxiety and depression disorders were alleviated for the convalescents, although depression status was sustained for a longer duration. CONCLUSIONS: Most COVID-19 convalescents had an overall improved physical and psychological health status, whereas sequelae symptoms, residual lesions on lung function, exercise impairment, and mental health disorders were still observed in a small proportion of participants at 18.5 months after infection. Implementing appropriate preventive and management strategies for the ever-growing COVID-19 population is warranted.

The Effect of Collectivism on Mental Health during COVID-19: A Moderated Mediation Model.

BACKGROUND: COVID-19 is an unprecedented public health emergency of international concern and has caused people to live in constant fear and posed a significant threat to their physical and mental health. METHOD: The study constructed a moderated mediation model to examine the mediating role of emotion regulation between collectivism and mental health and the moderating role of ego identity in the context of COVID-19. A total of 459 participants were recruited to complete the survey from 30 January to 8 May 2021.The Mental Health in COVID-19 Period Scale, Collectivism Tendency Scale, ERQ, and Identity Status Scale were used for the study. RESULTS: (1) Expressive suppression played a mediating role in the relationship between collectivism and mental health; (2) The direct effect of collectivism on mental health and the path from expressive suppression to mental health were moderated by ego identity. CONCLUSION: The effect of collectivism on mental health is indirectly generated through expressive suppression and ego identity showing different patterns of regulation of mental health in different pathways, and its mechanisms and other important influences could be further explored in the future.

Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

The Development and Preliminary Application of the Chinese Version of the COVID-19 Vaccine Literacy Scale.

(1) Background: Vaccine literacy (VL) of the public is crucial to deal with anti-vaccination rhetoric. This study aims to (1) develop a Chinese COVID-19 Vaccine Literacy Scale and examine the factor structure and psychometric characteristics, and (2) explore the association between COVID-19 VL and sociodemographic characteristics and other variables; (2) Methods: An online cross-sectional survey was conducted among 362 Chinese residents from 23 May 2022 to 31 May 2022 using snowball sampling; (3) Results: Exploratory and confirmatory factor analysis indicated that the scale of 15 items, consisting of three factors, functional, interactive and critical vaccine literacy, explained 63.3% of the total variance. Cronbach's α coefficient was 0.885 for the overall scale: 0.838, 0.891, and 0.857 for three subscales, respectively. The results showed a medium level of vaccine literacy (M = 3.71, SD = 0.72) and significant differences among functional, interactive, and critical vaccine literacy (p < 0.001). The level of vaccine literacy grew with the level of education (p < 0.001) and age (p = 0.049). Men, participants who were single, or those living in rural areas had a lower level of vaccine literacy; (4) Conclusions: The Chinese COVID-19 VL Scale has adequate validity and reliability for assessing vaccine literacy among Chinese residents. A deep understanding of the factors that affect vaccine literacy is needed.

Quantifying the dynamic transmission of COVID-19 asymptomatic and symptomatic infections: Evidence from four Chinese regions

The dynamic transmission of asymptomatic and symptomatic COVID-19 infections is difficult to quantify because asymptomatic infections are not readily recognized or self-identified. To address this issue, we collected data on asymptomatic and symptomatic infections from four Chinese regions (Beijing, Dalian, Xinjiang, and Guangzhou). These data were considered reliable because the government had implemented large-scale multiple testing during the outbreak in the four regions. We modified the classical susceptible–exposure–infection–recovery model and combined it with mathematical tools to quantitatively analyze the number of infections caused by asymptomatic and symptomatic infections during dynamic transmission, respectively. The results indicated that the ratios of the total number of asymptomatic to symptomatic infections were 0.13:1, 0.48:1, 0.29:1, and 0.15:1, respectively, in the four regions. However, the ratio of the total number of infections caused by asymptomatic and symptomatic infections were 4.64:1, 6.21:1, 1.49:1, and 1.76:1, respectively. Furthermore, the present study describes the daily number of healthy people infected by symptomatic and asymptomatic transmission and the dynamic transmission process. Although there were fewer asymptomatic infections in the four aforementioned regions, their infectivity was found to be significantly higher, implying a greater need for timely screening and control of infections, particularly asymptomatic ones, to contain the spread of COVID-19.

Reconnecting the Diverse Community [From the Guest Editors]

After two years of virtual conferences, the annual flagship conference of the IEEE Robotics and Automation Society (RAS), the IEEE International Conference on Robotics and Automation (ICRA), has returned in person. When I attended ICRA in Philadelphia in May, I felt excitement in the air when people greeted each other and friends shook hands and hugged each other. It was not easy for professors, students, industry practitioners, and other attendees traveling from all around the world to be under one roof, while the COVID-19 pandemic has not fully settled into its endemic stage. With more than 4,700 in-person participants, nearly half of whom were students, this year’s conference was the largest and youngest one ever in ICRA history.

Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study

Objectives: To develop and internally validate two clinical risk scores to detect coronavirus disease 2019 (COVID-19) during local outbreaks. Methods: Medical records were extracted for a retrospective cohort of 336 suspected patients admitted to Baodi hospital between 27 January to 20 February 2020. Multivariate logistic regression was applied to develop the risk-scoring models, which were internally validated using a 5-fold cross-validation method and Hosmer-Lemeshow (H-L) tests. Results: Fifty-six cases were diagnosed from the cohort. The first model was developed based on seven significant predictors, including age, close contact with confirmed/suspected cases, same location of exposure, temperature, leukocyte counts, radiological findings of pneumonia and bilateral involvement (the mean area under the receiver operating characteristic curve [AUC]:0.88, 95% CI: 0.84–0.93). The second model had the same predictors except leukocyte and radiological findings (AUC: 0.84, 95% CI: 0.78–0.89, Z = 2.56, p = 0.01). Both were internally validated using H-L tests and showed good calibration (both p > 0.10). Conclusion: Two clinical risk scores to detect COVID-19 in local outbreaks were developed with excellent predictive performances, using commonly measured clinical variables. Further external validations in new outbreaks are warranted.

Incidence Trends of New-Onset Diabetes in Children and Adolescents Before and During the COVID-19 Pandemic: Findings From Florida.

This study examined the incidence trends of new-onset type 1 and type 2 diabetes in children and adolescents in Florida before and during the coronavirus disease 2019 (COVID-19) pandemic. In this observational descriptive cohort study, we used a validated computable phenotype to identify incident diabetes cases among individuals <18 years of age in the OneFlorida+ network of the national Patient-Centered Clinical Research Network between January 2017 and June 2021. We conducted an interrupted time series analysis based on the autoregressive integrated moving average model to compare changes in age-adjusted incidence rates of type 1 and type 2 diabetes before and after March 2020, when COVID-19 was declared a national health emergency in the U.S. The age-adjusted incidence rates of both type 1 and type 2 diabetes increased post-COVID-19 for children and adolescents. These results highlight the need for longitudinal cohort studies to examine how the pandemic might influence subsequent diabetes onset in young individuals.

Exploring the Willingness of the COVID-19 Vaccine Booster Shots in China Using the Health Belief Model: Web-Based Online Cross-Sectional Study.

(1) Objective: To explore Chinese residents' willingness to receive COVID-19 vaccine booster shots and identify predictors of the level of willingness based on the health belief model (HBM). (2) Methods: The snowball sampling method was used to distribute online questionnaires. A chi-square test was used to analyze the relationship between different variables. The causal relationship between HBM-related factors and booster vaccination intentions was explored by Structural equation modeling (SEM). (3) Results: A total of 898 complete responses were included; 64.3% had already received the booster injection. Most respondents intended to vaccinate themselves, while 16.1% were hesitant. Nearly half of the respondents chose to take the booster injection to support China's vaccination policy. Using the SEM, perceived susceptibility and perceived barriers were found to have a negative effect on booster vaccination intentions, whereas perceived benefit and cues to action positively affected booster vaccination intentions in the HBM. (4) Conclusions: Factors included in this study have different effects on the willingness to take the COVID-19 booster injections. Sociodemographic characteristics and characteristics of participants' COVID-19 vaccination have a significant effect on the willingness to receive vaccine booster shots. The HBM constructs can serve as good predictors of the acceptance of vaccine booster shots with the exception of perceived severity, which may benefit health officials in terms of conducting targeted strategies in vaccine programs.