Intentions to be Vaccinated Against COVID-19: The Role of Prosociality and Conspiracy Beliefs across 20 Countries.

Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to encourage vaccine uptake.

Increased interleukin-6 is associated with long COVID-19: a systematic review and meta-analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) can involve persistence, sequelae, and other clinical complications that last weeks to months to evolve into long COVID-19. Exploratory studies have suggested that interleukin-6 (IL-6) is related to COVID-19; however, the correlation between IL-6 and long COVID-19 is unknown. We designed a systematic review and meta-analysis to assess the relationship between IL-6 levels and long COVID-19. METHODS: Databases were systematically searched for articles with data on long COVID-19 and IL-6 levels published before September 2022. A total of 22 published studies were eligible for inclusion following the PRISMA guidelines. Analysis of data was undertaken by using Cochran's Q test and the Higgins I-squared (I2) statistic for heterogeneity. Random-effect meta-analyses were conducted to pool the IL-6 levels of long COVID-19 patients and to compare the differences in IL-6 levels among the long COVID-19, healthy, non-postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (non-PASC), and acute COVID-19 populations. The funnel plot and Egger's test were used to assess potential publication bias. Sensitivity analysis was used to test the stability of the results. RESULTS: An increase in IL-6 levels was observed after SARS-CoV-2 infection. The pooled estimate of IL-6 revealed a mean value of 20.92 pg/ml (95% CI = 9.30-32.54 pg/ml, I2 = 100%, P < 0.01) for long COVID-19 patients. The forest plot showed high levels of IL-6 for long COVID-19 compared with healthy controls (mean difference = 9.75 pg/ml, 95% CI = 5.75-13.75 pg/ml, I2 = 100%, P < 0.00001) and PASC category (mean difference = 3.32 pg/ml, 95% CI = 0.22-6.42 pg/ml, I2 = 88%, P = 0.04). The symmetry of the funnel plots was not obvious, and Egger's test showed that there was no significant small study effect in all groups. CONCLUSIONS: This study showed that increased IL-6 correlates with long COVID-19. Such an informative revelation suggests IL-6 as a basic determinant to predict long COVID-19 or at least inform on the "early stage" of long COVID-19.

Pandemic boredom: Little evidence that lockdown-related boredom affects risky public health behaviors across 116 countries.

Some public officials have expressed concern that policies mandating collective public health behaviors (e.g., national/regional "lockdown") may result in behavioral fatigue that ultimately renders such policies ineffective. Boredom, specifically, has been singled out as one potential risk factor for noncompliance. We examined whether there was empirical evidence to support this concern during the COVID-19 pandemic in a large cross-national sample of 63,336 community respondents from 116 countries. Although boredom was higher in countries with more COVID-19 cases and in countries that instituted more stringent lockdowns, such boredom did not predict longitudinal within-person decreases in social distancing behavior (or vice versa; n = 8,031) in early spring and summer of 2020. Overall, we found little evidence that changes in boredom predict individual public health behaviors (handwashing, staying home, self-quarantining, and avoiding crowds) over time, or that such behaviors had any reliable longitudinal effects on boredom itself. In summary, contrary to concerns, we found little evidence that boredom posed a public health risk during lockdown and quarantine. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study.

BACKGROUND: The effective implementation of government policies and measures for controlling the coronavirus disease 2019 (COVID-19) pandemic requires compliance from the public. This study aimed to examine cross-sectional and longitudinal associations of trust in government regarding COVID-19 control with the adoption of recommended health behaviours and prosocial behaviours, and potential determinants of trust in government during the pandemic. METHODS: This study analysed data from the PsyCorona Survey, an international project on COVID-19 that included 23 733 participants from 23 countries (representative in age and gender distributions by country) at baseline survey and 7785 participants who also completed follow-up surveys. Specification curve analysis was used to examine concurrent associations between trust in government and self-reported behaviours. We further used structural equation model to explore potential determinants of trust in government. Multilevel linear regressions were used to examine associations between baseline trust and longitudinal behavioural changes. RESULTS: Higher trust in government regarding COVID-19 control was significantly associated with higher adoption of health behaviours (handwashing, avoiding crowded space, self-quarantine) and prosocial behaviours in specification curve analyses (median standardised ß = 0.173 and 0.229, p < 0.001). Government perceived as well organised, disseminating clear messages and knowledge on COVID-19, and perceived fairness were positively associated with trust in government (standardised ß = 0.358, 0.230, 0.056, and 0.249, p < 0.01). Higher trust at baseline survey was significantly associated with lower rate of decline in health behaviours over time (p for interaction = 0.001). CONCLUSIONS: These results highlighted the importance of trust in government in the control of COVID-19.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Impact of National Pandemic Lockdowns on Perceived Threat of Immigrants: A Natural Quasi-Experiment Across 23 Countries

Xenophobia and anti-immigrant attacks rose during the COVID-19 pandemic, yet this may not be solely due to the disease threat. According to theories of frustration and scapegoating, situational obstructions and deprivation can motivate prejudice against outgroups. Using a global natural quasi-experimental design, this study tests whether the restrictiveness of national lockdowns can explain higher individual-level perceptions of immigrant threat. Data of 45,894 participants from 23 countries were analyzed. Both lockdown duration and lockdown severity were positively associated with individuals' perceived threat of immigrants. The lockdown effects were independent of objective and subjective measures of disease threat, and there was no evidence that disease threat drives people's prejudice toward immigrants. Subgroup analysis suggested the lockdown effects were reliable in Europe and the Americas, but not in Asia. These findings suggest a need to mitigate frustration and scapegoating when implementing lockdowns, and to distinguish the influence of societal restrictions from disease threat.

Why some people do not get vaccinated against COVID-19: Social-cognitive determinants of vaccination behavior.

It is puzzling that a sizeable percentage of people refuse to get vaccinated against COVID-19. This study aimed to examine social psychological factors influencing their vaccine hesitancy. This longitudinal study traced a cohort of 2663 individuals in 25 countries from the time before COVID-19 vaccines became available (March 2020) to July 2021, when vaccination was widely available. Multilevel logistic regressions were used to examine determinants of actual COVID-19 vaccination behavior by July 2021, with country-level intercept as random effect. Of the 2663 participants, 2186 (82.1%) had been vaccinated by July 2021. Participants' attitude toward COVID-19 vaccines was the strongest predictor of both vaccination intention and subsequent vaccination behavior (p < .001). Perceived risk of getting infected and perceived personal disturbance of infection were also associated with higher likelihood of getting vaccinated (p < .001). However, religiosity, right-wing political orientation, conspiracy beliefs, and low trust in government regarding COVID-19 were negative predictors of vaccination intention and behavior (p < .05). Our findings highlight the importance of attitude toward COVID-19 vaccines and also suggest that certain life-long held convictions that predate the pandemic make people distrustful of their government and likely to accept conspiracy beliefs and therefore less likely to adopt the vaccination behavior.

Prevalence, risk factors and treatments for post-COVID-19 breathlessness: a systematic review and meta-analysis.

Persistent breathlessness >28 days after acute COVID-19 infection has been identified as a highly debilitating post-COVID symptom. However, the prevalence, risk factors, mechanisms and treatments for post-COVID breathlessness remain poorly understood. We systematically searched PubMed and Embase for relevant studies published from 1 January 2020 to 1 November 2021 (PROSPERO registration number: CRD42021285733) and included 119 eligible papers. Random-effects meta-analysis of 42 872 patients with COVID-19 reported in 102 papers found an overall prevalence of post-COVID breathlessness of 26% (95% CI 23-29) when measuring the presence/absence of the symptom, and 41% (95% CI 34-48) when using Medical Research Council (MRC)/modified MRC dyspnoea scale. The pooled prevalence decreased significantly from 1-6 months to 7-12 months post-infection. Post-COVID breathlessness was more common in those with severe/critical acute infection, those who were hospitalised and females, and was less likely to be reported by patients in Asia than those in Europe or North America. Multiple pathophysiological mechanisms have been proposed (including deconditioning, restrictive/obstructive airflow limitation, systemic inflammation, impaired mental health), but the body of evidence remains inconclusive. Seven cohort studies and one randomised controlled trial suggested rehabilitation exercises may reduce post-COVID breathlessness. There is an urgent need for mechanistic research and development of interventions for the prevention and treatment of post-COVID breathlessness.

Increased Interleukin-6 is Associated with Long COVID-19: Evidence from a Systematic Review and Meta-analysis (preprint)

Background: Coronavirus disease 2019 (COVID-19) can involve persistence, sequelae, and other clinical complications that last weeks to months to evolve into long COVID-19. Exploratory studies have suggested that interleukin-6 (IL-6) is related to COVID-19; however, no correlation between IL-6 and long COVID-19 is known. We designed a systematic review and meta-analysis to assess the relationship between IL-6 levels and long COVID-19. Methods: Databases were systematically searched for articles with data on long COVID-19 and IL-6 levels published before September 2022. A total of 22 published studies were eligible for inclusion following the PRISMA guidelines. Analysis of data was undertaken by using Cochran's Q test and the Higgins I-squared (I2) statistic for heterogeneity. Random-effect meta-analyses were conducted to pool the IL-6 levels of long COVID-19 patients and to compare the differences in IL-6 levels among the long COVID-19, healthy, non-post-acute sequelae of SARS-CoV-2 infection (non-PASC), and acute COVID-19 populations. The funnel plot and Egger's test were used to assess potential publication bias. Sensitivity analysis was used to test the stability of the results. Results: An increase in IL-6 levels was observed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The pooled estimate of IL-6 revealed a mean value of 20.92 pg/ml (95% CI = 9.30 – 32.54 pg/ml, I2 = 100%, p < 0.01) for long COVID-19. The forest plot showed high levels of IL-6 for long COVID-19 compared with healthy controls (mean difference = 9.75 pg/ml, 95% CI = 5.75 – 13.75 pg/ml, I2 = 100%, p < 0.00001) and PASC category (mean difference = 3.32 pg/ml, 95% CI = 0.22 – 6.42 pg/ml, I2 = 88%, p = 0.04). The symmetry of the funnel plots was not obvious, and Egger’s test showed that there was no significant small study effect in all groups (long COVID-19 versus healthy controls, p = 0.24; long COVID-19 versus non-PASC, p = 0.31). Conclusions: This study showed that increased IL-6 correlates with long COVID-19. Such an informative revelation suggests IL-6 as a basic determinant to predict long COVID-19 or at least inform on “early stage” of long COVID-19.

The Epidemiological, Clinical Features and Outcomes of Imported Chinese COVID-19 Patients Following Inactivated Vaccines Injection.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination had been demonstrated as an effective way to reduce the risk of coronavirus disease 2019 (COVID-19), and only a few vaccines suffered from SARS-CoV-2 infection. However, limited data concerning the clinical features of these vaccines infected with SARS-CoV-2 can be identified. Methods: We retrospectively collected and analyzed epidemiological and clinical characteristics data of the imported COVID-19 cases who received Chinese inactivated vaccines abroad. Data were extracted from electronic medical records from a designated hospital in the Shaanxi Province of China between March 22 and May 17, 2021. Results: Totally, 46 confirmed SARS-CoV-2 infection patients were enrolled. The mean age was 40.5 years (range 20-61), 41 (89.1%) are male. Eighteen (39.1%) patients were from Pakistan. Fourteen (30.4%) patients had at least one comorbidity. Forty (87.0%) and 6 cases were fully vaccinated and partly vaccinated. The time interval between vaccination and infection was 88 days (IQR, 33-123), 31 (67.4%) and 15 (32.6%) were asymptomatic and symptomatic cases, respectively. Fever (3/46, 6.5%) was the most common symptom; however, none had a body temperature higher than 38.0°C, and no severe case was observed. Notably, the rate of SARS-CoV-2 shedding discontinuation at 7 days after hospitalization in asymptomatic cases was higher than symptomatic one (93.5% vs 40%, P < 0.0001). Conclusion: Individuals who received Chinese inactivated vaccines abroad remain to have the probability of being infected with SARS-CoV-2, but all the vaccines infected with SARS-CoV-2 were asymptomatic or had mild symptoms with favorable clinical outcomes.

Correction: Politicization of COVID-19 health-protective behaviors in the United States: Longitudinal and cross-national evidence.

[This corrects the article DOI: 10.1371/journal.pone.0256740.].

Studying the mixed transmission in a community with age heterogeneity: COVID-19 as a case study.

COVID-19 has been prevalent worldwide for about 2 years now and has brought unprecedented challenges to our society. Before vaccines were available, the main disease intervention strategies were non-pharmaceutical. Starting December 2020, in Ontario, Canada, vaccines were approved for administering to vulnerable individuals and gradually expanded to all individuals above the age of 12. As the vaccine coverage reached a satisfactory level among the eligible population, normal social activities resumed and schools reopened starting September 2021. However, when schools reopen for in-person learning, children under the age of 12 are unvaccinated and are at higher risks of contracting the virus. We propose an age-stratified model based on the age and vaccine eligibility of the individuals. We fit our model to the data in Ontario, Canada and obtain a good fitting result. The results show that a relaxed between-group contact rate may trigger future epidemic waves more easily than an increased within-group contact rate. An increasing mixed contact rate of the older group quickly amplifies the daily incidence numbers for both groups whereas an increasing mixed contact rate of the younger group mainly leads to future waves in the younger group alone. The results indicate the importance of accelerating vaccine rollout for younger individuals in mitigating disease spread.

Berbamine hydrochloride potently inhibits SARS-CoV-2 infection by blocking S protein-mediated membrane fusion.

COVID-19 caused by SARS-CoV-2 has posed a significant threat to global public health since its outbreak in late 2019. Although there are a few drugs approved for clinical treatment to combat SARS-CoV-2 infection currently, the severity of the ongoing global pandemic still urges the efforts to discover new antiviral compounds. As the viral spike (S) protein plays a key role in mediating virus entry, it becomes a potential target for the design of antiviral drugs against COVID-19. Here, we tested the antiviral activity of berbamine hydrochloride, a bis-benzylisoquinoline alkaloid, against SARS-CoV-2 infection. We found that berbamine hydrochloride could efficiently inhibit SARS-CoV-2 infection in different cell lines. Further experiments showed berbamine hydrochloride inhibits SARS-CoV-2 infection by targeting the viral entry into host cells. Moreover, berbamine hydrochloride and other bis-benzylisoquinoline alkaloids could potently inhibit S-mediated cell-cell fusion. Furthermore, molecular docking results implied that the berbamine hydrochloride could bind to the post fusion core of SARS-CoV-2 S2 subunit. Therefore, berbamine hydrochloride may represent a potential efficient antiviral agent against SARS-CoV-2 infection.

COVID-19 stressors and health behaviors: A multilevel longitudinal study across 86 countries.

Anxiety associated with the COVID-19 pandemic and home confinement has been associated with adverse health behaviors, such as unhealthy eating, smoking, and drinking. However, most studies have been limited by regional sampling, which precludes the examination of behavioral consequences associated with the pandemic at a global level. Further, few studies operationalized pandemic-related stressors to enable the investigation of the impact of different types of stressors on health outcomes. This study examined the association between perceived risk of COVID-19 infection and economic burden of COVID-19 with health-promoting and health-damaging behaviors using data from the PsyCorona Study: an international, longitudinal online study of psychological and behavioral correlates of COVID-19. Analyses utilized data from 7,402 participants from 86 countries across three waves of assessment between May 16 and June 13, 2020. Participants completed self-report measures of COVID-19 infection risk, COVID-19-related economic burden, physical exercise, diet quality, cigarette smoking, sleep quality, and binge drinking. Multilevel structural equation modeling analyses showed that across three time points, perceived economic burden was associated with reduced diet quality and sleep quality, as well as increased smoking. Diet quality and sleep quality were lowest among respondents who perceived high COVID-19 infection risk combined with high economic burden. Neither binge drinking nor exercise were associated with perceived COVID-19 infection risk, economic burden, or their interaction. Findings point to the value of developing interventions to address COVID-related stressors, which have an impact on health behaviors that, in turn, may influence vulnerability to COVID-19 and other health outcomes.

Predictors of adherence to public health behaviors for fighting COVID-19 derived from longitudinal data.

The present paper examines longitudinally how subjective perceptions about COVID-19, one's community, and the government predict adherence to public health measures to reduce the spread of the virus. Using an international survey (N = 3040), we test how infection risk perception, trust in the governmental response and communications about COVID-19, conspiracy beliefs, social norms on distancing, tightness of culture, and community punishment predict various containment-related attitudes and behavior. Autoregressive analyses indicate that, at the personal level, personal hygiene behavior was predicted by personal infection risk perception. At social level, social distancing behaviors such as abstaining from face-to-face contact were predicted by perceived social norms. Support for behavioral mandates was predicted by confidence in the government and cultural tightness, whereas support for anti-lockdown protests was predicted by (lower) perceived clarity of communication about the virus. Results are discussed in light of policy implications and creating effective interventions.

Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic.

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample-exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual-level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior-and some theoretically derived predictors were relatively unimportant.

Long-Term Sequelae of COVID-19: A Systematic Review and Meta-Analysis of One-Year Follow-Up Studies on Post-COVID Symptoms.

Emerging evidence has shown that COVID-19 survivors could suffer from persistent symptoms. However, it remains unclear whether these symptoms persist over the longer term. This study aimed to systematically synthesise evidence on post-COVID symptoms persisting for at least 12 months. We searched PubMed and Embase for papers reporting at least one-year follow-up results of COVID-19 survivors published by 6 November 2021. Random-effects meta-analyses were conducted to estimate pooled prevalence of specific post-COVID symptoms. Eighteen papers that reported one-year follow-up data from 8591 COVID-19 survivors were included. Fatigue/weakness (28%, 95% CI: 18-39), dyspnoea (18%, 95% CI: 13-24), arthromyalgia (26%, 95% CI: 8-44), depression (23%, 95% CI: 12-34), anxiety (22%, 95% CI: 15-29), memory loss (19%, 95% CI: 7-31), concentration difficulties (18%, 95% CI: 2-35), and insomnia (12%, 95% CI: 7-17) were the most prevalent symptoms at one-year follow-up. Existing evidence suggested that female patients and those with more severe initial illness were more likely to suffer from the sequelae after one year. This study demonstrated that a sizeable proportion of COVID-19 survivors still experience residual symptoms involving various body systems one year later. There is an urgent need for elucidating the pathophysiologic mechanisms and developing and testing targeted interventions for long-COVID patients.

Hospital sewage treatment facilities witness the fighting against the COVID-19 pandemic.

Real-time evaluation of the fighting activities during a sudden unknown disaster like the COVID-19 pandemic is a critical challenge for control. This study demonstrates that the temporal variations of effluents from hospital sewage treatment facilities can be used as an effective indicator for such evaluation. Taking a typical infection-suffering city in China as an example, we found that there was an obvious decrease in effluent ammonia and COD concentrations in line with the start of city lockdown, and its temporal variations well indicated the major events happened during the pandemic control. Notably, the lagging period between the change point of effluent residual chlorine and the change points of COD and ammonia concentration coincided with a period in which there was a deficiency in local medical resources. In addition, the diurnal behavior of effluents from designated hospitals has varied significantly at different stages of the pandemic development. The effluent ammonia peaks shifted from daytime to nighttime after the outbreak of the COVID-19 pandemic, suggesting a high workload of the designated hospitals in fighting the rapidly emerging pandemic. This work well demonstrates the necessary for data integration at the wastewater-medical service nexus and highlights an unusual role of the effluents from hospital sewage treatment facilities in revealing the status of fighting the pandemic, which helps to control the pandemic.

A new screening system for entry inhibitors based on cell-to-cell transmitted syncytia formation mediated by self-propagating hybrid VEEV-SARS-CoV-2 replicon.

The extremely high transmission rate of SARS-CoV-2 and severe cases of COVID-19 pose the two critical challenges in the battle against COVID-19. Increasing evidence has shown that the viral spike (S) protein-driven syncytia may be responsible for these two events. Intensive attention has thus been devoted to seeking S-guided syncytium inhibitors. However, the current screening campaigns mainly rely on either live virus-based or plasmid-based method, which are always greatly limited by the shortage of high-level biosafety BSL-3 facilities or too much labour-intensive work. Here, we constructed a new hybrid VEEV-SARS-CoV-2-S-eGFP reporter vector through replacement of the structural genes of Venezuelan equine encephalitis virus (VEEV) with the S protein of SARS-CoV-2 as the single structural protein. VEEV-SARS-CoV-2-S-eGFP can propagate steadily through cell-to-cell transmission pathway in S- and ACE2-dependent manner, forming GFP positive syncytia. In addition, a significant dose-dependent decay in GFP signals was observed in VEEV-SARS-CoV-2-S-eGFP replicating cells upon treatment with SARS-CoV-2 antiserum or entry inhibitors, providing further evidence that VEEV-SARS-CoV-2-S-eGFP system is highly sensitive to characterize the anti-syncytium-formation activity of antiviral agents. More importantly, the assay is able to be performed in a BSL-2 laboratory without manipulation of live SARS-CoV-2. Taken together, our work establishes a more convenient and efficient VEEV-SARS-CoV-2-S-eGFP replicating cells-based method for rapid screening of inhibitors blocking syncytium formation.