Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa

Recent approaches in computational modelling for controlling pathogen threats

In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR). Many mechanisms of AMR are not well understood. As a result, it is hard to measure the current incidence of AMR, predict the future incidence, and design strategies to preserve existing antibiotic effectiveness. Next, we look at how to choose the finite number of bacterial strains that can be included in a vaccine. To do this, we need to understand what happens to vaccine and non-vaccine strains after vaccination programmes. Finally, we look at within-host modelling of antibody dynamics. The SARS-CoV-2 pandemic produced huge amounts of antibody data, prompting improvements in this area of modelling. We finish by discussing the challenges that persist in understanding these complex biological systems.

SARS-CoV-2 correlates of protection from infection against variants of concern

Serum neutralizing antibodies (nAbs) induced by vaccination have been linked to protection against symptomatic and severe coronavirus disease 2019. However, much less is known about the efficacy of nAbs in preventing the acquisition of infection, especially in the context of natural immunity and against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune-escape variants. Here we conducted mediation analysis to assess serum nAbs induced by prior SARS-CoV-2 infections as potential correlates of protection against Delta and Omicron infections, in rural and urban household cohorts in South Africa. We find that, in the Delta wave, D614G nAbs mediate 37% (95% confidence interval: 34-40%) of the total protection against infection conferred by prior exposure to SARS-CoV-2, and that protection decreases with waning immunity. In contrast, Omicron BA.1 nAbs mediate 11% (95% confidence interval: 9-12%) of the total protection against Omicron BA.1 or BA.2 infections, due to Omicron's neutralization escape. These findings underscore that correlates of protection mediated through nAbs are variant specific, and that boosting of nAbs against circulating variants might restore or confer immune protection lost due to nAb waning and/or immune escape. However, the majority of immune protection against SARS-CoV-2 conferred by natural infection cannot be fully explained by serum nAbs alone. Measuring these and other immune markers including T cell responses, both in the serum and in other compartments such as the nasal mucosa, may be required to comprehensively understand and predict immune protection against SARS-CoV-2.

Infectious disease surveillance needs for the United States: lessons from Covid-19

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID

BACKGROUND

Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection.

METHODS

We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan-Meier curves to better understand COVID-19 reinfections.

RESULTS

Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer's V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection.

CONCLUSIONS

In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections.

Incursion of SARS-CoV-2 BA.2.86.1 variant into Israel: National-scale wastewater surveillance using a novel quantitative real-time PCR assay

The emergence of the SARS-CoV-2 variant BA.2.86.1 raised a considerable concern, due to the large number of potentially virulent mutations. In this study, we developed a novel assay that specifically detects variant BA.2.86.1, and used it to screen environmental samples from wastewater treatment sites across Israel. By using a multiplex assay that included a general SARS-CoV-2 reaction, together with the BA.2.86.1-specific reaction and a control reaction, we quantified the absolute number of viral copies in each sample and its relative abundance, compared with the total copy number of circulating SARS-CoV-2. Evaluation of the new reactions showed that they are both sensitive and specific, detecting down to four copies per reaction, and maintain specificity in the presence of Omicron variants BA.1, 2 and 4 RNA. Examination of 279 samples from 30 wastewater collection sites during August-September 2023 showed that 35 samples (12.5 %) were positive, from 18 sites. Quantitative analysis of the samples showed that the relative abundance of variant BA.2.86.1 with respect to the total viral load of SARS-CoV-2 was very low and consisted between 0.01 % and 0.6 % of the total SARS-CoV-2 circulation. This study demonstrates the importance of combining wastewater surveillance with the development of specialized diagnostic assays, when clinical testing is insufficient. This approach may be useful for timely response by public health authorities in future outbreaks.

SARS-CoV-2-associated lymphopenia: possible mechanisms and the role of CD147

T lymphocytes play a primary role in the adaptive antiviral immunity. Both lymphocytosis and lymphopenia were found to be associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While lymphocytosis indicates an active anti-viral response, lymphopenia is a sign of poor prognosis. T-cells, in essence, rarely express ACE2 receptors, making the cause of cell depletion enigmatic. Moreover, emerging strains posed an immunological challenge, potentially alarming for the next pandemic. Herein, we review how possible indirect and direct key mechanisms could contribute to SARS-CoV-2-associated-lymphopenia. The fundamental mechanism is the inflammatory cytokine storm elicited by viral infection, which alters the host cell metabolism into a more acidic state. This "hyperlactic acidemia" together with the cytokine storm suppresses T-cell proliferation and triggers intrinsic/extrinsic apoptosis. SARS-CoV-2 infection also results in a shift from steady-state hematopoiesis to stress hematopoiesis. Even with low ACE2 expression, the presence of cholesterol-rich lipid rafts on activated T-cells may enhance viral entry and syncytia formation. Finally, direct viral infection of lymphocytes may indicate the participation of other receptors or auxiliary proteins on T-cells, that can work alone or in concert with other mechanisms. Therefore, we address the role of CD147-a novel route-for SARS-CoV-2 and its new variants. CD147 is not only expressed on T-cells, but it also interacts with other co-partners to orchestrate various biological processes. Given these features, CD147 is an appealing candidate for viral pathogenicity. Understanding the molecular and cellular mechanisms behind SARS-CoV-2-associated-lymphopenia will aid in the discovery of potential therapeutic targets to improve the resilience of our immune system against this rapidly evolving virus.

SARS-CoV-2 evolution has increased resistance to monoclonal antibodies and first-generation COVID-19 vaccines: Is there a future therapeutic role for soluble ACE2 receptors for COVID-19?

COVID-19 has caused calamitous health, economic and societal consequences. Although several COVID-19 vaccines have received full authorization for use, global deployment has faced political, financial and logistical challenges. The efficacy of first-generation COVID-19 vaccines is waning and breakthrough infections are allowing ongoing transmission and evolution of SARS-CoV-2. Furthermore, COVID-19 vaccine efficacy relies on a functional immune system. Despite receiving three primary doses and three or more heterologous boosters, some immunocompromised patients may not be adequately protected by COVID-19 vaccines and remain vulnerable to severe disease. The evolution of new SARS-CoV-2 variants has also resulted in the rapid obsolescence of monoclonal antibodies. Convalescent plasma from COVID-19 survivors has produced inconsistent results. New drugs such as Paxlovid (nirmatrelvir/ritonavir) are beyond the reach of low- and middle-income countries. With widespread use of Paxlovid, it is likely nirmatrelvir-resistant clades of SARS-CoV-2 will emerge in the future. There is thus an urgent need for new effective anti-SARS-CoV-2 treatments. The in vitro efficacy of soluble ACE2 against multiple SARS-CoV-2 variants including omicron (B.1.1.529), was recently described using a competitive ELISA assay as a surrogate marker for virus neutralization. This indicates soluble wild-type ACE2 receptors are likely to be resistant to viral evolution. Nasal and inhaled treatment with soluble ACE2 receptors has abrogated severe disease in animal models of COVID-19. There is an urgent need for clinical trials of this new class of antiviral therapeutics, which could complement vaccines and Paxlovid.

Differential epitope prediction across diverse circulating variants of SARS-COV-2 in Brazil

COVID-19, caused by the SARS-COV-2 virus, induces numerous immunological reactions linked to the severity of the clinical condition of those infected. The surface Spike protein (S protein) present in Sars-CoV-2 is responsible for the infection of host cells. This protein presents a high rate of mutations, which can increase virus transmissibility, infectivity, and immune evasion. Therefore, we propose to evaluate, using immunoinformatic techniques, the predicted epitopes for the S protein of seven variants of Sars-CoV-2. MHC class I and II epitopes were predicted and further assessed for their immunogenicity, interferon-gamma (IFN-γ) inducing capacity, and antigenicity. For B cells, linear and structural epitopes were predicted. For class I MHC epitopes, 40 epitopes were found for the clades of Wuhan, Clade 2, Clade 3, and 20AEU.1, Gamma, and Delta, in addition to 38 epitopes for Alpha and 44 for Omicron. For MHC II, there were differentially predicted epitopes for all variants and eight equally predicted epitopes. These were evaluated for differences in the MHC II alleles to which they would bind. Regarding B cell epitopes, 16 were found in the Wuhan variant, 14 in 22AEU.1 and in Clade 3, 15 in Clade 2, 11 in Alpha and Delta, 13 in Gamma, and 9 in Omicron. When compared, there was a reduction in the number of predicted epitopes concerning the Spike protein, mainly in the Delta and Omicron variants. These findings corroborate the need for updates seen today in bivalent mRNA vaccines against COVID-19 to promote a targeted immune response to the main circulating variant, Omicron, leading to more robust protection against this virus and avoiding cases of reinfection. When analyzing the specific epitopes for the RBD region of the spike protein, the Omicron variant did not present a B lymphocyte epitope from position 390, whereas the epitope at position 493 for MHC was predicted only for the Alpha, Gamma, and Omicron variants.

Protective effectiveness of previous infection against subsequent SARS-Cov-2 infection: systematic review and meta-analysis

Background

The protective effectiveness provided by naturally acquired immunity against SARS-CoV-2 reinfection remain controversial.

Objective

To systematically evaluate the protective effect of natural immunity against subsequent SARS-CoV-2 infection with different variants.

Methods

We searched for related studies published in seven databases before March 5, 2023. Eligible studies included in the analysis reported the risk of subsequent infection for groups with or without a prior SARS-CoV-2 infection. The primary outcome was the overall pooled incidence rate ratio (IRR) of SARS-CoV-2 reinfection/infection between the two groups. We also focused on the protective effectiveness of natural immunity against reinfection/infection with different SARS-CoV-2 variants. We used a random-effects model to pool the data, and obtained the bias-adjusted results using the trim-and-fill method. Meta-regression and subgroup analyses were conducted to explore the sources of heterogeneity. Sensitivity analysis was performed by excluding included studies one by one to evaluate the stability of the results.

Results

We identified 40 eligible articles including more than 20 million individuals without the history of SARS-CoV-2 vaccination. The bias-adjusted efficacy of naturally acquired antibodies against reinfection was estimated at 65% (pooled IRR = 0.35, 95% CI = 0.26-0.47), with higher efficacy against symptomatic COVID-19 cases (pooled IRR = 0.15, 95% CI = 0.08-0.26) than asymptomatic infection (pooled IRR = 0.40, 95% CI = 0.29-0.54). Meta-regression revealed that SARS-CoV-2 variant was a statistically significant effect modifier, which explaining 46.40% of the variation in IRRs. For different SARS-CoV-2 variant, the pooled IRRs for the Alpha (pooled IRR = 0.11, 95% CI = 0.06-0.19), Delta (pooled IRR = 0.19, 95% CI = 0.15-0.24) and Omicron (pooled IRR = 0.61, 95% CI = 0.42-0.87) variant were higher and higher. In other subgroup analyses, the pooled IRRs of SARS-CoV-2 infection were statistically various in different countries, publication year and the inclusion end time of population, with a significant difference (p = 0.02, p < 0.010 and p < 0.010), respectively. The risk of subsequent infection in the seropositive population appeared to increase slowly over time. Despite the heterogeneity in included studies, sensitivity analyses showed stable results.

Conclusion

Previous SARS-CoV-2 infection provides protection against pre-omicron reinfection, but less against omicron. Ongoing viral mutation requires attention and prevention strategies, such as vaccine catch-up, in conjunction with multiple factors.

Estimating time-varying epidemiological parameters and underreporting of Covid-19 cases in Brazil using a mathematical model with fuzzy transitions between epidemic periods

Our study conducts a comprehensive analysis of the Covid-19 pandemic in Brazil, spanning five waves over three years. We employed a novel Susceptible-Infected-Recovered-Dead-Susceptible (SIRDS) model with a fuzzy transition between epidemic periods to estimate time-varying parameters and evaluate case underreporting. The initial basic reproduction number (R0) is identified at 2.44 (95% Confidence Interval (CI): 2.42-2.46), decreasing to 1.00 (95% CI: 0.99-1.01) during the first wave. The model estimates an underreporting factor of 12.9 (95% CI: 12.5-13.2) more infections than officially reported by Brazilian health authorities, with an increasing factor of 5.8 (95% CI: 5.2-6.4), 12.9 (95% CI: 12.5-13.3), and 16.8 (95% CI: 15.8-17.5) in 2020, 2021, and 2022 respectively. Additionally, the Infection Fatality Rate (IFR) is initially 0.88% (95% CI: 0.81%-0.94%) during the initial phase but consistently reduces across subsequent outbreaks, reaching its lowest value of 0.018% (95% CI: 0.011-0.033) in the last outbreak. Regarding the immunity period, the observed uncertainty and low sensitivity indicate that inferring this parameter is particularly challenging. Brazil successfully reduced R0 during the first wave, coinciding with decreased human mobility. Ineffective public health measures during the second wave resulted in the highest mortality rates within the studied period. We attribute lower mortality rates in 2022 to increased vaccination coverage and the lower lethality of the Omicron variant. We demonstrate the model generalization by its application to other countries. Comparative analyses with serological research further validate the accuracy of the model. In forecasting analysis, our model provides reasonable outbreak predictions. In conclusion, our study provides a nuanced understanding of the Covid-19 pandemic in Brazil, employing a novel epidemiological model. The findings contribute to the broader discourse on pandemic dynamics, underreporting, and the effectiveness of health interventions.

Predictive biomarkers of COVID-19 prognosis identified in Bangladesh patients and validated in Japanese cohorts

Despite high vaccination rates globally, countries are still grappling with new COVID infections, and patients diagnosed as mild dying at home during outpatient treatment. Hence, this study aim to identify, then validate, biomarkers that could predict if newly infected COVID-19 patients would subsequently require hospitalization or could recover safely with medication as outpatients. Serum cytokine/chemokine data from 129 COVID-19 patients within 7 days after the onset of symptoms in Bangladesh were used as training data. The majority of patients were infected with the Omicron variant and over 88% were vaccinated. Patients were divided into those with mild symptoms who recovered, and those who deteriorated to moderate or severe illness. Using the Lasso method, 15 predictive markers were identified and used to classify patients into these two groups. The biomarkers were then validated in a cohort of 194 Covid patients in Japan with a predictive accuracy that exceeded 80% for patients infected with Delta and Omicron variants, and 70% for Wuhan and Alpha variants. In an environment of widespread vaccination, these biomarkers could help medical practitioners determine if newly infected COVID-19 patients will improve and can be managed on an out-patient basis, or if they will deteriorate and require hospitalization.

Projecting the future impact of emerging SARS-CoV-2 variants under uncertainty: Modeling the initial Omicron outbreak

Over the past several years, the emergence of novel SARS-CoV-2 variants has led to multiple waves of increased COVID-19 incidence. When the Omicron variant emerged, there was considerable concern about its potential impact in the winter of 2021-2022 due to its increased fitness. However, there was also considerable uncertainty regarding its likely impact due to questions about its relative transmissibility, severity, and degree of immune escape. We sought to evaluate the ability of an agent-based model to forecast incidence in the context of this emerging pathogen variant. To project COVID-19 cases and deaths in Indiana, we calibrated our model to COVID-19 hospitalizations, deaths, and test-positivity rates through November 2021, and then projected COVID-19 incidence through April 2022 under four different scenarios that covered the plausible ranges of Omicron's severity, transmissibility, and degree of immune escape. Our initial projections from December 2021 through March 2022 indicated that under a pessimistic scenario with high disease severity, the peak in weekly COVID-19 deaths in Indiana would be larger than the previous peak in December 2020. However, retrospective analyses indicate that Omicron's severity was closer to the optimistic scenario, and even though cases and hospitalizations reached a new peak, fewer deaths occurred than during the previous peak. According to our results, Omicron's rapid spread was consistent with a combination of higher transmissibility and immune escape relative to earlier variants. Our updated projections starting in January 2022 accurately predicted that cases would peak in mid-January and decline rapidly over the next several months. The performance of our projections shows that following the emergence of a new pathogen variant, models can help quantify the potential range of outbreak magnitudes and trajectories. Agent-based models are particularly useful in these scenarios because they can efficiently track individual vaccination and infection histories with multiple variants with varying degrees of cross-protection.

Analysis of SARS-CoV-2 omicron mutations that emerged during long-term replication in a lung cancer xenograft mouse model

SARS-CoV-2 Omicron has the largest number of mutations among all the known SARS-CoV-2 variants. The presence of these mutations might explain why Omicron is more infectious and vaccines have lower efficacy to Omicron than other variants, despite lower virulence of Omicron. We recently established a long-term in vivo replication model by infecting Calu-3 xenograft tumors in immunodeficient mice with parental SARS-CoV-2 and found that various mutations occurred majorly in the spike protein during extended replication. To investigate whether there are differences in the spectrum and frequency of mutations between parental SARS-CoV-2 and Omicron, we here applied this model to Omicron. At 30 days after infection, we found that the virus was present at high titers in the tumor tissues and had developed several rare sporadic mutations, mainly in ORF1ab with additional minor spike protein mutations. Many of the mutant isolates had higher replicative activity in Calu-3 cells compared with the original SARS-CoV-2 Omicron virus, suggesting that the novel mutations contributed to increased viral replication. Serial propagation of SARS-CoV-2 Omicron in cultured Calu-3 cells resulted in several rare sporadic mutations in various viral proteins with no mutations in the spike protein. Therefore, the genome of SARS-CoV-2 Omicron seems largely stable compared with that of the parental SARS-CoV-2 during extended replication in Calu-3 cells and xenograft model. The sporadic mutations and modified growth properties observed in Omicron might explain the emergence of Omicron sublineages. However, we cannot exclude the possibility of some differences in natural infection.

flepiMoP: The evolution of a flexible infectious disease modeling pipeline during the COVID-19 pandemic

The COVID-19 pandemic led to an unprecedented demand for projections of disease burden and healthcare utilization under scenarios ranging from unmitigated spread to strict social distancing policies. In response, members of the Johns Hopkins Infectious Disease Dynamics Group developed flepiMoP (formerly called the COVID Scenario Modeling Pipeline), a comprehensive open-source software pipeline designed for creating and simulating compartmental models of infectious disease transmission and inferring parameters through these models. The framework has been used extensively to produce short-term forecasts and longer-term scenario projections of COVID-19 at the state and county level in the US, for COVID-19 in other countries at various geographic scales, and more recently for seasonal influenza. In this paper, we highlight how the flepiMoP has evolved throughout the COVID-19 pandemic to address changing epidemiological dynamics, new interventions, and shifts in policy-relevant model outputs. As the framework has reached a mature state, we provide a detailed overview of flepiMoP's key features and remaining limitations, thereby distributing flepiMoP and its documentation as a flexible and powerful tool for researchers and public health professionals to rapidly build and deploy large-scale complex infectious disease models for any pathogen and demographic setup.

Fatality Rates After Infection With the Omicron Variant (B.1.1.529): How Deadly has it been? A Systematic Review and Meta-Analysis

Background

Since late 2019, the global community has been gripped by the uncertainty surrounding the SARS-CoV-2 pandemic. In November 2021, the emergence of the Omicron variant in South Africa added a new dimension. This study aims to assess the disease's severity and determine the extent to which vaccinations contribute to reducing mortality rates.

Methods

A systematic review and meta-analysis of the epidemiological implications of the omicron variant of SARS-CoV-2 were performed, incorporating an analysis of articles from November 2021that address mortality rates.

Results

The analysis incorporated data from 3,214,869 patients infected with omicron, as presented in 270 articles. A total of 6,782 deaths from the virus were recorded (0.21%). In the analysed articles, the pooled mortality rate was 0.003 and the pooled in-house mortality rate was 0.036. Vaccination is an effective step in preventing death (odds ratio: 0.391, p < 0.01).

Conclusion

The mortality rates for the omicron variant are lower than for the preceding delta variant. mRNA vaccination affords secure and effective protection against severe disease and death from omicron.

Clinical characteristics and prognostic factors of COVID-19 infection among cancer patients during the December 2022 - February 2023 Omicron variant outbreak

Objective

To analyze the clinical characteristics and prognostic impacts of SARS-CoV-2 Omicron infection among cancer inpatients during the December 2022 - February 2023 surge, in order to provide scientific evidence for clinical treatment and prevention and control measures.

Methods

A retrospective analysis was conducted on the clinical features, prognosis, and vaccination status of cancer in-patients infected with the Omicron variant during the COVID-19 pandemic of December 2022 - February 2023.

Results

A total of 137 cancer inpatients were included in the study, with a median age of 61 years, and 75 patients (54.74%) were male. The main symptoms were cough (69 cases, 50.36%), expectoration (60 cases, 43.80%), and fever (53 cases, 39.69%). Chest CT examination revealed bilateral pneumonia in 47 cases (34.31%, 47/137) and pleural effusion in 24 cases (17.52%, 24/137). Among the cancer patients, 116 cases (84.67%, 116/137) had solid tumors, and 21 cases (15.33%, 21/137) had hematologic malignancies, with the main types being breast cancer (25 cases, 18.25%) and lung cancer (24 cases, 17.52%). Among the cancer patients, 46 cases (33.58%) were asymptomatic, 81 cases (59.12%) had mild disease, 10 cases (7.30%) had severe infection, and 8 cases (5.84%) died. A total of 91 patients (66.42%) had been vaccinated, with 58 patients (42.34%) receiving three doses. Multivariate analysis showed that cerebral infarction and hypoproteinemia were risk factors for death from COVID-19 infection.

Conclusion

Cancer patients infected with SARS-CoV-2 Omicron typically exhibit mild disease manifestations, but some cancer patients infected with the Omicron variant might progress to severe illness, and even death, necessitating close monitoring and attention during the early stages of infection. Additionally, the presence of cerebral infarction and hypoproteinemia significantly increases the risk of death.

Comparative safety profile of bivalent and original COVID-19 mRNA vaccines regarding myocarditis/pericarditis: A pharmacovigilance study

OBJECTIVES

Bivalent COVID-19 mRNA vaccines, which contain two different components, were authorized to provide protection against both the original strain of SARS-CoV-2 and the Omicron variant as a measure to address the COVID-19 pandemic. Concerns regarding the risk of myocarditis/pericarditis associated with bivalent vaccination have been raised due to the observed superior neutralizing antibody responses. This study aimed to investigate the risk of myocarditis/pericarditis following bivalent COVID-19 mRNA vaccination compared to monovalent vaccination.

METHODS

The CDC COVID Data Tracker and the Vaccines Adverse Event Reporting System (VAERS) were analyzed between December 13, 2020 to March 8, 2023. Reporting rates were determined by dividing the number of myocarditis/pericarditis cases by the total number of vaccine doses administered. Disproportionality patterns regarding myocarditis/pericarditis were evaluated for various COVID-19 mRNA vaccinations using reporting odds ratios (RORs).

RESULTS

The reporting rate for myocarditis/pericarditis following original monovalent COVID-19 mRNA vaccination was 6.91 (95 % confidence interval [95 %CI] 6.71-7.12) per million doses, while the reporting rate for bivalent vaccination was significantly lower (1.24, 95%CI 0.96-1.58). Disproportionality analysis revealed a higher reporting of myocarditis/pericarditis following original vaccination with a ROR of 2.21 (95 %CI 2.00-2.43), while bivalent COVID-19 mRNA vaccination was associated with fewer reports of myocarditis/pericarditis (ROR 0.57, 95 %CI 0.45-0.72). Sub-analyses based on symptoms, sex, age and manufacturer further supported these findings.

CONCLUSION

This population-based study provides evidence that bivalent COVID-19 mRNA vaccination is not associated with risk of myocarditis/pericarditis. These findings provide important insights into the safety profile of bivalent COVID-19 mRNA vaccines and support their continued use as updated boosters.

Development of a colloidal gold-based immunochromatographic assay for rapid detection of nasal mucosal secretory IgA against SARS-CoV-2

Introduction

Infection with SARS-CoV-2 begins in the upper respiratory tract and can trigger the production of mucosal spike-specific secretory IgA (sIgA), which provides protection against reinfection. It has been recognized that individuals with high level of nasal spike-specific IgA have a lower risk of reinfection. However, mucosal spike-specific sIgA wanes over time, and different individuals may have various level of spike-specific sIgA and descending kinetics, leading to individual differences in susceptibility to reinfection. A method for detecting spike-specific sIgA in the nasal passage would be valuable for predicting the risk of reinfection so that people at risk can have better preparedness.

Methods

In this study, we describe the development of a colloidal gold-based immunochromatographic (ICT) strip for detecting SARS-CoV-2 Omicron spike-specific sIgA in nasal mucosal lining fluids (NMLFs).

Results

The ICT strip was designed to detect 0.125 μg or more spike-specific sIgA in 80 μL of NMLFs collected using a nasal swab. Purified nasal sIgA samples from individuals who recently recovered from an Omicron BA.5 infection were used to demonstrate that this ICT strip can specifically detect spike-specific sIgA. The signal levels positively correlated with neutralizing activities against XBB. Subsequent analysis revealed that people with low or undetectable levels of spike-specific sIgA in the nasal passage were more susceptible to SARS-CoV-2 reinfection.

Conclusions

This nasal spike-specific sIgA ICT strip provides a non-invasive, rapid, and convenient method to assess the risk of reinfection for achieving precision preparedness.

Infection with COVID-19 Complicated by Sinus Arrest

As a respiratory tract-transmitted disease, coronavirus disease 2019 (COVID-19) exerts a profound immune injury effect, leading not only to pulmonary impairment but also to cardiac complications. We present a case of a 79-year-old woman, who had previously contracted COVID-19 and subsequently developed sinus arrest (SA) following her second infection. The longest asystole time detected by Holter monitoring was 7.2 seconds. Although the patient met criteria for permanent pacemaker implantation, her family declined this intervention and conservative management was pursued instead. However, after a period of observation, the patient's SA resolved. The present case study describes a patient who experienced SA upon reinfection with COVID-19, which was not present during the initial infection. It emphasizes the impact of COVID-19 on cardiac health, particularly its potential to induce arrhythmias. In addition, it is worth noting that the arrhythmia induced by a COVID-19 infection may show reversibility, suggesting that a permanent pacemaker might not be the priority option if further pacing therapy is being considered.

An Omicron-specific, self-amplifying mRNA booster vaccine for COVID-19: a phase 2/3 randomized trial

Here we conducted a multicenter open-label, randomized phase 2 and 3 study to assess the safety and immunogenicity of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron-specific (BA.1/B.1.1.529), monovalent, thermostable, self-amplifying mRNA vaccine, GEMCOVAC-OM, when administered intradermally as a booster in healthy adults who had received two doses of BBV152 or ChAdOx1 nCoV-19. GEMCOVAC-OM was well tolerated with no related serious adverse events in both phase 2 and phase 3. In phase 2, the safety and immunogenicity of GEMCOVAC-OM was compared with our prototype mRNA vaccine GEMCOVAC-19 (D614G variant-specific) in 140 participants. At day 29 after vaccination, there was a significant rise in anti-spike (BA.1) IgG antibodies with GEMCOVAC-OM (P < 0.0001) and GEMCOVAC-19 (P < 0.0001). However, the IgG titers (primary endpoint) and seroconversion were higher with GEMCOVAC-OM (P < 0.0001). In phase 3, GEMCOVAC-OM was compared with ChAdOx1 nCoV-19 in 3,140 participants (safety cohort), which included an immunogenicity cohort of 420 participants. At day 29, neutralizing antibody titers against the BA.1 variant of SARS-CoV-2 were significantly higher than baseline in the GEMCOVAC-OM arm (P < 0.0001), but not in the ChAdOx1 nCoV-19 arm (P = 0.1490). GEMCOVAC-OM was noninferior (primary endpoint) and superior to ChAdOx1 nCoV-19 in terms of neutralizing antibody titers and seroconversion rate (lower bound 95% confidence interval of least square geometric mean ratio >1 and difference in seroconversion >0% for superiority). At day 29, anti-spike IgG antibodies and seroconversion (secondary endpoints) were significantly higher with GEMCOVAC-OM (P < 0.0001). These results demonstrate that GEMCOVAC-OM is safe and boosts immune responses against the B.1.1.529 variant. Clinical Trial Registry India identifier: CTRI/2022/10/046475 .

SARS-CoV-2 Transmission in Alberta, British Columbia, and Ontario, Canada, January 2020-January 2022

We estimated COVID-19 transmission potential and case burden by variant type in Alberta, British Columbia, and Ontario, Canada, during January 23, 2020-January 27, 2022; we also estimated the effectiveness of public health interventions to reduce transmission. We estimated time-varying reproduction number (Rt) over 7-day sliding windows and nonoverlapping time-windows determined by timing of policy changes. We calculated incidence rate ratios (IRRs) for each variant and compared rates to determine differences in burden among provinces. Rt corresponding with emergence of the Delta variant increased in all 3 provinces; British Columbia had the largest increase, 43.85% (95% credible interval [CrI] 40.71%-46.84%). Across the study period, IRR was highest for Omicron (8.74 [95% CrI 8.71-8.77]) and burden highest in Alberta (IRR 1.80 [95% CrI 1.79-1.81]). Initiating public health interventions was associated with lower Rt and relaxing restrictions and emergence of new variants associated with increases in Rt.

Investigation of epidemiological and clinical characteristics of people infected with SARS-CoV-2 during the second pandemic of COVID-19 in Chengdu, China

Objective

This study investigated the epidemiological and clinical characteristics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients during the second pandemic of COVID-19 (coronavirus disease of 2019) in Chengdu, China. Furthermore, the differences between first infection and re-infection cases were also compared and analyzed to provide evidence for better prevention and control of SARS-CoV-2 re-infection.

Methods

An anonymous questionnaire survey was conducted using an online platform (wjx.cn) between May 20, 2023 to September 12, 2023.

Results

This investigation included 62.94% females and 32.97% of them were 18-30 years old. Furthermore, 7.19-17.18% of the participants either did not receive vaccination at all or only received full vaccination, respectively. Moreover, 577 (57.64%) participants were exposed to cluster infection. The clinical manifestations of these patients were mainly mild to moderate; 78.18% of participants had a fever for 1-3 days, while 37.84% indicated a full course of disease for 4-6 days. In addition, 40.66% of the participants had re-infection and 72.97% indicated their first infection approximately five months before. The clinical symptoms of the first SARS-CoV-2 infection were moderate to severe, while re-infection indicated mild to moderate symptoms (the severity of symptoms other than diarrhea and conjunctival congestion had statistically significant differences) (p < 0.05). Moreover, 70.53 and 59.21% of first and re-infection cases had fever durations of 3-5 and 0-2 days, respectively. Whereas 47.91 and 46.40% of first and re-infection cases had a disease course of 7-9 and 4-6 days.

Conclusion

The SARS-CoV-2 infected individuals in Chengdu, China, during the second pandemic of COVID-19 had mild clinical symptoms and a short course of disease. Furthermore, compared with the first infection, re-infection cases had mild symptoms, low incidences of complications, short fever duration, and course of disease.

Prevalence of SARS-CoV-2-specific antibodies in a sample of the Lithuanian population-based study in Spring 2023

Objectives

Despite positive trends in SARS-CoV-2 epidemiology, seroprevalence surveys remain an important tool for estimating the magnitude of the COVID-19 pandemic. This study aimed to investigate the prevalence of IgG antibodies against SARS-CoV-2 nucleocapsid (N) and spike (S) proteins in a sample of the Lithuanian population (N = 517) and evaluate how the pattern of seropositivity correlates with the levels of SARS-CoV-2 infection and vaccination.

Methods

Study participants (aged 18-88 years) filled in the questionnaire self-reporting their demographic-social variables, health status, and SARS-CoV-2-related status. The anti-S and anti-N IgG levels were estimated using a microarray ELISA test.

Results

After several pandemic waves and vaccination campaign, the seroprevalence of SARS-CoV-2-specific IgG in the analyzed sample was 97.87 % by March-May 2023. We determined the 96.91 % prevalence of anti-S and 58.03 % prevalence of anti-N IgG. The majority of study participants (71.18 %) had hybrid immunity induced by vaccination and SARS-CoV-2 infection. 20.3 % of study participants were anti-N IgG positive without reporting any previous symptoms or a positive SARS-CoV-2 test. A decline of anti-N IgG positivity within 9 months after infection was observed.

Conclusions

This study demonstrates high total seroprevalence in March-May 2023 in all age groups indicating a widely established humoral immunity against SARS-CoV-2 in Lithuania.

Wide Real-Life Data Support Reduced Sensitivity of Antigen Tests for Omicron SARS-CoV-2 Infections

With the continuous spread of new SARS-CoV-2 variants of concern (VOCs), the monitoring of diagnostic test performances is mandatory. We evaluated the changes in antigen diagnostic tests' (ADTs) accuracy along the Delta to Omicron VOCs transition, exploring the N protein mutations possibly affecting ADT sensitivity and assessing the best sampling site for the diagnosis of Omicron infections. In total, 5175 subjects were enrolled from 1 October 2021 to 15 July 2022. The inclusion criteria were SARS-CoV-2 ADT combined with a same-day RT-PCR swab test. For the sampling site analysis, 61 patients were prospectively recruited during the Omicron period for nasal and oral swab analyses by RT-PCR. Next-Generation Sequencing data were obtained to evaluate the different sublineages. Using RT-PCR as a reference, 387 subjects resulted in becoming infected and the overall sensitivity of the ADT decreased from 63% in the Delta period to 33% in the Omicron period. This decrease was highly statistically significant (p < 0.001), and no decrease in viral load was detected at the RNA level. The nasal site presented a significantly higher viral load than the oral site during the Omicron wave. The reduced detection rate of Omicron infections by ADT should be considered in the global testing strategy to preserve accurate diagnoses across the changing SARS-CoV-2 variants.

Substantial transmission of SARS-CoV-2 through casual contact in retail stores: Evidence from matched administrative microdata on card payments and testing

This paper presents quasiexperimental evidence of Covid-19 transmission through casual contact between customers in retail stores. For a large sample of individuals in Denmark, we match card payment data, indicating exactly where and when each individual made purchases, with Covid-19 test data, indicating when each individual was tested and whether the test was positive. The resulting dataset identifies more than 100,000 instances where an infected individual made a purchase in a store and, in each instance, allows us to track the infection dynamics of other individuals who made purchases in the same store around the same time. We estimate transmissions by comparing the infection rate of exposed customers, who made a purchase within 5 min of an infected individual, and nonexposed customers, who made a purchase in the same store 16 to 30 min before. We find that exposure to an infected individual in a store increases the infection rate by around 0.12 percentage points (P < 0.001) between day 3 and day 7 after exposure. The estimates imply that transmissions in stores contributed around 0.04 to the reproduction number for the average infected individual and significantly more in the period where Omicron was the dominant variant.

Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

Modelling the impact of hybrid immunity on future COVID-19 epidemic waves

BACKGROUND

Since the emergence of SARS-CoV-2 (COVID-19), there have been multiple waves of infection and multiple rounds of vaccination rollouts. Both prior infection and vaccination can prevent future infection and reduce severity of outcomes, combining to form hybrid immunity against COVID-19 at the individual and population level. Here, we explore how different combinations of hybrid immunity affect the size and severity of near-future Omicron waves.

METHODS

To investigate the role of hybrid immunity, we use an agent-based model of COVID-19 transmission with waning immunity to simulate outbreaks in populations with varied past attack rates and past vaccine coverages, basing the demographics and past histories on the World Health Organization Western Pacific Region.

RESULTS

We find that if the past infection immunity is high but vaccination levels are low, then the secondary outbreak with the same variant can occur within a few months after the first outbreak; meanwhile, high vaccination levels can suppress near-term outbreaks and delay the second wave. Additionally, hybrid immunity has limited impact on future COVID-19 waves with immune-escape variants.

CONCLUSIONS

Enhanced understanding of the interplay between infection and vaccine exposure can aid anticipation of future epidemic activity due to current and emergent variants, including the likely impact of responsive vaccine interventions.

Immunological imprinting shapes the specificity of human antibody responses against SARS-CoV-2 variants

The spike glycoprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to accumulate substitutions, leading to breakthrough infections of vaccinated individuals. It remains unclear if exposures to antigenically distant SARS-CoV-2 variants can overcome memory B cell biases established by initial SARS-CoV-2 encounters. We determined the specificity and functionality of antibody and B cell responses following exposure to BA.5 and XBB variants in individuals who received ancestral SARS-CoV-2 mRNA vaccines. BA.5 exposures elicited antibody responses that targeted epitopes conserved between the BA.5 and ancestral spike. XBB exposures also elicited antibody responses that primarily targeted epitopes conserved between the XBB.1.5 and ancestral spike. However, unlike BA.5, a single XBB exposure elicited low frequencies of XBB.1.5-specific antibodies and B cells in some individuals. Pre-existing cross-reactive B cells and antibodies were correlated with stronger overall responses to XBB but weaker XBB-specific responses, suggesting that baseline immunity influences the activation of variant-specific SARS-CoV-2 responses.

The effectiveness of novel oral antiviral treatment for non-hospitalized high-risk patients with COVID-19 during predominance of omicron XBB subvariants

OBJECTIVES

This study investigated the association between nirmatrelvir plus ritonavir (NMV-r) or molnupiravir and the outcomes of non-hospitalized high-risk patients with COVID-19 during Omicron XBB subvariants.

METHODS

The retrospective cohort study used the TriNetX US collaborative network to identify non-hospitalized high-risk adult patients with COVID-19 between 1 February 2023, and 31 August 2023. Propensity score matching (PSM) was used to match patients receiving NMV-r or MOV (the study group) with those not receiving antivirals (the control group).

RESULTS

Using PSM, two cohorts of 17,654 patients each with balanced baseline characteristics were identified. During the follow-up period, the study group had a lower risk of all-cause hospitalization, or death (3.2% [n = 564] versus 3.8% [n = 669]; HR, 0.796; 95% confidence interval [CI], 95% CI, 0.712-0.891). Compared with the control group, the study group had a significantly lower risk of all-cause hospitalization (3.1% vs. 3.4%; HR, 0.847; 95% CI, 0.754-0.950) and mortality (0.1% vs. 0.4%; HR, 0.295; 95% CI, 0.183-0.476).

CONCLUSION

The use of novel oral antiviral including NMV-r or MOV can be associated with a lower risk of all-cause hospitalization, or death in non-hospitalized high-risk patients with COVID-19 during Omicron XBB wave.

What makes SARS-CoV-2 unique? Focusing on the spike protein

Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) seriously threatens public health and safety. Genetic variants determine the expression of SARS-CoV-2 structural proteins, which are associated with enhanced transmissibility, enhanced virulence, and immune escape. Vaccination is encouraged as a public health intervention, and different types of vaccines are used worldwide. However, new variants continue to emerge, especially the Omicron complex, and the neutralizing antibody responses are diminished significantly. In this review, we outlined the uniqueness of SARS-CoV-2 from three perspectives. First, we described the detailed structure of the spike (S) protein, which is highly susceptible to mutations and contributes to the distinct infection cycle of the virus. Second, we systematically summarized the immunoglobulin G epitopes of SARS-CoV-2 and highlighted the central role of the nonconserved regions of the S protein in adaptive immune escape. Third, we provided an overview of the vaccines targeting the S protein and discussed the impact of the nonconserved regions on vaccine effectiveness. The characterization and identification of the structure and genomic organization of SARS-CoV-2 will help elucidate its mechanisms of viral mutation and infection and provide a basis for the selection of optimal treatments. The leaps in advancements regarding improved diagnosis, targeted vaccines and therapeutic remedies provide sound evidence showing that scientific understanding, research, and technology evolved at the pace of the pandemic.

Case fatality rates of COVID-19 during epidemic periods of variants of concern: A meta-analysis by continents

OBJECTIVES

To calculate the case fatality rates (CFR) of COVID-19 during epidemic periods of different variants of concern (VOC) by continents.

METHODS

We systematically searched five authoritative databases (Web of Science, PubMed, Embase, Cochrane Library, and MedRxiv) for epidemiological studies on the CFR of COVID-19 published between January 1, 2020, and March 31, 2023. After identifying the epidemic trends of variants, we used a random-effects model to calculate the pooled CFRs during periods of different VOCs. This meta-analysis was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered with PROSPERO (CRD42023431572).

RESULTS

There were variations in the CFRs among different variants of COVID-19 (Alpha: 2.62%, Beta: 4.19%, Gamma: 3.60%, Delta: 2.01%, Omicron: 0.70%), and disparities in CFRs also existed among continents. On the whole, the CFRs of COVID-19 in Europe and Oceania were slightly lower than in other continents. There was a statistically significant association between the variant, HDI value, age distribution, coverage of full vaccination of cases, and the CFR.

CONCLUSIONS

The CFRs of COVID-19 varied across the epidemic periods of different VOCs, and disparities existed among continents. The CFR value reflected combined effects of various factors within a certain context. Caution should be exercised when comparing CFRs due to disparities in testing capabilities and age distribution among countries, etc.

Current Progress, Challenges and Prospects in the Development of COVID-19 Vaccines

The COVID-19 pandemic has resulted in over 772 million confirmed cases, including nearly 7 million deaths, according to the World Health Organization (WHO). Leveraging rapid development, accelerated vaccine approval processes, and large-scale production of various COVID-19 vaccines using different technical platforms, the WHO declared an end to the global health emergency of COVID-19 on May 5, 2023. Current COVID-19 vaccines encompass inactivated, live attenuated, viral vector, protein subunit, nucleic acid (DNA and RNA), and virus-like particle (VLP) vaccines. However, the efficacy of these vaccines is diminishing due to the constant mutation of SARS-CoV-2 and the heightened immune evasion abilities of emerging variants. This review examines the impact of the COVID-19 pandemic, the biological characteristics of the virus, and its diverse variants. Moreover, the review underscores the effectiveness, advantages, and disadvantages of authorized COVID-19 vaccines. Additionally, it analyzes the challenges, strategies, and future prospects of developing a safe, broad-spectrum vaccine that confers sufficient and sustainable immune protection against new variants of SARS-CoV-2. These discussions not only offer insight for the development of next-generation COVID-19 vaccines but also summarize experiences for combating future emerging viruses.

Dynamic changes of Bacterial Microbiomes in Oropharynx during Infection and Recovery of COVID-19 Omicron Variant

Oropharyngeal microbiomes play a significant role in the susceptibility and severity of COVID-19, yet the role of these microbiomes play for the development of COVID-19 Omicron variant have not been reported. A total of 791 pharyngeal swab samples were prospectively included in this study, including 297 confirmed cases of Omicron variant (CCO), 222 confirmed case of Omicron who recovered (CCOR), 73 confirmed cases of original strain (CCOS) and 199 healthy controls (HC). All samples completed MiSeq sequencing. The results showed that compared with HC, conditional pathogens increased in CCO, while acid-producing bacteria decreased. Based on six optimal oropharyngeal operational taxonomy units (OTUs), we constructed a marker microbial classifier to distinguish between patients with Omicron variant and healthy people, and achieved high diagnostic efficiency in both the discovery queue and the verification queue. At same time, we introduced a group of cross-age infection verification cohort and Omicron variant subtype XBB.1.5 branch, which can be accurately distinguished by this diagnostic model. We also analyzed the characteristics of oropharyngeal microbiomes in two subgroups of Omicron disease group-severity of infection and vaccination times, and found that the change of oropharyngeal microbiomes may affect the severity of the disease and the efficacy of the vaccine. In addition, we found that some genera with significant differences gradually increased or decreased with the recovery of Omicron variant infection. The results of Spearman analysis showed that 27 oropharyngeal OTUs were closely related to 6 clinical indexes in CCO and HC. Finally, we found that the Omicron variant had different characterization of oropharyngeal microbiomes from the original strain. Our research characterizes oropharyngeal microbiomes of Omicron variant cases and rehabilitation cases, successfully constructed and verified the non-invasive diagnostic model of Omicron variant, described the correlation between microbial OTUs and clinical indexes. It was found that the infection of Omicron variant and the infection of original strain have different characteristics of oropharyngeal microbiomes.

How does the SARS-CoV-2 reinfection rate change over time? The global evidence from systematic review and meta-analysis

BACKGROUND

There is a significant increase in the number of SARS-CoV-2 reinfection reports in various countries. However, the trend of reinfection rate over time is not clear.

METHODS

We searched PubMed, Web of Science, Medline, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, and Wanfang for cohort studies, case-control studies, and cross-sectional studies up to March 16, 2023, to conduct a meta-analysis of global SARS-CoV-2 reinfection rate. Subgroup analyses were performed for age, country, study type, and study population, and time-varying reinfection rates of SARS-CoV-2 were estimated using meta-regression. The risk of bias was assessed using the Newcastle-Ottawa Scale and the Joanna Briggs Institute critical appraisal tool.

RESULT

A total of 55 studies involving 111,846 cases of SARS-CoV-2 reinfection were included. The pooled SARS-CoV-2 reinfection rate was 0.94% (95% CI: 0.65 -1.35%). In the subgroup analyses, there were statistically significant differences in the pooled reinfection rates by reinfection variant, and study type (P < 0.05). Based on meta-regression, the reinfection rate fluctuated with time.

CONCLUSION

Meta-regression analysis found that the overall reinfection rate increased and then decreased over time, followed by a period of plateauing and then a trend of increasing and then decreasing, but the peak of the second wave of reinfection rate was lower than the first wave. SARS-CoV-2 is at risk of reinfection and the Omicron variant has a higher reinfection rate than other currently known variants. The results of this study could help guide public health measures and vaccination strategies in response to the Coronavirus Disease 2019 (COVID-19) pandemic.

Predicting Vaccine Effectiveness for Hospitalization and Symptomatic Disease for Novel SARS-CoV-2 Variants Using Neutralizing Antibody Titers

The emergence of new virus variants, including the Omicron variant (B.1.1.529) of SARS-CoV-2, can lead to reduced vaccine effectiveness (VE) and the need for new vaccines or vaccine doses if the extent of immune evasion is severe. Neutralizing antibody titers have been shown to be a correlate of protection for SARS-CoV-2 and other pathogens, and could be used to quickly estimate vaccine effectiveness for new variants. However, no model currently exists to provide precise VE estimates for a new variant against severe disease for SARS-CoV-2 using robust datasets from several populations. We developed predictive models for VE against COVID-19 symptomatic disease and hospitalization across a 54-fold range of mean neutralizing antibody titers. For two mRNA vaccines (mRNA-1273, BNT162b2), models fit without Omicron data predicted that infection with the BA.1 Omicron variant increased the risk of hospitalization 2.8-4.4-fold and increased the risk of symptomatic disease 1.7-4.2-fold compared to the Delta variant. Out-of-sample validation showed that model predictions were accurate; all predictions were within 10% of observed VE estimates and fell within the model prediction intervals. Predictive models using neutralizing antibody titers can provide rapid VE estimates, which can inform vaccine booster timing, vaccine design, and vaccine selection for new virus variants.

Clinical Manifestations of Infections with the Omicron Sub-Lineages BA.1, BA.2, and BA.5: A Retrospective Follow-Up Analysis of Public Health Data from Mecklenburg-Western Pomerania, Germany

The Omicron variants BA.1, BA.2, and BA.5 caused several waves of SARS-CoV-2 in Germany in 2022. In this comparative study, public health data on SARS-CoV-2 infections from Mecklenburg-Western Pomerania, Germany, between January and October 2022 were examined retrospectively using Pearson's chi-squared tests and Fisher's exact tests for testing for statistical significance. Compared to BA.5 infections, BA.1 and BA.2 infections affected younger individuals aged up to 19 years significantly more often, whereas BA.5 infections occurred significantly more frequently in patients between 40 and 59 years of age when compared to BA.1 and BA.2. Infections with all three variants predominantly caused flu-like symptoms; nevertheless, there were significant differences between the reported symptoms of BA.1, BA.2, and BA.5 infections. Especially, the symptoms of 'fever', 'severe feeling of sickness', 'loss of taste', and 'loss of smell' were significantly more often present in patients with BA.5 infections compared to BA.1 and BA.2 cases. Additionally, BA.2 and BA.5 cases reported significantly more often the symptoms of 'runny nose' and 'cough' than BA.1-infected cases. Our findings indicate remarkable differences in the clinical presentations among the sub-lineages, especially in BA.5 infections. Furthermore, the study demonstrates a powerful tool to link epidemiological data with genetic data in order to investigate their potential impact on public health.

Distinct evolution of SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 lineages combining increased fitness and antibody evasion

The unceasing circulation of SARS-CoV-2 leads to the continuous emergence of novel viral sublineages. Here, we isolate and characterize XBB.1, XBB.1.5, XBB.1.9.1, XBB.1.16.1, EG.5.1.1, EG.5.1.3, XBF, BA.2.86.1 and JN.1 variants, representing >80% of circulating variants in January 2024. The XBB subvariants carry few but recurrent mutations in the spike, whereas BA.2.86.1 and JN.1 harbor >30 additional changes. These variants replicate in IGROV-1 but no longer in Vero E6 and are not markedly fusogenic. They potently infect nasal epithelial cells, with EG.5.1.3 exhibiting the highest fitness. Antivirals remain active. Neutralizing antibody (NAb) responses from vaccinees and BA.1/BA.2-infected individuals are markedly lower compared to BA.1, without major differences between variants. An XBB breakthrough infection enhances NAb responses against both XBB and BA.2.86 variants. JN.1 displays lower affinity to ACE2 and higher immune evasion properties compared to BA.2.86.1. Thus, while distinct, the evolutionary trajectory of these variants combines increased fitness and antibody evasion.

Possible temporal relationship between SARS-CoV-2 infection and anti-NMDA receptor encephalitis: a meta-analysis

The global impact of SARS-CoV-2 infection has raised concerns about secondary diseases beyond acute illness. This review explores the significance and potential underlying mechanisms of how SARS-CoV-2 infection might elicit an immune response targeting N-methyl-D-aspartate (NMDA) receptors, and its implications for autoimmune-driven neuropsychiatric manifestations. We identified 19 published case reports of NMDA receptor encephalitis associated with SARS-CoV-2 infection or vaccination by a systematic literature search. The significance of these reports was limited since it is not clear if a coincidental or causal relationship exists between SARS-CoV-2 infection or vaccination and manifestation of NMDA receptor encephalitis. The included studies were hampered by difficulties in establishing if these patients had pre-existing NMDA receptor antibodies which entered the brain by infection- or vaccination-associated transient blood-brain barrier leakage. In addition, four cases had comorbid ovarian teratoma, which is a known trigger for development of NMDA receptor encephalitis. Considering that billions of people have contracted COVID-19 or have been vaccinated against this virus, the publication of only 19 case reports with a possible link to NMDA receptor encephalitis, indicates that it is rare. In conclusion, these findings do not support the case that SARS-CoV-2 infection or vaccination led to an increase of existing or de novo encephalitis mediated by an autoimmune response targeting NMDA receptor function. Nevertheless, this work underscores the importance of ongoing vigilance in monitoring viral outbreaks and their potential impact on the central nervous system through basic, epidemiological and translational research.

Tracheal computed tomography radiomics model for prediction of the Omicron variant of severe acute respiratory syndrome coronavirus 2

OBJECTIVES

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, fast-spreading, and insidious. Most patients present with normal findings on lung computed tomography (CT). The current study aimed to develop and validate a tracheal CT radiomics model to predict Omicron variant infection.

MATERIALS AND METHODS

In this retrospective study, a radiomics model was developed based on a training set consisting of 157 patients with an Omicron variant infection and 239 healthy controls between 1 January and 30 April 2022. A set of morphological expansions, with dilations of 1, 3, 5, 7, and 9 voxels, was applied to the trachea, and radiomic features were extracted from different dilation voxels of the trachea. Logistic regression (LR), support vector machines (SVM), and random forests (RF) were developed and evaluated; the models were validated on 67 patients with the Omicron variant and on 103 healthy controls between 1 May and 30 July 2022.

RESULTS

Logistic regression with 12 radiomic features extracted from the tracheal wall with dilation of 5 voxels achieved the highest classification performance compared with the other models. The LR model achieved an area under the curve of 0.993 (95% confidence interval [CI]: 0.987-0.998) in the training set and 0.989 (95% CI: 0.979-0.999) in the validation set. Sensitivity, specificity, and accuracy of the model for the training set were 0.994, 0.946, and 0.965, respectively, whereas those for the validation set were 0.970, 0.952, and 0.959, respectively.

CONCLUSION

The tracheal CT radiomics model reliably identified the Omicron variant of SARS-CoV‑2, and may help in clinical decision-making in future, especially in cases of normal lung CT findings.

Rapid isolation of pan-neutralizing antibodies against Omicron variants from convalescent individuals infected with SARS-CoV-2

Introduction

The emergence of SARS-CoV-2 Omicron subvariants has presented a significant challenge to global health, as these variants show resistance to most antibodies developed early in the pandemic. Therapeutic antibodies with potent efficacy to the Omicron variants are urgently demanded.

Methods

Utilizing the rapid antibody discovery platform, Berkeley Lights Beacon, we isolated two monoclonal neutralizing antibodies, 2173-A6 and 3462-A4. These antibodies were isolated from individuals who recently recovered from Omicron infections.

Results

Both antibodies, 2173-A6 and 3462-A4, demonstrated high affinity for the RBD and effectively neutralized pseudoviruses from various Omicron lineages, including BA.4/5, XBB.1.16, XBB.1.5, and EG.5.1. This neutralization was achieved through binding to identical or overlapping epitopes.

Discussion

The use of the Beacon platform enabled the rapid isolation and identification of effective neutralizing antibodies within less than 10 days. This process significantly accelerates the development of novel therapeutic antibodies, potentially reducing the time required to respond to unknown infectious diseases in the future.

Divergent pathogenetic outcomes in BALB/c mice following Omicron subvariant infection

Following the emergence of B.1.1.529 Omicron, the SARS-CoV-2 virus evolved into a significant number of sublineage variants that possessed numerous mutations throughout the genome, but particularly within the spike glycoprotein (S) gene. For example, the BQ.1.1 and the XBB.1 and XBB.1.5 subvariants contained 34 and 41 mutations in S, respectively. However, these variants elicited largely replication only or mild disease phenotypes in mice. To better model pathogenic outcomes and measure countermeasure performance, we developed mouse adapted versions (BQ.1.1 MA; XBB.1 MA; XBB.1.5 MA) that reflect more pathogenic acute phase pulmonary disease symptoms of SARS-CoV-2, as well as derivative strains expressing nano-luciferase (nLuc) in place of ORF7 (BQ.1.1 nLuc; XBB.1 nLuc; XBB.1.5 nLuc). Amongst the mouse adapted (MA) viruses, a wide range of disease outcomes were observed including mortality, weight loss, lung dysfunction, and tissue viral loads in the lung and nasal turbinates. Intriguingly, XBB.1 MA and XBB.1.5 MA strains, which contained identical mutations throughout except at position F486S/P in S, exhibited divergent disease outcomes in mice (Ao et al., 2023). XBB.1.5 MA infection was associated with significant weight loss and ∼45 % mortality across two independent studies, while XBB.1 MA infected animals suffered from mild weight loss and only 10 % mortality across the same two independent studies. Additionally, the development and use of nanoluciferase expressing strains provided moderate throughput for live virus neutralization assays. The availability of small animal models for the assessment of Omicron VOC disease potential will enable refined capacity to evaluate the efficacy of on market and pre-clinical therapeutics and interventions.

Prevalence of SARS-CoV-2 variants in Prague wastewater determined by nanopore-based sequencing

The early detection of upcoming disease outbreaks is essential to avoid both health and economic damage. The last four years of COVID-19 pandemic have proven wastewater-based epidemiology is a reliable system for monitoring the spread of SARS-CoV-2, a causative agent of COVID-19, in an urban population. As this monitoring enables the identification of the prevalence of spreading variants of SARS-CoV-2, it could provide a critical tool in the fight against this viral disease. In this study, we evaluated the presence of variants and subvariants of SARS-CoV-2 in Prague wastewater using nanopore-based sequencing. During August 2021, the data clearly showed that the number of identified SARS-CoV-2 RNA copies increased in the wastewater earlier than in clinical samples indicating the upcoming wave of the Delta variant. New SARS-CoV-2 variants consistently prevailed in wastewater samples around a month after they already prevailed in clinical samples. We also analyzed wastewater samples from smaller sub-sewersheds of Prague and detected significant differences in SARS-CoV-2 lineage progression dynamics among individual localities studied, e.g., suggesting faster prevalence of new variants among the sites with highest population density and mobility.

Immunogenicity and safety of heterologous booster with protein-based COVID-19 vaccine (NVX-CoV2373) in healthy adults: A comparative analysis with mRNA vaccines

BACKGROUND

Information on the protein-based severe acute respiratory syndrome (SARS-CoV-2) vaccine-NVX-CoV2373 (Novavax), as a heterologous booster remains limited. We investigated the immunogenicity and adverse events of NVX-CoV2373 as a second booster and compared them with those of mRNA vaccines in healthy adults.

METHODS

Healthcare workers who had received an mRNA vaccine (mRNA-1273 or BNT-162b2) as the first booster (third dose) 12 weeks prior were recruited. Participants voluntarily received either NVX-CoV2373 or an mRNA vaccine as a second booster. Participants with a history of SARS-CoV-2 infection were excluded. The primary outcomes included serum anti-SARS-CoV-2 spike protein (SP) and neutralizing antibody titers against B.1.1.7 (Alpha), B.1.1.529 (Omicron) BA2, and BA5 variants on the 28th day after the boost. Secondary outcomes included new SARS-CoV-2 infections and adverse events reported during the study period.

RESULTS

A total of 160 participants were enrolled in this study. Compared with the mRNA vaccination group (n = 59), the NVX-CoV2373 vaccination group (n = 101) had significantly lower anti-SARS-CoV-2 SP antibody titers and neutralizing antibody titers against all variants tested after the boost. During the study period, higher rates of new SARS-CoV-2 infections and a lower incidence of adverse events were observed in the NVX-CoV2373 vaccination group. No significant differences in cellular immune responses were observed between the two groups.

CONCLUSION

Compared to a homologous mRNA booster vaccination, heterologous boosters with NVX-CoV2373 showed lower antibody responses, a higher incidence of new SARS-CoV-2 infections, and fewer adverse events.

Clinical features that predict the mortality risk in older patients with Omicron pneumonia: the MLWAP score

In December 2022, the Chinese suffered widespread Omicron of SARS-CoV-2 with variable symptom severity and outcome. We wanted to develop a scoring model to predict the mortality risk of older Omicron pneumonia patients by analyzing admission data. We enrolled 227 Omicron pneumonia patients aged 60 years and older, admitted to our hospital from December 15, 2022, to January 16, 2023, and divided them randomly into a 70% training set and a 30% test set. The former were used to identify predictors and develop a model, the latter to verify the model, using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, a calibration curve to test its performance and comparing it to the existing scores. The MLWAP score was calculated based on a multivariate logistic regression model to predict mortality with a weighted score that included immunosuppression, lactate ≥ 2.4, white blood cell count ≥ 6.70 × 109/L, age ≥ 77 years, and PaO2/FiO2 ≤ 211. The AUC for the model in the training and test sets was 0.852 (95% CI, 0.792-0.912) and 0.875 (95% CI, 0.789-0.961), respectively. The calibration curves showed a good fit. We grouped the risk scores into low (score 0-7 points), medium (8-10 points), and high (11-13 points). This model had a sensitivity of 0.849, specificity of 0.714, and better predictive ability than the CURB-65 and PSI scores (AUROC = 0.859 vs. 0.788 vs. 0.801, respectively). The MLWAP-mortality score may help clinicians to stratify hospitalized older Omicron pneumonia patients into relevant risk categories, rationally allocate medical resources, and reduce the mortality.

Magnitude and Duration of Serum Neutralizing Antibody Titers Induced by a Third mRNA COVID-19 Vaccination against Omicron BA.1 in Older Individuals

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) is dominating coronavirus disease 2019 (COVID-19) worldwide. The waning protective effect of available vaccines against the Omicron variant is a critical public health issue. This study aimed to assess the impact of the third COVID-19 vaccination on immunity against the SARS-CoV-2 Omicron BA.1 strain in older individuals.

MATERIALS AND METHODS

Adults aged ≥60 years who had completed two doses of the homologous COVID-19 vaccine with either BNT162b2 (Pfizer/BioNTech, New York, NY, USA, BNT) or ChAdOx1 nCoV (SK bioscience, Andong-si, Gyeongsangbuk-do, Korea, ChAd) were registered to receive the third vaccination. Participants chose either BNT or mRNA-1273 (Moderna, Norwood, MA, USA, m1273) mRNA vaccine for the third dose and were categorized into four groups: ChAd/ChAd/BNT, ChAd/ChAd/m1273, BNT/BNT/BNT, and BNT/BNT/m1273. Four serum specimens were obtained from each participant at 0, 4, 12, and 24 weeks after the third dose (V1, V2, V3, and V4, respectively). Serum-neutralizing antibody (NAb) activity against BetaCoV/Korea/KCDC03/2020 (NCCP43326, ancestral strain) and B.1.1.529 (NCCP43411, Omicron BA.1 variant) was measured using plaque reduction neutralization tests. A 50% neutralizing dilution (ND50) >10 was considered indicative of protective NAb titers.

RESULTS

In total, 186 participants were enrolled between November 24, 2021, and June 30, 2022. The respective groups received the third dose at a median (interquartile range [IQR]) of 132 (125 - 191), 123 (122 - 126), 186 (166 - 193), and 182 (175 - 198) days after the second dose. Overall, ND50 was lower at V1 against Omicron BA.1 than against the ancestral strain. NAb titers against the ancestral strain and Omicron BA.1 variant at V2 were increased at least 30-fold (median [IQR], 1235.35 [1021.45 - 2374.65)] and 129.8 [65.3 - 250.7], respectively). ND50 titers against the ancestral strain and Omicron variant did not differ significantly among the four groups (P = 0.57). NAb titers were significantly lower against the Omicron variant than against the ancestral strain at V3 (median [IQR], 36.4 (17.55 - 75.09) vs. 325.9 [276.07 - 686.97]; P = 0.012). NAb titers against Omicron at V4 were 16 times lower than that at V3. Most sera exhibited a protective level (ND50 >10) at V4 (75.0% [24/32], 73.0% [27/37], 73.3% [22/30], and 70.6% [12/17] in the ChAd/ChAd/BNT, ChAd/ChAd/m1273, BNT/BNT/BNT, and BNT/BNT/m1273 groups, respectively), with no significant differences among groups (P = 0.99).

CONCLUSION

A third COVID-19 mRNA vaccine dose restored waning NAb titers against Omicron BA.1. Our findings support a third-dose vaccination program to prevent the waning of humoral immunity to SARS-CoV-2.

The evolution and interpretation of seroprevalence of SARS-CoV-2 antibodies among South African blood donors from the Beta to Omicron variant-driven waves

BACKGROUND AND OBJECTIVES

Confirmed COVID-19 diagnoses underestimate the total number of infections. Blood donors can provide representative seroprevalence estimates, which can be leveraged into reasonable estimates of total infection counts and infection fatality rate (IFR).

MATERIALS AND METHODS

Blood donors who donated after each of three epidemic waves (Beta, Delta and first Omicron waves) were tested for anti-SARS-CoV-2 nucleocapsid antibodies using the Roche Elecsys anti-SARS-CoV-2 total immunoglobulin assay. Roche Elecsys anti-spike antibody testing was done for the post-Omicron sampling. Prevalence of antibodies was estimated by age, sex, race and province and compared to official case reporting. Province and age group-specific IFRs were estimated using external excess mortality estimates.

RESULTS

The nationally weighted anti-nucleocapsid seroprevalence estimates after the Beta, Delta and Omicron waves were 47% (46.2%-48.6%), 71% (68.8%-73.5%) and 87% (85.5%-88.4%), respectively. There was no variation by age and sex, but there were statistically and epidemiologically significant differences by province (except at the latest time point) and race. There was a 13-fold higher seroprevalence than confirmed case counts at the first time point. Age-dependent IFR roughly doubled for every 10 years of age increase over 6 decades from 0.014% in children to 6.793% in octogenarians.

CONCLUSION

Discrepancies were found between seroprevalence and confirmed case counts. High seroprevalence rates found among Black African donors can be ascribed to historical inequities. Our IFR estimates were useful in refining previous large disagreements about the severity of the epidemic in South Africa. Blood donor-based serosurveys provided a valuable and efficient way to provide near real-time monitoring of the ongoing SARS-CoV-2 outbreak.

Understanding SARS-CoV-2 spike glycoprotein clusters and their impact on immunity of the population from Rio Grande do Norte, Brazil

SARS-CoV-2 genome underwent mutations since it started circulating within the human population. The aim of this study was to understand the fluctuation of the spike clusters concomitant to the population immunity either due to natural infection and/or vaccination in a state of Brazil that had both high rate of natural infection and vaccination coverage. A total of 1725 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and to correlate with circulating variants. From March 2020 to June 2022, the state of Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across the three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta (AY.*), which circulated in Brazil in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma (P.1 + P.1.*)) dominated the first half of 2021. Late 2021 had two new clusters, Cluster 2 (Omicron, (B.1.1.529 + BA.*)), and Cluster 3 (BA.*) with the most unique epitopes, in addition to Cluster 4 (Delta sub lineages) which emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome.

Self-correction of cycle threshold values by a normal distribution-based process to improve accuracy of quantification in real-time digital PCR

The digital polymerase chain reaction (dPCR) is a new and developing nucleic acid detection technology with high sensitivity that can realize the absolute quantitative analysis of samples. In order to improve the accuracy of quantitative results, real-time digital PCR emphasizes the kinetic information during amplification to identify prominent abnormal data. However, it is challenging to use a unified standard to accurately classify the amplification curve of each well as negative and positive, due to the interference caused by various factors in the experiment. In this work, a normal distribution-based cycle threshold value self-correcting model (NCSM) was established, which focused on the feature of the cycle threshold values in amplification curves and conducted continuous detection and correction on the whole. The cycle threshold value distribution was closer to the ideal normal distribution to avoid the influence of interference. Thus, the model achieves a more accurate classification between positive and negative results. The corrective process was applied to plasmid samples and resulted in an accuracy improvement from 92 to 99%. The coefficient of variation was below 5% when considering the quantitation of a range between 100 and 10,000 copies. At the same time, by utilizing this model, the distribution of cycle threshold values at the endpoint can be predicted with fewer thermal cycles, which can reduce the cycling time by around 25% while maintaining a consistency of more than 98%. Therefore, using the NCSM can effectively enhance the quantitative accuracy and increase the detection efficiency based on the real-time dPCR platform.

Comparing COVID-19 severity in patients hospitalized for community-associated Delta, BA.1 and BA.4/5 variant infection

Background

Despite decreasing COVID-19 disease severity during the Omicron waves, a proportion of patients still require hospitalization and intensive care.

Objective

To compare demographic characteristics, comorbidities, vaccination status, and previous infections in patients hospitalized for community-associated COVID-19 (CAC) in predominantly Delta, Omicron BA.1 and BA.4/5 SARS-CoV-2 waves.

Methods

Data were extracted from three national databases-the National COVID-19 Database, National Vaccination Registry and National Registry of Hospitalizations.

Results

Among the hospitalized CAC patients analyzed in this study, 5,512 were infected with Delta, 1,120 with Omicron BA.1, and 1,143 with the Omicron BA.4/5 variant. The age and sex structure changed from Delta to BA.4/5, with the proportion of women (9.5% increase), children and adolescents (10.4% increase), and octa- and nonagenarians increasing significantly (24.5% increase). Significantly more patients had comorbidities (measured by the Charlson Comorbidity Index), 30.3% in Delta and 43% in BA.4/5 period. The need for non-invasive ventilatory support (NiVS), ICU admission, mechanical ventilation (MV), and in-hospital mortality (IHM) decreased from Delta to Omicron BA.4/5 period for 12.6, 13.5, 11.5, and 6.3%, respectively. Multivariate analysis revealed significantly lower odds for ICU admission (OR 0.68, CI 0.54-0.84, p < 0.001) and IHM (OR 0.74, CI 0.58-0.93, p = 0.011) during the Delta period in patients who had been fully vaccinated or boosted with a COVID-19 vaccine within the previous 6 months. In the BA.1 variant period, patients who had less than 6 months elapsed between the last vaccine dose and SARS-CoV-2 positivity had lower odds for MV (OR 0.38, CI 0.18-0.72, p = 0.005) and IHM (OR 0.56, CI 0.37- 0.83, p = 0.005), but not for NIVS or ICU admission.

Conclusion

The likelihood of developing severe CAC in hospitalized patients was higher in those with the Delta and Omicron BA.1 variant compared to BA.4/5.

Public acceptance of COVID-19 control measures and associated factors during Omicron-dominant period in China: a cross-sectional survey

OBJECTIVES

This study aims to evaluate the public acceptance of coronavirus disease 2019 (COVID-19) control measures during the Omicron-dominant period and its associated factors.

METHODS

A cross-sectional design was conducted and 1391 study participants were openly recruited to participate in the questionnaire survey. Logistic regression model was performed to assess the association between the public acceptance and potential factors more specifically.

RESULTS

By August 26, 2022, 58.9% of the study participants were less acceptive of the control measures while 41.1% expressed higher acceptance. Factors associated with lower acceptance included young age, such as < 18 (OR = 8.251, 95% CI: 2.009 to 33.889) and 18-29 (OR = 2.349, 95% CI: 1.564 to 3.529), and household per capita monthly income lower than 5000 yuan (OR = 1.512, 95% CI: 1.085 to 2.105). Furthermore, individuals who perceived that the case fatality rate (CFR) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was very low (OR = 6.010, 95% CI: 2.475 to 14.595) and that the restrictions could be eased once the CFR dropped to 2-3 times of the influenza (OR = 2.792, 95% CI: 1.939 to 4.023) showed greater oppositional attitudes. Likewise, respondents who were dissatisfied with control measures (OR = 9.639, 95% CI: 4.425 to 20.998) or preferred fully relaxation as soon as possible (OR = 13.571, 95% CI: 7.751 to 23.758) had even lower acceptability. By contrast, rural residents (OR = 0.683, 95% CI: 0.473 to 0.987), students (OR = 0.510, 95% CI: 0.276 to 0.941), public (OR = 0.417, 95% CI: 0.240 to 0.727) and private (OR = 0.562, 95% CI: 0.320 to 0.986) employees, and vaccinated participants (OR = 0.393, 95% CI: 0.204 to 0.756) were more compliant with control measures.

CONCLUSION

More than half of the Chinese public were less supportive of COVID-19 control measures during Omicron-dominant period, which varied based on their different demographic characteristics, cognition and overall attitude towards SARS-CoV-2 infection. Control measures that struck a balance between public safety and individual freedom would be more acceptable during the pandemic.