The mechanisms facilitating the relationship between low income and COVID-19 severity have not been partitioned in the presence of SARS-CoV-2 variants of concern (VOCs). To address this, we used causal mediation analysis to quantify the possible mediating role infection with VOC has on the relationship between neighborhood income (exposure) and hospitalization due to COVID-19 among cases (outcome). A population-based cohort of 65 629 individuals residing in British Columbia, Canada, was divided into 3 periods of VOC co-circulation in the 2021 calendar year, whereby each period included co-circulation of an emerging and an established VOC. Each cohort was subjected to g-formula mediation techniques to decompose the relationship between exposure and outcome into total, direct, and indirect effects. In the mediation analysis, the total effects indicated that low income was associated with increased odds of hospitalization across all periods. Further decomposition of the effects revealed that income is directly and indirectly associated with hospitalization. The resulting indirect effect through VOC accounted for approximately between 6% and 13% of the total effect of income on hospitalization. This study underscores, conditional on the analysis, the importance of addressing underlying inequities to mitigate the disproportionate impact on historically marginalized communities by adopting an equity lens as central to pandemic preparedness and response from the onset.

Numerous studies have highlighted a link between COVID-19 and respiratory allergic conditions such as asthma and allergic rhinitis (AR). Despite the growing volume of research, there remains a notable gap in the form of a comprehensive bibliometric analysis that consolidates the findings on this association. This study aims to fill that gap by systematically exploring how asthma and AR interact with COVID-19.

By using the Web of Science Core Collection, we selected publications from January 2020 to October 2024 that related to COVID-19 and asthma/AR. Analysis tools such as VOSviewer and CiteSpace were employed to perform network mappings and citation analyses, focusing on co-authorship networks, keyword co-occurrences, and citation impacts to understand the research dynamics and collaborative patterns within this field.

A collection of 553 publications was obtained, revealing an upward trend in research volume over the study period. The United States, China, and the United Kingdom were predominant in the research output, demonstrating extensive international collaborations. The study highlighted key areas of impact, such as the influence of asthma types on COVID-19 severity and the protective effects of specific treatments like inhaled corticosteroids and biologics. Emerging trends identified included the significance of socioeconomic factors and obesity in disease outcomes, as well as evolving strategies in vaccination and interventions.

This bibliometric analysis highlights the significant role of global research in exploring the interactions between COVID-19 and asthma/AR. It points out the reported safety and effectiveness of COVID-19 vaccines for these conditions and acknowledges the challenges in vaccine uptake among minority and socioeconomically disadvantaged groups. The study also identifies unique risks for children and obese patients during the pandemic and underscores the need for increased international collaboration and more comprehensive clinical trials, to evaluate the efficacy of treatments like inhaled corticosteroids and biologics.

COVID-19, caused by SARS-CoV-2 infection, left widespread impacts worldwide. In Brazil, immunization reduced incidence rates. However, six months later, waning neutralizing antibody titers and new immune-evading variants increased cases, resulting in recurring waves. This study evaluated hospitalized COVID-19 patients after the vaccination rollout, comparing the clinical outcomes between vaccinated and unvaccinated patients. Positive samples underwent nucleotide sequencing. A total of 218 patients were included; 202 (92 %) had vaccination data, 98 received at least one dose, and 64 completed the vaccination schedule, predominantly with CoronaVac®. Vaccinated individuals were older on average since the campaign was primarily conducted among the elderly. The Gamma variant predominated during the study period. While not statistically significant, trends indicated greater respiratory assistance needs, more extended hospital stays, and increased ICU time among unvaccinated patients. Mortality was 45 % in vaccinated and 37 % in unvaccinated groups, with no notable difference. However, patients with a complete vaccination schedule showed a higher chance of survival, though not significant (p = 0.11). The factors significantly associated with higher mortality were older patients, those requiring vasopressor drugs, and mechanical ventilation. These findings provide clinical, epidemiological, and phylogenetic insights into COVID-19 patients during vaccination implementation. They underscore the need to evaluate vaccine effectiveness against circulating variants and highlight the importance of complete vaccination schedules for improving patient outcomes.

Understanding how interpersonal interactions and immunological factors shape severe acute respiratory syndrome coronavirus 2 transmission in households is crucial for designing control measures. We developed a Bayesian data augmentation transmission model to evaluate the effects of isolation, parental care, and vaccine-induced immunity on Delta variant transmission from the follow-up of 1093 Israeli households (July-August 2021). Among the 2883 household contacts, 1096 (38%) were infected. Children were 38% (95% Credibleconfidence interval [CrI], 7%-81%) more likely to be infected than adults. Isolation measures reduced transmission by 52% (95% CrI, 46%-57%). Transmission was 39% (95% CrI, 11%-76%) higher between children and female adults than between children and male adults. Vaccine effectiveness was 78% (95% CrI, 54%-90%), 85% (95% CrI, 70%-94%), and 73% (95% CrI, 49%-88%), respectively, for 1, 2, and 3 recent vaccine doses (within ≤90 days) but dropped to 18% (95% 95% CrI, -6% to 36%) for 2 doses administered >90 days earlier. Household member interactions significantly shaped transmission, and isolation measures effectively reduced transmission.

The emergence of highly transmissible SARS-CoV-2 variants has posed significant challenges to public health efforts worldwide. During the summer of 2021, the Delta variant (B.1.617.2) rapidly displaced the Alpha variant (B.1.1.7) in Catalonia, Spain, leading to a resurgence in infections despite ongoing vaccination campaigns. Understanding the epidemiological drivers of this outbreak is critical for refining future mitigation strategies.

We employed a Bayesian age-stratified epidemiological model, incorporating vaccination status and variant-specific transmission dynamics, to analyze the outbreak in Catalonia. The model was calibrated using daily reported cases, hospitalizations, sequencing data, and vaccination coverage across age groups. We inferred contact patterns dynamically to assess their role in the epidemic resurgence and estimated the transmission advantage of the Delta variant over Alpha.

Our analysis revealed that increased social interactions among younger, less vaccinated populations significantly contributed to the surge in infections. The long weekend of Sant Joan (June 23-24) coincided with a peak in contact rates, driving a rise in the reproduction number, particularly among individuals aged 20-29. We estimated that the Delta variant had a 40-60.

Our findings underscore the critical role of vaccination coverage in mitigating the impact of emerging variants. The combination of increased social interactions and uneven vaccine distribution exacerbated the Delta-driven resurgence. NPIs alone proved insufficient in controlling transmission, highlighting the necessity of targeted vaccination strategies to achieve robust epidemic control. This study provides a framework for assessing future variant-specific threats and informing tailored public health interventions.

With the emergence of Omicron during the pandemic and the establishment of antibody waning over time, vaccine effectiveness, especially against infection, declined sharply from the original levels seen after the initial rollout. However, studies have demonstrated that they still provided substantial protection vs severe/fatal disease even with Omicron and after waning. Social media has been rife with reports claiming vaccines provided no benefit and some even claiming they made things worse, often driven by simple presentations of raw observational data using erroneous arguments involving epidemiologic fallacies including the base rate fallacy, Simpson's paradox, and the ecological fallacy and ignoring the extensive bias especially from confounding that is an inherent feature of these data. Similar fallacious arguments have been made by some in promoting vaccination policies, as well. Generally, vaccine effectiveness cannot be accurately estimated from raw population summaries but instead require rigorous, careful studies using epidemiologic designs and statistical analysis tools attempting to adjust for key confounders and sources of bias. This article summarizes what aggregated evidence across studies reveals about effectiveness of the mRNA vaccines as the pandemic has evolved, chronologically summarized with emerging variants and highlighting some of the fallacies and flawed arguments feeding social media-based claims that have obscured society's collective understanding.

Background: Malnutrition is an often-overlooked yet potentially crucial factor influencing COVID-19 outcomes. Poor nutritional status weakens immune function, increases infection susceptibility, and worsens prognoses in hospitalized patients. However, its specific role in COVID-19 mortality remains insufficiently characterized. The aim of the study was to assess the impact of malnutrition, as determined by the Nutritional Risk Score (NRS-2002), on in-hospital mortality. Methods: This retrospective, single-center study analyzed 222 patients hospitalized with COVID-19 during the Delta variant predominance. Thirty-one patients died during hospitalization. Malnutrition (NRS ≥ 3) emerged as a strong predictor of in-hospital mortality in univariate Cox proportional hazard models, both before and after adjustment for potential confounders. Adjusted analyses used 10 different sets of three out of five mortality-related variables. Results: Hazard ratios for malnutrition ranged from 3.19 to 5.88 (p < 0.01 for all models), highlighting its substantial impact on mortality risk. The high Nagelkerke's R2 values (0.66-0.77) indicate that the models explained a significant proportion of mortality variance. Nutritional status plays a critical role in COVID-19 survival among hospitalized patients. Conclusions: Given its simplicity and effectiveness, integrating the NRS-2002 into routine clinical assessments may help identify high-risk patients early. Future research should explore whether early nutritional interventions can mitigate the mortality risks associated with malnutrition in severe COVID-19 cases or patients with other infectious diseases or acute inflammation.

In 2021, the severe acute respiratory syndrome coronavirus 2 Delta variant rapidly proliferated and became dominant. Some but not all research evidence supports that Delta was associated with increased maternal risk. The purpose of this study was to determine whether Delta was associated with risk for cardiac and respiratory complications in a national sample. Of an estimated 3,495,188 delivery hospitalizations in 2021, 1.8% of pre-Delta deliveries (n = 29,580; January-June) and 2.1% of Delta-period deliveries (n = 37,545; July-December) had a coronavirus disease 2019 (COVID-19) diagnosis. The Delta period was associated with increased adjusted odds of respiratory complications (adjusted odds ratio [aOR] = 1.54, 95% CI: 1.41, 1.69) and cardiac severe maternal morbidity (SMM; aOR = 1.54, 95% CI: 1.40, 1.69). Among deliveries with a COVID-19 diagnosis, the Delta period was associated with a higher incidence of respiratory complications (8.4 vs. 3.7%) and cardiac SMM (8.4 vs. 3.5%; p < 0.01 for both). These findings corroborate prior clinical studies suggesting that the Delta strain was associated with an increased maternal population-level clinical burden. · The Delta strain was associated with an increased maternal population-level clinical burden.. · The Delta period was associated with an increased risk for cardiac and respiratory complications.. · Among deliveries with a COVID-19 diagnosis, the Delta period was associated with increased risk..

The persistence of SARS-CoV-2 infections at a global level reflects the repeated emergence of variant strains encoding unique constellations of mutations. These variants have been generated principally because of a dynamic host immune landscape, the countermeasures deployed to combat disease, and selection for enhanced infection of the upper airway and respiratory transmission. The resulting viral diversity creates a challenge for vaccination efforts to maintain efficacy, especially regarding humoral aspects of protection. Here, we review our understanding of how SARS-CoV-2 has evolved during the pandemic, the immune mechanisms that confer protection, and the impact viral evolution has had on transmissibility and adaptive immunity elicited by natural infection and/or vaccination. Evidence suggests that SARS-CoV-2 evolution initially selected variants with increased transmissibility but currently is driven by immune escape. The virus likely will continue to drift to maintain fitness until countermeasures capable of disrupting transmission cycles become widely available.

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.

Large-scale population studies are important to monitor and evaluate aspects of a vaccination programme including vaccine coverage, real-world effectiveness, and post-licensure vaccine safety. These types of epidemiological studies often come under the remit of public health agencies, such as the UK Health Security Agency (UKHSA) in England, which are required to undertake surveillance of vaccine-preventable diseases, including via seroepidemiological studies and data linkage studies using national-level electronic healthcare data. An individual-level national vaccine register with an accurate denominator can be the key to gaining insights into vaccine coverage, effectiveness, and safety. During the coronavirus disease 2019 pandemic, England's first vaccine register was developed. This enabled timely estimates of real-world vaccine effectiveness in the whole population of England, as well as enabling epidemiological investigations of rare potential risks from vaccines in specific populations. Population-based research studies, including prospective cohort studies, are complementary to surveillance and combined, enable more comprehensive assessments. As there was an unprecedented investment into research studies and infrastructure during the pandemic, the scale of these studies meant they were able to contribute to vaccine programme evaluations in a way that had not been possible for previous vaccine programmes. In this review, we summarise the different large-scale surveillance and research studies that have been used to evaluate and inform vaccine policy from the time of the first data linkage studies undertaken in England in the 1990s to the present-day post-COVID-19 pandemic.

Brass bands that include wind instruments are heavily affected by rules established during the pandemic. The aim of this experimental work was to assess the aerosols emitted through different wind instruments. The Aerodynamic Particle Sizer (APS) was used to measure the aerosols emitted and transmit those characteristics to a database. The results revealed that the dynamic level at which a note is produced, regardless of whether it is a clarinet, trumpet, or bassoon, significantly changes in aerosol concentrations emitted. Specifically, if there is a higher dynamic level, an increase in emissions of particle concentration will occur by comparing the levels piano, mezzo forte, and forte. These aerosols are produced with a diameter of approximately 0.8 μm, except for the Navarra bagpipe, which has a diameter of 1.8 μm. In addition, this last instrument is the one that emits more particles every second, reaching a value five times larger than that with two reeds, such as the bassoon. Staccato and legato are two well-known techniques among musicians that help in articulating a musical piece. The difference between the two methods in terms of the concentration of the number of particles is not remarkable and is almost negligible.

In a previous pilot randomised controlled trial conducted on UK adults, we found that hypertonic saline nasal irrigation and gargling (HSNIG) reduced common cold symptoms, the need for over-the-counter medications, viral shedding, and the duration and transmission of the illness. It is unclear whether HSNIG improves outcomes of the coronavirus disease 2019 (COVID-19). Hypertonic saline can be prepared and HSNIG performed at home, making it a safe and scalable intervention, particularly well-suited for low- and middle-income countries.

We conducted a pragmatic randomised controlled trial in Pakistan on adults with suspected or confirmed COVID-19, initially within 48 hours of symptom onset, later extended to within five days due to recruitment challenges. Participants were randomised to one of two groups: the intervention group received instructions on preparing a 2.6% hypertonic saline solution for HSNIG, while the control group was instructed on performing ablution for Muslim prayers (wudu), which involves nasal washing and gargling with tap water. Our primary outcome was the time to symptom resolution, measured by two consecutive days of scoring zero on relevant questions from the validated, self-reported, adapted short form of the Wisconsin Upper Respiratory Symptom Survey (WURSS-24). Secondary outcomes included the severity of all symptoms, the severity and time to resolution of individual symptoms, health care contacts (GP/physician, emergency contacts), hospital attendance (and length of stay if admitted), over-the-counter (OTC) medication (frequency and cost), and transmission to household contacts. The analysis was conducted on an intention-to-treat basis. Logistic regression was used to calculate adjusted odds ratios (aORs) of improvement and Cox regression to calculate adjusted hazard ratios (aHRs) for the time to improvement with accompanying 95% confidence intervals (CIs).

We randomised 576 people: 279 to the HSNIG group and 297 to the control group. Among those, 10 out of 279 (3.6%) in the HSNIG had symptom resolution, compared with 11 out of 297 (3.7%) in the control group (aOR = 1.20, 95% CI = 0.46- 3.22). The time-to-event analysis also showed no significant benefit (aHR = 1.23, 95% CI = 0.51-2.97). Excluding the 127 participants with no data on the primary outcome (who did not complete the study), 10 out of 222 (4.5%) in the HSNIG group had symptom resolution, compared to 11 out of 227 (4.8%) in the control group.

HSNIG was not effective for individuals with suspected or confirmed COVID-19 who began the intervention within five days of symptoms onset and therefore cannot be recommended for use. Further investigation is needed for interventions started within 48 hours of illness onset.

ClinicalTrials.gov (NCT05104372).

Prior infection with SARS-CoV-2 can provide protection against infection and severe COVID-19. We aimed to determine the impact of preexisting immunity on vaccine effectiveness (VE) estimates. We systematically reviewed and meta-analyzed 66 test-negative design studies that examined VE against infection or severe disease (hospitalization, intensive care unit admission, or death) for primary vaccination series. Pooled VE among studies that included people with prior COVID-19 infection was lower against infection (77%; 95% CI, 72-81) and severe disease (86%; 95% CI, 83-89) compared with studies that excluded people with prior COVID-19 infection (pooled VE against infection: 87% [95% CI, 85-89]; pooled VE against severe disease: 93% [95% CI, 91-95]). There was a negative correlation between VE estimates against infection and severe disease, and the cumulative incidence of cases before the start of the study or incidence rates during the study period. We found clear empirical evidence that higher levels of preexisting immunity were associated with lower VE estimates. Prior infections should be treated as both a confounder and effect modificatory when the policies target the whole population or are stratified by infection history, respectively.

With the emergence of SARS-CoV-2, various non-pharmaceutical interventions were adopted to control virus transmission, including school closures. Subsequently, the introduction of vaccines mitigated not only disease severity but also the spread of SARS-CoV-2. This study leveraged an adapted SIR model and non-linear mixed-effects modeling to quantify the impact of remote learning, school holidays, the emergence of Variants of Concern (VOCs), and the role of vaccinations in controlling SARS-CoV-2 spread across 16 German federal states with an age-stratified approach. Findings highlight a significant inverse correlation (Spearman's ρ = -0.92, p < 0.001) between vaccination rates and peak incidence rates across all age groups. Model-parameter estimation using the observed number of cases stratified by federal state and age allowed to assess the effects of school closure and holidays, considering adjustments for vaccinations and spread of VOCs over time. Here, modeling revealed significant (p < 0.001) differences in the virus's spread among pre-school children (0-4), children (5-11), adolescents (12-17), adults (18-59), and the elderly (60+). The transition to remote learning emerged as a critical measure in significantly reducing infection rates among children and adolescents (p < 0.001), whereas an increased infection risk was noted among the elderly during these periods, suggesting a shift in infection networks due to altered caregiving roles. Conversely, during school holiday periods, infection rates among adolescents mirrored those observed when schools were open. Simulation exercises based on the model provided evidence that COVID-19 vaccinations might serve a dual purpose: they protect the vaccinated individuals and contribute to the broader community's safety.

We used a spatially explicit agent-based model of SARS-CoV-2 transmission combined with spatially fine-grained COVID-19 observation data from Public Health Scotland to investigate the initial rise of the Omicron (BA.1) variant of concern. We evaluated plausible scenarios for transmission rate advantage and vaccine immune escape relative to the Delta variant based on the data that would have been available at that time. We also explored possible outcomes of different levels of imposed non-pharmaceutical intervention. The initial results of these scenarios were used to inform the Scottish Government in the early outbreak stages of the Omicron variant. Using the model with parameters fit over the Delta variant epidemic, some initial assumptions about Omicron transmission rate advantage and vaccine escape, and a simple growth rate fitting procedure, we were able to capture the initial outbreak dynamics for Omicron. We found that the modelled dynamics hold up to retrospective scrutiny. The modelled imposition of extra non-pharmaceutical interventions planned by the Scottish Government at the time would likely have little effect in light of the transmission rate advantage held by the Omicron variant and the fact that the planned interventions would have occurred too late in the outbreak's trajectory. Finally, we found that any assumptions made about the projected distribution of vaccines in the model population had little bearing on the outcome, in terms of outbreak size and timing. Instead, it was the landscape of prior immunity that was most important.

Amidst the ongoing global challenge of the SARS-CoV-2 pandemic, the quest for effective antiviral medications remains paramount. This comprehensive review delves into the dynamic landscape of FDA-approved medications repurposed for COVID-19, categorized as antiviral and non-antiviral agents. Our focus extends beyond conventional narratives, encompassing vaccination targets, repurposing efficacy, clinical studies, innovative treatment modalities, and future outlooks. Unveiling the genomic intricacies of SARS-CoV-2 variants, including the WHO-designated Omicron variant, we explore diverse antiviral categories such as fusion inhibitors, protease inhibitors, transcription inhibitors, neuraminidase inhibitors, nucleoside reverse transcriptase, and non-antiviral interventions like importin α/β1-mediated nuclear import inhibitors, neutralizing antibodies, and convalescent plasma. Notably, Molnupiravir emerges as a pivotal player, now licensed in the UK. This review offers a fresh perspective on the historical evolution of COVID-19 therapeutics, from repurposing endeavors to the latest developments in oral anti-SARS-CoV-2 treatments, ushering in a new era of hope in the battle against the pandemic.

Long COVID, a highly heterogeneous syndrome affecting millions of people worldwide, is emerging as an urgent public health threat, but data on the predictors of specific clinical manifestations over long follow-up periods are limited. The aim of this study is to investigate the role of viral variants and other predictors in long COVID incidence and clinical manifestations.

All COVID-19 patients aged > 18 years and hospitalized from March 1 2020 to April 2022 in two Italian University Hospitals were enrolled. Incidence and clinical presentation of long COVID were assessed through structured questionnaires delivered by phone calls. The association between possible risk factors collected during hospitalization and long COVID was reported using an adjusted logistic regression and reported as odds ratios (ORs) with their 95% confidence intervals (CIs).

Among 1,012 recruited patients, over a median follow-up of 19 months (IQR: 15-24 months), the cumulative incidence of long COVID was 91.7%, with the most common clinical manifestations involving the respiratory system (80.5%) and the neurological system (77.3%). Among 1,012 recruited patients, over a median follow-up of 19 months (IQR: 15-24 months), the cumulative incidence of long COVID was 91.7%, with the most common clinical manifestations involving the respiratory system (80.5%) and the neurological system (77.3%). Overall, 54% reported long COVID symptomatology between 18 and 24 months. Multivariate analysis suggested that being vaccinated against SARS-CoV-2 was associated with reduced odds of reporting any long COVID symptomatology (OR: 0.34; 95% CI: 0.21-0.58), while infection with the Delta variant was a strong predictor (OR: 9.61, p < 0.0001) for the development of post-COVID conditions characterized by neuropsychiatric symptoms.

In this study long COVID symptoms were still highly prevalent after 18-24 months of follow-up and, when compared to wild-type virus, infection with the Delta variant was associated with a higher risk of developing a neurological post-COVID condition.

This Special Issue, titled 'Vaccination and Global Health,' compiles 11 broad-ranging papers, each exploring critical facets of vaccination, public health, and global healthcare systems [...].

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to the genus Beta coronavirus and the family of Coronaviridae. It is a positive-sense, non-segmented single-strand RNA virus. Four common types of human coronaviruses circulate globally, particularly in the fall and winter seasons. They are responsible for 10%-30% of all mild upper respiratory tract infections in adults. These are 229E, NL63 of the Alfacoronaviridae family, OC43, and HKU1 of the Betacoronaviridae family. However, there are three highly pathogenic human coronaviruses: SARS-CoV-2, Middle East respiratory syndrome coronavirus, and the latest pandemic caused by the SARS-CoV-2 infection. All viruses, including SARS-CoV-2, have the inherent tendency to evolve. SARS-CoV-2 is still evolving in humans. Additionally, due to the development of herd immunity, prior infection, use of medication, vaccination, and antibodies, the viruses are facing immune pressure. During the replication process and due to immune pressure, the virus may undergo mutations. Several SARS-CoV-2 variants, including the variants of concern (VOCs), such as B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617/B.1.617.2 (Delta), P.1 (Gamma), and B.1.1.529 (Omicron) have been reported from various parts of the world. These VOCs contain several important mutations; some of them are on the spike proteins. These mutations may lead to enhanced infectivity, transmissibility, and decreased neutralization efficacy by monoclonal antibodies, convalescent sera, or vaccines. Mutations may also lead to a failure of detection by molecular diagnostic tests, leading to a delayed diagnosis, increased community spread, and delayed treatment. We searched PubMed, EMBASE, Covariant, the Stanford variant Database, and the CINAHL from December 2019 to February 2023 using the following search terms: VOC, SARS-CoV-2, Omicron, mutations in SARS-CoV-2, etc. This review discusses the various mutations and their impact on infectivity, transmissibility, and neutralization efficacy.

In January 2020, WHO declared the 2019 Coronavirus Disease (COVID-19) a pandemic. Though COVID-19 vaccines are recommended, ongoing surveillance is crucial due to potential unforeseen events. Evaluation of long-term effectiveness and safety and addressing emerging variants are vital. This study integrates systematic reviews to assess COVID-19 vaccine efficacy, immunogenicity, and safety comprehensively.

This study was an umbrella review study on the feasibility and effectiveness of vaccines for COVID-19. We conducted a comprehensive search in PubMed, Web of Sciences, and Scopus, using MeSH terms and keywords related to COVID-19 vaccines. Inclusion criteria comprised peer-reviewed systematic reviews and meta-analyses in English, focusing on feasibility and effectiveness. Exclusion criteria targeted non-systematic reviews exclusively on vaccine safety and duplicates. Two independent reviewers screened and resolved discrepancies. Data extraction included key details. Methodological quality was assessed using the ROBIS tool. Data synthesis involves narrative and, if applicable, quantitative synthesis (meta-analysis). Reporting followed PRISMA guidelines.

A total of 32 systematic reviews were included in the study, of which 20 also conducted a meta-analysis. The studies investigated in the included reviews ranged from 7 to 74. The included articles were conducted in various countries around the globe. The findings indicated that COVID-19 vaccines are generally safe and effective for individuals with various medical conditions. The overall risk of bias for the included studies was assessed as low risk.

The study outcomes indicated that mRNA vaccines exhibit a higher incidence of adverse events but demonstrate greater efficacy. Conversely, inactivated and protein subunit vaccines are safer but exhibit lower efficiency. Moreover, the vaccine is considered safe for individuals with specific conditions such as inflammatory bowel disease, solid organ transplant recipients, children, pregnant individuals, and those with hematologic problems. Ultimately, the acceptance of the COVID-19 vaccine among individuals is influenced by various factors, including geographic, socioeconomic, and pandemic-related considerations.

SARS-CoV-2 variants of concern (VOCs) emerged and rapidly replaced the original strain worldwide. The increased transmissibility of these new variants led to increases in infections, hospitalizations, and mortality. However, there is a scarcity of retrospective investigations examining the severity of all the main VOCs in presence of key public health measures and within various social determinants of health (SDOHs).

This study aims to provide a retrospective assessment of the clinical severity of COVID-19 VOCs in the context of heterogenous SDOHs and vaccination rollout.

We used a population-based retrospective cohort design with data from the British Columbia COVID-19 Cohort, a linked provincial surveillance platform. To assess the relative severity (hospitalizations, intensive care unit [ICU] admissions, and deaths) of Gamma, Delta, and Omicron infections during 2021 relative to Alpha, we used inverse probability treatment weighted Cox proportional hazard modeling. We also conducted a subanalysis among unvaccinated individuals, as assessed severity differed across VOCs and SDOHs.

We included 91,964 individuals infected with a SARS-CoV-2 VOC (Alpha: n=20,487, 22.28%; Gamma: n=15,223, 16.55%; Delta: n=49,161, 53.46%; and Omicron: n=7093, 7.71%). Delta was associated with the most severe disease in terms of hospitalization, ICU admissions, and deaths (hospitalization: adjusted hazard ratio [aHR] 2.00, 95% CI 1.92-2.08; ICU: aHR 2.05, 95% CI 1.91-2.20; death: aHR 3.70, 95% CI 3.23-4.25 relative to Alpha), followed generally by Gamma and then Omicron and Alpha. The relative severity by VOC remained similar in the unvaccinated individual subanalysis, although the proportion of individuals infected with Delta and Omicron who were hospitalized was 2 times higher in those unvaccinated than in those fully vaccinated. Regarding SDOHs, the proportion of hospitalized individuals was higher in areas with lower income across all VOCs, whereas among Alpha and Gamma infections, 2 VOCs that cocirculated, differential distributions of hospitalizations were found among racially minoritized groups.

Our study provides robust severity estimates for all VOCs during the COVID-19 pandemic in British Columbia, Canada. Relative to Alpha, we found Delta to be the most severe, followed by Gamma and Omicron. This study highlights the importance of targeted testing and sequencing to ensure timely detection and accurate estimation of severity in emerging variants. It further sheds light on the importance of vaccination coverage and SDOHs in the context of pandemic preparedness to support the prioritization of allocation for resource-constrained or minoritized groups.

The ongoing COVID-19 pandemic has significantly impacted special populations, including immunocompromised individuals, people living with HIV (PLWHIV), pediatric patients, and those with chronic liver disease (CLD). This scoping review aims to map the clinical outcomes of these vulnerable groups when infected with various SARS-CoV-2 variants. The review identifies trends and patterns, noting that early variants, such as Alpha and Delta, are associated with more severe outcomes, including higher hospitalization and mortality rates. In contrast, the Omicron variant, despite its increased transmissibility, tends to cause milder clinical manifestations. The review highlights the necessity for ongoing surveillance and tailored healthcare interventions due to the heterogeneity of patient populations and the evolving nature of the virus. Continuous monitoring and adaptive healthcare strategies are essential to mitigate the impact of COVID-19 on these high-risk groups.

Treatment with antiviral drugs for non-severe, early time from onset, adult outpatients with Coronavirus Disease 2019 (COVID-19) had not been established in 2021. However, some new variants of SARS-CoV-2 had caused rapid exacerbation and hospitalization among non-elderly outpatients with COVID-19, contributing to widespread crises within healthcare systems.

From July to October 2021, we urgently assessed a therapeutic program using oral colchicine (1.0 mg loading dose, followed approximately half a day later by 0.5 mg twice daily for 5 days, and then 0.5 mg once daily for 4 days) and low-dose aspirin (100 mg once daily for 10 days), for non-elderly, non-severe, early time from onset, adult outpatients with COVID-19. To verify its effectiveness, we set loxoprofen as a control arm, and com parison of these two arms was performed. The primary outcomes were hospitalization, criticality, and death rates.

Thirty-eight patients (23 receiving colchicine and low-dose aspirin [CA]; 15 receiving loxoprofen [LO]) were evaluated. Hospitalization rate was lower in the CA group (1/23; 4.3%) than in the LO group (2/15; 13.3%); however, no significant difference was found between the two groups (p=0.34). No critical cases, deaths, or severe adverse events were found in either group.

Our CA regimen did not show superiority over LO treatment. However, our clinical experience should be recorded as part of community health care activities carried out in Kurume City against the unprece dented COVID-19 pandemic.

We undertook a national analysis to characterise and identify risk factors for acute respiratory infections (ARIs) resulting in hospitalisation during the winter period in Scotland.

A population-based retrospective cohort analysis.

Scotland.

The study involved 5.4 million residents in Scotland.

Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association between risk factors and ARI hospitalisation.

Between 1 September 2022 and 31 January 2023, there were 22,284 (10.9% of 203,549 with any emergency hospitalisation) ARI hospitalisations (1759 in children and 20,525 in adults) in Scotland. Compared with the reference group of children aged 6-17 years, the risk of ARI hospitalisation was higher in children aged 3-5 years (aHR = 4.55; 95% CI: 4.11-5.04). Compared with those aged 25-29 years, the risk of ARI hospitalisation was highest among the oldest adults aged ≥80 years (aHR = 7.86; 95% CI: 7.06-8.76). Adults from more deprived areas (most deprived vs. least deprived, aHR = 1.64; 95% CI: 1.57-1.72), with existing health conditions (≥5 vs. 0 health conditions, aHR = 4.84; 95% CI: 4.53-5.18) or with history of all-cause emergency admissions (≥6 vs. 0 previous emergency admissions, aHR = 7.53; 95% CI: 5.48-10.35) were at a higher risk of ARI hospitalisations. The risk increased by the number of existing health conditions and previous emergency admission. Similar associations were seen in children.

Younger children, older adults, those from more deprived backgrounds and individuals with greater numbers of pre-existing conditions and previous emergency admission were at increased risk for winter hospitalisations for ARI.

The SARS-CoV-2 pandemic has heightened concerns about immunological protection, especially for individuals with inborn errors of immunity (IEI). While COVID-19 vaccines elicit strong immune responses in healthy individuals, their effectiveness in IEI patients remains unclear, particularly against new viral variants and vaccine formulations. This uncertainty has led to anxiety, prolonged self-isolation, and repeated vaccinations with uncertain benefits among IEI patients. Despite some level of immune response from vaccination, the definition of protective immunity in IEI individuals is still unknown. Given their susceptibility to severe COVID-19, strategies such as immunoglobulin replacement therapy (IgRT) and monoclonal antibodies have been employed to provide passive immunity, and protection against both current and emerging variants. This review examines the efficacy of COVID-19 vaccines and antibody-based therapies in IEI patients, their capacity to recognize viral variants, and the necessary advances required for the ongoing protection of people with IEIs.

Definitive data demonstrating the utility of coronavirus disease 2019 (COVID-19) convalescent plasma (CCP) for treating immunocompromised patients remains elusive. To better understand the mechanism of action of CCP, we studied viral replication and disease progression in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected hamsters treated with CCP obtained from recovered COVID-19 patients that were also vaccinated with an mRNA vaccine, hereafter referred to as Vaxplas. Vaxplas transiently enhanced disease severity and lung pathology in hamsters treated near peak viral replication due to immune complex and activated complement deposition in pulmonary endothelium, and recruitment of M1 proinflammatory macrophages into the lung parenchyma. However, aside from one report, transient enhanced disease has not been reported in CCP recipient patients, and the transient enhanced disease in Vaxplas hamsters may have been due to mismatched species IgG-FcR interactions, infusion timing, or other experimental factors. Despite transient disease enhancement, Vaxplas dramatically reduced virus replication in lungs and improved infection outcome in SARS-CoV-2-infected hamsters.

The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection ($P{E}_S$) by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case-control study design to derive $P{E}_S$. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for $P{E}_S$ and true value of $P{E}_S$ was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of $P{E}_S$ and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated $P{E}_S$, but the underestimate was considerable only when > 50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated $P{E}_S$. The test-negative design was applied to national-level testing data in Qatar to estimate $P{E}_S$ for SARS-CoV-2. $P{E}_S$ against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI, 93.6-98.6) and 85.5% (95% CI, 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.

In adults, viral load and disease severity can differ by SARS-CoV-2 variant, patterns less understood in children. We evaluated symptomatology, cycle threshold (Ct) values, and SARS-CoV-2 variants among 2,299 pediatric SARS-CoV-2 patients (0-21 years of age) in Colorado, USA, to determine whether children infected with Delta or Omicron had different symptom severity or Ct values than during earlier variants. Children infected during the Delta and Omicron periods had lower Ct values than those infected during pre-Delta, and children <1 year of age had lower Ct values than older children. Hospitalized symptomatic children had lower Ct values than asymptomatic patients. Compared with pre-Delta, more children infected during Delta and Omicron were symptomatic (75.4% pre-Delta, 95.3% Delta, 99.5% Omicron), admitted to intensive care (18.8% pre-Delta, 39.5% Delta, 22.9% Omicron), or received oxygen support (42.0% pre-Delta, 66.3% Delta, 62.3% Omicron). Our data reinforce the need to include children, especially younger children, in pathogen surveillance efforts.

The COVID-19 pandemic has affected hundreds of millions of individuals and caused more than six million deaths. The prolonged pandemic duration and the continual inter-individual transmissibility have contributed to the emergence of a wide variety of SARS-CoV-2 variants. Genomic surveillance and phylogenetic studies have shown that substantial mutations in crucial supersites of spike glycoprotein modulate the binding affinity of the evolved SARS-COV-2 lineages to ACE2 receptors and modify the binding of spike protein with neutralizing antibodies. The immunological spike mutations have been associated with differential transmissibility, infectivity, and therapeutic efficacy of the vaccines and the immunological therapies among the new variants. This review highlights the diverse genetic mutations assimilated in various SARS-CoV-2 variants. The implications of the acquired mutations related to viral transmission, infectivity, and COVID-19 severity are discussed. This review also addresses the effectiveness of human neutralizing antibodies induced by SARS-CoV-2 infection or immunization and the therapeutic antibodies against the ascended variants.

The COVID-19 pandemic led to 231,841 deaths and 940,243 hospitalisations in England, by the end of March 2023. This paper calculates the real-time infection hospitalisation risk (IHR) and infection fatality risk (IFR) using the Office for National Statistics Coronavirus Infection Survey (ONS CIS) and the Real-time Assessment of Community Transmission Survey between November 2020 to March 2023. The IHR and the IFR in England peaked in January 2021 at 3.39% (95% Credible Intervals (CrI): 2.79, 3.97) and 0.97% (95% CrI: 0.62, 1.36), respectively. After this time, there was a rapid decline in the severity from infection, with the lowest estimated IHR of 0.32% (95% CrI: 0.27, 0.39) in December 2022 and IFR of 0.06% (95% CrI: 0.04, 0.08) in April 2022. We found infection severity to vary more markedly between regions early in the pandemic however, the absolute heterogeneity has since reduced. The risk from infection of SARS-CoV-2 has changed substantially throughout the COVID-19 pandemic with a decline of 86.03% (80.86, 89.35) and 89.67% (80.18, 93.93) in the IHR and IFR, respectively, since early 2021. From April 2022 until March 2023, the end of the ONS CIS study, we found fluctuating patterns in the severity of infection with the resumption of more normative mixing, resurgent epidemic waves, patterns of waning immunity, and emerging variants that have shown signs of convergent evolution.

Vaccine hesitancy and refusal can hinder the control of infectious diseases such as coronavirus disease 2019 (COVID-19). Although forcibly displaced individuals are at high risk of contracting COVID-19, evidence shows that they are less likely to accept the COVID-19 vaccine. Given their predicament, the factors influencing vaccine uptake in the general population might differ vastly from those in displaced populations. Given the limited evidence on vaccine uptake from humanitarian settings, the current study examined the determinants of COVID-19 vaccine uptake among the forcibly displaced in Libya.

Data were extracted from the World Bank/United Nations High Commissioner for Refugees (UNHCR) microdata repository. Data were collected between April and July 2021 after the rollout of the first dose of the COVID-19 vaccine in Libya. Percentages, means, and standard deviations were used to quantify the distribution of the sample population. Logistic regression models were employed to identify factors influencing COVID-19 vaccine uptake.

Odds ratios (ORs) with p values are used to present the regression analysis results. The study revealed that people unaffected by COVID-19 were less likely (OR = .71, 95%CI = 0.67-0.89) to accept the vaccine. Similarly, individuals with access to free COVID-19 vaccines were more likely to be vaccinated than those without free vaccines (OR = 38, 95%CI = 0.19-0.28). Finally, the results indicated that individuals were six times more likely to be vaccinated at mass vaccination sites ((OR = 6.31, 95%CI = 5.46- 7.94) and 1.92 times more likely to be vaccinated at local health centers (OR = 1.92, 95%CI = 0.1.72-3.11) than they were at hospitals and distant health facilities.

Implementing comprehensive mass vaccination venues, public education initiatives, and awareness campaigns regarding the importance of vaccination can decrease vaccine hesitancy among the forcibly displaced.

We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a highly contagious and dangerous virus that caused the global COVID-19 pandemic in early 2020. It primarily affects the respiratory system, leading to severe illness and high rates of mortality worldwide. The virus enters the body by binding to a receptor called ACE2, which is present in specific cells of the lungs known as type 2 alveolar epithelial cells. Numerous studies have investigated the consequences of SARS-CoV-2 infection, revealing various impacts on the body. This review provides an overview of SARS-CoV-2, including its structure and how it infects cells. It also examines the different variants of concern, such as Alpha, Beta, Gamma, Delta, and the more recent Omicron variant, discussing their characteristics and the level of damage they cause. The usage of drugs to treat COVID-19 is another aspect that has been covered and compares the effectiveness and use of antiviral drugs in the treatment and its potential benefits in COVID-19 treatment. Furthermore, this review explores the consequences and abnormalities associated with SARS-CoV-2 infection, including its impact on various organs and systems in the body. And also discussing the different COVID-19 vaccines available and their effectiveness in preventing infection and reducing the severity of illness. The current review ensures the recent update of the COVID research with expert's knowledge, collection of numerous data from reliable sources and methodologies as well as update of findings based on reviews. This review also provided clear contextual explanations to aid the interpretation and application of the results. The main motto and limitation of this manuscript are to address the computational methods of drug discovery against the rapidly evolving SARS-CoV-2 virus, which has been discussed. Additionally, current computational approaches which are cost effective and can able to predict the therapeutic agents for the treatment against the virus have also been discussed.

Background and Objectives: Coronavirus disease 2019 (COVID-19) caused several cardiovascular complications, including acute myocardial infarction (AMI), in infected patients. This study aims to understand the overall trends of AMI among COVID-19 patients during the first two years of the pandemic and the disparities and outcomes between the first and second years. Materials and Methods: The retrospective analysis was conducted via the 2020 and 2021 National Inpatient Sample (NIS) database for hospitalizations between April 2020 and December 2021 being analyzed for adults with a primary diagnosis of COVID-19 who experienced events of AMI. A comparison of month-to-month events of AMI and mortality of AMI patients with concomitant COVID-19 was made alongside their respective patient characteristics. Results: Out of 2,541,992 COVID-19 hospitalized patients, 3.55% experienced AMI. The highest rate of AMI was in December 2021 (4.35%). No statistical differences in trends of AMI mortality were noted over the 21 months. AMI cases in 2021 had higher odds of undergoing PCI (aOR 1.627, p < 0.01). They experienced higher risks of acute kidney injury (aOR 1.078, p < 0.01), acute ischemic stroke (aOR 1.215, p < 0.01), cardiac arrest (aOR 1.106, p < 0.01), need for mechanical ventilation (aOR 1.133, p < 0.01), and all-cause mortality (aOR 1.032, 95% CI 1.001-1.064, p = 0.043). Conclusions: The incidence of AMI among COVID-19 patients fluctuated over the 21 months of this study, with a peak in December 2021. COVID-19 patients reporting AMI in 2021 experienced higher overall odds of multiple complications, which could relate to the exhaustive burden of the pandemic in 2021 on healthcare, the changing impact of the virus variants, and the hesitancy of infected patients to seek care.