The real-life impact of vaccination on COVID-19 mortality in Europe and Israel

Case-cohort design as an efficient approach to evaluating COVID-19 vaccine effectiveness, waning, heterologous immune effect and optimal dosing interval

Though widely applied in other epidemiological fields, the case-cohort study design has seen little application in the field of vaccinology. Case-cohort studies use probabilistic sampling and reweighting to draw inferences about effects (in this case vaccine efficacy) at the population level in an efficient manner. The SARS-CoV-2 pandemic was met with high vaccine uptake, and high rates of population testing prior to the emergence of Omicron variants of concern, in Ontario, Canada, providing an ideal environment for application of case-cohort methodology. We combined a population-based case line list and vaccination database for the province of Ontario between December 2020 and October 2021. Risk of infection after vaccination was evaluated in all laboratory-confirmed vaccinated SARS-CoV-2 cases, and a 2 % sample of vaccinated controls, evaluated using survival analytic methods, including construction of Cox proportional hazards models. Vaccination status was treated as a time-varying covariate. First and second doses of SARS-CoV-2 vaccine markedly reduced risk of infection (first dose efficacy 68 %, 95 % CI 67 %-69 %; second dose efficacy 88 %, 95 % CI 87-88 %). In multivariable models, extended dosing intervals were associated with lowest risk of breakthrough infection (HR for redosing 0.64 (95 % CI 0.61-0.67) at 6-8 weeks). Heterologous vaccine schedules that mixed viral vector vaccine first doses with mRNA second doses were significantly more effective than mRNA only vaccines. Risk of infection largely vanished during the time period 4-6 months after the second vaccine dose, but rose markedly thereafter. We conclude that a case-cohort design provided an efficient means to identify strong protective effects associated with SARS-CoV-2 vaccination in real time, and also served to quantify the timing and magnitude of infection breakthrough risk in the same cohort. Heterologous vaccination and extended dosing intervals improved the durability of immune response.

SARS-CoV-2 infection and vaccination in patients with pituitary diseases: the experience of a Brazilian reference center

PURPOSE

To evaluate the prevalence and characteristics of SARS-CoV-2 infection, and the prevalence, efficacy, and safety of anti-SARS-CoV-2 vaccination in patients with pituitary diseases.

METHODS

Observational, cross-sectional study of adult patients with pituitary diseases followed in a reference center. Clinical data were collected and a questionnaire about SARS-CoV-2 infection, vaccination and its possible adverse effects was applied. COVID-19 disease severity was defined as mild, moderate, and severe according to the WHO classification.

RESULTS

145 patients were studied (79 women; age 50 ± 15.8 years; duration of pituitary disease 16.8 ± 11.5 years), the cause of pituitary disease was tumoral in 74.5%, and 45.9% were on glucocorticoid replacement due to ACTH deficiency. SARS-CoV-2 infection was confirmed in 51 patients (35.2%; 32 women; age 53.8 ± 14.8 years, 22 before vaccination), with 28 (54.9%), 17 (33.3%) and 6 (11.8%) cases of mild, moderate, and severe disease, respectively, and hospitalization was indicated in 7 (14%) cases. One mild case presented pituitary apoplexy after SARS-CoV-2 infection. Advanced age was a risk factor for COVID-19. Patients with moderate and severe forms of COVID-19 had higher prevalence of dyslipidemia and duration of pituitary disease. All but one of the participants were vaccinated against COVID-19, and 60.4% had adverse events, the most common local pain (54.0%), fever (33.3%), and headache (18.4%), with one case of alopecia and two of persistent fatigue.

CONCLUSION

The prevalence of SARS-CoV-2 infection in our cohort was 35.2%, including 14% of moderate and severe cases requiring hospitalization. The vaccination was universal and safe.

Braving the waves: exploring capability well-being patterns in seven European countries during the COVID-19 pandemic

The COVID-19 pandemic considerably impacted the lives of European citizens. This study aims to provide a nuanced picture of well-being patterns during the pandemic across Europe with a special focus on relevant socio-economic sub-groups. This observational study uses data from a repeated, cross-sectional, representative population survey with nine waves of data from seven European countries from April 2020 to January 2022. The analysis sample contains a total of 25,062 individuals providing 64,303 observations. Well-being is measured using the ICECAP-A, a multi-dimensional instrument for approximating capability well-being. Average levels of ICECAP-A index values and sub-dimension scores were calculated across waves, countries, and relevant sub-groups. In a fixed effects regression framework, associations of capability well-being with COVID-19 incidence, mortality, and the stringency of the imposed lockdown measures were estimated. Denmark, the Netherlands, and France experienced a U-shaped pattern in well-being (lowest point in winter 2020/21), while well-being in the UK, Germany, Portugal, and Italy followed an M-shape, with increases after April 2020, a drop in winter 2020, a recovery in the summer of 2021, and a decline in winter 2021. However, observed average well-being reductions were generally small. The largest declines were found in the well-being dimensions attachment and enjoyment and among individuals with a younger age, a financially unstable situation, and lower health. COVID-19 mortality was consistently negatively associated with capability well-being and its sub-dimensions, while stringency and incidence rate were generally not significantly associated with well-being. Further investigation is needed to understand underlying mechanisms of presented patterns.

Neurovascular Adverse Effects of Sars-Cov-2 Vaccination

The global deployment of SARS-CoV-2 vaccines has been pivotal in curbing the COVID-19 pandemic, reducing morbidity and mortality associated with the virus. While most of these vaccines have demonstrated high efficacy and overall safety, emerging reports have highlighted potential neurovascular adverse effects, albeit uncommon, associated with these vaccinations. This review aims to assess and summarize the current knowledge on the neurovascular complications arising post-SARS-CoV-2 vaccination. We conducted an extensive literature review, focusing on clinical studies and case reports to identify reported neurovascular events, such as ischemic stroke, cerebral sinus venous thrombosis, intracerebral hemorrhage, pituitary apoplexy and primary CNS angiitis Despite the relative rarity of these events, their impact on affected individuals underscores the importance of ongoing surveillance, early detection, and management strategies. We aim to provide healthcare professionals with the latest evidence on neurovascular adverse effects, facilitating informed decision-making in the context of SARS-CoV-2 vaccination programs. Furthermore, we highlight areas requiring further research to understand the pathophysiology of these adverse events better and to develop targeted prevention and treatment strategies.

Marine natural products and human immunity: novel biomedical resources for anti-infection of SARS-CoV-2 and related cardiovascular disease

Marine natural products (MNPs) and marine organisms include sea urchin, sea squirts or ascidians, sea cucumbers, sea snake, sponge, soft coral, marine algae, and microalgae. As vital biomedical resources for the discovery of marine drugs, bioactive molecules, and agents, these MNPs have bioactive potentials of antioxidant, anti-infection, anti-inflammatory, anticoagulant, anti-diabetic effects, cancer treatment, and improvement of human immunity. This article reviews the role of MNPs on anti-infection of coronavirus, SARS-CoV-2 and its major variants (such as Delta and Omicron) as well as tuberculosis, H. Pylori, and HIV infection, and as promising biomedical resources for infection related cardiovascular disease (irCVD), diabetes, and cancer. The anti-inflammatory mechanisms of current MNPs against SARS-CoV-2 infection are also discussed. Since the use of other chemical agents for COVID-19 treatment are associated with some adverse effects in cardiovascular system, MNPs have more therapeutic advantages. Herein, it's time to protect this ecosystem for better sustainable development in the new era of ocean economy. As huge, novel and promising biomedical resources for anti-infection of SARS-CoV-2 and irCVD, the novel potential mechanisms of MNPs may be through multiple targets and pathways regulating human immunity and inhibiting inflammation. In conclusion, MNPs are worthy of translational research for further clinical application.

Network-based uncertainty quantification for mathematical models in epidemiology

After the new Coronavirus disease (COVID-19) emerged in the end of January 2020 in Germany, a large number of individuals suffered from severe symptoms and eventually needed intensive care in hospitals. Due to the rapid spread of the disease, the number of deceased individuals increased as well, which is a motivation to prevent as many new infections as possible. Therefore, the knowledge about the current evolution of the virus spread is crucial to predict its future behavior and to react with suitable interventions. In this paper, the evolution of the COVID-19 pandemic in Germany is forecasted by a network-based inference method, in which the interactions of individuals are taken into account using a contact matrix. Then the results are compared to the predictions without considering a contact matrix as well as to the logistic regression, which shows the advantage of incorporating the contact matrix. Furthermore, the basic reproduction number of the pandemic in Germany using a neural network approach is estimated and used for further predictions of the evolution of COVID-19 in Germany. In order to mathematically model the different compartments of the population in the considered regions, the classical SIR model is employed. In this work, we deploy the LASSO (Least Absolute Shrinkage and Selection Operator) for the unknown parameter estimation. Furthermore, we calculate and illustrate the MAPE (Mean Absolute Percentage Error) of the estimations to show the accuracy of the predictions. The results include model parameter estimation and model validation, as well as the outbreak forecasting using network-informed algorithms. Our findings show that the network-inference based approach outperforms the logistic regression as well as the neural network approach and the SIR model calibration without a contact network. Furthermore according to the results, the network-inference based approach is particularly suitable for short- to mid-term predictions, even when there is not much information about the new disease. Moreover, the predictions based on the estimation of the reproduction number in Germany can yield more reliable results with increasing the availability of data, but could not outperform the network-inference based algorithm.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

BACKGROUND

The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19).

METHODOLOGY

PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542.

FINDINGS

In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias.

INTERPRETATION

The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

Challenging Axillary Lymph Nodes on PET/CT in Cancer Patients throughout COVID-19 Vaccination Era

BACKGROUND

The unexpected detection of axillary lymphadenopathy (AxL) in cancer patients (pts) represents a real concern during the COVID-19 vaccination era. Benign reactions may take place after vaccine inoculation, which can mislead image interpretation in patients undergoing F-18-FDG, F-18-Choline, and Ga-68-DOTATOC PET/CT. They may also mimic loco-regional metastases or disease. We assessed PET/CT findings after COVID-19 first dose vaccination in cancer patients and the impact on their disease course management.

METHODS

We evaluated 333 patients undergoing PET/CT (257 F-18-FDG, 54 F-18-Choline, and 23 Ga-68 DOTATOC) scans after the first vaccination with mRNA vaccine (Pfizer-BioNTech) (study group; SG). The uptake index (SUVmax) of suspected AxL was defined as significant when the ratio was > 1.5 as compared to the contralateral lymph nodes. Besides, co-registered CT (Co-CT) features of target lymph nodes were evaluated. Nodes with aggregate imaging positivity were further investigated.

RESULTS

Overall, the prevalence of apparently positive lymph nodes on PET scans was 17.1% during the vaccination period. 107 pts of the same setting, who had undergone PET/CT before the COVID-19 pandemic, represented the control group (CG). Only 3 patients of CG showed reactive lymph nodes with a prevalence of 2.8% (p < 0.001 as compared to the vaccination period). 84.2% of SG patients exhibited benign characteristics on co-CT images and only 9 pts needed thorough appraisal.

CONCLUSION

The correct interpretation of images is crucial to avoid unnecessary treatments and invasive procedures in vaccinated cancer pts. A detailed anamnestic interview and the analysis of lymph nodes' CT characteristics, after performing PET/CT, may help to clear any misleading diagnosis.

COVID-19 in Pakistan: A national analysis of five pandemic waves

OBJECTIVES

The COVID-19 pandemic showed distinct waves where cases ebbed and flowed. While each country had slight, nuanced differences, lessons from each wave with country-specific details provides important lessons for prevention, understanding medical outcomes and the role of vaccines. This paper compares key characteristics from the five different COVID-19 waves in Pakistan.

METHODS

Data was sourced from daily national situation reports (Sitreps) prepared by the National Emergency Operations Centre (NEOC) in Islamabad. We use specific criteria to define COVID-19 waves. The start of each COVID-19 wave is marked by the day of the lowest number of daily cases preceding a sustained increase, while the end is the day with the lowest number of cases following a 7-days decline, which should be lower than the 7 days following it. Key variables such as COVID-19 tests, cases, and deaths with their rates of change to the peak and then to the trough are used to draw descriptive comparisons. Additionally, a linear regression model estimates daily new COVID-19 deaths in Pakistan.

RESULTS

Pakistan saw five distinct waves, each of which displayed the typical topology of a complete infectious disease epidemic. The time from wave-start to peak became progressively shorter, and from wave-peak to trough, progressively longer. Each wave appears to also be getting shorter, except for wave 4, which lasted longer than wave 3. A one percent increase in vaccinations decreased deaths by 0.38% (95% CI: -0.67, -0.08) in wave 5 and the association is statistically significant.

CONCLUSION

Each wave displayed distinct characteristics that must be interpreted in the context of the level of response and the variant driving the epidemic. Key indicators suggest that COVID-19 preventive measures kept pace with the disease. Waves 1 and 2 were mainly about prevention and learning how to clinically manage patients. Vaccination started late during wave 3 and its impact on hospitalizations and deaths became visible in wave 5. The impact of highly virulent strains Alpha/B.1.1.7 and Delta/B.1.617.2 variants during wave 3 and milder but more infectious Omicron/B.1.1.529 during wave 5 are apparent.

Patterns of protection, infection, and detection: Country-level effectiveness of COVID-19 vaccination in reducing mortality worldwide

Background

The relationship between COVID-19 vaccination and mortality has been established through clinical trials and other investigations at the individual level. In this study, we aimed to investigate the negative relationship between mortality and COVID-19 vaccination at country level.

Study design

We conducted an exploratory, correlational, country-level analysis of open data centralized by Our World in Data concerning the cumulative COVID-19 mortality for the winter wave (October 2021-March 2022) of the pandemic as function of the vaccination rate in October 2021.

Methods

We controlled variables that capture country-level social development and level of testing. We also deployed three segmentation tactics, distinguishing among countries based on their level of COVID-19 testing, age structure, and types of vaccines used.

Results

Controlling for confounding factors did not highlight a statistically significant relationship between vaccination and cumulative mortality in the total country sample. Still, a strong, significant, negative relationship between cumulative mortality (log scale) and vaccination was highlighted through segmentation analysis for countries positioned at the higher end of the social development spectrum. The strongest estimate for vaccine effectiveness at ecological level was obtained for the set of countries that used Western-only vaccines.

Conclusions

COVID-19 testing (log scale) has a significant and positive relationship with cumulative mortality for all subsamples, consistent with patterns of under- and overreporting of COVID-19 deaths at country level, partly driven by testing. This indicates that testing intensity should be controlled as a potential confounder in future ecological analyses of COVID-19 mortality.

The joint determination of morbidity and vaccination in the spatiotemporal epidemiology of COVID-19

This paper examines the mutual dependence between COVID-19 morbidity and vaccination rollout. A theory of endogenous immunization is proposed in which the decision to become vaccinated varies directly with the risks of contagion, and the public self-selects into self-protection. Hence, COVID-19 morbidity varies inversely with vaccination rollout, and vaccination rollout varies directly with COVID-19 morbidity. The paper leverages the natural sequencing between morbidity and immunization to identify the causal order in the dynamics of this relationship. A modified SIR model is estimated using spatial econometric methods for weekly panel data for Israel at a high level of spatial granularity. Connectivity between spatial units is measured using physical proximity and a unique mobility-based measure. Spatiotemporal models for morbidity and vaccination rollout show that not only does morbidity vary inversely with vaccination rollout, vaccination rollout varies directly with morbidity. The utility of the model for public health policy targeting, is highlighted.

Factors associated with COVID-19 vaccine uptake in adolescents: a national cross-sectional study, August 2021-January 2022, England

OBJECTIVES

To assess socioeconomic and geographical factors associated with COVID-19 vaccine uptake in pupils attending state-funded secondary schools in England.

DESIGN

Cross-sectional observational study.

SETTING

State-funded schools in England.

PARTICIPANTS

Pupils aged 12-17 years attending state-funded schools in England for the academic year 2021/2022.

OUTCOME MEASURES

Demographic, socioeconomic and geographical factors associated with vaccination uptake. We linked individual-level data from the English Schools Census to the National Immunisation Management System to obtain COVID-19 vaccination status of 3.2 million adolescents. We used multivariable logistic regression to assess demographic, socioeconomic and geographical factors associated with vaccination.

RESULTS

By 9 January 2022, 56.8% of adolescents aged 12-17 years old had received at least one dose, with uptake increasing from 48.7% in those aged 12 years old to 77.2% in those aged 17 years old. Among adolescents aged 12-15 years old, there were large variations in vaccine uptake by region and ethnic group. Pupils who spoke English as an additional language (38.2% vs 55.5%), with special educational needs (48.1% vs 53.5%), eligible for free school meals (35.9% vs 58.9%) and lived in more deprived areas (36.1% in most deprived vs 70.3% in least deprived) had lower vaccine uptake. Socioeconomic variables had greater impact on the odds of being vaccinated than geographical variables. School-level analysis found wide variation in vaccine uptake between schools even within the same region. Schools with higher proportions of pupils eligible for free school meals had lower vaccine uptake.

CONCLUSIONS

We found large differences in vaccine uptake by geographical region and ethnicity. Socioeconomic variables had a greater impact on the odds of being vaccinated than geographical variables. Further research is required to identify evidence-based interventions to improve vaccine uptake in adolescents.

Clinical characteristics and prognosis of temporary miller fisher syndrome following COVID-19 vaccination: a systematic review of case studies

BACKGROUND

Miller Fisher syndrome (MFS) is a subtype of Guillain-Barré syndrome (GBS) which is characterized by the three components of ophthalmoplegia, ataxia, and areflexia. Some studies reported MFS as an adverse effect of the COVID-19 vaccination. We aimed to have a detailed evaluation on demographic, clinical, and para-clinical characteristics of subjects with MFS after receiving COVID-19 vaccines.

MATERIALS AND METHODS

A thorough search strategy was designed, and PubMed, Web of Science, and Embase were searched to find relevant articles. Each screening step was done by twice, and in case of disagreement, another author was consulted. Data on different characteristics of the patients and types of the vaccines were extracted. The risk of bias of the studies was assessed using Joanna Briggs Institute (JBI) tools.

RESULTS

In this study, 15 patients were identified from 15 case studies. The median age of the patients was 64, ranging from 24 to 84 years. Ten patients (66.6%) were men and Pfizer made up 46.7% of the injected vaccines. The median time from vaccination to symptoms onset was 14 days and varied from 7 to 35 days. Furthermore,14 patients had ocular signs, and 78.3% (11/14) of ocular manifestations were bilateral. Among neurological conditions, other than MFS triad, facial weakness or facial nerve palsy was the most frequently reported side effect that was in seven (46.7%) subjects. Intravenous immunoglobulin (IVIg) was the most frequently used treatment (13/15, 86.7%). Six patients received 0.4 g/kg and the four had 2 g/kg. Patients stayed at the hospital from five to 51 days. No fatal outcomes were reported. Finally, 40.0% (4/15) of patients completely recovered, and the rest experienced improvement.

CONCLUSION

MFS after COVID-19 immunization has favorable outcomes and good prognosis. However, long interval from disease presentation to treatment in some studies indicates that more attention should be paid to MFS as the adverse effect of the vaccination. Due to the challenging diagnosis, MFS must be considered in list of the differential diagnosis in patients with a history of recent COVID-19 vaccination and any of the ocular complaints, ataxia, or loss of reflexes, specially for male patients in their 60s and 70s.

Correlates of COVID-19 vaccination intentions and opinions about mandates among four groups of adults in South Africa with distinct vaccine intentions: evidence from a large national survey

INTRODUCTION

Despite a high number of recorded COVID-19 infections and deaths in South Africa, COVID-19 vaccine coverage remained low in March 2022, ten months into the national vaccine roll-out. This study provides evidence on the correlates of vaccine intentions, attitudes towards vaccination and opinions about mandates.

METHODS

We used data from the second COVID-19 Vaccine Survey (CVACS), a telephone survey conducted February-March 2022 among 3,608 South African adults who self-reported not being vaccinated against COVID-19. The survey instrument was designed in consultation with government, policymakers, and civil society; and segmented the sample into four distinct groups with different vaccine intentions (synonymous with vaccine hesitancy levels). Kruskal-Wallis and Mann-Whitney tests were used to examine the sociodemographic characteristics, attitudes and behaviours associated with the different vaccination intentions groups. Thematic coding of responses to open-ended questions elicited insights on reasons for not being vaccinated and attitudes towards mandates.

RESULTS

Intentions to get vaccinated were greater among individuals with lower socio-economic status (Mann-Whitney Z = -11.3, p < 0.001); those believing the vaccine protects against death (Kruskal-Wallis Χ2 = 494, p < 0.001); and those who perceived themselves at risk of COVID-19-related illness (Χ2 = 126, p < 0.01). Vaccine intentions were lower among individuals who believed that the vaccine causes death (Χ2 = 163, p < 0.001); believed that the vaccine is unsafe for the babies of pregnant/breastfeeding mothers, or the chronically ill (Χ2 = 123, p < 0.01); those not trusting government health information about COVID-19 and the COVID-19 vaccine (Kendall's τ = -0.41, p < 0.01); and those in opposition to mandates (τ = 0.35, p < 0.001). Only 25% supported mandates, despite 48% thinking mandates would work well, with 54% citing individual rights as their main reason for mandate opposition.

CONCLUSION

The profile of individuals not vaccinated against COVID-19 as of March 2022 varied markedly by self-reported vaccination intentions, underscoring the importance of tailored demand-creation efforts. This paper highlights several factors which differ significantly across these groups. These findings could inform the design of future vaccination campaigns, potentially increasing their likelihood of success. This is an important policy objective given widespread vaccine hesitancy, and further work is required on this topic. Mandates remain an option to increase coverage but need to be carefully considered given extensive opposition.

Nasal application of sesame oil-based Anu taila as 'biological mask' for respiratory health during COVID-19

This article narrates the potential role of sesame oil-based Anu taila for respiratory health and the prevention of COVID-19. Ayurveda recommends the use of sesame oil and A. taila as a part of daily routine (dinacharya) for oral gargling and transnasal application (Nasya) for preventing upper respiratory tract infections. Recent studies on COVID-19 have elucidated the activity of certain fatty acids in restricting viral binding. Based on the evidence gathered from in-silico, pre-clinical, and pharmacological studies as well as references from classical textbooks of Ayurveda, this article infers that the transnasal application of sesame oil and/or A. taila could provide resilience/protection to the respiratory system. It can act as a 'biological mask' to prevent respiratory infections like COVID-19. Detailed pharmacological study can give fuller confirmation of our informed "inference" that A. taila offers a cost-effective intervention for the prevention of COVID-19 like infections of the upper respiratory tract.

COVID-19 mRNA vaccine immunogenicity decay and breakthrough illness in adolescents and young adults with childhood-onset rheumatic diseases

OBJECTIVES

To evaluate the humoral immunogenicity for 6 months after the two-dose coronavirus disease 2019 (COVID-19) mRNA vaccination in adolescents and young adults (AYAs) with childhood-onset rheumatic diseases (cRDs).

METHODS

This monocentric observational study was conducted between August 2020 and March 2022. Humoral immunogenicity was assessed at 2-3 weeks after first vaccine dose and 1, 3 and 6 months after the second dose by the cPass™ severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralization antibody (nAb) assay. An inhibition signal of ≥30% defined the seroconversion threshold and the readings were calibrated against the World Health Organization International Standard for SARS-CoV-2 antibodies.

RESULTS. ONE HUNDRED AND SIXTY-NINE

AYAs with cRDs were recruited [median age 16.8 years (interquartile range, IQR 14.7-19.5), 52% female, 72% Chinese]. JIA (58%) and SLE (18%) comprised the major diagnoses. After second vaccine dose, 99% seroconverted with a median nAb titre of 1779.8 IU/ml (IQR 882.8-2541.9), declining to 935.6 IU/ml (IQR 261.0-1514.9) and 683.2 IU/ml (IQR 163.5-1400.5) at the 3- and 6-month timepoints, respectively. The diagnosis of JIA [odds ratio (OR) 10.1, 95% CI 1.8-58.4, P = 0.010] and treatment with anti-TNF-α (aTNF) (OR 10.1, 95% CI 1.5-70.0, P = 0.019) were independently associated with a >50% drop of nAb titres at 6 months. Withholding MTX or MMF did not affect the vaccine response or decay rate. The COVID-19 breakthrough infection was estimated at 18.2 cases/1000 patient-months with no clinical risk factors identified.

CONCLUSION

Over half of AYAs with cRDs had a significant drop in SARS-CoV-2 nAb at 6-month despite an initial robust humoral response. JIA and aTNF usage are predictors of a faster decay rate.

Early impact of COVID-19 vaccination on older populations in four countries of the Americas, 2021

Objective

To estimate the early impact of coronavirus disease 2019 (COVID-19) vaccination on cases in older populations in four countries (Chile, Colombia, Guatemala, and the United States of America), and on deaths in Chile and Guatemala.

Methods

Data were obtained from national databases of confirmed COVID-19 cases and deaths and vaccinations between 1 July 2020 and 31 August 2021. In each country, pre- and post-vaccination incidence ratios were calculated for COVID-19 cases and deaths in prioritized groups (50-59, 60-69, and ≥70 years) compared with those in the reference group (<50 years). Vaccination effect was calculated as the percentage change in incidence ratios between pre- and post-vaccination periods.

Results

The ratio of COVID-19 cases in those aged ≥50 years to those aged <50 years decreased significantly after vaccine implementation by 9.8% (95% CI: 9.5 to 10.1%) in Chile, 22.5% (95% CI: 22.0 to 23.1%) in Colombia, 20.8% (95% CI: 20.6 to 21.1%) in Guatemala, and 7.8% (95% CI: 7.6 to 7.9%) in the USA. Reductions in the ratio were highest in adults aged ≥70 years. The effect of vaccination on deaths, with time lags incorporated, was highest in the age group ≥70 years in both Chile and Guatemala: 14.4% (95% CI: 11.4 to 17.4%) and 37.3% (95% CI: 30.9 to 43.7%), respectively.

Conclusions

COVID-19 vaccination significantly reduced morbidity in the early post-vaccination period in targeted groups. In the context of a global pandemic with limited vaccine availability, prioritization strategies are important to reduce the burden of disease in high-risk age groups.

Unveiling the Impact of COVID-19 Vaccines: A Meta-Analysis of Survival Rates Among Patients in the United States Based on Vaccination Status

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a significant number of cases and deaths worldwide. Vaccination is the most effective preventive measure against the disease. This study aimed to assess the mortality rates of COVID-19 patients in the United States and the effectiveness of Pfizer (Pfizer, NY, USA), Moderna (Moderna, MA, USA), and Janssen (Johnson & Johnson, NJ, USA) vaccines in preventing mortality. A systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA-2020) guidelines. Eligible studies reporting on the effectiveness of COVID-19 vaccines on patient outcomes were included. The search was performed in PubMed, Cochrane, and Google Scholar databases. The data were extracted, and risk ratios (RR) were calculated for mortality outcomes. The analysis was performed using Review Manager software, and bias assessments were conducted using the Joanna Briggs Institute (JBI) Meta-Analysis tools. A total of seven studies with 21,618,297 COVID-19 patients were included in the meta-analysis. The odds ratio (OR) for mortality among unvaccinated patients compared to vaccinated patients was 2.46 (95% CI: 1.71-3.53), indicating that unvaccinated patients were 2.46 times more likely to die from COVID-19. The findings of this study support the effectiveness of COVID-19 vaccination in reducing mortality among infected individuals. Unvaccinated patients had a significantly higher risk of mortality compared to vaccinated patients. Vaccination remains a crucial strategy to mitigate the severity of the disease and reduce mortality rates. Efforts should be made to address vaccine hesitancy and ensure widespread vaccine coverage.

A rapid mixed-methods evaluation of remote home monitoring models during the COVID-19 pandemic in England

Background

Remote home monitoring services were developed and implemented for patients with COVID-19 during the pandemic. Patients monitored blood oxygen saturation and other readings (e.g. temperature) at home and were escalated as necessary.

Objective

To evaluate effectiveness, costs, implementation, and staff and patient experiences (including disparities and mode) of COVID-19 remote home monitoring services in England during the COVID-19 pandemic (waves 1 and 2).

Methods

A rapid mixed-methods evaluation, conducted in two phases. Phase 1 (July-August 2020) comprised a rapid systematic review, implementation and economic analysis study (in eight sites). Phase 2 (January-June 2021) comprised a large-scale, multisite, mixed-methods study of effectiveness, costs, implementation and patient/staff experience, using national data sets, surveys (28 sites) and interviews (17 sites).

Results

Phase 1 Findings from the review and empirical study indicated that these services have been implemented worldwide and vary substantially. Empirical findings highlighted that communication, appropriate information and multiple modes of monitoring facilitated implementation; barriers included unclear referral processes, workforce availability and lack of administrative support. Phase 2 We received surveys from 292 staff (39% response rate) and 1069 patients/carers (18% response rate). We conducted interviews with 58 staff, 62 patients/carers and 5 national leads. Despite national roll-out, enrolment to services was lower than expected (average enrolment across 37 clinical commissioning groups judged to have completed data was 8.7%). There was large variability in implementation of services, influenced by patient (e.g. local population needs), workforce (e.g. workload), organisational (e.g. collaboration) and resource (e.g. software) factors. We found that for every 10% increase in enrolment to the programme, mortality was reduced by 2% (95% confidence interval: 4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1.8% (-1.2% to 4.9%). None of these results are statistically significant. We found slightly longer hospital lengths of stay associated with virtual ward services (adjusted incidence rate ratio 1.05, 95% confidence interval 1.01 to 1.09), and no statistically significant impact on subsequent COVID-19 readmissions (adjusted odds ratio 0.95, 95% confidence interval 0.89 to 1.02). Low patient enrolment rates and incomplete data may have affected chances of detecting possible impact. The mean running cost per patient varied for different types of service and mode; and was driven by the number and grade of staff. Staff, patients and carers generally reported positive experiences of services. Services were easy to deliver but staff needed additional training. Staff knowledge/confidence, NHS resources/workload, dynamics between multidisciplinary team members and patients' engagement with the service (e.g. using the oximeter to record and submit readings) influenced delivery. Patients and carers felt services and human contact received reassured them and were easy to engage with. Engagement was conditional on patient, support, resource and service factors. Many sites designed services to suit the needs of their local population. Despite adaptations, disparities were reported across some patient groups. For example, older adults and patients from ethnic minorities reported more difficulties engaging with the service. Tech-enabled models helped to manage large patient groups but did not completely replace phone calls.

Limitations

Limitations included data completeness, inability to link data on service use to outcomes at a patient level, low survey response rates and under-representation of some patient groups.

Future work

Further research should consider the long-term impact and cost-effectiveness of these services and the appropriateness of different models for different groups of patients.

Conclusions

We were not able to find quantitative evidence that COVID-19 remote home monitoring services have been effective. However, low enrolment rates, incomplete data and varied implementation reduced our chances of detecting any impact that may have existed. While services were viewed positively by staff and patients, barriers to implementation, delivery and engagement should be considered.

Study registration

This study is registered with the ISRCTN (14962466).

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (RSET: 16/138/17; BRACE: 16/138/31) and NHSEI and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. 13. See the NIHR Journals Library website for further project information. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care.

Intensive care unit nurses' knowledge, attitudes and practices of COVID-19 infection prevention and control

Background

Intensive care units (ICUs) had to rapidly adapt infection prevention and control (IPC) practices during the coronavirus disease 2019 (COVID-19) pandemic.

Objectives

To determine ICU nurses' COVID-19 IPC-related knowledge, attitudes, practices, and perceptions.

Method

A mixed-methods study was conducted at the Groote Schuur Hospital ICU, Cape Town, South Africa (20 April 2021 and 30 May 2021). Participants completed anonymous, self-administered, knowledge, attitudes and practices (KAP) questionnaires. Individual interviews were conducted regarding nurses' lived experiences and perceptions of COVID-19 IPC in critical care.

Results

In total, 116 ICU nurses participated (93.5% response rate) including 57 professional nurses (49%), 34 enrolled nurses (29%) and 25 enrolled nursing assistants (22%); young females (31-49 years) predominating (n = 99; 85.3%). Nurses' overall COVID-19 IPC knowledge scores were moderately good (78%); professional nurses had greater knowledge of COVID-19 transmission (p < 0.001). Intensive care unit nurses' attitude scores towards COVID-19 IPC were low (55%), influenced by limited IPC training, insufficient time to implement IPC and shortages of personal protective equipment (PPE). Respondents' scores for self-reported COVID-19 IPC practices were moderate (65%); highest compliance rates were for hand hygiene after touching patient surroundings (68%). Only 47% ICU nurses underwent N95 respirator fit-testing despite working in a COVID-19 ICU.

Conclusion

Regular COVID-19 IPC training is needed to equip ICU nurses with the knowledge and skills to prevent healthcare-associated COVID-19 transmission. Enhanced IPC training and consistent PPE availability may support more favourable attitudes and better IPC practices. Comprehensive IPC and occupational health support should be offered to ensure ICU nurses' wellbeing during pandemics.

Contribution

Enhanced IPC training and consistent PPE availability may support better attitudes and IPC practices.

Phylodynamic of SARS-CoV-2 during the second wave of COVID-19 in Peru

At over 0.6% of the population, Peru has one of the highest SARS-CoV-2 mortality rate in the world. Much effort to sequence genomes has been done in this country since mid-2020. However, an adequate analysis of the dynamics of the variants of concern and interest (VOCIs) is missing. We investigated the dynamics of the COVID-19 pandemic in Peru with a focus on the second wave, which had the greatest case fatality rate. The second wave in Peru was dominated by Lambda and Gamma. Analysis of the origin of Lambda shows that it most likely emerged in Peru before the second wave (June-November, 2020). After its emergence it reached Argentina and Chile from Peru where it was locally transmitted. During the second wave in Peru, we identify the coexistence of two Lambda and three Gamma sublineages. Lambda sublineages emerged in the center of Peru whereas the Gamma sublineages more likely originated in the north-east and mid-east. Importantly, it is observed that the center of Peru played a prominent role in transmitting SARS-CoV-2 to other regions within Peru.

Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study

Several effective COVID-19 vaccines are administered to combat the COVID-19 pandemic globally. In most African countries, there is a comparatively limited deployment of vaccination programs. In this work, we develop a mathematical compartmental model to assess the impact of vaccination programs on curtailing the burden of COVID-19 in eight African countries considering SARS-CoV-2 cumulative case data for each country for the third wave of the COVID-19 pandemic. The model stratifies the total population into two subgroups based on individual vaccination status. We use the detection and death rates ratios between vaccinated and unvaccinated individuals to quantify the vaccine's effectiveness in reducing new COVID-19 infections and death, respectively. Additionally, we perform a numerical sensitivity analysis to assess the combined impact of vaccination and reduction in the SARS-CoV-2 transmission due to control measures on the control reproduction number (Rc). Our results reveal that on average, at least 60% of the population in each considered African country should be vaccinated to curtail the pandemic (lower the Rc below one). Moreover, lower values of Rc are possible even when there is a low (10%) or moderate (30%) reduction in the SARS-CoV-2 transmission rate due to NPIs. Combining vaccination programs with various levels of reduction in the transmission rate due to NPI aids in curtailing the pandemic. Additionally, this study shows that vaccination significantly reduces the severity of the disease and death rates despite low efficacy against COVID-19 infections. The African governments need to design vaccination strategies that increase vaccine uptake, such as an incentive-based approach.

Analyzing the impact of vaccinations and weather factors on the COVID-19 pandemic

OBJECTIVES

A world-wide immunization project was launched at the peak of COVID-19 pandemic to contain and minimize the adverse effects of SARS-CoV-2 virus. We carried out a series of statistical analyses in this paper to determine, confirm and quantify the impact of the vaccinations on COVID-19 cases and mortalities, amidst critical confounding factors - temperature and solar irradiance.

METHODS

The experiments in this paper were carried out on the world data, data from 21 countries and the five major continents. The significance of the 2020 - 2022 vaccinations on the COVID-19 cases and mortalities response data were evaluated via Hypotheses' tests. Correlation coefficient analyses were carried out to determine the extent of the relationship between vaccination coverage and corresponding COVID-19 mortalities data. The impact of vaccination was quantified. The effects of the weather factors - temperature and solar irradiance, on COVID-19 cases and mortalities data were analyzed.

RESULTS

The series of hypotheses tests carried out reveal that vaccinations did not affect cases; however, vaccinations significantly impacted the mean daily mortalities in all five major continents and globally. The correlation coefficient analysis results show vaccination coverage to be highly and negatively correlated with daily mortalities in the world - the five major continents and most of the countries studied in this work. The percentage reduction in mortalities as a result of wider vaccination coverage was indeed significant. Temperature and solar irradiance impacted daily COVID-19 cases and mortalities data during the vaccination and post vaccination periods.

CONCLUSION

Results show that the world-wide Vaccination against COVID-19 project had a significant impact in reducing mortalities and minimizing the adverse effects due to COVID-19 globally, in all five (5) major continents of the world and the countries studied in this work, however, temperature and solar irradiance still had effects on COVID-19 response in the vaccination eras.

Literature review on COVID-19 vaccine efficacy in the immunocompromised population, and possible implications to future vaccination in kidney transplant patients

Since the emergence of the virulent coronavirus in 2019, efforts to tackle the coronavirus-disease-2019 (COVID-19) pandemic have been made globally. The development of the coronavirus disease (COVID) vaccine was a significant breakthrough in ways to tackle the virus. Various research studies have been conducted to identify how the virus works and ways to manage COVID, including the efficacy of the vaccines. However, there is limited data on how these measures work for the immunocompromised, despite the grave impact of these virulent strains in this population. Specifically, this review aims to focus on kidney transplant recipients (KTRs). Studies have suggested that there is significantly lower vaccine response in some immunocompromised groups despite additional booster doses, and hence warrants an augmented or alternative protection against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for these patients. This suggests a need for alternative or more tailored approach in providing adequate protection against the COVID-19 in these cohorts. Some suggested ways include withholding immunosuppressants before and/or after vaccination, increasing the vaccine doses or reducing intervals and providing a mixture of monoclonal antibody (mAb) or antiviral therapy. However, the appropriate degree of alteration and augmentation, as well as its safety and effectiveness remains to be determined. Furthermore, continuous emergence of more virulent strains, such as the Omicron and its sub-lineages or the Deltacron, emphasises the need for ongoing research to assess the effectiveness of the current treatment against these new variants. Overall, active interest and appropriate updates to COVID-19 guidelines is necessary.

Prevalence and epidemiological trends in mortality due to COVID-19 in Saudi Arabia

OBJECTIVES

This article describes the prevalence and epidemiological trends of COVID-19 mortality in the largest registry in the Kingdom of Saudi Arabia (KSA).

STUDY DESIGN

A prospective epidemiological cohort study using data from all healthcare facilities in KSA collected between March 23, 2020, and April 30, 2022. Data on the number of daily deaths directly related to COVID-19 were gathered, analyzed, and reported.

METHOD

Data analysis was carried out using national and regional crude case fatality rate and death per 100,000 population. Descriptive statistics using numbers and proportions were used to describe age, gender, nationality, and comorbidities. The mortality trend was plotted and compared with international figures. In addition, the most common comorbidities associated with mortality and the proportion of patients who received COVID-19 vaccine were reported.

RESULTS

The total reported number of deaths between March 23, 2020, and April 30, 2022, was 9085. Crude case fatality rate was 1.21%, and death per 100,000 population was 25.38, which compared favorably to figures reported by several developed countries. The highest percentages of deaths were among individuals aged between 60 and 69 years, males (71%), and individuals with diabetes (60%). Only 2.8% of mortalities occur in patients who received COVID-19 vaccine. Diabetes, hypertension, and heart failure had the highest attributable risk of mortality among patients who died due to COVID-19.

CONCLUSION

Case fatality rate and death per 100,000 population in KSA are among the lowest in the world due to multiple factors. Several comorbidities have been identified, namely, diabetes, hypertension, obesity, and cardiac arrhythmias.

Can COVID-19 Vaccines Induce Premature Non-Communicable Diseases: Where Are We Heading to?

According to the WHO, as of January 2023, more than 850 million cases and over 6.6 million deaths from COVID-19 have been reported worldwide. Currently, the death rate has been reduced due to the decreased pathogenicity of new SARS-CoV-2 variants, but the major factor in the reduced death rates is the administration of more than 12.8 billion vaccine doses globally. While the COVID-19 vaccines are saving lives, serious side effects have been reported after vaccinations for several premature non-communicable diseases (NCDs). However, the reported adverse events are low in number. The scientific community must investigate the entire spectrum of COVID-19-vaccine-induced complications so that necessary safety measures can be taken, and current vaccines can be re-engineered to avoid or minimize their side effects. We describe in depth severe adverse events for premature metabolic, mental, and neurological disorders; cardiovascular, renal, and autoimmune diseases, and reproductive health issues detected after COVID-19 vaccinations and whether these are causal or incidental. In any case, it has become clear that the benefits of vaccinations outweigh the risks by a large margin. However, pre-existing conditions in vaccinated individuals need to be taken into account in the prevention and treatment of adverse events.

An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data

The prevalence of COVID-19 has been the most serious health challenge of the 21th century to date, concerning national health systems on a daily basis, since December 2019 when it appeared in Wuhan City. Nevertheless, most of the proposed mathematical methodologies aiming to describe the dynamics of an epidemic, rely on deterministic models that are not able to reflect the true nature of its spread. In this paper, we propose a SEIHCRDV model - an extension/improvement of the classic SIR compartmental model - which also takes into consideration the populations of exposed, hospitalized, admitted in intensive care units (ICU), deceased and vaccinated cases, in combination with an unscented Kalman filter (UKF), providing a dynamic estimation of the time dependent system's parameters. The stochastic approach is considered necessary, as both observations and system equations are characterized by uncertainties. Apparently, this new consideration is useful for examining various pandemics more effectively. The reliability of the model is examined on the daily recordings of COVID-19 in France, over a long period of 265 days. Two major waves of infection are observed, starting in January 2021, which signified the start of vaccinations in Europe providing quite encouraging predictive performance, based on the produced NRMSE values. Special emphasis is placed on proving the non-negativity of SEIHCRDV model, achieving a representative basic reproductive number R 0 and demonstrating the existence and stability of disease equilibria according to the formula produced to estimate R 0 . The model outperforms in predictive ability not only deterministic approaches but also state-of-the-art stochastic models that employ Kalman filters. Furthermore, the relevant analysis supports the importance of vaccination, as even a small increase in the dialy vaccination rate could lead to a notable reduction in mortality and hospitalizations.

Evolution of antibody profiles against SARS-CoV-2 in experienced and naïve vaccinated elderly people

Introduction

The third dose of the COVID-19 vaccine is especially necessary in people over 65 years of age due to their lower immune response.

Methods

We designed a multicentre, prospective observational study including 98 people ≤65 years old who lived in two nursing homes in Valladolid, Spain. One of the groups had previous experience with SARS-CoV-2 (n=68;69.4%) and the other was naïve (n=30;30.6%). We evaluated the response to the three doses of the Comirnaty vaccine and the dynamics of antibodies during 5 consecutive serum samplings: 2 after the first two doses of vaccination, one three months after the first dose, another at 6 months and the last one month after the third dose. IgG antibodies against SARS-CoV-2 S1, RBD and N antigens were analysed.

Results

Both groups increased the level of Abs against S1 and RBD, but the experienced group showed a 130-fold higher humoral response due to hybrid immunisation (infection+vaccination). The response to vaccination with Comirnaty against COVID-19 was higher in those ≤65 years with previous experience than those who were naïve. However, the amount of antibodies against S1 and RBD equalised at 6 months. After the third dose, both groups raised the amount of antibodies to a similar level. The reinfections suggested by the analysis of antibodies against N were frequent in both groups.

Discussion

The third dose showed a clear benefit for elderly people, with the reinforcement of the antibody levels after the decline suffered after six months of the first two doses.

Case series in Indonesia: B.1.617.2 (delta) variant of SARS-CoV-2 infection after a second dose of vaccine

BACKGROUND

The B.1.617.2 (delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in Maharashtra in late 2020 and has rapidly expanded across India and worldwide. It took only 2 mo for this variant to spread in Indonesia, making the country the new epicenter of the delta variant as of July 2021. Despite efforts made by accelerating massive rollouts of current vaccines to protect against infection, cases of fully-vaccinated people infected with the delta variant have been reported.

AIM

To describe the demographic statistics and clinical presentation of the delta variant infection after the second dose of vaccine in Indonesia.

METHODS

A retrospective, single-centre case series of the general consecutive population that worked or studied at Faculty of Medicine, Universitas Indonesia with confirmed Delta Variant Infection after a second dose of vaccine from 24 June and 25 June 2021. Cases were collected retrospectively based on a combination of author recall, reverse transcription-polymerase chain reaction (RT-PCR), and whole genome sequencing results from the Clinical Microbiology Laboratory, Faculty of Medicine, Universitas Indonesia.

RESULTS

Between 24 June and 25 June 2021, 15 subjects were confirmed with the B.1.617.2 (delta) variant infection after a second dose of the vaccine. Fourteen subjects were vaccinated with CoronaVac (Sinovac) and one subject with ChAdOx1 nCoV-19 (Oxford-AstraZeneca). All of the subjects remained in home isolation, with fever being the most common symptom at the onset of illness (n = 10, 66.67%). The mean duration of symptoms was 7.73 d (± 5.444). The mean time that elapsed from the first positive swab to a negative RT-PCR test for SARS-CoV-2 was 17.93 d (± 6.3464). The median time that elapsed from the second dose of vaccine to the first positive swab was 87 d (interquartile range: 86-128).

CONCLUSION

Although this case shows that after two doses of vaccine, subjects are still susceptible to the delta variant infection, currently available vaccines remain the most effective protection. They reduce clinical manifestations of COVID-19, decrease recovery time from the first positive swab to negative swab, and lower the probability of hospitalization and mortality rate compared to unvaccinated individuals.

Statistical analysis supports UTR (untranslated region) deletion theory in SARS-CoV-2

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

Study of the Deep Processes of COVID-19 in Russia: Finding Ways to Identify Preventive Measures

The novel coronavirus disease 2019 (COVID-19) pandemic has had a huge impact on all areas of human life. Since the risk of biological threats will persist in the future, it is very important to ensure mobilization readiness for a prompt response to the possible emergence of epidemics of infectious diseases. Therefore, from both a theoretical and practical standpoint, it is currently necessary to conduct a thorough examination of the COVID-19 epidemic. The goal of this research is to investigate the underlying processes that led to the COVID-19 pandemic in Russia and to identify ways to improve preventive measures and ensure mobilization readiness for a quick response to potential COVID-19-like pandemics. This research will analyze the daily dynamics of the number of infection cases and the number of new lethal cases of COVID-19. We analyzed the daily number of new cases of COVID-19 infection N(d), the daily number of new lethal cases L(d), their percentage ratio L(d)/N(d) 100% in Russia for 2 years of the pandemic (from the beginning of the pandemic to 23 March 2022), the rate of increase and decrease of these indicators (dN(d)/dd and dL(d)/dd), as well as their spectra created on the basis of wavelet analysis. Wavelet analysis of the deep structure of the N(d) and L(d) wavelet spectra made it possible to identify the presence of internal cycles, the study of which makes it possible to predict the presence of days with the maximum number of infections and new deaths in a pandemic similar to COVID-19 and outline ways and methods for improving preventive measures and measures to ensure mobilization readiness for a rapid response to the potential emergence of pandemics similar to COVID-19.

Cardiopulmonary Resuscitation: Let's Together Step into a New Era!

Although the out-of-hospital cardiac arrest (OHCA) survival rate has improved due to the spread of cardiopulmonary resuscitation (CPR) techniques and insights, OHCA remains a major public health issue worldwide [...].

Risk-based decision-making related to preprocedural coronavirus disease 2019 testing in the setting of GI endoscopy: management of risks, evidence, and behavioral health economics

BACKGROUND AND AIMS

Controversies exist regarding the benefits and most appropriate approach for preprocedural coronavirus disease 2019 (COVID-19) testing (eg, rapid antigen test, polymerase chain reaction, or real-time polymerase chain reaction) for outpatients undergoing diagnostic and therapeutic procedures, such as GI endoscopy, to prevent COVID-19 infections among staff. Guidelines for protecting healthcare workers (HCWs) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from outpatient procedures varies across medical professional organizations. This study provides an evidence-based decision support tool for key decision-makers (eg, clinicians) to respond to COVID-19 transmission risks and reduce the effect of personal biases.

METHODS

A scoping review was used to identify relevant factors influencing COVID-19 transmission risk relevant for GI endoscopy. From 12 relevant publications, 8 factors were applicable: test sensitivity, prevalence of SARS-CoV-2 in the population, age-adjusted SARS-CoV-2 prevalence in the patient cohort, proportion of asymptomatic patients, risk of transmission from asymptomatic carriers, risk reduction by personal protective equipment (PPE), vaccination rates of HCWs, and risk reduction of SAE by vaccination. The probability of a serious adverse event (SAE), such as workplace-acquired infection resulting in HCW death, under various scenarios with preprocedural testing was determined to inform decision-makers of expected costs of reductions in SAEs.

RESULTS

In a setting of high community transmission, without testing and PPE, 117.5 SAEs per million procedures were estimated to occur, and this was reduced to between .079 and 2.35 SAEs per million procedures with the use of PPE and preprocedural testing. When these variables are used and a range of scenarios are tested, the probability of an SAE was low even without testing but was reduced by preprocedural testing.

CONCLUSIONS

Under all scenarios tested, preprocedural testing reduced the SAE risk for HCWs regardless of the SARS-CoV-2 variant. Benefits of preprocedural testing are marginal when community transmission is low (eg, below 10 infections a day per 100,000 population). The proposed decision support tool can assist in developing rational preprocedural testing policies.

"I Can Sense When My Hands Need Washing": A Qualitative Study and Thematic Analysis of Factors Affecting Young Adults' Hand Hygiene

Handwashing is one of the most effective and low-cost public health measures. However, it is often not practiced frequently enough or correctly by the public. Young adults in particular have poorer intentions to wash their hands, frequency of handwashing, and sanitizer use compared to other age groups. Therefore, there is a need to identify barriers and facilitators affecting hand hygiene within this group. The objective of this qualitative study was to apply the Theoretical Domains Framework to explore factors which influence hand hygiene among young adults aged 18 to 25 years old. An online questionnaire (n = 37) and thematic analysis were used to generate 3 overarching themes. The main findings indicated internal factors such as knowledge and intentions; interpersonal factors such as social norms; and environmental factors such as reminders, cues, accessibility, and cleanliness of handwashing facilities determined the level of hand hygiene practiced among young adults. The findings suggest that behavior change techniques such as social comparisons and tailored messaging to suit the needs of young adults may be more effective at increasing hand hygiene.

Long-term quantitative assessment of anti-SARS-CoV-2 spike protein immunogenicity (QUASI) after COVID-19 vaccination in older people living with HIV (PWH)

BACKGROUND

The durability of immune responses to COVID-19 vaccines among older people living with HIV (PWH) is clinically important.

METHODS

We aimed to assess vaccine-induced humoral immunity and durability in older PWH (≥ 55 years, n = 26) over 6 months (post-initial BNT162b2 series). A secondary and exploratory objective was to assess T-cell response and BNT162b2 booster reactogenicity, respectively. Our Visit 1 (3 weeks post-initial BNT162b2 dose) SARS-CoV-2 humoral immunity results are previously reported; these subjects were recruited for Visit 2 [2 weeks (+ 1 week window) post-second vaccination] and Visit 3 [6 months (± 2 week window) post-initial vaccination] in a single-center longitudinal observational study. Twelve participants had paired Visit 2/3 SARS-CoV-2 Anti-Spike IgG data. At Visit 3, SARS-CoV-2 Anti-Spike IgG testing occurred, and 5 subjects underwent T-cell immune response evaluation. Thereafter, subjects were offered BNT162b2 booster (concurrent day outside our study) per US FDA/CDC guidance; reactogenicity was assessed. The primary study outcome was presence of detectable Visit 3 SARS-CoV-2 Anti-Spike-1-RBD IgG levels. Secondary and exploratory outcomes were T-cell immune response and BNT162b2 booster reactogenicity, respectively. Wilcoxon signed-rank tests analyzed median SARS-CoV-2 Anti-Spike IgG 6-month trends.

RESULTS

At Visit 3, 26 subjects underwent primary analysis with demographics noted: Median age 61 years; male n = 16 (62%), female n = 10 (38%); Black n = 13 (50%), White n = 13 (50%). Most subjects (n = 20, 77%) had suppressed HIV viremia on antiretroviral therapy, majority (n = 24, 92%) with CD4 > 200 cells/µL. At Visit 3, 26/26 (100%) had detectable Anti-Spike-1-RBD (≥ 0.8 U/mL). Among 12 subjects presenting to Visit 2/3, median SARS-CoV-2 Anti-Spike 1-RBD was 2087 U/mL at Visit 2, falling to 581.5 U/mL at Visit 3 (p = 0.0923), with a median 3.305-fold decrease over 6 months. Among subjects (n = 5) with 6-month T-cell responses measured, all had detectable cytokine-secreting anti-spike CD4 responses; 3 had detectable CD4 + Activation induced marker (AIM) + cells. Two had detectable cytokine-secreting CD8 responses, but all had positive CD8 + AIM + cells.

CONCLUSIONS

Among older PWH, SARS-CoV-2 Anti-Spike IgG and virus-specific T-cell responses are present 6 months post-primary BNT162b2 vaccination, and although waning, suggest retention of some degree of long-term protective immunity.

Is Mexico's population hesitant towards COVID-19 vaccines? A 2021 survey on different levels of hesitancy and its determinants

Vaccine hesitancy is a well-known phenomenon whereby individuals in a population reject or delay being vaccinated despite having access to vaccine services. This phenomenon is especially problematic in the current context of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) pandemic because vaccine hesitancy can decrease vaccination rates. In Mexico, vaccine hesitancy has been less thoroughly studied than in other countries such as the United States despite its importance and the potential impact of overlooking the problem. Understanding and effectively tackling this problem requires a more in-depth analysis of the defining characteristics of vaccination hesitancy. For this purpose, the World Health Organization’s (WHO) Vaccine Hesitancy Determinants Matrix (VHDM in this study) is highly useful. In the present study, a digital survey was conducted using Google Forms to assess the level of vaccine hesitancy in the Mexican population and the vaccine determinants of the VHDM model associated with the respondents' different levels of vaccine hesitancy. The sample consisted of 1,195 people divided into four levels of vaccine hesitancy based on their answers. Tests for association were performed, identifying an association between some determinants of the VHDM model and the levels of vaccine hesitancy. Based on the analysis of the survey results, areas of opportunity for addressing COVID-19 vaccine hesitancy in Mexico were found and discussed; these included the importance of studying vaccine hesitancy as a complex and changing gradient, the high connectivity of people with high level of vaccine hesitancy to networks of people with vaccine hesitancy, the relatively high trust in physicians at all levels of vaccine hesitancy, the low trust in government authorities at high and moderate levels of vaccine hesitancy, and the strong association of the fear of suffering side effects and knowing people who have suffered them with the level of vaccine hesitancy.

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Non-binary classification of hesitancy is essential for vaccine hesitancy studies.

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Determinants from all domains of the WHO VHDM were identified in the population.

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Trust in physicians has a high potential to help address Mexico’s vaccine hesitancy.

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Mistrust in government and previous experiences should be considered.

The collateral damage of COVID-19 to cardiovascular services: a meta-analysis

AIMS

The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic.

METHODS AND RESULTS

From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66-0.94) and revascularisation (RR 0.73, 95% CI 0.62-0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10-1.37) and heart failure (RR 1.08, 95% CI 1.04-1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave.

CONCLUSIONS

There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification.

Vaccination, life expectancy, and trust: patterns of COVID-19 and measles vaccination rates around the world

OBJECTIVES

We estimate patterns of covariation between COVID-19 and measles vaccination rates and a set of widely used indicators of human, social, and economic capital across 146 countries.

STUDY DESIGN

We conduct exploratory analyses of social patterns that uphold vaccination success for COVID-19 and measles.

METHODS

We use publicly available data on COVID vaccination rates and other country-level indicators from Our World in Data, Human Development Report, Corruption Perception Index, and the World Bank to devise bivariate correlations and multiple regression models.

RESULTS

About 70% of the variability in COVID-19 vaccination rates in February 2022 can be explained by differences in the Human Development Index (HDI) and, specifically, in life expectancy at birth. Trust in doctors and nurses adds predictive value beyond HDI, clarifying controversial discrepancies between vaccination rates in countries with similar levels of HDI and vaccine availability. Cardiovascular disease deaths, an indicator of general health system effectiveness, and infant measles immunization coverage, an indicator of country-level immunization effectiveness, are also significant, though weaker, predictors of COVID-19 vaccination success. Measles vaccination in 2019 is similarly predicted by HDI and trust in doctors and nurses.

CONCLUSIONS

The remaining variability in COVID-19 vaccination success that cannot be pinned down through these sets of metrics points to a considerable scope for collective and individual agency in a time of crisis. The mobilization and coordination in the vaccination campaigns of citizens, medical professionals, scientists, journalists, and politicians, among others, account for at least some of this variability in overcoming vaccine hesitancy and inequity.

COVID-19 Severity and Mortality after Vaccination against SARS-CoV-2 in Central Greece

Background: Vaccination against SARS-CoV-2 (COVID-19) has become crucial for limiting disease transmission and reducing its severity, hospitalizations and mortality; however, despite universal acceptance, vaccine hesitancy is still significant. In the present manuscript, we aim to assess COVID-19-attributed mortality after the prevalence of new variants of the virus (Delta and Omicron viral strains) and to evaluate the vaccination effect. Methods: All patients that were hospitalized due to COVID-19 infection in the Respiratory Department of a tertiary referral center in central Greece between 1st of June 2021 and 1st of February 2022 were included in the present study. Results: 760 consecutive patients were included in the study; 89 (11.7%) were diagnosed with severe COVID-19 and 220 (38.7%) patients were fully vaccinated. In logistic regression, increased age (aOR = 1.12, p < 0.001), male gender (aOR = 2.29, p = 0.013) and vaccination against SARS-CoV-2 virus (aOR = 0.2, p < 0.001) were associated with mortality attributed to COVID-19 with a statistically significant association. Moreover, increased age (aOR = 1.09, p < 0.001), male gender (aOR = 1.92, p = 0.025) and vaccination against SARS-CoV-2 virus (aOR = 0.25, p < 0.001) were statistically significantly associated with clinical severity of COVID-19 infection. However, when comparing the length of hospitalization between vaccinated and unvaccinated patients, the difference was not statistically significant between the two groups (p = 0.138). Conclusions: Vaccination against SARS-CoV-2 virus had a protective effect in terms of mortality and clinical severity of COVID-19 during the fourth wave of the pandemic in Central Greece. The national vaccination policy has to focus on vulnerable populations that are expected to benefit the most from the vaccine’s protection.

The effect of SARS-CoV-2 vaccination on post-acute sequelae of COVID-19 (PASC): A prospective cohort study

BACKGROUND

Symptoms of post-acute sequelae of COVID-19 (PASC) may improve following SARS-CoV-2 vaccination. However few prospective data that also explore the underlying biological mechanism are available. We assessed the effect of vaccination on symptomatology of participants with PASC, and compared antibody dynamics between those with and without PASC.

METHODS

RECoVERED is a prospective cohort study of adult patients with mild to critical COVID-19, enrolled from illness onset. Among participants with PASC, vaccinated participants were exact-matched 1:1 on age, sex, obesity status and time since illness onset to unvaccinated participants. Between matched pairs, we compared the monthly mean numbers of symptoms over a 3-month follow-up period, and, using exact logistic regression, the proportion of participants who fully recovered from PASC. Finally, we assessed the association between PACS status and rate of decay of spike- and RBD-binding IgG titers up to 9 months after illness onset using Bayesian hierarchical linear regression.

FINDINGS

Of 349 enrolled participants, 316 (90.5%) had ≥3 months of follow-up, of whom 186 (58.9%) developed PASC. Among 36 matched pairs with PASC, the mean number of symptoms reported each month during 3 months of follow-up were comparable between vaccinated and unvaccinated groups. Odds of full recovery from PASC also did not differ between matched pairs (OR 1.57 [95%CI 0.46-5.84]) within 3 months after the matched time-point. The median half-life of spike- and RBD-binding IgG levels were, in days (95%CrI), 233 (183-324) and 181 (147-230) among participants with PASC, and 170 (125-252) and 144 (113-196) among those without PASC, respectively.

INTERPRETATION

Our study found no strong evidence to suggest that vaccination improves symptoms of PASC. This was corroborated by comparable spike- and RBD-binding IgG waning trajectories between those with and without PASC, refuting any immunological basis for a therapeutic effect of vaccination on PASC.

Machine Learning-Assisted Screening of Herbal Medicine Extracts as Vaccine Adjuvants

Adjuvants are important vaccine components, composed of a variety of chemical and biological materials that enhance the vaccine antigen-specific immune responses by stimulating the innate immune cells in both direct and indirect manners to produce a variety cytokines, chemokines, and growth factors. It has been developed by empirical methods for decades and considered difficult to choose a single screening method for an ideal vaccine adjuvant, due to their diverse biochemical characteristics, complex mechanisms of, and species specificity for their adjuvanticity. We therefore established a robust adjuvant screening strategy by combining multiparametric analysis of adjuvanticity in vivo and immunological profiles in vitro (such as cytokines, chemokines, and growth factor secretion) of various library compounds derived from hot-water extracts of herbal medicines, together with their diverse distribution of nano-sized physical particle properties with a machine learning algorithm. By combining multiparametric analysis with a machine learning algorithm such as rCCA, sparse-PLS, and DIABLO, we identified that human G-CSF and mouse RANTES, produced upon adjuvant stimulation in vitro, are the most robust biological parameters that can predict the adjuvanticity of various library compounds. Notably, we revealed a certain nano-sized particle population that functioned as an independent negative parameter to adjuvanticity. Finally, we proved that the two-step strategy pairing the negative and positive parameters significantly improved the efficacy of screening and a screening strategy applying principal component analysis using the identified parameters. These novel parameters we identified for adjuvant screening by machine learning with multiple biological and physical parameters may provide new insights into the future development of effective and safe adjuvants for human use.

The impact of COVID-19 vaccination on case fatality rates in a city in Southern Brazil

BACKGROUND

Recent studies have established that vaccination plays a significant role in reducing COVID-19-related deaths. Here, we investigated differences in COVID-19 case fatality rates (CFRs) among vaccinated and unvaccinated populations, and analyzed whether the age composition of confirmed cases has a significant effect on the variations in the observed CFRs across these groups.

METHODS

The study considered 59,853 confirmed cases and 1,687 deaths from COVID-19, reported between January 1 to October 20, 2021, by the Health Department of Londrina, a city in Southern Brazil. We used Negative Binomial regression models to estimate CFRs according to vaccination status and age range.

RESULTS

There are significant differences between the CFR for fully vaccinated and unvaccinated populations (IRR = 0.596, 95% CI [0.460 - 0.772], P < .001). Vaccinated populations experience fatality rates 40.4% lower than non-vaccinated. In addition, the age composition of confirmed cases explains more than two-thirds of the variation in the CFR between these 2 groups.

CONCLUSIONS

Our novel findings reinforce the importance of vaccination as an essential public health measure for reducing COVID-19 fatality rates in all age groups. The results also provide means for accurately assessing differences in CFRs across vaccinated and unvaccinated populations. Such assessment is essential to inform and determine appropriate containment and mitigation interventions in Brazil and elsewhere.

Predictors of Uncertainty and Unwillingness to Receive the COVID-19 Vaccine in Men Who Have Sex with Men in France

The development of vaccines against COVID-19 has given hope to populations. Public acceptability of vaccination is a major driver in containing the disease. However, in marginalized and stigmatized populations, uncertainty and unwillingness may be a challenge. This study aimed to analyze the factors associated with uncertainty and unwillingness to vaccinate against COVID-19 in men who have sex with men (MSM) living in France. The data used came from Rapport au Sexe (ERAS) 2021, a voluntary, cross-sectional, anonymous, self-administered, online survey conducted from 26 February to 11 April 2021. Among the 15,426 respondents included in the analysis, 60.5% were willing to vaccinate (these included persons already vaccinated), 17.5% were not, and 22% were uncertain. Factors independently associated with uncertainty and unwillingness were lower education level, low health literacy level, financial hardship, being under 30 years of age, and living in a rural area. HIV-positive MSM were less likely to report vaccination uncertainty and unwillingness than HIV-negative MSM and those with unknown serostatus. Although more impacted by COVID-19, socioeconomically vulnerable MSM were the sub-group most unwilling to vaccinate. To improve acceptability of COVID-19 vaccination in MSM, policy makers and researchers must increase access to and understanding of medical information by considering the general public's health literacy when developing information sources. Moreover, a dedicated global care approach, which ensures these populations can be reached, is necessary.

Identifying Country-Level Risk Factors for the Spread of COVID-19 in Europe Using Machine Learning

Coronavirus disease 2019 (COVID-19) has resulted in approximately 5 million deaths around the world with unprecedented consequences in people’s daily routines and in the global economy. Despite vast increases in time and money spent on COVID-19-related research, there is still limited information about the factors at the country level that affected COVID-19 transmission and fatality in EU. The paper focuses on the identification of these risk factors using a machine learning (ML) predictive pipeline and an associated explainability analysis. To achieve this, a hybrid dataset was created employing publicly available sources comprising heterogeneous parameters from the majority of EU countries, e.g., mobility measures, policy responses, vaccinations, and demographics/generic country-level parameters. Data pre-processing and data exploration techniques were initially applied to normalize the available data and decrease the feature dimensionality of the data problem considered. Then, a linear ε-Support Vector Machine (ε-SVM) model was employed to implement the regression task of predicting the number of deaths for each one of the three first pandemic waves (with mean square error of 0.027 for wave 1 and less than 0.02 for waves 2 and 3). Post hoc explainability analysis was finally applied to uncover the rationale behind the decision-making mechanisms of the ML pipeline and thus enhance our understanding with respect to the contribution of the selected country-level parameters to the prediction of COVID-19 deaths in EU.

The impact of remote home monitoring of people with COVID-19 using pulse oximetry: A national population and observational study

BACKGROUND

Remote home monitoring of people testing positive for COVID-19 using pulse oximetry was implemented across England during the Winter of 2020/21 to identify falling blood oxygen saturation levels at an early stage. This was hypothesised to enable earlier hospital admission, reduce the need for intensive care and improve survival. This study is an evaluation of the clinical effectiveness of the pre-hospital monitoring programme, COVID oximetry @home (CO@h).

METHODS

The setting was all Clinical Commissioning Group (CCG) areas in England where there were complete data on the number of people enrolled onto the programme between 2nd November 2020 and 21st February 2021. We analysed relationships at a geographical area level between the extent to which people aged 65 or over were enrolled onto the programme and outcomes over the period between November 2020 to February 2021.

FINDINGS

For every 10% increase in coverage of the programme, mortality was reduced by 2% (95% confidence interval:4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1·8% (-1·2% to 4·9%). None of these results are statistically significant, although the confidence interval indicates that any adverse effect on mortality would be small, but a mortality reduction of up to 4% may have resulted from the programme.

INTERPRETATION

There are several possible explanations for our findings. One is that CO@h did not have the hypothesised impact. Another is that the low rates of enrolment and incomplete data in many areas reduced the chances of detecting any impact that may have existed. Also, CO@h has been implemented in many different ways across the country and these may have had varying levels of effect.

FUNDING

This is independent research funded by the National Institute for Health Research, Health Services & Delivery Research programme (RSET Project no. 16/138/17; BRACE Project no. 16/138/31) and NHSEI. NJF is an NIHR Senior Investigator.

Death after the Administration of COVID-19 Vaccines Approved by EMA: Has a Causal Relationship Been Demonstrated?

More than eight billion doses of COVID-19 vaccines have been administered globally so far and 44.29% of people are fully vaccinated. Pre-authorization clinical trials were carried out and the safety of vaccines is still continuously monitored through post-commercialization surveillance. However, some people are afraid of vaccine side effects, claiming they could lead to death, and hesitate to get vaccinated. Herein, a literature review of COVID-19-vaccine-related deaths has been carried out according to the PRISMA standards to understand if there is a causal relationship between vaccination and death and to highlight the real extent of such events. There have been 55 cases of death after COVID-19 vaccination reported and a causal relationship has been excluded in 17 cases. In the remaining cases, the causal link between the vaccine and the death was not specified (8) or considered possible (15), probable (1), or very probable/demonstrated (14). The causes of deaths among these cases were: vaccine-induced immune thrombotic thrombocytopenia (VITT) (32), myocarditis (3), ADEM (1), myocardial infarction (1), and rhabdomyolysis (1). In such cases, the demonstration of a causal relationship is not obvious, and more studies, especially with post-mortem investigations, are needed to deepen understanding of the possible pathophysiological mechanisms of fatal vaccine side effects. In any event, given the scarcity of fatal cases, the benefits of vaccination outweigh the risks and the scientific community needs to be cohesive in asserting that vaccination is fundamental to containing the spread of SARS-CoV-2.

COVID-19 Recovery Patterns Across Alpha (B.1.1.7) and Delta (B.1.617.2) Variants of SARS-CoV-2

Background

B.1.1.7 (alpha) and B.1.617.2 (delta) variants of concern for SARS-CoV-2 have been reported to have differential infectivity and pathogenicity. Difference in recovery patterns across these variants and the interaction with vaccination status has not been reported in population-based studies.

Objective

The objective of this research was to study the length of stay and temporal trends in RT-PCR cycle times (Ct) across alpha and delta variants of SARS-CoV-2 between vaccinated and unvaccinated individuals.

Methods

Participants consisted of patients admitted to national COVID-19 treatment facilities if they had a positive RT-PCR test for SARS-CoV-2, and analysis of variants was performed (using whole genome sequencing). Information on vaccination status, age, sex, cycle times (Ct) for four consecutive RT-PCR tests conducted during hospital stay, and total length of hospital stay for each participant were ascertained from electronic medical records.

Results

Patients infected with the delta variant were younger (mean age = 35years vs 39 years for alpha, p<0.001) and had lesser vaccination coverage (54% vs 72% for alpha, p<0.001). RT-PCR Ct values were similar for both variants at the baseline test; however by the fourth test, delta variant patients had significantly lower Ct values (27 vs 29, p=0.05). Length of hospital stay was higher in delta variant patients in vaccinated (3 days vs 2.9 days for alpha variant) as well as in unvaccinated patients (5.2 days vs 4.4 days for alpha variant, p<0.001). Hazards of hospital discharge after adjusting for vaccination status, age, and sex was higher for alpha variant infections (HR=1.2, 95% CI: 1.01-1.41, p=0.029).

Conclusion

Patients infected with the delta variant of SARS-CoV-2 were found to have a slower recovery as indicated by longer length of stay and higher shedding of the virus compared to alpha variant infections, and this trend was consistent in both vaccinated and unvaccinated patients.

On the association between SARS-COV-2 variants and COVID-19 mortality during the second wave of the pandemic in Europe

OBJECTIVE

This study aims at investigating associations between COVID-19 mortality and SARS-COV-2 variants spread during the second wave of COVID-19 pandemic in Europe.

METHODS

For 38 European countries, data on numbers of COVID-19 deaths, SARS-COV-2 variants spread through time using Nextstrain classification, demographic and health characteristics were collected. Cumulative number of COVID-19 deaths and height of COVID-19 daily deaths peak during the second wave of the pandemic were considered as outcomes. Pearson correlations and multivariate generalized linear models with selection algorithms were used.

RESULTS

The average proportion of B.1.1.7 variant was found to be a significant predictor of cumulative COVID-19 deaths within two months before the peak and between 1 January-25 February 2021, as well as of the deaths peak height considering proportions during the second wave and the pre-peak period. The average proportion of EU2 variant (S:477 N) was a significant predictor of cumulative COVID-19 deaths in the pre-peak period.

CONCLUSIONS

Our findings suggest that spread of a new variant of concern B.1.1.7 had a significant impact on mortality during the second wave of COVID-19 pandemic in Europe and that proportions of EU2 and B.1.1.7 variants were associated with increased mortality in the initial phase of that wave.