Relationship between Influenza Vaccination Coverage Rate and COVID-19 Outbreak: An Italian Ecological Study

Evaluation of the Effect of Influenza Vaccine on the Development of Symptoms in SARS-CoV-2 Infection and Outcome in Patients Hospitalized due to COVID-19

BACKGROUND

COVID-19 is an infectious disease caused by SARS-CoV-2. It is unclear whether influenza vaccination reduces the severity of disease symptoms. Previous studies have suggested a beneficial effect of influenza vaccination on the severity of COVID-19. The aim of this study was to evaluate the possible protective effect of the influenza vaccine on the occurrence of SARS-CoV-2 infection symptoms and prognosis in patients hospitalized with COVID-19.

METHODS

This was a retrospective cohort study of patients who tested positive for SARS-CoV-2, identified by quantitative real-time polymerase chain reaction. Chi-square tests, Kaplan-Meier analysis, and multivariate analysis were performed to assess the association between influenza vaccination and the presence of symptoms in hospitalized patients with COVID-19 and their outcome.

RESULTS

In this study, 1712 patients received positive laboratory tests for SARS-CoV-2; influenza vaccination was a protective factor against the presence of characteristic COVID-19 symptoms such as polypnea, anosmia, dysgeusia, and fever (p < 0.001). Influenza-vaccinated patients had fewer days of hospitalization (p = 0.029).

CONCLUSIONS

The findings of this study support that influenza vaccination is associated with a decrease in the number of symptoms in patients hospitalized due to COVID-19, with fewer days of hospitalization, but not with the outcome of disease.

Influenza Vaccination Mediates SARS-CoV-2 Spike Protein Peptide-Induced Inflammatory Response via Modification of Histone Acetylation

The effectiveness of coronavirus disease 2019 (COVID-19) vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain rapidly wanes over time. Growing evidence from epidemiological studies suggests that influenza vaccination is associated with a reduction in the risk of SARS-CoV-2 infection and COVID-19 severity. However, the underlying mechanisms remain elusive. Here, we investigate the cross-reactive immune responses of influenza vaccination to SARS-CoV-2 spike protein peptides based on in vitro study. Our data indicate enhanced activation-induced-marker (AIM) expression on CD4+ T cells in influenza-vaccination (IV)-treated peripheral blood mononuclear cells (PBMCs) upon stimulation with spike-protein-peptide pools. The fractions of other immune cell subtypes, including CD8+ T cells, monocytes, NK cells, and antigen-presenting cells, were not changed between IV-treated and control PBMCs following ex vivo spike-protein-peptide stimulation. However, the classical antiviral (IFN-γ) and anti-inflammatory (IL-1RA) cytokine responses to spike-protein-peptide stimulation were still enhanced in PBMCs from both IV-immunized adult and aged mice. Decreased expression of proinflammatory IL-1β, IL-12p40, and TNF-α is associated with inhibited levels of histone acetylation in PBMCs from IV-treated mice. Remarkably, prior immunity to SARS-CoV-2 does not result in modification of histone acetylation or hemagglutinin-protein-induced cytokine responses. This response is antibody-independent but can be mediated by manipulating the histone acetylation of PBMCs. These data experimentally support that influenza vaccination could induce modification of histone acetylation in immune cells and reveal the existence of potential cross-reactive immunity to SARS-CoV-2 antigens, which may provide insights for the adjuvant of influenza vaccine to limit COVID-19-related inflammatory responses.

Influenza vaccination and COVID-19 infection risk and disease severity: A systematic review and multilevel meta-analysis of prospective studies

BACKGROUND

In light of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, the influence of influenza vaccination on the risk and severity of Coronavirus Disease 19 (COVID-19) has been a subject of debate. This systematic review and meta-analysis of prospective studies aim to assess the association between influenza immunization and the risk of SARS-CoV-2 infection and subsequent COVID-19 disease severity.

METHODS

A comprehensive search of PubMed and Embase databases was performed to identify prospective studies published before March 2024. We focused on evaluating the effect of influenza vaccination on SARS-CoV-2 infection risk and severe COVID-19 outcomes, such as hospitalization and mortality. The analysis employed a multilevel random effects meta-analysis approach. The risk of bias assessment was conducted using the Newcastle-Ottawa Scale.

RESULTS

From an initial pool of 5,863 records, 14 studies were selected for inclusion. The aggregated data yielded a summary relative risk (SRR) that showed no significant protective correlation between influenza vaccination and SARS-CoV-2 infection risk (SRR 0.95, 95% confidence interval [CI] 0.81-1.11), COVID-19-associated hospitalization (SRR 0.90, 95% CI 0.68-1.19), or COVID-19-related mortality (SRR 0.83, 95% CI 0.56-1.23).

CONCLUSIONS

This systematic review and meta-analysis, based exclusively on prospective studies, demonstrates the lack of a proven protective effect of influenza vaccination against COVID-19 and related outcomes. Our results do not support a significant protective effect of influenza vaccination against the risk or severe outcomes of COVID-19.

Specific and Nonspecific Effects of Influenza Vaccines

With the introduction of the influenza vaccine in the official immunization schedule of most countries, several data regarding the efficacy, tolerability, and safety of influenza immunization were collected worldwide. Interestingly, together with the confirmation that influenza vaccines are effective in reducing the incidence of influenza virus infection and the incidence and severity of influenza disease, epidemiological data have indicated that influenza immunization could be useful for controlling antimicrobial resistance (AMR) development. Knowledge of the reliability of these findings seems essential for precise quantification of the clinical relevance of influenza immunization. If definitively confirmed, these findings can have a relevant impact on influenza vaccine development and use. Moreover, they can be used to convince even the most recalcitrant health authorities of the need to extend influenza immunization to the entire population. In this narrative review, present knowledge regarding these particular aspects of influenza immunization is discussed. Literature analysis showed that the specific effects of influenza immunization are great enough per se to recommend systematic annual immunization of younger children, old people, and all individuals with severe chronic underlying diseases. Moreover, influenza immunization can significantly contribute to limiting the emergence of antimicrobial resistance. The problem of the possible nonspecific effects of influenza vaccines remains unsolved. The definition of their role as inducers of trained immunity seems essential not only to evaluate how much they play a role in the prevention of infectious diseases but also to evaluate whether they can be used to prevent and treat clinical conditions in which chronic inflammation and autoimmunity play a fundamental pathogenetic role.

Flu vaccine administration in the period before SARS-CoV-2 infection and its outcomes: An umbrella review

Objective

The potential association between influenza vaccination and SARS-CoV-2 infection and related outcomes is still controversial. The aim of this umbrella review is to represent the impact of previous influenza vaccination and COVID-19 outcomes using evidence currently available in literature.

Methods

A literature search of MEDLINE, EMBASE, Scopus, Web of Science and Cochrane Library was conducted. The paper selection was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method by two-blinded authors. The quality of meta-analyses was assessed using the AMSTAR 2 scale (A MeaSurement Tool to Assess systematic Reviews). The outcomes investigated were SARS-CoV-2 infection after influenza vaccination, hospitalization, intensive care unit admission, mechanical ventilation and mortality.

Results

The literature research identified 7 ecological studies and 6 meta-analyses. All the ecological studies show a negative relationship between influenza vaccination and COVID-19. The meta-analyses suggest a protective action of influenza vaccination against SARS-CoV-2 infection. Regarding the outcomes evaluated, only two studies reported a statistically significant reduction of 12% and of 17% in hospitalization and intensive care unit admission, respectively. Regarding mechanical ventilation, three studies showed a risk reduction of 31%, 27% and 28%. A substantial reduction of mortality risk was also observed in one study.

Conclusions

These results suggest that influenza vaccination could be associated with reduced susceptibility to SARS-CoV-2 infection, mechanical ventilation and mortality. Our findings highlighted how the administration of flu vaccine in subjects at risk could lead to a reduction in mortality, particularly in the over 65y.

Vaccination against influenza viruses reduces infection, not hospitalization or death, from respiratory COVID-19: A systematic review and meta-analysis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and has brought a huge burden in terms of human lives. Strict social distance and influenza vaccination have been recommended to avoid co-infections between influenza viruses and SARS-CoV-2. Scattered reports suggested a protective effect of influenza vaccine on COVID-19 development and severity. We analyzed 51 studies on the capacity of influenza vaccination to affect infection with SARS-CoV-2, hospitalization, admission to Intensive Care Units (ICU), and mortality. All subjects taken into consideration did not receive any anti-SARS-CoV-2 vaccine, although their status with respect to previous infections with SARS-CoV-2 is not known. Comparison between vaccinated and not-vaccinated subjects for each of the four endpoints was expressed as odds ratio (OR), with 95% confidence intervals (CIs); all analyses were performed by DerSimonian and Laird model, and Hartung-Knapp model when studies were less than 10. In a total of 61 029 936 subjects from 33 studies, influenza vaccination reduced frequency of SARS-CoV-2 infection [OR plus 95% CI = 0.70 (0.65-0.77)]. The effect was significant in all studies together, in health care workers and in the general population; distance from influenza vaccination and the type of vaccine were also of importance. In 98 174 subjects from 11 studies, frequency of ICU admission was reduced with influenza vaccination [OR (95% CI) = 0.71 (0.54-0.94)]; the effect was significant in all studies together, in pregnant women and in hospitalized subjects. In contrast, in 4 737 328 subjects from 14 studies hospitalization was not modified [OR (95% CI) = 1.05 (0.82-1.35)], and in 4 139 660 subjects from 19 studies, mortality was not modified [OR (95% CI) = 0.76 (0.26-2.20)]. Our study emphasizes the importance of influenza vaccination in the protection against SARS-CoV-2 infection.

An overview on viral interference during SARS-CoV-2 pandemic

Respiratory viruses represent the most frequent cause of mortality, morbidity and high healthcare costs for emergency visits and hospitalization in the pediatric age. Respiratory viruses can circulate simultaneously and can potentially infect the same host, determining different types of interactions, the so-called viral interference. The role of viral interference has assumed great importance since December 2019, when the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) came on the scene. The aim of this narrative review is to present our perspective regarding research in respiratory virus interference and discuss recent advances on the topic because, following SARS-CoV-2 restrictions mitigation, we are experimenting the co-circulation of respiratory viruses along with SARS-CoV-2. This scenario is raising many concerns about possible virus-virus interactions, both positive and negative, and the clinical, diagnostic and therapeutic management of these coinfections. Moreover, we cannot rule out that also climatic conditions and social behaviours are involved. Thus, this situation can lead to different population epidemic dynamics, including changes in the age of the targeted population, disease course and severity, highlighting the need for prospective epidemiologic studies and mathematical modelling able to predict the timing and magnitude of epidemics caused by SARS-CoV-2/seasonal respiratory virus interactions in order to adjust better public health interventions.

Flu vaccination coverage in Italy in the COVID-19 era: A fuzzy functional k-means (FFKM) approach

BACKGROUND

In Europe, flu vaccination coverage has decreased, and there are complex barriers to overcome to vaccinate against flu. Many studies have been conducted to estimate vaccination coverage. The COVID-19 pandemic threatens to disrupt immunization programs in many countries, including Italy, where vaccination against the flu is recommended but not mandatory. This paper aims to understand changes in flu vaccine uptake in Italian regions.

METHODS

Using functional data analysis and fuzzy functional k-means clustering, we investigated changes in flu vaccine coverage in Italian regions before (2010-2019) and after (2020-2022) the COVID-19 vaccination period.

RESULTS

The period of COVID-19 pandemic brought an increase in vaccine coverage globally. Elbow's method determined that the optimal number of clusters in vaccination uptake is 2. Apulia, Basilicata, Emilia Romagna, Liguria, Molise, Tuscany, and Umbria in 2019 belong less to the group with low flu vaccination uptake (G1) but increase their tendency to belong to this group over time: they decrease their propensity to be vaccinated for flu. For others, it seems that COVID-19 served as a push to increase flu vaccination coverage rates. Sicily appears to be the region that has responded best to the pandemic, changing its membership value from 2019 to 2022.

CONCLUSION

The present study highlights that the COVID-19 era has resulted in a higher flu vaccination coverage rate. Moreover, the regional level's improvement or worsening in flu vaccination coverage rate is not affected by the historical gap and socio-cultural and economic differences prevailing among Italian regions.

Pleiotropic Effects of Influenza Vaccination

Influenza vaccines are designed to mimic natural influenza virus exposure and stimulate a long-lasting immune response to future infections. The evolving nature of the influenza virus makes vaccination an important and efficacious strategy to reduce healthcare-related complications of influenza. Several lines of evidence indicate that influenza vaccination may induce nonspecific effects, also referred to as heterologous or pleiotropic effects, that go beyond protection against infection. Different explanations are proposed, including the upregulation and downregulation of cytokines and epigenetic reprogramming in monocytes and natural killer cells, imprinting an immunological memory in the innate immune system, a phenomenon termed "trained immunity". Also, cross-reactivity between related stimuli and bystander activation, which entails activation of B and T lymphocytes without specific recognition of antigens, may play a role. In this review, we will discuss the possible nonspecific effects of influenza vaccination in cardiovascular disease, type 1 diabetes, cancer, and Alzheimer's disease, future research questions, and potential implications. A discussion of the potential effects on infections by other pathogens is beyond the scope of this review.

Ethnic disparities in COVID-19 outcomes: a multinational cohort study of 20 million individuals from England and Canada

BACKGROUND

Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes.

METHODS

We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the 'percentage of excess risk mediated' by these risk factors in the QResearch cohort.

RESULTS

There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death.

CONCLUSION

International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health policy as the pandemic continues.

The Effect of COVID-19 Vaccine Acceptance, Intention, and/or Hesitancy and Its Association with Our Health and/or Important Areas of Functioning

The emergence of coronavirus 2019 (COVID-19) has had a significant negative impact on the world, with its effect noted in various areas, such as commerce [...].

Analysis on the intention and influencing factors of free influenza vaccination among the elderly people aged 70 and above in Hangzhou in 2022

Background

Although influenza vaccination is recommended for people aged 70 and above in Hangzhou, and the vaccine is provided free of charge, the elderly influenza vaccination rate is still low. The purpose of this study was to understand the barriers and motivations of older people in deciding to receive free influenza vaccine through questionnaires.

Methods

The method of stratified random sampling was adopted to take samples. A questionnaire survey was conducted among the elderly aged 70 years and above by face-to-face interview or telephone interview.

Results

A total of 11,663 elderly people aged 70-100 years were successfully and effectively interviewed. 85.98% of the respondent were willing to get the influenza shot, 8.91% were unwilling to get the influenza shot, and 5.11% were on vaccine hesitancy. The people of age of 70-79 years old (hesitancy: OR 70~79 = 0.668, 95%CI: 0.571 0.782, Unwilling: OR 70 - 79 = 0.755, 95%CI: 0.622 0.916), primary school degree or below (hesitancy: OR Secondary school degree or above = 1.467, 95%CI: 1.249 1.724, Unwilling: OR Secondary school degree or above = 1.255, 95%CI: 1.028 1.535), remote areas (hesitancy: OR near central urban area = 2.111, 95%CI: 1.604 2.778, OR central urban area = 2.957, 95%CI: 2.255 3.877, Unwilling: OR near central urban area = 1.687, 95%CI: 1.230 2.313. OR centralurbanarea = 2.218, 95%CI: 1.626 3.027), and convenient for movement (hesitancy: OR yes = 0.494, 95%CI: 0.420 0.580, Unwilling: OR yes = 0.585, 95%CI: 0.480 0.713), understanding of the free vaccine policy (hesitancy: OR understand = 0.204, 95%CI: 0.171 0.245, Unwilling: OR understand = 0.164, 95%CI: 0.128 0.210), influenza knowledge level≥ 13 points (hesitancy: OR ≥13points = 0.628, 95%CI: 0.533 0.739, Unwilling: OR ≥13points = 0.538, 95%CI: 0.437 0.662), influenza vaccine knowledge level≥ 12 points (hesitancy: OR ≥12points = 0.422, 95%CI: 0.350 0.508, Unwilling: OR ≥12points = 0.370, 95%CI: 0.290 0.472), and social trust level ≥ 12 points (hesitancy: OR ≥12points = 0.134, 95%CI: 0.112 0.160, Unwilling: OR ≥12points = 0.220, 95%CI: 0.180 0.269) are more willing to receive free influenza vaccine.

Conclusion

The proportion of elderly people aged 70 and above who are willing to receive free influenza vaccine is high in Hangzhou. But the level of knowledge about influenza, vaccine and trust in society is low. The government should continue to improve the elderly's awareness and trust in society through medical staff, family members, television and radio media, and guide the elderly to actively vaccinate against influenza. Effective publicity should be carried out through the above channels to guide the elderly to actively vaccinate against influenza.

Influenza and Pneumococcal Vaccination and the Risk of COVID-19: A Systematic Review and Meta-Analysis

A number of studies have investigated the potential on-specific effects of some routinely administered vaccines (e.g., influenza, pneumococcal) on COVID-19 related outcomes, with contrasting results. In order to elucidate this discrepancy, we conducted a systematic review and meta-analysis to assess the association between seasonal influenza vaccination and pneumococcal vaccination with SARS-CoV-2 infection and its clinical outcomes. PubMed and medRxiv databases were searched up to April 2022. A random effects model was used in the meta-analysis to pool odds ratio (OR) and adjusted estimates with 95% confidence intervals (CIs). Heterogeneity was quantitatively assessed using the Cochran's Q and the I2 index. Subgroup analysis, sensitivity analysis and assessment of publication bias were performed for all outcomes. In total, 38 observational studies were included in the meta-analysis and there was substantial heterogeneity. Influenza and pneumococcal vaccination were associated with lower risk of SARS-CoV-2 infection (OR: 0.80, 95% CI: 0.75-0.86 and OR: 0.70, 95% CI: 0.57-0.88, respectively). Regarding influenza vaccination, it seems that the majority of studies did not properly adjust for all potential confounders, so when the analysis was limited to studies that adjusted for age, gender, comorbidities and socioeconomic indices, the association diminished. This is not the case regarding pneumococcal vaccination, for which even after adjustment for such factors the association persisted. Regarding harder endpoints such as ICU admission and death, current data do not support the association. Possible explanations are discussed, including trained immunity, inadequate matching for socioeconomic indices and possible coinfection.

Factors associated with influenza vaccination coverage and willingness in the elderly with chronic diseases in Shenzhen, China

Elderly individuals with chronic illnesses are more prone to get influenza. We aimed to investigate the factors associated with influenza coverage and willingness in chronic disease patients aged ≥60 years in Longhua district, Shenzhen City of southern China. Data collected in October 2020 were used in this work. The immunization status of older persons with chronic conditions and their willingness to receive the vaccine were assessed. Multivariable logistic regression was employed to determine the respective independent factors related to vaccination coverage and willingness for influenza. Only 4.8% of 5045 people were immunized against influenza, whereas 92.7% of the individuals agreed to receive the vaccine. Individuals between the ages of 70 and 79 (adjusted OR [aOR] 1.47, P = .012), those with higher education levels (aOR 1.53, P = .005 for high school; aOR 2.44, P < .001 for college or above), those who use of a family doctor (aOR 2.91, P < .001), those who frequently have physical examinations once a year (aOR 2.52, P < .001), and those who have never smoked (aOR 1.62, P = .018) were positively associated with the influenza vaccination. Meanwhile, older age was adversely linked with influenza vaccination willingness (aOR 0.68 for 70-79 years, P = .003; aOR 0.55 for≥80 years, P = .025) in contrast to those aged 60-69. High willingness to get vaccinated was more frequent in people with a high school diploma (aOR 1.33, P = .037). In this work, we observed that the coverage is poor but the immunization desire is high regarding influenza vaccination. Interestingly, older age was associated with higher coverage and lower willingness. These suggest that raising immunization rates among older people with chronic conditions and strengthening health education for caregivers should be the primary concerns.

Association between influenza vaccination and SARS-CoV-2 infection and its outcomes: systematic review and meta-analysis

BACKGROUND

World Health Organization recommends that influenza vaccines should benefit as much of the population as possible, especially where resources are limited. Corona virus disease 2019 (COVID-19) has become one of the greatest threats to health systems worldwide. The present study aimed to extend the evidence of the association between influenza vaccination and COVID-19 to promote the former.

METHODS

In this systematic review, four electronic databases, including the Cochrane Library, PubMed, Embase, and Web of Science, were searched for related studies published up to May 2022. All odds ratios (ORs) with 95% confidence intervals (CIs) were pooled by meta-analysis.

RESULTS

A total of 36 studies, encompassing 55,996,841 subjects, were included in this study. The meta-analysis for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provided an OR of 0.80 (95% CI: 0.73-0.87). The statistically significant estimates for clinical outcomes were 0.83 (95% CI: 0.72-0.96) for intensive care unit admission, 0.69 (95% CI: 0.57-0.84) for ventilator support, and 0.69 (95% CI: 0.52-0.93) for fatal infection, while no effect seen in hospitalization with an OR of 0.87 (95% CI: 0.68-1.10).

CONCLUSION

Influenza vaccination helps limit SARS-CoV-2 infection and severe outcomes, but further studies are needed.

REGISTRATION

PROSPERO, CRD42022333747.

Forecasting Model Based on Lifestyle Risk and Health Factors to Predict COVID-19 Severity

The COVID-19 pandemic has now spread worldwide, becoming a real global health emergency. The main goal of this work is to present a framework for studying the impact of COVID-19 on Italian territory during the first year of the pandemic. Our study was based on different kinds of health features and lifestyle risk factors and exploited the capabilities of machine learning techniques. Furthermore, we verified through our model how these factors influenced the severity of the pandemics. Using publicly available datasets provided by the Italian Civil Protection, Italian Ministry of Health and Italian National Statistical Institute, we cross-validated the regression performance of a Random Forest model over 21 Italian regions. The robustness of the predictions was assessed by comparison with two other state-of-the-art regression tools. Our results showed that the proposed models reached a good agreement with data. We found that the features strongly associated with the severity of COVID-19 in Italy are the people aged over 65 flu vaccinated (24.6%) together with individual lifestyle behaviors. These findings could shed more light on the clinical and physiological aspects of the disease.

Impact of influenza vaccination on GP-diagnosed COVID-19 and all-cause mortality: a Dutch cohort study

OBJECTIVES

As clinical presentation and complications of both viruses overlap, it was hypothesised that influenza vaccination was associated with lower general practitioner (GP)-diagnosed COVID-19 rates and lower all-cause mortality rates.

STUDY DESIGN

From a primary care population-based cohort in the Netherlands, GP-diagnosed COVID-19 (between 10 March and 22 November 2020) and all-cause mortality events (between 30 December 2019 and 22 November 2020) were recorded. 223 580 persons were included, representing the influenza vaccination 2019 target group (all aged ≥60 years, and those <60 years with a medical indication). Proportional hazards regression analyses evaluated associations between influenza vaccination in 2019 and two outcomes: GP-diagnosed COVID-19 and all-cause mortality. Covariables were sex, age, comorbidities and number of acute respiratory infection primary care consultations in 2019.

RESULTS

A slightly positive association (HR 1.15; 95% CI 1.08 to 1.22) was found between influenza vaccination in 2019 and GP-diagnosed COVID-19, after adjusting for covariables. A slightly protective effect for all-cause mortality rates (HR 0.90; 95% CI 0.83 to 0.97) was found for influenza vaccination, after adjusting for covariables. A subgroup analysis among GP-diagnosed COVID-19 cases showed no significant association between influenza vaccination in 2019 and all-cause mortality.

CONCLUSIONS

Our hypothesis of a possibly negative association between influenza vaccination in 2019 and GP-diagnosed COVID-19 was not confirmed as we found a slightly positive association. A slightly protective effect on all-cause mortality was found after influenza vaccination, possibly by a wider, overall protective effect on health. Future research designs should include test-confirmed COVID-19 cases and controls, adjustments for behavioural, socioeconomic and ethnic factors and validated cause-specific mortality cases.

Cross-reactivity of SARS-CoV-2- and influenza A-specific T cells in individuals exposed to SARS-CoV-2

Cross-reactive immunity between SARS-CoV-2 and other related coronaviruses has been well-documented, and it may play a role in preventing severe COVID-19. Epidemiological studies early in the pandemic showed a geographical association between high influenza vaccination rates and lower incidence of SARS-CoV-2 infection. We, therefore, analyzed whether exposure to influenza A virus (IAV) antigens could influence the T cell repertoire in response to SARS-CoV-2, indicating a heterologous immune response between these 2 unrelated viruses. Using artificial antigen-presenting cells (aAPCs) combined with real-time reverse-transcription PCR (RT-qPCR), we developed a sensitive assay to quickly screen for antigen-specific T cell responses and detected a significant correlation between responses to SARS-CoV-2 epitopes and IAV dominant epitope (M158-66). Further analysis showed that some COVID-19 convalescent donors exhibited both T cell receptor (TCR) specificity and functional cytokine responses to multiple SARS-CoV-2 epitopes and M158-66. Utilizing an aAPC-based stimulation/expansion assay, we detected cross-reactive T cells with specificity to SARS-CoV-2 and IAV. In addition, TCR sequencing of the cross-reactive and IAV-specific T cells revealed similarities between the TCR repertoires of the two populations. These results indicate that heterologous immunity shaped by our exposure to other unrelated endemic viruses may affect our immune response to novel viruses such as SARS-CoV-2.

Does Influenza Vaccination Reduce the Risk of Contracting COVID-19?

The concurrent timing of the COVID-19 pandemic and the seasonal occurrence of influenza, makes it especially important to analyze the possible effect of the influenza vaccine on the risk of contracting COVID-19, or in reducing the complications caused by both diseases, especially in vulnerable populations. There is very little scientific information on the possible protective role of the influenza vaccine against the risk of contracting COVID-19, particularly in groups at high-risk of influenza complications. Reducing the risk of contracting COVID-19 in high-risk patients (those with a higher risk of infection, complications, and death) is essential to improve public well-being and to reduce hospital pressure and the collapse of primary health centers. Apart from overlapping in time, COVID-19 and flu share common aspects of transmission, so that measures to protect against flu might be effective in reducing the risk of contracting COVID-19. In this study, we conclude that the risk of contracting COVID-19 is reduced if patients are vaccinated against flu, but the reduction is small (0.22%) and therefore not clinically important. When this reduction is analysed based on the risk factor suffered by the patient, statistically significant differences have been obtained for patients with cardiovascular problems, diabetics, chronic lung and chronic kidney disease; in all four cases the reduction in the risk of contagion does not reach 1%. It is worth highlighting the behaviour that is completely different from the rest of the data for institutionalized patients. The data for these patients does not suggest a reduction in the risk of contagion for patients vaccinated against the flu, but rather the opposite, a significant increase of 6%. Socioeconomic conditions, as measured by the MEDEA deprivation index, explain increases in the risk of contracting COVID-19, and awareness campaigns should be increased to boost vaccination programs.

How influenza vaccination and virus interference may impact combined influenza-coronavirus disease burden

Demand for influenza vaccine rose as countries prepared for the second COVID-19 wave over the winter months of 2020-2021. High coverage of the influenza vaccine can significantly reduce morbidity and mortality of the burden of influenza. Natural influenza infection creates short-term non-specific immunity against respiratory viruses (virus interference). We model two viral diseases, both of the SEIR type, to investigate whether the influenza vaccine increases the combined disease burden of influenza and COVID-19 in a dual outbreak. We show that the combined disease burden’s behavior depends on virus interference factors and the proportion of the population vaccinated against influenza. Our results indicate that influenza vaccination only lowers the overall disease burden when net virus interference is relatively low.

Health impact of the first and second wave of COVID-19 and related restrictive measures among nursing home residents: a scoping review

Background and objectives

COVID-19 disproportionally affects older adults living in nursing homes. The purpose of this review was to explore and map the scientific literature on the health impact of COVID-19 and related restrictive measures during the first and second wave among nursing home residents. A specific focus was placed on health data collected among nursing home residents themselves.

Research design and methods

In this study, best practices for scoping reviews were followed. Five databases were systematically searched for peer-reviewed empirical studies published up until December 2020 in which data were collected among nursing home residents. Articles were categorized according to the type of health impact (physical, social and/or psychological) and study focus (impact of COVID-19 virus or related restrictive measures). Findings were presented using a narrative style.

Results

Of 60 included studies, 57 examined the physical impact of COVID-19. All of these focused on the direct impact of the COVID-19 virus. These studies often used an observational design and quantitative data collection methods, such as swab testing or reviewing health records. Only three studies examined the psychological impact of COVID-19 of which one study focused on the impact of COVID-19-related restrictive measures. Findings were contradictory; both decreased and improved psychological wellbeing was found during the pandemic compared with before. No studies were found that examined the impact on social wellbeing and one study examined other health-related outcomes, including preference changes of nursing home residents in Advanced Care planning following the pandemic.

Discussion and implications

Studies into the impact of the first and second wave of the COVID-19 pandemic among nursing home residents predominantly focused on the physical impact. Future studies into the psychological and social impact that collect data among residents themselves will provide more insight into their perspectives, such as lived experiences, wishes, needs and possibilities during later phases of the pandemic. These insights can inform policy makers and healthcare professionals in providing person-centered care during the remaining COVID-19 pandemic and in future crisis periods.

The Association Between Previous Influenza Vaccination and COVID-19 Infection Risk and Severity: A Systematic Review and Meta-analysis

INTRODUCTION

The association between influenza vaccination and COVID-19 remains controversial. This meta-analysis aimed to investigate whether influenza vaccination reduces the susceptibility and severity of SARS-CoV-2 infection.

METHODS

A systematic literature search of PubMed, Web of Science, the Cochrane Library, Embase, China National Knowledge Infrastructure, SinoMed, Wanfang Data Knowledge Service Platform, and China Science and Technology Journal VIP Database was conducted from database inception to August 2021. The pooled RR with 95% CI was used to estimate the effect of influenza vaccination on COVID-19. The I² value was used to assess heterogeneity. If I²>50%, the random-effects model was used as the pooling method.

RESULTS

A total of 23 published articles with 1,037,445 participants were identified. This meta-analysis showed that influenza vaccination was associated with reduced risk of COVID-19 infection (RR=0.83, 95% CI=0.76, 0.90) and hospitalization (RR=0.71, 95% CI=0.59, 0.84), although not significantly associated with intensive care unit admission and death (risk of intensive care unit admission: RR=0.93, 95% CI=0.64, 1.36; risk of death: RR=0.83, 95% CI=0.68, 1.01). Further analysis suggested that the tetravalent influenza vaccine may be associated with a reduced risk of COVID-19 infection (RR=0.74, 95% CI=0.65, 0.84).

DISCUSSION

The results suggest that influenza vaccination is associated with reduced susceptibility to or disease severity of COVID-19 and that influenza vaccination may reduce the risk of COVID-19 and improve clinical outcomes.

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Background

The COVID-19 is a significant public health issue, and monitoring confirmed cases and deaths is an essential epidemiologic tool. We evaluated the features in Brazilian hospitalized patients due to severe acute respiratory infection (SARI) during the COVID-19 pandemic in Brazil. We grouped the patients into the following categories: Influenza virus infection (G1), other respiratory viruses' infection (G2), other known etiologic agents (G3), SARS-CoV-2 infection (patients with COVID-19, G4), and undefined etiological agent (G5).

Methods

We performed an epidemiological study using data from DataSUS (https://opendatasus.saude.gov.br/) from December 2019 to October 2021. The dataset included Brazilian hospitalized patients due to SARI. We considered the clinical evolution of the patients with SARI during the COVID-19 pandemic according to the SARI patient groups as the outcome. We performed the multivariate statistical analysis using logistic regression, and we adopted an Alpha error of 0.05.

Results

A total of 2,740,272 patients were hospitalized due to SARI in Brazil, being the São Paulo state responsible for most of the cases [802,367 (29.3%)]. Most of the patients were male (1,495,416; 54.6%), aged between 25 and 60 years (1,269,398; 46.3%), and were White (1,105,123; 49.8%). A total of 1,577,279 (68.3%) patients recovered from SARI, whereas 701,607 (30.4%) died due to SARI, and 30,551 (1.3%) did not have their deaths related to SARI. A major part of the patients was grouped in G4 (1,817,098; 66.3%) and G5 (896,207; 32.7%). The other groups account for &lt;1% of our sample [G1: 3,474 (0.1%), G2: 16,627 (0.6%), and G3: 6,866 (0.3%)]. The deaths related to SARI were more frequent in G4 (574,887; 34.7%); however, the deaths not related to SARI were more frequent among the patients categorized into the G3 (1,339; 21.3%) and G5 (25,829; 4.1%). In the multivariate analysis, the main predictors to classify the patients in the G5 when compared with G4 or G1-G4 were female sex, younger age, Black race, low educational level, rural place of residence, and the use of antiviral to treat the clinical signs. Furthermore, several features predict the risk of death by SARI, such as older age, race (Black, Indigenous, and multiracial background), low educational level, residence in a flu outbreak region, need for intensive care unit, and need for mechanical ventilatory support.

Conclusions

The possible COVID-19 underreporting (G5) might be associated with an enhanced mortality rate, more evident in distinct social groups. In addition, the patients' features are unequal between the patients' groups and can be used to determine the risk of possible COVID-19 underreporting in our population. Patients with a higher risk of death had a different epidemiological profile when compared with patients who recovered from SARI, like older age, Black, Indigenous, and multiracial background races, low educational level, residence in a flu outbreak region, need for intensive care unit and need for mechanical ventilatory support.

Flu and COVID-19 Vaccination: What Happens to the Flu Shot When the Campaigns Overlap? Experience from a Large Italian Research Hospital

Influenza represents a threat to global health and health care workers (HCWs) have an increased risk of contracting the influenza virus in the workplace. The COVID-19 pandemic has brought back the importance of influenza vaccination, as the influenza virus can circulate together with SARS-CoV-2. The aim of this report is to describe the actual flu vaccination coverage among healthcare workers of a research hospital and the trend changes, with respect to the past flu vaccination campaigns, in light of the present pandemic and COVID-19 vaccination. A Pearson’s χ2 test was used to test the correlation of flu vaccination coverage, across all professional categories, between the last two years. A linear regression model was adopted to predict the total vaccination coverage of this year. A statistically significant decrease (p < 0.01) was observed in vaccination coverage among all the professional categories with a 50% reduction in vaccination trends between the last two years. Analyzing the data from the previous six flu vaccination campaigns, the expected value, according to the linear regression model, was estimated to be 38.5% while the observed value was 24%. The decrease in vaccination coverage may be due to the fear of the pandemic situation and especially to the uncertainty related to the consequences of a concurrent administration which may overload the immune system or may be more reactogenic. The COVID-19 pandemic represents an opportunity to promote and support large-scale influenza vaccination among HCWs through structured programs, adequate funding, and tailored communication strategies.

Ecologic study of influenza vaccination uptake and COVID-19 death rate in New York City

BACKGROUND

The aim of this ecological study was to assess the area-level relationship between cumulative death rate for COVID-19 and historic influenza vaccination uptake in the New York City population.

METHODS

Predictors of COVID-19 death included self-reported influenza vaccination in 2017, as well as four CDC-defined risk factors of severe COVID-19 infection available at the ecological level, which were diabetes, asthma, BMI 30-100 (2 kg/m2) and hypertension, in addition to race and age (65 + years).

RESULTS

After adjusting for potential confounders, for every one-unit increase in influenza vaccination uptake for each zip code area, the rate of COVID-19 deaths decreased by 5.17 per 100,000 residents (p < 0.0001).

CONCLUSIONS

Zip codes with a higher prevalence of influenza vaccination had lower rates of COVID-19 mortality, inciting the need to further explore the relationship between influenza vaccination uptake and COVID-19 mortality at the individual level.

Association between influenza vaccination and mortality due to COVID-19

Background

It has recently been suggested that influenza vaccination may be a factor associated with decreased COVID-19 mortality.

Methods

An age-matched case–control study based on hospital cases. We included subjects aged 18 years and older with a diagnosis of moderate to severe COVID-19. Infection was corroborated by RT-PCR test for SARS-COV-2. Deceased subjects were considered cases, controls were patients discharged due to improvement of acute symptoms. We used bivariate analysis to determine factors associated with death from COVID-19, and calculated odds ratios and 95% confidence intervals.

Results

A total of 560 patients were included in the study, 214 (38.2%) were considered cases and 346 (61.7%) controls. A significant difference was observed with the presence of type 2 diabetes mellitus [54% vs. 39.3% between cases and controls, respectively (P = 0.04)] and having received influenza vaccination (P = 0.02). Type 2 diabetes mellitus was associated with higher COVID-19 mortality [OR 1.8 (95% CI 1.2–2.5) P = 0.01], whereas having been immunised against influenza in 2019 was associated with lower mortality in this group of patients [OR 0.6 (95% CI 0.4–0.9) P = 0.02].

Conclusions

Influenza vaccination in the previous year appears to be associated with lower mortality from COVID-19; whereas type 2 diabetes mellitus is confirmed as a condition associated with higher mortality.

Prevalence of Anti-SARS-CoV-2 Antibodies and Potential Determinants among the Belgian Adult Population: Baseline Results of a Prospective Cohort Study

The prevalence of anti-SARS-CoV-2 antibodies and potential determinants were assessed in a random sample representative of the Belgian adult population. In total, 14,201 individuals (≥18 years) were invited by mail to provide saliva via an Oracol^® swab. Survey weights were applied, and potential determinants were estimated using multivariable logistic regressions. Between March and August 2021, 2767 individuals participated in the first data collection. During this period, which coincided with the onset of the vaccination campaign, the seroprevalence in the population increased from 25.2% in March/April to 78.1% in July. Among the vaccinated there was an increase from 74,2% to 98.8%; among the unvaccinated, the seroprevalence remained stable (around 17%). Among the vaccinated, factors significantly associated with the presence of antibodies were: having at least one chronic disease (OR_a 0.22 (95% CI 0.08–0.62)), having received an mRNA-type vaccine (OR_a 5.38 (95% CI 1.72–16.80)), and having received an influenza vaccine in 2020–2021 (OR_a 3.79 (95% CI 1.30–11.07)). Among the unvaccinated, having a non-O blood type (OR_a 2.00 (95% CI 1.09–3.67)) and having one or more positive COVID-19 tests (OR_a 11.04 (95% CI 4.69–26.02)) were significantly associated. This study provides a better understanding of vaccine- and/or natural-induced presence of anti-SARS-CoV-2 antibodies and factors that are associated with this presence.

Effect of COVID-19 Pandemic on Influenza Vaccination Intention: A Meta-Analysis and Systematic Review

Poorer outcomes have been reported with COVID-19 and influenza coinfections. As the COVID-19 pandemic rages on, protection against influenza by vaccination is becoming increasingly important. This study examines how COVID-19 has influenced influenza vaccination intentions from a global perspective. A literature search was conducted on Embase, PubMed, and CNKI from 1 January 2019 to 31 December 2021 for articles reporting rates of influenza vaccination pre-COVID-19 (19/20 season), and intention and/or uptake of influenza vaccination post-COVID-19 (20/21 season). The changes in vaccination intention and reasons for changes were reported. Subgroup analyses were performed by region, gender, age, and occupation. Newcastle Ottawa Scale was used for quality assessment of the articles. Twenty-seven studies with 39,193 participants were included. Among 22 studies reporting intention to vaccinate in 20/21, there was increased intention to vaccinate (RR 1.50, 95% CI 1.32−1.69, p < 0.001) regardless of age, gender, and occupation. The remaining five studies reporting vaccination intention and uptake in 20/21 showed a similar increase (RR 1.68, 95%CI 1.20−2.36). Important determinants include historical vaccine acceptance, and perception of influenza severity and vaccine safety. The COVID-19 pandemic has increased intention to vaccinate against influenza internationally. The pandemic could be a window of opportunity to promote influenza vaccination and decrease vaccine hesitancy.

Effect of the 2020/21 season influenza vaccine on SARS-CoV-2 infection in a cohort of Italian healthcare workers

OBJECTIVES

Healthcare workers (HCWs) are a priority group for seasonal influenza vaccination (SIV). The 2020/21 SIV campaign was conducted during the second wave of the COVID-19 pandemic. Vaccines, including SIV, may exert non-specific protective effects on other infectious diseases which may be ascribable to the concept of trained immunity. The aim of this study was to explore the association between 2020/21 SIV and SARS-CoV-2 positivity in a cohort of Italian HCWs.

METHODS

In this observational study, a cohort of HCWs employed by a large (ca 5000 employees) referral tertiary acute-care university hospital was followed up retrospectively until the start of the COVID-19 vaccination campaign. The independent variable of interest was the 2020/21 SIV uptake. Both egg-based and cell culture-derived quadrivalent SIVs were available. The study outcome was the incidence of new SARS-CoV-2 infections, as determined by RT-PCR. Multivariable Cox regression was applied in order to discern the association of interest.

RESULTS

The final cohort consisted of 2561 HCWs who underwent ≥1 RT-PCR test and accounted for a total of 94,445 person-days of observation. SIV uptake was 35.6%. During the study period, a total of 290 new SARS-CoV-2 infections occurred. The incidence of new SARS-CoV-2 was 1.62 (95% CI: 1.22-2.10) and 3.91 (95% CI: 3.43-4.45) per 1000 person-days in vaccinated and non-vaccinated HCWs, respectively, with an adjusted non-proportional hazard ratio of 0.37 (95% CI: 0.22-0.62). E-values suggested that unmeasured confounding was unlikely to explain the association.

CONCLUSIONS

A lower risk of SARS-CoV-2 infection was observed among SIV recipients.

Epidemiological Consequences of Viral Interference: A Mathematical Modeling Study of Two Interacting Viruses

Some viruses have the ability to block or suppress growth of other viruses when simultaneously present in the same host. This type of viral interference or viral block has been suggested as a potential interaction between some respiratory viruses including SARS-CoV-2 and other co-circulating respiratory viruses. We explore how one virus' ability to block infection with another within a single host affects spread of the viruses within a susceptible population using a compartmental epidemiological model. We find that population-level effect of viral block is a decrease in the number of people infected with the suppressed virus. This effect is most pronounced when the viruses have similar epidemiological parameters. We use the model to simulate co-circulating epidemics of SARS-CoV-2 and influenza, respiratory syncytial virus (RSV), and rhinovirus, finding that co-circulation of SARS-CoV-2 and RSV causes the most suppression of SARS-CoV-2. Paradoxically, co-circulation of SARS-CoV-2 and influenza or rhinovirus results in almost no change in the SARS-CoV-2 epidemic, but causes a shift in the timing of the influenza and rhinovirus epidemics.

COVID-19 and Seasonal Influenza Vaccination: Cross-Protection, Co-Administration, Combination Vaccines, and Hesitancy

SARS-CoV-2 and influenza are the main respiratory viruses for which effective vaccines are currently available. Strategies in which COVID-19 and influenza vaccines are administered simultaneously or combined into a single preparation are advantageous and may increase vaccination uptake. Here, we comprehensively review the available evidence on COVID-19/influenza vaccine co-administration and combination vaccine candidates from the standpoints of safety, immunogenicity, efficacy, policy and public acceptance. While several observational studies have shown that the trained immunity induced by influenza vaccines can protect against some COVID-19-related endpoints, it is not yet understood whether co-administration or combination vaccines can exert additive effects on relevant outcomes. In randomized controlled trials, co-administration has proved safe, with a reactogenicity profile similar to that of either vaccine administered alone. From the immunogenicity standpoint, the immune response towards four influenza strains and the SARS-CoV-2 spike protein in co-administration groups is generally non-inferior to that seen in groups receiving either vaccine alone. Several public health authorities have advocated co-administration. Different combination vaccine candidates are in (pre)-clinical development. The hesitancy towards vaccine co-administration or combination vaccines is a multifaceted phenomenon and may be higher than the acceptance of either vaccine administered separately. Public health implications are discussed.

The Influenza Vaccine May Protect Pregnant and Postpartum Women against Severe COVID-19

The SARS-CoV-2 pandemic has imposed a huge challenge on the antenatal care of pregnant women worldwide, with the maternal mortality rate being raised to alarming levels. While COVID-19 vaccines were developed, some studies highlighted a possible relationship between influenza vaccination and lower odds of COVID-19 infection. As obstetric patients belong to a high-risk group for respiratory diseases, this study evaluated whether influenza vaccination reduces the severity of COVID-19 infection and mortality among pregnant and postpartum women. We conducted a retrospective cohort study on 3370 pregnant and postpartum women from the Brazilian national database, where they were grouped according to their influenza vaccination status before the onset of COVID-19 symptoms. The intensive care unit admission and intubation rates were significantly higher among subjects in the unvaccinated group (p = 0.002 and p < 0.001, respectively). The odds of mortality risk among those who received the vaccine was 0.33, with a 95% confidence interval of 0.23–0.47. The numbers of patients who needed to be vaccinated to avoid a case of intensive care unit admission, intubation, or death due to COVID-19 were 11, 15, and 11, respectively. Influenza vaccines could confer protection against severe COVID-19 infection in pregnant and postpartum women.

Impact of COVID-19 on deaths from respiratory diseases: Panel data evidence from Chile

The COVID-19 pandemic has relegated pathologies that were previously commonplace to a secondary context. Therefore, it is necessary to study the evolution of these diseases in the presence or absence of COVID-19.

OBJECTIVE

The present study had the following objectives: 1. to evaluate the relationship between the COVID-19 epidemic and the possible decrease in death from respiratory disease (DRd) in Chile; and 2. to study the relationships between meteorological variables and severity of COVID-19 with respect to DRd from January 2018 to February 2021.

METHODS

The variable number of DRds in Chile was analyzed considering the monthly records of meteorological variables (temperature, precipitation and humidity) in each region of Chile and the severity of COVID-19 to evaluate the mortality trend before and after the pandemic. For this, different nonobservable heterogeneity models for panel data were used.

RESULTS

The variables that affect DRd include the number of deaths from COVID-19, which led to a decrease in DRd (negative effect) when increased, the number of patients with COVID-19 in the intensive care unit (ICU), which led to an increase in DRd (positive effect) when increased, and the minimum temperature, which had a negative effect on DRd. These results are supported by the application of panel regression with one-way random-effects models.

CONCLUSION

This study revealed a reduction in the number of DRds other than COVID-19 during the pandemic in Chile. This could be explained by the sanitary measures applied by the Ministry of Health of Chile in relation to mobility restrictions and social distancing, among others. Therefore, DRd decreased in accordance with the appearance of the COVID-19 pandemic.

A Knowledge, Attitude, and Perception Study on Flu and COVID-19 Vaccination during the COVID-19 Pandemic: Multicentric Italian Survey Insights

In January 2020, Chinese health authorities identified a novel coronavirus strain never before isolated in humans. It quickly spread across the world, and was eventually declared a pandemic, leading to about 310 million confirmed cases and to 5,497,113 deaths (data as of 11 January 2022). Influenza viruses affect millions of people during cold seasons, with high impacts, in terms of mortality and morbidity. Patients with comorbidities are at a higher risk of acquiring severe problems due to COVID-19 and the flu—infections that could impact their underlying clinical conditions. In the present study, knowledge, attitudes, and opinions of the general population regarding COVID-19 and influenza immunization were evaluated. A multicenter, web-based, cross-sectional study was conducted between 10 February and 12 July 2020, during the first wave of SARS-CoV-2 infections among the general population in Italy. A sample of 4116 questionnaires was collected at the end of the study period. Overall, 17.5% of respondents stated that it was unlikely that they would accept a future COVID-19 vaccine (n = 720). Reasons behind vaccine refusal/indecision were mainly a lack of trust in the vaccine (41.1%), the fear of side effects (23.4%), or a lack of perception of susceptibility to the disease (17.1%). More than 50% (53.8%; n = 2214) of the sample participants were willing to receive flu vaccinations in the forthcoming vaccination campaign, but only 28.2% of cases had received it at least once in the previous five seasons. A higher knowledge score about SARS-CoV-2/COVID-19 and at least one flu vaccination during previous influenza seasons were significantly associated with the intention to be vaccinated against COVID-19 and influenza. The continuous study of factors, determining vaccination acceptance and hesitancy, is fundamental in the current context, in regard to improve vaccination confidence and adherence rates against vaccine preventable diseases.

Heterologous vaccination interventions to reduce pandemic morbidity and mortality: Modeling the US winter 2020 COVID-19 wave

COVID-19 remains a stark health threat worldwide, in part because of minimal levels of targeted vaccination outside high-income countries and highly transmissible variants causing infection in vaccinated individuals. Decades of theoretical and experimental data suggest that nonspecific effects of non-COVID-19 vaccines may help bolster population immunological resilience to new pathogens. These routine vaccinations can stimulate heterologous cross-protective effects, which modulate nontargeted infections. For example, immunization with Bacillus Calmette-Guérin, inactivated influenza vaccine, oral polio vaccine, and other vaccines have been associated with some protection from SARS-CoV-2 infection and amelioration of COVID-19 disease. If heterologous vaccine interventions (HVIs) are to be seriously considered by policy makers as bridging or boosting interventions in pandemic settings to augment nonpharmaceutical interventions and specific vaccination efforts, evidence is needed to determine their optimal implementation. Using the COVID-19 International Modeling Consortium mathematical model, we show that logistically realistic HVIs with low (5 to 15%) effectiveness could have reduced COVID-19 cases, hospitalization, and mortality in the United States fall/winter 2020 wave. Similar to other mass drug administration campaigns (e.g., for malaria), HVI impact is highly dependent on both age targeting and intervention timing in relation to incidence, with maximal benefit accruing from implementation across the widest age cohort when the pandemic reproduction number is >1.0. Optimal HVI logistics therefore differ from optimal rollout parameters for specific COVID-19 immunizations. These results may be generalizable beyond COVID-19 and the US to indicate how even minimally effective heterologous immunization campaigns could reduce the burden of future viral pandemics.

Vaccination and Quarantine Effect on COVID-19 Transmission Dynamics Incorporating Chinese-Spring-Festival Travel Rush: Modeling and Simulations

The COVID-19 pandemic has adversely affected the entire world. The effective implementation of vaccination strategy is critical to prevent the resurgence of the pandemic, especially during large-scale population migration. We establish a multiple patch coupled model based on the transportation network among the 31 provinces in China, under the combined strategies of vaccination and quarantine during large-scale population migration. Based on the model, we derive a critical quarantine rate to control the pandemic transmission and a vaccination rate to achieve herd immunity. Furthermore, we evaluate the influence of passenger flow on the effective reproduction number during the Chinese-Spring-Festival travel rush. Meanwhile, the spread of the COVID-19 pandemic is investigated for different control strategies, viz. global control and local control. The impact of vaccine-related parameters, such as the number, the effectiveness and the immunity period of vaccine, are explored. It is believed that the articulated models as well as the presented simulation results could be beneficial to design of feasible strategies for preventing COVID-19 transmission during the Chinese-Spring-Festival travel rush or the other future events involving large-scale population migration.

SARS-CoV-2 subunit vaccine adjuvants and their signaling pathways

INTRODUCTION

Vaccines are the agreed upon weapon against the COVID-19 pandemic. This review discusses about COVID-19 subunit vaccines adjuvants and their signaling pathways, which could provide a glimpse into the selection of appropriate adjuvants for prospective vaccine development studies.

AREAS COVERED

In the introduction, a brief background about the SARS-CoV-2 pandemic, the vaccine development race and classes of vaccine adjuvants were provided. . The antigen, trial stage, and types of adjuvants were extracted from the included articles and thun assimilated. Finally, the pattern recognition receptors (PRRs), their classes, cognate adjuvants, and potential signaling pathways were comprehended.

EXPERT OPINION

Adjuvants are unsung heroes of subunit vaccines. The in silico studies are very vital in avoiding several costly trial errors and save much work times. The majority of the (pre)clinical studies are promising. It is encouraging that most of the selected adjuvants are novel. Much emphasis must be paid to the optimal paring of antigen-adjuvant-PRRs for obtaining the desired vaccine effect. A good subunit vaccine/adjuvant is one that has high efficacy, safety, dose sparing, and rapid seroconversion rate and broad spectrum of immune response. In the years to come, COVID-19 adjuvanted subunit vaccines are expected to have superior utility than any other vaccines for various reasons.

The Potential Benefits of the Influenza Vaccination on COVID-19 Mortality Rate-A Retrospective Analysis of Patients in Poland

In this study, we used publicly available data from the Centrum e-Zdrowia (CeZ) Polish Databank proposing a possible correlation between influenza vaccination and mortality due to COVID-19. We limited our search to the patients with positive COVID-19 laboratory tests from 1 January 2020 to 31 March 2021 and who filled a prescription for any influenza vaccine during the 2019–2020 influenza season. In total, we included 116,277 patients and used a generalized linear model to analyze the data. We found out that patients aged 60+ who received an influenza vaccination have a lower probability of death caused by COVID-19 in comparison to unvaccinated, and the magnitude of this difference grows with age. For people below 60 years old, we did not observe an influence of the vaccination. Our results suggest a potential protective effect of the influenza vaccine on COVID-19 mortality of the elderly. Administration of the influenza vaccine before the influenza season would reduce the burden of increased influenza incidence, the risk of influenza and COVID-19 coinfection and render the essential medical resources accessible to cope with another wave of COVID-19. To our knowledge, this is the first study showing a correlation between influenza vaccination and the COVID-19 mortality rate in Poland.

Effect and Tolerability of a Nutritional Supplement Based on a Synergistic Combination of β-Glucans and Selenium- and Zinc-Enriched Saccharomyces cerevisiae (ABB C1®) in Volunteers Receiving the Influenza or the COVID-19 Vaccine: A Randomized, Double-Blind, Placebo-Controlled Study

A single-center, randomized, double-blind, placebo-controlled study was conducted in 72 volunteers who received a synergistic combination of yeast-based ingredients with a unique β-1,3/1,6-glucan complex and a consortium of heat-treated probiotic Saccharomyces cerevisiae rich in selenium and zinc (ABB C1^®) or placebo on the next day after getting vaccinated against influenza (Chiromas^®) (n = 34) or the COVID-19 (Comirnaty^®) (n = 38). The duration of treatment was 30 and 35 days for the influenza and COVID-19 vaccine groups, respectively. Mean levels of CD4+T cells increased from 910.7 at baseline to 1000.2 cells/µL after the second dose of the COVID-19 vaccine in the ABB C1^® group, whereas there was a decrease from 1055.1 to 929.8 cells/µL in the placebo group. Changes of CD3+T and CD8+T lymphocytes showed a similar trend. In the COVID-19 cohort, the increases in both IgG and IgM were higher in the ABB C1^® supplement than in the placebo group. Serum levels of selenium and zinc showed a higher increase in subjects treated with the active product than in those receiving placebo. No serious adverse events related to ABB C1^® or tolerance issues were reported. The study findings validate the capacity of the ABB C1^® product to stimulate trained immunity.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

The Effect of Influenza Vaccination on COVID-19 Morbidity, Severity and Mortality: Systematic Review and Meta-Analysis

Coronavirus disease 2019 (COVID-19) pandemic is rapidly developing worldwide with a high mortality rate. In this meta-analysis study, the effect of influenza vaccination on the prevention of COVID-19 and its consequences in patients were investigated. The systematic search for this study was performed from November 2019 to 25 November 2020, in the databases of Medline, PubMed, Scopus, Web of Science, Embase, Ebsco, Cochrane and medRxiv. Search terms used included COVID-19, coronavirus, SARS-CoV-2, covid, influenza, flu, grippe and vaccine. The present study examined the association between influenza vaccination and COVID-19 including COVID-19 infection, mortality, hospitalisation and intensive care unit (ICU) admission. Finally, the pooled estimates for different outcomes were calculated by the software for statistics and data science (STATA) version 15 and I2 was used to determine the heterogeneity. By analysing the data of articles, the pooled estimates of these data indicated that influenza vaccination could lower probability of COVID-19 infection up to 24% (OR = 0.77; 95% CI: 0.65, 0.91), of death up to 32% (OR = 0.68; 95% CI: 0.42, 1.11), of the hospitalisation up to 25% (OR = 0.75; 95% CI: 0.46; 1.23) and of admission to ICU up to 29% (OR = 0.71; 95% CI: 0.40, 1.27). Influenza vaccination can help decrease the COVID-19 infection and reduce hospitalisation and the need for ICU and mortality rates.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

Effect of inactivated influenza vaccination on human coronavirus infection: Secondary analysis of a randomized trial in Hutterite colonies

Background

Although influenza vaccines provide protection against influenza viruses, concern has been raised that they may increase susceptibility to non-influenza respiratory viruses. As pandemic lockdowns end, temporal overlap of circulation of seasonal influenza viruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is expected. Understanding the impact of influenza vaccination on risk of coronavirus infection is therefore of considerable public health importance.

Methods

We performed a secondary analysis of a randomized trial where children and adolescents in Canadian Hutterite colonies were randomly assigned by colony to receive the 2008–2009 seasonal inactivated trivalent influenza vaccine (TIV) or a control hepatitis A (HepA) vaccine. All 3273 colony members (vaccinated children and nonvaccine recipients) were followed for the primary outcome of RT-PCR confirmed seasonal coronavirus infection. Serum collected pre- and post-vaccination was analyzed for titers of IgG antibodies towards human coronaviruses (HCoV).

Results

The incidence of coronavirus infection was 0·18/1000 person-days in the colonies that received TIV vs 0.36/1000 person-days in the control group, hazard ratio (HR) 0.49 [0.21–1.17]. The risk reduction among non-vaccine recipients in the TIV group compared to the control group was HR 0.55 [0.24–1.23]. There was an increase in the geometric mean fold change of HCoV-OC43 antibody titers following TIV compared to HepA vaccine (mean difference 1.2 [0.38–2.06], p = 0.007), and an increase in geometric mean HCoV-NL63 antibody titers post-TIV (262.9 vs 342.9, p = 0.03).

Conclusion

The influenza vaccine does not increase the risk of a coronavirus infection. Instead, the influenza vaccine may reduce the rate of coronavirus infections by inducing cross-reactive anti-coronavirus IgG antibodies.

Epidemiology and Regional Predictors of COVID-19 Clusters: A Bayesian Spatial Analysis Through a Nationwide Contact Tracing Data

Purpose: Revealing the clustering risks of COVID-19 and prediction is essential for effective quarantine policies, since clusters can lead to rapid transmission and high mortality in a short period. This study aimed to present which regional and social characteristics make COVID-19 cluster with high risk. Methods: By analyzing the data of all confirmed cases (14,423) in Korea between January 10 and August 3, 2020, provided by the Korea Disease Control and Prevention Agency, we manually linked each case and discovered clusters. After classifying the cases into clusters as nine types, we compared the duration and size of clusters by types to reveal high-risk cluster types. Also, we estimated odds for the risk factors for COVID-19 clustering by a spatial autoregressive model using the Bayesian approach. Results: Regarding the classified clusters (n = 539), the mean size was 19.21, and the mean duration was 9.24 days. The number of clusters was high in medical facilities, workplaces, and nursing homes. However, multilevel marketing, religious facilities, and restaurants/business-related clusters tended to be larger and longer when an outbreak occurred. According to the spatial analysis in COVID-19 clusters of more than 20 cases, the global Moran's I statistics value was 0.14 (p < 0.01). After adjusting for population size, the risks of COVID-19 clusters were related to male gender (OR = 1.29) and low influenza vaccination rate (OR = 0.87). After the spatial modeling, the predicted probability of forming clusters was visualized and compared with the actual incidence and local Moran's I statistics 2 months after the study period. Conclusions: COVID-19 makes different sizes of clusters in various contact settings; thus, precise epidemic control measures are needed. Also, when detecting and screening for COVID-19 clusters, regional risks such as vaccination rate should be considered for predicting risk to control the pandemic cost-effectively.

The estimated age-group specific influenza vaccine coverage rates in Hong Kong and the impact of the school outreach vaccination program

Previous studies have shown that seasonal influenza strikes annually causing millions to fall sick and several hundred thousand to die globally. Hence, universal vaccination is a public health aim to control influenza. The Hong Kong Government started to introduce the School Outreach Vaccination (SOV) program in 2018 to increase vaccination rates in children. This study looked at the impact this had on hospital admissions and estimated vaccination rates in the total population, using a questionnaire-based tool. The SOV program significantly increased vaccination coverage rates with a 1% increase associated with a reduction of 4.3 influenza-related hospital admissions of school-aged children. The estimation of vaccine coverage rates among the under 5-year olds (48.5%), primary school children (69.3%) and over 65-year olds (45.7%), through the questionnaire-based tool, was within the 95% confidence interval of the coverage rates published by the Center for Health Protection of the Hong Kong Government, 47.4%, 68.1% and 45.8%, respectively. Extension of the SOV program should be considered in secondary schools to increase the coverage rates in adolescents. The questionnaire survey may inform government how to achieve universal vaccination for specific age groups.

COVID-19 and Seasonal Influenza: No Room for Two

Objective With the outbreak of COVID-19 in December 2019 fears were expressed for a possible twindemic in the coming flu seasons. Fortunately, this was not the case for the 2019-2020 and 2020-2021 flu seasons as flu showed very low historical rates during these periods. The objective of our study was to look at the existing flu data for the 2019-2021 period and analyze possible reasons for the near absence of seasonal flu. Methods We performed retrospective surveillance regarding seasonal influenza rates for the years 2019-2021, the years that the COVID-19 was present. Epidemiological data concerning seasonal influenza for the years 2019-2021 were collected and analyzed Results Extremely low numbers of flu cases were reported in FluNet, FluView, and TESSy influenza surveillance systems during the years 2019, 2020, and 2021 compared to previous years prior to COVID-19. Conclusions A twindemic outbreak during the 2019-2021 flu seasons did not occur despite expressed concerns. The worldwide implementation of mitigation measures for individuals and communities to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, the increased flu vaccination rate, the virus interference and the lower rate of testing for flu are the main reasons for the marked decrease in reported flu cases during 2019-2021 flu seasons.

Attitudes toward the SARS-CoV-2 and Influenza Vaccination in the Metropolitan Cities of Bologna and Palermo, Italy

Vaccine hesitancy (VH) is known to play a relevant role in thwarting the efforts toward reaching satisfactory influenza vaccination coverage, and has caused similar difficulties during the COVID-19 pandemic. This study aims to describe the phenomenon and produce insights on the reasons behind VH. A survey was administered between December 2020 and February 2021 to adults living in the cities of Bologna and Palermo. Of the 443 subjects enrolled, 47.3% were likely to get the influenza vaccination, while 75.6% were willing to receive the COVID-19 vaccination. The most frequent determinants that motivated the willingness to get the COVID-19 vaccine were trust in the safety of vaccines and belief that the vaccine is an effective tool. As for people’s unwillingness to be vaccinated, being exposed to information that produced doubts about the vaccine and lack of trust in a newly developed vaccine were the most frequently involved determinants. Statistically significant positive associations were found between the willingness to be vaccinated and postgraduate education and the propensity towards influenza vaccination. A negative association with being over 40 years old and of female gender was also found. These results might have an impact in better understanding individual reasons behind VH, identifying which categories are more exposed to it and which strategies should be implemented.

Autoinflammatory Diseases and Cytokine Storms-Imbalances of Innate and Adaptative Immunity

Innate and adaptive immune responses have a well-known link and represent the distinctive origins of several diseases, many of which may be the consequence of the loss of balance between these two responses. Indeed, autoinflammation and autoimmunity represent the two extremes of a continuous spectrum of pathologic conditions with numerous overlaps in different pathologies. A common characteristic of these dysregulations is represented by hyperinflammation, which is an exaggerated response of the immune system, especially involving white blood cells, macrophages, and inflammasome activation with the hyperproduction of cytokines in response to various triggering stimuli. Moreover, hyperinflammation is of great interest, as it is one of the main manifestations of COVID-19 infection, and the cytokine storm and its most important components are the targets of the pharmacological treatments used to combat COVID-19 damage. In this context, the purpose of our review is to provide a focus on the pathogenesis of autoinflammation and, in particular, of hyperinflammation in order to generate insights for the identification of new therapeutic targets and strategies.