COVID-19 and the next influenza season

SARS-CoV-2 and Influenza Co-Infection: Fair Competition or Sinister Combination?

The COVID-19 pandemic remains a serious public health problem globally. During winter influenza seasons, more aggressive SARS-CoV-2 infections and fatalities have been documented, indicating that influenza co-infections may significantly impact the disease outcome of COVID-19. Both influenza and SARS-CoV-2 viruses share many similarities in their transmission and their cellular tropism for replication in the human respiratory tract. However, the complex intricacies and multi-faceted dynamics of how the two pathogens interact to ensure their survival in the same lung microenvironment are still unclear. In addition, clinical studies on influenza co-infections in COVID-19 patients do not provide conclusive evidence of how influenza co-infection mechanistically modifies disease outcomes of COVID-19. This review discusses various viral as well as host factors that potentially influence the survival or synergism of these two respiratory pathogens in the infected lung microenvironment.

Health beliefs and attitudes toward Influenza and COVID-19 vaccination in Portugal: a study using a mixed-method approach

Introduction

Vaccination is one of the most effective population strategies to prevent infectious diseases and mitigate pandemics, and it is important to understand vaccine uptake determinants since vaccine hesitancy has been increasing for the past few decades. The Health Belief Model (HBM) has been widely used for understanding vaccination behavior. The current study aimed to assess influenza vaccine (IV) non-uptake and attitudes toward COVID-19 vaccination, two important respiratory diseases with similar symptoms, and routes of transmission in the Portuguese population.

Methods

We conducted a cross-sectional study using a panel sample of randomly chosen Portuguese households. A total of 1,050 individuals aged 18 years and over responded to a telephone or online questionnaire. Through a mixed-method approach, we employed thematic content analysis to describe reasons for not taking the IV, considering the HBM dimensions, and quantitative statistical analysis to estimate IV and COVID-19 vaccine coverage.

Results

The IV uptake for the overall population was 30.7% (CI 95%: 26.5, 35.2). Susceptibility was found to be a main factor for IV non-uptake, followed by barriers, such as stock availability and fear of adverse effects. The uptake of the COVID-19 vaccine was very high in the study population (83.1%, CI 95%: 13.6%-20.9%). There was a high perception of COVID-19-associated severity and fear of the consequences. Individuals who reported IV uptake seemed to perceive a higher severity of COVID-19 and a higher benefit of taking the COVID-19 vaccine for severe complications.

Discussion

Thus, the population does not seem to consider influenza to be a health risk, as opposed to COVID-19, which is considered to be a possibly severe disease. The association between IV uptake and COVID-19 perceptions highlights that an overall attitude toward vaccination in general may be an important individual determinant.

Risk factors, clinical characteristics and prognostic value of acute kidney injury in COVID-19 compared with influenza virus and respiratory syncytial virus

BACKGROUND

Acute Kidney Injury (AKI) complicates a substantial part of patients with COVID-19. Direct viral penetration of renal cells through the Angiotensin Converting Enzyme 2 receptor, and indirect damage by the aberrant inflammatory response characteristic of COVID-19 are likely mechanisms. Nevertheless, other common respiratory viruses such as Influenza and Respiratory Syncytial Virus (RSV) are also associated with AKI.

METHODS

We retrospectively compared the incidence, risk factors and outcomes of AKI among patients who were admitted to a tertiary hospital because of infection with COVID-19, influenza (A + B) or RSV.

RESULTS

We collected data of 2593 patients hospitalized with COVID-19, 2041 patients with influenza and 429 with RSV. Patients affected by RSV were older, had more comorbidities and presented with higher rates of AKI at admission and within 7 days (11.7% vs. 13.3% vs. 18% for COVID-19, influenza and RSV, respectively p = 0.001). Nevertheless, patients hospitalized with COVID-19 had higher mortality (18% with COVID-19 vs. 8.6% and 13.5% for influenza and RSV, respectively P < 0.001) and higher need of mechanical ventilation (12.4% vs. 6.5% vs.8.2% for COVID-19, influenza and RSV, respectively, P = 0.002). High ferritin levels and low oxygen saturation were independent risk factors for severe AKI only in the COVID-19 group. AKI in the first 48 h of admission and in the first 7 days of hospitalization were strong independent risk factors for adverse outcome in all groups.

CONCLUSION

Despite many reports of direct kidney injury by SARS-COV-2, AKI was less in patients with COVID-19 compared to influenza and RSV patients. AKI was a prognostic marker for adverse outcome across all viruses.

Population Attributable Fraction of Nonvaccination of Child and Adolescent Vaccines Attributed to Parental Vaccine Hesitancy, 2018-2019

Understanding the role of vaccine hesitancy in undervaccination or nonvaccination of childhood vaccines is important for increasing vaccine confidence and uptake. We used data from April to June interviews in the 2018 and 2019 National Immunization Survey-Flu (n = 78,725, United States), a nationally representative cross-sectional household cellular telephone survey. We determined the adjusted population attributable fraction (PAF) for each recommended childhood vaccine to assess the contribution of vaccine hesitancy to the observed nonvaccination level. Hesitancy is defined as being somewhat or very hesitant toward childhood vaccines. Furthermore, we assessed the PAF of nonvaccination for influenza according to sociodemographic characteristics, Department of Health and Human Services region, and state. The proportion of nonvaccination attributed to parental vaccine hesitancy was lowest for hepatitis B birth dose vaccine (6.5%) and highest for ≥3-dose diphtheria and tetanus toxoids and acellular pertussis vaccine (31.3%). The PAF of influenza nonvaccination was highest for non-Hispanic Black populations (15.4%), households with high educational (17.7%) and income (16.5%) levels, and urban areas (16.1%). Among states, PAF ranged from 25.4% (New Hampshire) to 7.5% (Louisiana). Implementing strategies to increase vaccination confidence and uptake are important, particularly during the coronavirus disease 2019 pandemic.

Advancing Lung Immunology Research: An Official American Thoracic Society Workshop Report

The mammalian airways and lungs are exposed to a myriad of inhaled particulate matter, allergens, and pathogens. The immune system plays an essential role in protecting the host from respiratory pathogens, but a dysregulated immune response during respiratory infection can impair pathogen clearance and lead to immunopathology. Furthermore, inappropriate immunity to inhaled antigens can lead to pulmonary diseases. A complex network of epithelial, neural, stromal, and immune cells has evolved to sense and respond to inhaled antigens, including the decision to promote tolerance versus a rapid, robust, and targeted immune response. Although there has been great progress in understanding the mechanisms governing immunity to respiratory pathogens and aeroantigens, we are only beginning to develop an integrated understanding of the cellular networks governing tissue immunity within the lungs and how it changes after inflammation and over the human life course. An integrated model of airway and lung immunity will be necessary to improve mucosal vaccine design as well as prevent and treat acute and chronic inflammatory pulmonary diseases. Given the importance of immunology in pulmonary research, the American Thoracic Society convened a working group to highlight central areas of investigation to advance the science of lung immunology and improve human health.

Letalidad por SARS-CoV-2 en Colombia años 2020 y 2021

Introducción: esta pandemia ha marcado la necesidad de comprender cómo sobrevivimos a las infecciones y por qué el tratamiento puede ser heterogéneo. Objetivo:  reseñar la tasa de letalidad por COVID-19 en Colombia entre el 6 de marzo 2020 y 31 de diciembre 2021. Metodología: estudio transversal, como fuente de información se obtuvo el plan nacional de vacunación contra COVID-19 del sitio web del Ministerio de Salud y Protección Social. Resultados: se establecieron por meses las tasas de letalidad por COVID-19 por meses en 2020 y 2021 en Colombia. Se apreció que en el período mencionado el mes con mayor tasa de letalidad fue febrero 2021 con 3,69% y el de menor fue diciembre 2021 con 1,61%. Conclusión: los registros de letalidad y tasas de mortalidad por COVID-19 posibilitan monitorear la pandemia, pero están sesgados por el diagnóstico posterior de la infección por SAR-CoV2 y la demora en la notificación.

How Drivers of Seasonality in Respiratory Infections May Impact Vaccine Strategy: A Case Study in How Coronavirus Disease 2019 (COVID-19) May Help Us Solve One of Influenza's Biggest Challenges

Vaccines against seasonal infections like influenza offer a recurring testbed, encompassing challenges in design, implementation, and uptake to combat a both familiar and ever-shifting threat. One of the pervading mysteries of influenza epidemiology is what causes the distinctive seasonal outbreak pattern. Proposed theories each suggest different paths forward in being able to tailor precision vaccines and/or deploy them most effectively. One of the greatest challenges in contrasting and supporting these theories is, of course, that there is no means by which to actually test them. In this communication we revisit theories and explore how the ongoing coronavirus disease 2019 (COVID-19) pandemic might provide a unique opportunity to better understand the global circulation of respiratory infections. We discuss how vaccine strategies may be targeted and improved by both isolating drivers and understanding the immunological consequences of seasonality, and how these insights about influenza vaccines may generalize to vaccines for other seasonal respiratory infections.

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.

SARS-CoV-2 and Influenza Viruses: Strategies to Cope with Co-infection and Bioinformatics Perspective

Almost a century after the devastating pandemic of the Spanish flu, humankind is facing the relatively comparable global outbreak of COVID‐19. COVID‐19 is an infectious disease caused by SARS‐CoV‐2 with an unprecedented transmission pattern. In the face of the recent repercussions of COVID‐19, many have argued that the clinical experience with influenza through the last century may have tremendous implications in the containment of this newly emerged viral disease. During the last 2 years, from the emergence of COVID‐19, tremendous advances have been made in diagnosing and treating coinfections. Several approved vaccines are available now for the primary prevention of COVID‐19 and specific treatments exist to alleviate symptoms. The present review article aims to discuss the pathophysiology, diagnosis, and treatment of SARS‐CoV‐2 and influenza A virus coinfection while delivering a bioinformatics‐based insight into this subject matter.

Epigenetic Control of Regulatory T Cell Stability and Function: Implications for Translation

FoxP3+ regulatory T (Treg) cells maintain immune homeostasis, promote self-tolerance, and have an emerging role in resolving acute inflammation, providing tissue protection, and repairing tissue damage. Some data suggest that FoxP3+ T cells are plastic, exhibiting susceptibility to losing their function in inflammatory cytokine-rich microenvironments and paradoxically contributing to inflammatory pathology. As a result, plasticity may represent a barrier to Treg cell immunotherapy. Here, we discuss controversies surrounding Treg cell plasticity and explore determinants of Treg cell stability in inflammatory microenvironments, focusing on epigenetic mechanisms that clinical protocols could leverage to enhance efficacy and limit toxicity of Treg cell-based therapeutics.

Reduced spread of influenza and other respiratory viral infections during the COVID-19 pandemic in southern Puerto Rico

INTRODUCTION

Impacts of COVID-19 mitigation measures on seasonal respiratory viruses is unknown in sub-tropical climates.

METHODS

We compared weekly testing and test-positivity of respiratory infections in the 2019-2020 respiratory season to the 2012-2018 seasons in southern Puerto Rico using Wilcoxon signed rank tests.

RESULTS

Compared to the average for the 2012-2018 seasons, test-positivity was significantly lower for Influenza A (p<0.001) & B (p<0.001), respiratory syncytial virus (RSV) (p<0.01), respiratory adenovirus (AdV) (p<0.05), and other respiratory viruses (p<0.001) following March 2020 COVID-19 stay at home orders.

CONCLUSIONS

Mitigation measures and behavioral social distancing choices may have reduced respiratory viral spread in southern Puerto Rico.

Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base

Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.

Parents' Willingness to Vaccinate Their Children Against Seasonal Influenza After the COVID-19 Pandemic in Saudi Arabia: A Retrospective Cross-Sectional Survey

PURPOSE

To explore the impact of the novel coronavirus (COVID-19) pandemic on caregivers' willingness to vaccinate their children against influenza in 2021 in Saudi Arabia and the factors influencing this decision.

PATIENTS AND METHODS

An online survey of 2501 caregivers in Saudi Arabia with children aged 6 months-18 years was conducted between July 15, 2021, and August 2, 2021. A convenience sample of participants that met the inclusion criteria was used as the study sample. Social Science Package Statistical (SPSS) was used for the statistical analysis. Categorical variables were reported as frequencies and percentages. The Chi-square test was used for categorical variables to assess the difference between the variables and the parents' willingness to vaccinate their children against seasonal influenza after the COVID-19 pandemic.

RESULTS

Of the 2501 respondents to the survey, 1185 (47.3%) parents plan to give their children the influenza vaccine next year, which is an increase from 745 (29.8%) in the previous year. The following were the main reasons for not giving children the vaccine: children were less likely to get seasonal flu (617, 24.7%), fear of side effects (491, 19.6%), and fear of needles and syringes (484, 19.4%). Among the parents, 1222 (48.9%) were more likely to receive the seasonal flu vaccine themselves the following year, and 1361 (54.4%), which is more than half, were concerned about their children contracting seasonal influenza.

CONCLUSION

Parents' decision-making to vaccinate their children against seasonal influenza has been influenced by the COVID-19 pandemic. Numerous factors including a caregiver who had received the seasonal influenza vaccine themselves, who had vaccinated or planned to vaccinate their children during the previous or current seasonal influenza season, and/or who had a higher education level were associated with increased willingness to receive the flu vaccine.

Mitigating COVID-19 Transmission in Schools With Digital Contact Tracing

Precision mitigation of COVID-19 is in pressing need for postpandemic time with the absence of pharmaceutical interventions. In this study, the effectiveness and cost of digital contact tracing (DCT) technology-based on-campus mitigation strategy are studied through epidemic simulations using high-resolution empirical contact networks of teachers and students. Compared with traditional class, grade, and school closure strategies, the DCT-based strategy offers a practical yet much more efficient way of mitigating COVID-19 spreading in the crowded campus. Specifically, the strategy based on DCT can achieve the same level of disease control as rigid school suspensions but with significantly fewer students quarantined. We further explore the necessary conditions to ensure the effectiveness of DCT-based strategy and auxiliary strategies to enhance mitigation effectiveness and make the following recommendation: social distancing should be implemented along with DCT, the adoption rate of DCT devices should be assured, and swift virus tests should be carried out to discover asymptomatic infections and stop their subsequent transmissions. We also argue that primary schools have higher disease transmission risks than high schools and, thereby, should be alerted when considering reopenings.

Clinical and virological impact of single and dual infections with influenza A (H1N1) and SARS-CoV-2 in adult inpatients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mimics the influenza A (H1N1) virus in terms of clinical presentation, transmission mechanism, and seasonal coincidence. Comprehensive data for the clinical severity of adult patients co-infected by both H1N1 and SARS-CoV-2, and, particularly, the relationship with PCR cycle threshold (Ct) values are not yet available. All participants in this study were tested for H1N1 and SARS-CoV-2 simultaneously at admission. Demographic, clinical, treatment, and laboratory data were extracted from electronic medical records and compared among adults hospitalized for H1N1 infection, SARS-CoV-2 infection and co-infection with both viruses. Ct values for viral RNA detection were further compared within SARS-CoV-2 and co-infection groups. Score on seven-category ordinal scale of clinical status at day 7 and day 14 were assessed. Among patients with monoinfection, H1N1 infection had higher frequency of onset symptoms but lower incidence of adverse events during hospitalization than SAR-CoV-2 infection (P < 0.05). Co-infection had an increased odds of acute kidney injury, acute heart failure, secondary bacterial infections, multilobar infiltrates and admittance to ICU than monoinfection. Score on seven-category scale at day 7 and day 14 was higher in patients with coinfection than patients with SAR-CoV-2 monoinfection (P<0.05). Co-infected patients had lower initial Ct values (referring to higher viral load) (median 32) than patients with SAR-CoV-2 monoinfection (median 36). Among co-infected patients, low Ct values were significantly and positively correlated with acute kidney injury and ARDS (P = 0.03 and 0.02, respectively). Co-infection by SARS-CoV-2 and H1N1 caused more severe disease than monoinfection by either virus in adult inpatients. Early Ct value could provide clues for the later trajectory of the co-infection. Multiplex molecular diagnostics for both viruses and early assessment of SAR-CoV-2 Ct values are recommended to achieve optimal treatment for improved clinical outcome.

The baseline enrolled 505 patients admitted to Guangzhou Eighth People’s Hospital (Guangzhou, Guangdong) with a diagnosis of COVID-19 or H1N1. All the patients were tested by both viruses at admission. Demographic, clinical, treatment, and laboratory data were extracted from electronic medical records and compared among adults (≥18 years) hospitalized for H1N1 infection (n = 220), SARS-CoV-2 infection (n = 249) and co-infection with both viruses (n = 36). The prevalence rate of H1N1 co-infection was 12.6% (36/285) among patients hospitalized with COVID-19. Co-infection affected a predominantly older age group and was associated with poorer clinical outcome. We also described the viral load trajectory in patients with diverse types of infection. Lower initial Ct values (higher viral loads in nasopharyngeal swabs) of co-infected patients was found to be associated with a higher number of adverse events and clinical symptoms. Considering the COVID-19 pandemic and a simultaneous epidemic of seasonal influenza, the data in China may critically inform future therapeutic or prophylactic strategies, especially for other developing countries.

Seasonal influenza vaccination coverage and its association with COVID-19 in Saudi Arabia

Coronavirus Disease 2019 (COVID-19) pandemic is still on-going worldwide. The available information regarding the seasonal influenza vaccine (SIV) coverage during the COVID-19 pandemic and its impact on SARS-CoV-2 spread are limited. Moreover, it is argued that SIV may or may not lessen the COVID-19 severity. No previous studies have been revealed SIV coverage among COVID-19 patients and its association with COVID-19 spread and severity, especially in Saudi Arabia. Hence, this study aimed to estimate the influenza vaccine uptake in confirmed COVID-19 patients and investigate its impact on COVID-19 spread and severity. Accordingly, 1734 COVID-19 confirmed patients were included from three government hospitals in Saudi Arabia (SA). The data were collected electronically through a newly formed, self-administrated questionnaire. Among those patients, 335 were covered with SIV (19.31%), and the coverage rate of females and males was 23.4% and 15.8%, respectively. Severe COVID-19 cases were less in vaccinated patients than in non-vaccinated (2.69% vs. 3.5%, respectively). Additionally, the results showed a significant decrease in getting infected by SARS-CoV-2 after receiving SIV (P = 0.022). Even with the tremendous efforts to promote SIV uptake among the general population and high-risk groups, the SIV coverage in SA is not optimal yet. Nevertheless, there is a significant decrease in the probability of getting infected with SARS-CoV-2 after receiving SIV. Such findings with the continuous progression of the COVID-19 pandemic call for a novel approach regarding vaccination policies to increase SIV and COVID-19 vaccine uptake.

Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory disease coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Efficient diagnostic tools are in high demand, as rapid and large-scale testing plays a pivotal role in patient management and decelerating disease spread. This paper reviews current technologies used to detect SARS-CoV-2 in clinical laboratories as well as advances made for molecular, antigen-based, and immunological point-of-care testing, including recent developments in sensor and biosensor devices. The importance of the timing and type of specimen collection is discussed, along with factors such as disease prevalence, setting, and methods. Details of the mechanisms of action of the various methodologies are presented, along with their application span and known performance characteristics. Diagnostic imaging techniques and biomarkers are also covered, with an emphasis on their use for assessing COVID-19 or monitoring disease severity or complications. While the SARS-CoV-2 literature is rapidly evolving, this review highlights topics of interest that have occurred during the pandemic and the lessons learned throughout. Exploring a broad armamentarium of techniques for detecting SARS-CoV-2 will ensure continued diagnostic support for clinicians, public health, and infection prevention and control for this pandemic and provide advice for future pandemic preparedness.

Comparison of Vaccine Acceptance Between COVID-19 and Seasonal Influenza Among Women in China: A National Online Survey Based on Health Belief Model

Background: Influenza could circulate in parallel with COVID-19. Studies focusing on the comparison of vaccine acceptance between COVID-19 and seasonal influenza are lacking. The aim of the study was to assess and compare vaccine acceptance of COVID-19 and influenza among reproductive women in China, in order to better understand and address factors associated with vaccine acceptance and to provide guidance for targeted measures to promote vaccination.

Methods: A national anonymous cross-sectional survey on COVID-19 and influenza vaccine acceptance among reproductive women aged 18–49 years in China was conducted online based on health belief model, a model widely used to evaluate health beliefs. Sociodemographic characteristics, health status, knowledge, attitude, and health beliefs related to COVID-19 and influenza infection and vaccination were retrieved. Pearson's χ² test was used to compare the vaccine acceptance by the factors mentioned above. Multivariable logistic regression was used to assess the adjusted associations of factors related to vaccine acceptance. Paired t-test was used to compare scores of health beliefs between influenza and COVID-19 vaccinations.

Results: COVID-19 vaccine acceptance rate among reproductive women was 90.3% (95% CI 89.2–91.3%), which was significantly higher than influenza vaccine acceptance rate (85.5%, 95% CI: 84.2–86.7%). Influenza and COVID-19 vaccine acceptance both had the trends to decrease with age (all p < 0.05). Living in the western region, young age, a high level of knowledge scores on disease and vaccines, a high level of perceived susceptibility, a high level of cues to action, and a low level of perceived barriers were positively associated with both COVID-19 and influenza vaccine acceptance (all p < 0.05), while influenza vaccination history was additionally associated with influenza vaccine acceptance (p < 0.05).

Conclusions: Our findings suggest that tailored public health measures are needed to improve reproductive women's knowledge of COVID-19, influenza, and vaccines to alleviate women's vaccine hesitancy and expand vaccine uptake.

Sequential infection with H1N1 and SARS-CoV-2 aggravated COVID-19 pathogenesis in a mammalian model, and co-vaccination as an effective method of prevention of COVID-19 and influenza

Influenza A virus may circulate simultaneously with the SARS-CoV-2 virus, leading to more serious respiratory diseases during this winter. However, the influence of these viruses on disease outcome when both influenza A and SARS-CoV-2 are present in the host remains unclear. Using a mammalian model, sequential infection was performed in ferrets and in K18-hACE2 mice, with SARS-CoV-2 infection following H1N1. We found that co-infection with H1N1 and SARS-CoV-2 extended the duration of clinical manifestation of COVID-19, and enhanced pulmonary damage, but reduced viral shedding of throat swabs and viral loads in the lungs of ferrets. Moreover, mortality was increased in sequentially infected mice compared with single-infection mice. Compared with single-vaccine inoculation, co-inoculation of PiCoVacc (a SARS-CoV-2 vaccine) and the flu vaccine showed no significant differences in neutralizing antibody titers or virus-specific immune responses. Combined immunization effectively protected K18-hACE2 mice against both H1N1 and SARS-CoV-2 infection. Our findings indicated the development of systematic models of co-infection of H1N1 and SARS-CoV-2, which together notably enhanced pneumonia in ferrets and mice, as well as demonstrated that simultaneous vaccination against H1N1 and SARS-CoV-2 may be an effective prevention strategy for the coming winter.

Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Background

COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data.

Material/Methods

A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set.

Results

We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis.

Conclusions

This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

Multiplex Real-Time Reverse-Transcription Polymerase Chain Reaction Assays for Diagnostic Testing of Severe Acute Respiratory Syndrome Coronavirus 2 and Seasonal Influenza Viruses: A Challenge of the Phase 3 Pandemic Setting

BACKGROUND

Pandemic coronavirus disease 2019 (COVID-19) disease represents a challenge for healthcare structures. The molecular confirmation of samples from infected individuals is crucial and therefore guides public health decision making. Clusters and possibly increased diffuse transmission could occur in the context of the next influenza season. For this reason, a diagnostic test able to discriminate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from influenza viruses is urgently needed.

METHODS

A multiplex real-time reverse-transcription polymerase chain reaction (PCR) assay was assessed using 1 laboratory protocol with different real-time PCR instruments. Overall, 1000 clinical samples (600 from samples SARS-CoV-2-infected patients, 200 samples from influenza-infected patients, and 200 negative samples) were analyzed.

RESULTS

The assay developed was able to detect and discriminate each virus target and to intercept coinfections. The limit of quantification of each assay ranged between 5 and 10 genomic copy numbers, with a cutoff value of 37.7 and 37.8 for influenza and SARS-CoV-2 viruses, respectively. Only 2 influenza coinfections were detected in COVID-19 samples.

CONCLUSIONS

This study suggests that multiplex assay is a rapid, valid, and accurate method for the detection of SARS-CoV-2 and influenza viruses in clinical samples. The test may be an important diagnostic tool for both diagnostic and surveillance purposes during the seasonal influenza activity period.

A Strategy to Elicit M2e-Specific Antibodies Using a Recombinant H7N9 Live Attenuated Influenza Vaccine Expressing Multiple M2e Tandem Repeats

Influenza viruses remain a serious public health problem. Vaccination is the most effective way to prevent the disease; however, seasonal influenza vaccines demonstrate low or no effectiveness against antigenically drifted and newly emerged influenza viruses. Different strategies of eliciting immune responses against conserved parts of various influenza virus proteins are being developed worldwide. We constructed a universal live attenuated influenza vaccine (LAIV) candidate with enhanced breadth of protection by modifying H7N9 LAIV by incorporating four epitopes of M2 protein extracellular part into its hemagglutinin molecule. The new recombinant H7N9+4M2e vaccine induced anti-M2e antibody responses and demonstrated increased protection against heterosubtypic challenge viruses in direct and serum passive protection studies, compared to the classical H7N9 LAIV. The results of our study suggest that the H7N9+4M2e warrants further investigation in pre-clinical and phase 1 clinical trials.

Willingness to Vaccinate Children against Influenza after the Coronavirus Disease 2019 Pandemic

OBJECTIVES

To determine factors associated with parents who plan to vaccinate their children against influenza next year, especially those who did not vaccinate against influenza last year using a global survey.

STUDY DESIGN

A survey of caregivers accompanying their children aged 1-19 years old in 17 pediatric emergency departments in 6 countries at the peak of the coronavirus disease 2019 (COVID-19) pandemic. Anonymous online survey included caregiver and child demographic information, vaccination history and future intentions, and concern about the child and caregiver having COVID-19 at the time of emergency department visit.

RESULTS

Of 2422 surveys, 1314 (54.2%) caregivers stated they plan to vaccinate their child against influenza next year, an increase of 15.8% from the previous year. Of 1459 caregivers who did not vaccinate their children last year, 418 (28.6%) plan to do so next year. Factors predicting willingness to change and vaccinate included child's up-to-date vaccination status (aOR 2.03, 95% CI 1.29-3.32, P = .003); caregivers' influenza vaccine history (aOR 3.26, 95% CI 2.41-4.40, P < .010), and level of concern their child had COVID-19 (aOR 1.09, 95% CI 1.01-1.17, P = .022).

CONCLUSIONS

Changes in risk perception due to COVID-19, and previous vaccination, may serve to influence decision-making among caregivers regarding influenza vaccination in the coming season. To promote influenza vaccination among children, public health programs can leverage this information.

Pharmacy response to COVID-19: lessons learnt from Canada

When the first wave of COVID-19 hit in March 2020, health care professionals across Canada were challenged to quickly and efficiently adapt to change their work practices in these unprecedented times. Pharmacy professionals, being some of the very few front-line health care workers who remained accessible in person for patients, had to rapidly adopt critical changes in their pharmacies to respond in the best interest of their patients and their pharmacy staff. As challenging and demanding as such changes were, they provided pharmacists with invaluable lessons that would be imperative as the country enters a potentially more dangerous second wave. This article seeks to identify and summarize opportunities for improvement in pharmacy as learnt from the pandemic’s first wave. Such areas include but are not limited to handling of drug shortage and addressing drug hoarding and stockpiling, providing physical and mental support for staff, timing of flu vaccine and COVID-19 screening/testing, collaboration between different health care sites as well as collaboration with patients and with other health care professionals, telemedicine and willingness to adopt innovative ideas, need for more staff training and more precise research to provide accurate information and finally the need for more organizational and workplace support. Learning from what went well and what did not work in the early stages of the pandemic is integral to ensure pharmacy professionals are better prepared to protect themselves and their patients amidst a second and possibly subsequent waves.

Estimación de las tasas de mortalidad y letalidad por COVID-19 en Colombia

Introducción: el mundo está en aguas inéditas para la temporada 2020 del virus respiratorio. Por primera vez en la historia moderna, el mundo afronta la posibilidad de la pandemia de la enfermedad por coronavirus 2019 (COVID-19) y una epidemia simultánea de influenza estacional.  Objetivo: presentar un método para calcular las tasas de mortalidad y letalidad en los diferentes departamentos de Colombia por COVID-19. Metodología: para desarrollar la investigación se utilizó la base de datos de las personas fallecidas por COVID-19; la información de los datos corresponde a la base de acumulada hasta el 10 de agosto de 2020. Resultados: el grupo etario que presentó mayor tasa de mortalidad es la de 90-99, con 338 muertes por cada 100.000 habitantes, seguido del grupo entre 80-89, con 335 muertes por cada 100 habitantes, y los grupos con menor tasa de mortalidad de 0-9 y 10-19, que no alcanzan a tener una sola muerte por cada 100.000 habitantes. A nivel nacional la tasa por cada 100.000 habitantes fue 26 muertes. Conclusiones: el rastreo al exceso de mortalidad y la exploración activa de casos patentados con diagnósticos confirmados y presuntivos de infección por COVID-19, son necesarios para comprobar cuales funciones suceden por causa directa del coronavirus COVID-19, con una infección concomitante, o por causas diferentes.