Immunopathological similarities between COVID-19 and influenza: Investigating the consequences of Co-infection

Nanoparticle-mediated enhancement of DNA Vaccines: Revolutionizing immunization strategies

DNA vaccines are a novel form of vaccination that aims to harness genetic material to produce targeted immune responses. Nevertheless, their therapeutic application is hampered by low transfection efficacy, immunogenicity, and instability. Nanoparticle (NP) - based delivery systems are beneficial in enhancing DNA stability, increasing DNA uptake by antigen-presenting cells (APCs), and controlling antigen release. Some key progress includes the polymeric, lipid-based, and hybrid NPs and biocompatible carriers with inherent adjuvant effects. These systems have helped to enhance the antigen cross-presentation and T-cell activation significantly. In addition, biocompatible hybrid nanocarriers, antigen cross-presentation strategies, and next-generation sequencing (NGS) technologies are speeding up the identification of new antigens, while AI and machine learning are facilitating the development of efficient delivery systems. This review aims to assess how NPs have contributed to improving the effectiveness of DNA vaccines for treating diseases, cancer, and emerging diseases, as well as advancing the next generation of DNA vaccines.

Co-infection of SARS-CoV-2 and influenza A/B among patients with COVID-19: a systematic review and meta-analysis

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) is a public health problem and may result in co-infection with other pathogens such as influenza virus. This review investigates the co-infection of SARS-CoV-2 and influenza A/B among patients with COVID-19.

METHODS

This meta- analysis included 38 primary studies investigating co-infection of SARS-CoV-2 with influenza in confirmed cases of COVID-19. The global online databases were used to identify relevant studies published between December 2019 and July 2024. Data analysis was performed using STATA Ver. 17 software, and standard errors of prevalence were calculated using the binomial distribution formula. Heterogeneity of study results was evaluated using the I-square and Q index, and publication bias was examined using the Begg's and Egger's tests, as well as funnel plot. A random effects model was used to determine prevalence rates, and a forest plot diagram was used to present results with 95% confidence intervals. In addition, sensitivity analyses were performed to check the impact of each primary study on the overall estimate.

RESULT

The analysis found that the prevalence of influenza in co-infected patients at 95% confidence interval using a random effect model was 14% (95% CI: 8-20%). Significant heterogeneity was observed in the random-effects model for influenza A, 11% (95% CI: 5-18%) and B, 4% (95% CI: 2-7%) in co-infected patients. The highest prevalence of influenza A/B (21%), influenza A (17%) and influenza B (20%) was shown in Asia and Europe respectively. Subgroup analysis by study year showed that the co-prevalence of COVID-19 and influenza A/B was similar in the pre-2021 and post-2021 time periods, at 14% (95% CI: 5-23%) for pre-2021 and 6-22% for 2021 and post-2021. Also, the overall prevalence of influenza A and B in COVID-19 patients is 11% and 4%, and there was no significant difference between the time periods before and after 2021. Meta-regression with a random-effects model showed that the variables location, year group, and total patients showed only 2.71% of very high heterogeneity (I² = 99.92%), and none of these variables had a significant effect on the co-prevalence of COVID-19 and influenza A/B (p > 0.05). Also, meta-regression results showed that these variables had no significant effect on influenza A and B prevalence (p > 0.05) and showed only a small proportion of the very high heterogeneity (I² = 99.72%), (I² = 68.78%). In our study, Egger's test indicated that there was publication bias or small study effects in this meta-analysis (p = 0.0000).

CONCLUSION

The combination of SARS-CoV-2 with influenza and other respiratory viruses requires the best treatment protocols to reduce the severity of the disease. In this approach, high vaccination coverage against seasonal influenza and SARS-CoV-2 could reduce the risk of co-infection in the recent pandemic.

Changes in the Epidemiological Features of Influenza After the COVID-19 Pandemic in China, the United States, and Australia: Updated Surveillance Data for Influenza Activity

BACKGROUND

There has been a global decrease in seasonal influenza activity since the onset of the COVID-19 pandemic.

OBJECTIVE

We aimed to describe influenza activity during the 2021/2022 season and compare it to the trends from 2012 to 2023. We also explored the influence of social and public health prevention measures during the COVID-19 pandemic on influenza activity.

METHODS

We obtained influenza data from January 1, 2012, to February 5, 2023, from publicly available platforms for China, the United States, and Australia. Mitigation measures were evaluated per the stringency index, a composite index with 9 measures. A general additive model was used to assess the stringency index and the influenza positivity rate correlation, and the deviance explained was calculated.

RESULTS

We used over 200,000 influenza surveillance data. Influenza activity remained low in the United States and Australia during the 2021/2022 season. However, it increased in the United States with a positive rate of 26.2% in the 49th week of 2022. During the 2021/2022 season, influenza activity significantly increased compared with the previous year in southern and northern China, with peak positivity rates of 28.1% and 35.1% in the second week of 2022, respectively. After the COVID-19 pandemic, the dominant influenza virus genotype in China was type B/Victoria, during the 2021/2022 season, and accounted for >98% (24,541/24,908 in the South and 20,543/20,634 in the North) of all cases. Influenza virus type B/Yamagata was not detected in all these areas after the COVID-19 pandemic. Several measures individually significantly influence local influenza activity, except for influenza type B in Australia. When combined with all the measures, the deviance explained values for influenza A and B were 87.4% (P<.05 for measures of close public transport and restrictions on international travel) and 77.6% in southern China and 83.4% (P<.05 for measures of school closing and close public transport) and 81.4% in northern China, respectively. In the United States, the association was relatively stronger, with deviance-explained values of 98.6% for influenza A and 99.1% (P<.05 for measures of restrictions on international travel and public information campaign) for influenza B. There were no discernible effects on influenza B activity in Australia between 2020 and 2022 due to the incredibly low positive rate of influenza B. Additionally, the deviance explained values were 95.8% (P<.05 for measures of restrictions on gathering size and restrictions on international travel) for influenza A and 72.7% for influenza B.

CONCLUSIONS

Influenza activity has increased gradually since 2021. Mitigation measures for COVID-19 showed correlations with influenza activity, mainly driven by the early stage of the pandemic. During late 2021 and 2022, the influence of mitigation management for COVID-19 seemingly decreased gradually, as the activity of influenza increased compared to the 2020/2021 season.

Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model

BACKGROUND

Influenza, an acute infectious respiratory disease, presents a significant global health challenge. Accurate prediction of influenza activity is crucial for reducing its impact. Therefore, this study seeks to develop a hybrid Convolution Neural Network-Long Short Term Memory neural network (CNN-LSTM) model to forecast the percentage of influenza-like-illness (ILI) rate in Hebei Province, China. The aim is to provide more precise guidance for influenza prevention and control measures.

METHODS

Using ILI% data from 28 national sentinel hospitals in the Hebei Province, spanning from 2010 to 2022, we employed the Python deep learning framework PyTorch to develop the CNN-LSTM model. Additionally, we utilized R and Python to develop four other models commonly used for predicting infectious diseases. After constructing the models, we employed these models to make retrospective predictions, and compared each model's prediction performance using mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and other evaluation metrics.

RESULTS

Based on historical ILI% data from 28 national sentinel hospitals in Hebei Province, the Seasonal Auto-Regressive Indagate Moving Average (SARIMA), Extreme Gradient Boosting (XGBoost), Convolution Neural Network (CNN), Long Short Term Memory neural network (LSTM) models were constructed. On the testing set, all models effectively predicted the ILI% trends. Subsequently, these models were used to forecast over different time spans. Across various forecasting periods, the CNN-LSTM model demonstrated the best predictive performance, followed by the XGBoost model, LSTM model, CNN model, and SARIMA model, which exhibited the least favorable performance.

CONCLUSION

The hybrid CNN-LSTM model had better prediction performances than the SARIMA model, CNN model, LSTM model, and XGBoost model. This hybrid model could provide more accurate influenza activity projections in the Hebei Province.

An end-point multiplex RT-PCR for SARS-CoV-2, Influenza A and B detection, including simultaneous RNAse P amplification: a timely tool for more accessible differential diagnosis

The multiplex molecular diagnostic assays described for severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), influenza A (IAV) and B (IBV) viruses have been mainly based on real-time reaction, which limits their access to many laboratories or diagnostic institutions. To contribute to available strategies and expand access to differential diagnosis, we describe an end-point multiplex RT-PCR targeting SARS-CoV-2, IAV and IBV with simultaneous endogenous control amplification. Initially, we looked for well-established primers sets for SARS-CoV-2, IAV, IBV and RNAse P whose amplicons could be distinguished on agarose gel. The multiplex assay was then standardized by optimizing the reaction mix and cycle conditions. The limit of detection (LoD) was determined using titrated viruses (for SARS-CoV-2 and IAV) and by dilution from a pool of IBV-positive samples. The diagnostic performance of the multiplex was evaluated by testing samples with different RNAse P and viral loads, previously identified as positive or negative for the target viruses. The amplicons of IAV (146 bp), SARS-CoV-2 (113 bp), IBV (103 bp) and RNAse P (65 bp) were adequately distinguished in our multiplex. The LoD for SARS-CoV-2, IAV and IBV was 0.02 TCID50/ml, 0.07 TCID50/ml and 10-3 from a pool of positive samples, respectively. All samples positive for SARS-CoV-2 (n=70, Ct 17.2-36.9), IAV (n=53, Ct 14-34.9) and IBV (n=12, Ct 23.9-31.9) remained positive in our multiplex assay. RNAse P from negative samples (n=40, Ct 25.2-30.2) was also amplified in the multiplex. Overall, our assay is a timely and alternative tool for detecting SARS-CoV-2 and influenza viruses in laboratories with limited access to supplies/equipment.

Immunogenicity and safety of concomitant bivalent COVID-19 and quadrivalent influenza vaccination: implications of immune imprinting and interference

OBJECTIVES

Concomitant COVID-19 and influenza vaccination would be an efficient strategy. Although the co-administration of monovalent COVID-19 and influenza vaccinations showed acceptable immunogenicity, it remains unknown whether the bivalent COVID-19 vaccine could intensify immune interference. We aimed to evaluate the immunogenicity and safety of concomitant BA.5-based bivalent COVID-19 and influenza vaccination.

METHODS

An open-label, nonrandomized clinical trial was conducted for 154 age-matched and sex-matched healthy adults between October 2022 and December 2022. Participants received either a concomitant bivalent COVID-19 mRNA booster and quadrivalent influenza vaccination (group C) or separate vaccinations (group S) at least 4 weeks apart. Solicited and unsolicited adverse events were reported up to 6 months postvaccination. Immunogenicity was evaluated by anti-spike (S) IgG electrochemiluminescence immunoassay, focus reduction neutralization test, and hemagglutination inhibition assay.

RESULTS

Group C did not meet the noninferiority criteria for the seroconversion rates of anti-S IgG and neutralizing antibodies against the wild-type SARS-CoV-2 strain compared with group S (44.2% vs. 46.8%, difference of -2.6% [95% CI, -18 to 13.4]; 44.2% vs. 57.1%, difference of -13.0% [95% CI to -28.9 to 2.9]). However, group C showed a stronger postvaccination neutralizing antibody response against Omicron BA.5 (72.7% vs. 64.9%). Postvaccination geometric mean titers for SARS-CoV-2 and influenza strains were similar between groups, except for influenza B/Victoria. Most adverse events were mild and comparable between the study groups.

DISCUSSION

Concomitant administration of bivalent COVID-19 mRNA and quadrivalent influenza vaccines showed tolerable safety profiles and sufficient immunogenicity, particularly attenuating immune imprinting induced by previous ancestral vaccine strains.

The Role and Value of Professional Rapid Testing of Acute Respiratory Infections (ARIs) in Europe: A Special Focus on the Czech Republic, Poland, and Romania

This review aims to explore the role of professional diagnostic rapid testing of acute respiratory infections (ARIs), especially COVID-19 and influenza, ensuring proper disease management and treatment in Europe, and particularly in Czech Republic, Poland, and Romania. The paper was constructed based on a review of scientific evidence and national and international policies and recommendations, as well as a process of validation by four experts. The development of new testing technologies, treatment options, and increased awareness of the negative multidimensional impact of ARI profiles transformed differential diagnosis into a tangible and desirable reality. This review covers the following topics: (1) the multidimensional impact of ARIs, (2) ARI rapid diagnostic testing platforms and their value, (3) the policy landscape, (4) challenges and barriers to implementation, and (5) a set of recommendations illustrating a path forward. The findings indicate that rapid diagnostic testing, including at the point of care (POC), can have a positive impact on case management, antimicrobial and antibiotic stewardship, epidemiological surveillance, and decision making. Integrating this strategy will require the commitment of governments and the international and academic communities, especially as we identified room for improvement in the access and expansion of POC rapid testing in the focus countries and the inclusion of rapid testing in relevant policies.

COVID-19 in pregnant women: a systematic review and meta-analysis on the risk and prevalence of pregnancy loss

BACKGROUND

Pregnant women infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more likely to experience preterm birth and their neonates are more likely to be stillborn or admitted to a neonatal unit. The World Health Organization declared in May 2023 an end to the coronavirus disease 2019 (COVID-19) pandemic as a global health emergency. However, pregnant women are still becoming infected with SARS-CoV-2 and there is limited information available regarding the effect of SARS-CoV-2 infection in early pregnancy on pregnancy outcomes.

OBJECTIVE AND RATIONALE

We conducted this systematic review to determine the prevalence of early pregnancy loss in women with SARS-Cov-2 infection and compare the risk to pregnant women without SARS-CoV-2 infection.

SEARCH METHODS

Our systematic review is based on a prospectively registered protocol. The search of PregCov19 consortium was supplemented with an extra electronic search specifically on pregnancy loss in pregnant women infected with SARS-CoV-2 up to 10 March 2023 in PubMed, Google Scholar, and LitCovid. We included retrospective and prospective studies of pregnant women with SARS-CoV-2 infection, provided that they contained information on pregnancy losses in the first and/or second trimester. Primary outcome was miscarriage defined as a pregnancy loss before 20 weeks of gestation, however, studies that reported loss up to 22 or 24 weeks were also included. Additionally, we report on studies that defined the pregnancy loss to occur at the first and/or second trimester of pregnancy without specifying gestational age, and for second trimester miscarriage only when the study presented stillbirths and/or foetal losses separately from miscarriages. Data were stratified into first and second trimester. Secondary outcomes were ectopic pregnancy (any extra-uterine pregnancy), and termination of pregnancy. At least three researchers independently extracted the data and assessed study quality. We calculated odds ratios (OR) and risk differences (RDs) with corresponding 95% CI and pooled the data using random effects meta-analysis. To estimate risk prevalence, we performed meta-analysis on proportions. Heterogeneity was assessed by I2.

OUTCOMES

We included 120 studies comprising a total of 168 444 pregnant women with SARS-CoV-2 infection; of which 18 233 women were in their first or second trimester of pregnancy. Evidence level was considered to be of low to moderate certainty, mostly owing to selection bias. We did not find evidence of an association between SARS-CoV-2 infection and miscarriage (OR 1.10, 95% CI 0.81-1.48; I2 = 0.0%; RD 0.0012, 95% CI -0.0103 to 0.0127; I2 = 0%; 9 studies, 4439 women). Miscarriage occurred in 9.9% (95% CI 6.2-14.0%; I2 = 68%; 46 studies, 1797 women) of the women with SARS CoV-2 infection in their first trimester and in 1.2% (95% CI 0.3-2.4%; I2 = 34%; 33 studies; 3159 women) in the second trimester. The proportion of ectopic pregnancies in women with SARS-CoV-2 infection was 1.4% (95% CI 0.02-4.2%; I2 = 66%; 14 studies, 950 women). Termination of pregnancy occurred in 0.6% of the women (95% CI 0.01-1.6%; I2 = 79%; 39 studies; 1166 women).

WIDER IMPLICATIONS

Our study found no indication that SARS-CoV-2 infection in the first or second trimester increases the risk of miscarriages. To provide better risk estimates, well-designed studies are needed that include pregnant women with and without SARS-CoV-2 infection at conception and early pregnancy and consider the association of clinical manifestation and severity of SARS-CoV-2 infection with pregnancy loss, as well as potential confounding factors such as previous pregnancy loss. For clinical practice, pregnant women should still be advised to take precautions to avoid risk of SARS-CoV-2 exposure and receive SARS-CoV-2 vaccination.

Antiviral responses versus virus-induced cellular shutoff: a game of thrones between influenza A virus NS1 and SARS-CoV-2 Nsp1

Following virus recognition of host cell receptors and viral particle/genome internalization, viruses replicate in the host via hijacking essential host cell machinery components to evade the provoked antiviral innate immunity against the invading pathogen. Respiratory viral infections are usually acute with the ability to activate pattern recognition receptors (PRRs) in/on host cells, resulting in the production and release of interferons (IFNs), proinflammatory cytokines, chemokines, and IFN-stimulated genes (ISGs) to reduce virus fitness and mitigate infection. Nevertheless, the game between viruses and the host is a complicated and dynamic process, in which they restrict each other via specific factors to maintain their own advantages and win this game. The primary role of the non-structural protein 1 (NS1 and Nsp1) of influenza A viruses (IAV) and the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respectively, is to control antiviral host-induced innate immune responses. This review provides a comprehensive overview of the genesis, spatial structure, viral and cellular interactors, and the mechanisms underlying the unique biological functions of IAV NS1 and SARS-CoV-2 Nsp1 in infected host cells. We also highlight the role of both non-structural proteins in modulating viral replication and pathogenicity. Eventually, and because of their important role during viral infection, we also describe their promising potential as targets for antiviral therapy and the development of live attenuated vaccines (LAV). Conclusively, both IAV NS1 and SARS-CoV-2 Nsp1 play an important role in virus-host interactions, viral replication, and pathogenesis, and pave the way to develop novel prophylactic and/or therapeutic interventions for the treatment of these important human respiratory viral pathogens.

Prior Influenza Infection Mitigates SARS-CoV-2 Disease in Syrian Hamsters

Seasonal infection rates of individual viruses are influenced by synergistic or inhibitory interactions between coincident viruses. Endemic patterns of SARS-CoV-2 and influenza infection overlap seasonally in the Northern hemisphere and may be similarly influenced. We explored the immunopathologic basis of SARS-CoV-2 and influenza A (H1N1pdm09) interactions in Syrian hamsters. H1N1 given 48 h prior to SARS-CoV-2 profoundly mitigated weight loss and lung pathology compared to SARS-CoV-2 infection alone. This was accompanied by the normalization of granulocyte dynamics and accelerated antigen-presenting populations in bronchoalveolar lavage and blood. Using nasal transcriptomics, we identified a rapid upregulation of innate and antiviral pathways induced by H1N1 by the time of SARS-CoV-2 inoculation in 48 h dual-infected animals. The animals that were infected with both viruses also showed a notable and temporary downregulation of mitochondrial and viral replication pathways. Quantitative RT-PCR confirmed a decrease in the SARS-CoV-2 viral load and lower cytokine levels in the lungs of animals infected with both viruses throughout the course of the disease. Our data confirm that H1N1 infection induces rapid and transient gene expression that is associated with the mitigation of SARS-CoV-2 pulmonary disease. These protective responses are likely to begin in the upper respiratory tract shortly after infection. On a population level, interaction between these two viruses may influence their relative seasonal infection rates.

Identification of key genes associated with persistent immune changes and secondary immune activation responses induced by influenza vaccination after COVID-19 recovery by machine learning methods

COVID-19 is hypothesized to exert enduring effects on the immune systems of patients, leading to alterations in immune-related gene expression. This study aimed to scrutinize the persistent implications of SARS-CoV-2 infection on gene expression and its influence on subsequent immune activation responses. We designed a machine learning-based approach to analyze transcriptomic data from both healthy individuals and patients who had recovered from COVID-19. Patients were categorized based on their influenza vaccination status and then compared with healthy controls. The initial sample set encompassed 86 blood samples from healthy controls and 72 blood samples from recuperated COVID-19 patients prior to influenza vaccination. The second sample set included 123 blood samples from healthy controls and 106 blood samples from recovered COVID-19 patients who had been vaccinated against influenza. For each sample, the dataset captured expression levels of 17,060 genes. Above two sample sets were first analyzed by seven feature ranking algorithms, yielding seven feature lists for each dataset. Then, each list was fed into the incremental feature selection method, incorporating three classic classification algorithms, to extract essential genes, classification rules and build efficient classifiers. The genes and rules were analyzed in this study. The main findings included that NEXN and ZNF354A were highly expressed in recovered COVID-19 patients, whereas MKI67 and GZMB were highly expressed in patients with secondary immune activation post-COVID-19 recovery. These pivotal genes could provide valuable insights for future health monitoring of COVID-19 patients and guide the creation of continued treatment regimens.

Purinergic signaling: decoding its role in COVID-19 pathogenesis and promising treatment strategies

The pathogenesis of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), is complex and involves dysregulated immune responses, inflammation, and coagulopathy. Purinergic signaling, mediated by extracellular nucleotides and nucleosides, has emerged as a significant player in the pathogenesis of COVID-19. Extracellular adenosine triphosphate (ATP), released from damaged or infected cells, is a danger signal triggering immune responses. It activates immune cells, releasing pro-inflammatory cytokines, contributing to the cytokine storm observed in severe COVID-19 cases. ATP also promotes platelet activation and thrombus formation, contributing to the hypercoagulability seen in COVID-19 patients. On the other hand, adenosine, an immunosuppressive nucleoside, can impair anti-viral immune responses and promote tissue damage through its anti-inflammatory effects. Modulating purinergic receptors represents a promising therapeutic strategy for COVID-19. Understanding the role of purinergic signaling in COVID-19 pathogenesis and developing targeted therapeutic approaches can potentially improve patient outcomes. This review focuses on the part of purinergic signaling in COVID-19 pathogenesis and highlights potential therapeutic approaches targeting purinergic receptors.

Influenza A, like Omicron SARS-CoV-2, Is Similarly Detected in Saliva or Nasopharyngeal Samples via RT-qPCR

After the Coronavirus pandemic, the importance of virus surveillance was highlighted, reinforcing the constant necessity of discussing and updating the methods for collection and diagnoses, including for other respiratory viruses. Although the nasopharyngeal swab is the gold-standard sample for detecting and genotyping SARS-CoV-2 and Influenza viruses, its collection is uncomfortable and requires specialized teams, which can be costly. During the pandemic, non-invasive saliva samples proved to be a suitable alternative for SARS-CoV-2 diagnosis, but for Influenza virus the use of this sample source is not recognized yet. In addition, most SARS-CoV-2 comparisons were conducted before the Omicron variant emerged. Here, we aimed to compare Influenza A and Omicron RT-qPCR analysis of nasopharyngeal swabs and saliva self-collection in paired samples from 663 individuals. We found that both nasopharyngeal swab and saliva collection are efficient for the diagnosis of Omicron (including sub-lineages) and for Influenza A, with high sensitivity and accuracy (>90%). The kappa index is 0.938 for Influenza A and 0.905 for SARS-CoV-2. These results showed excellent agreement between the two samples reinforcing saliva samples as a reliable source for detecting Omicron and highlighting saliva as a valid sample source for Influenza detection, considering this cheaper and more comfortable alternative.

A systematic review of the clinical characteristics of influenza-COVID-19 co-infection

COVID-19 has impacted populations across the globe and has been a major cause of morbidity and mortality. Influenza is another potentially deadly respiratory infection that affects people worldwide. While both of these infections pose major health threats, little is currently understood regarding the clinical aspects of influenza and COVID-19 co-infection. Our objective was to therefore provide a systematic review of the clinical characteristics, treatments, and outcomes for patients who are co-infected with influenza and COVID-19. Our review, which was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, involved searching for literature in seven different databases. Studies were eligible for inclusion if they included at least one co-infected patient, were available in English, and described clinical characteristics for the patients. Data were pooled after extraction. Study quality was assessed using the Joanna Brigg's Institute Checklists. Searches produced a total of 5096 studies, and of those, 64 were eligible for inclusion. A total of 6086 co-infected patients were included, 54.1% of whom were male; the mean age of patients was 55.9 years (SD = 12.3). 73.6% of cases were of influenza A and 25.1% were influenza B. 15.7% of co-infected patients had a poor outcome (death/deterioration). The most common symptoms were fever, cough, and dyspnea, with the most frequent complications being pneumonia, linear atelectasis, and acute respiratory distress syndrome. Oseltamivir, supplemental oxygen, arbidol, and vasopressors were the most common treatments provided to patients. Having comorbidities, and being unvaccinated for influenza, were shown to be important risk factors. Co-infected patients show symptoms that are similar to those who are infected with COVID-19 or influenza only. However, co-infected patients have been shown to be at an elevated risk for poor outcomes compared to mono-infected COVID-19 patients. Screening for influenza in high-risk COVID-19 patients is recommended. There is also a clear need to improve patient outcomes with more effective treatment regimens, better testing, and higher rates of vaccination.

Analysis of the effectiveness of non-pharmaceutical interventions on influenza during the Coronavirus disease 2019 pandemic by time-series forecasting

BACKGROUND

Coronavirus disease 2019 (COVID-19) was first identified in South Korea during the 2019-2020 seasonal influenza epidemic. The social distancing measures, as effective non-pharmaceutical interventions (NPIs), adopted to mitigate the spread of COVID-19 might have influenced influenza activity. We evaluated IFV(influenza virus) activity during the COVID-19 pandemic and the effect of NPI intensity on influenza transmission.

METHODS

IFV activity and epidemic duration during COVID-19 pandemic were predicted under a counterfactual scenario with no NPIs against COVID-19. The Seasonal Autoregressive Integrated Moving Average Model was used to quantify the effects of NPIs on the transmission of influenza virus. Influenza-like illness/1000 outpatients and IFV positivity rate from the 2011-2012 to 2021-2022 seasons were used in this study.

RESULTS

Comparison of the 2020-2021 and 2021-2022 seasonal influenza activities with those in 2013-2019 showed that COVID-19 outbreaks and associated NPIs such as face mask use, school closures, and travel restrictions reduced the influenza incidence by 91%. Without NPIs against COVID-19, the rates of influenza-like illness and IFV positivity would have been high during the influenza epidemic season, as in previous seasons. NPI intensity decreased the transmission of influenza; the magnitude of the reduction increased as the intensity of social-distancing measures increased (weak social distancing; step-by-step daily recovery: 58.10%, strong social distancing; special quarantine measures: 95.12%).

CONCLUSIONS

Our results suggest that NPIs and personal hygiene can be used to suppress influenza transmission. NPIs against COVID-19 may be useful strategies for the prevention and control of influenza epidemics.

Synthesis and Biological Evaluation of Benzothiazolyl-pyridine Hybrids as New Antiviral Agents against H5N1 Bird Flu and SARS-COV-2 Viruses

A novel series of benzothiazolyl-pyridine hybrids 8a-h and 14a-e were produced from the reaction of enamine derivative 4 with each of the arylcyanoacetamides 5a-h and cyanoacetohydrazides 9a-e. The new products were characterized by spectral techniques (IR, 1H NMR, 13C NMR, and MS). Biological evaluation of 8a-h and 14a-e in vitro against H5N1 and SARS-COV-2 viruses showed that several compounds had significant activity. Compounds 8f-h, which contain fluorine atoms, have better activity against H5N1 and anti-SARS-CoV-2 viruses than the other compounds included in this study. Compound 8h has a trifluoromethyl group at position-3 of the phenyl ring and exhibits a high activity against H5N1 virus with 93 and 60% inhibition at concentrations of 0.5 and 0.25 μmol/μL, respectively, among the tested compounds, and it also showed anti-SARS-CoV-2 virus with a half-maximum inhibition rate of 3.669 μM, among the remaining compounds. The mechanism of action of 8f-h, which is expected to be repurposed against COVID-19, was investigated. The results showed that the compounds have virucidal effects at different stages of the three mechanisms of action. Furthermore, compounds 8f-h were found to possess CoV-3CL protease inhibitory activities with IC50 values of 544.6, 868.2, and 240.6 μg/mL, respectively, compared to IC50 = 129.8 μg/mL of the standard drug lopinavir. Interestingly, compounds 8f-h also showed high inhibitory activity against the H5N1 virus as well as the SARS-CoV-2 virus. Moreover, compounds 8f-h fit admirably into the active site of the SARS-CoV-2 main protease (PDB ID: 6LU7) using the molecular docking Moe software 2015.10.

The impact of trimester of COVID-19 infection on pregnancy outcomes after recovery

OBJECTIVES

Many physiological adaptations occur during pregnancy. It is not currently known how timing of COVID-19 infection impacts pregnancy. We hypothesize that maternal and neonatal outcomes are different if COVID-19 infection occurs in different trimesters of pregnancy.

METHODS

This retrospective cohort study was conducted from 3/2020 to 6/2022. Pregnant patients with a positive COVID-19 infection more than 10 days before delivery (COVID-recovered) were identified and grouped by trimester of infection. Demographics and maternal, obstetric, and neonatal outcomes were analyzed. ANOVA, Wilcoxon rank-sum test, Pearson's chi-squared test, and Fisher's exact test were used to compare continuous and categorical data.

RESULTS

A total of 298 COVID-recovered pregnant patients were identified. Of those, 48 (16 %) were infected in the 1st trimester, 123 (41 %) in the 2nd, and 127 (43 %) in the 3rd. There were no significant demographic differences between the study groups. Vaccination status was similar. Hospital admission rate and the need for oxygen therapy while infected were significantly higher in patients with 2nd or 3rd trimester infection (18 % & 20 % vs. 2 % and 13 % & 14 % vs. 0 %, respectively). Rates of preterm birth (PTB) and extreme PTB were higher in the 1st trimester infection group. Infants born to mothers infected in the 2nd trimester had more neonatal sepsis workups (22 % vs. 12 % & 7 %). Other outcomes were similar between groups.

CONCLUSIONS

First trimester COVID-recovered patients were more likely to have a preterm birth despite having lower rates of hospital admission and oxygen supplementation while infected than patients who recovered from a 2nd or 3rd trimester infection.

Natural killer cells and their exosomes in viral infections and related therapeutic approaches: where are we?

Innate immunity is the first line of the host immune system to fight against infections. Natural killer cells are the innate immunity lymphocytes responsible for fighting against virus-infected and cancerous cells. They have various mechanisms to suppress viral infections. On the other hand, viruses have evolved to utilize different ways to evade NK cell-mediated responses. Viruses can balance the response by regulating the cytokine release pattern and changing the proportion of activating and inhibitory receptors on the surface of NK cells. Exosomes are a subtype of extracellular vesicles that are involved in intercellular communication. Most cell populations can release these nano-sized vesicles, and it was shown that these vesicles produce identical outcomes to the originating cell from which they are released. In recent years, the role of NK cell-derived exosomes in various diseases including viral infections has been highlighted, drawing attention to utilizing the therapeutic potential of these nanoparticles. In this article, the role of NK cells in various viral infections and the mechanisms used by viruses to evade these important immune system cells are initially examined. Subsequently, the role of NK cell exosomes in controlling various viral infections is discussed. Finally, the current position of these cells in the treatment of viral infections and the therapeutic potential of their exosomes are reviewed. Video Abstract.

Evaluation of the relationship between serum interleukin-1β levels and expression of inflammasome-related genes in patients with COVID-19

BACKGROUND

Inflammasomes are a group of molecules that are strongly involved in causing inflammation. This study aimed to evaluate the expression of NLR family pyrin domain containing 1 (NLRP1), NLRP3, and Apoptosis-associated speck-like protein containing a CARD (ASC) as well as their association with serum level of interleukin (IL)-1β in patients with coronavirus disease 2019 (COVID-19).

METHODS

Thirty COVID-19 patients and 30 healthy subjects (HS) were recruited. Peripheral blood specimens were collected from subjects to assess NLRP1, NLRP3, and ASC gene expression by Real time-PCR technique. Serum levels of IL-1β were also measured via the enzyme-linked immunosorbent assay (ELISA).

RESULTS

The findings showed no significant differences in serum IL-1β level between COVID-19 patients and the HS group. mRNA expression of ASC (P = 0.008) and NLRP1 (P = 0.03) gene had a significant increase in COVID-19 patients compared to HS, while there was no significant increase in the expression of NLRP3 between the studied group. There were significant correlations between patient's data and expression levels of NLRP1, NLRP3, IL-1β, and ACS.

CONCLUSIONS

NLRP1 and ASC may have a more critical role in the generation of the active form of IL-1β in COVID-19 patients compared to NLRP3. However, serum levels of IL-1β in patients did not show a significant increase, which may be due to the patient's condition and the application of virus escape mechanisms through impaired NLRP3 expression and its malfunction.

The convergent evolution of influenza A virus: Implications, therapeutic strategies and what we need to know

Influenza virus infection, more commonly known as the 'cold flu', is an etiological agent that gives rise to recurrent annual flu and many pandemics. Dated back to the 1918- Spanish Flu, the influenza infection has caused the loss of many human lives and significantly impacted the economy and daily lives. Influenza virus can be classified into four different genera: influenza A-D, with the former two, influenza A and B, relevant to humans. The capacity of antigenic drift and shift in Influenza A has given rise to many novel variants, rendering vaccines and antiviral therapies useless. In light of the emergence of a novel betacoronavirus, the SARS-CoV-2, unravelling the underpinning mechanisms that support the recurrent influenza epidemics and pandemics is essential. Given the symptom similarities between influenza and covid infection, it is crucial to reiterate what we know about the influenza infection. This review aims to describe the origin and evolution of influenza infection. Apart from that, the risk factors entail the implication of co-infections, especially regarding the COVID-19 pandemic is further discussed. In addition, antiviral strategies, including the potential of drug repositioning, are discussed in this context. The diagnostic approach is also critically discussed in an effort to understand better and prepare for upcoming variants and potential influenza pandemics in the future. Lastly, this review encapsulates the challenges in curbing the influenza spread and provides insights for future directions in influenza management.

Surveillance Methods Used to Detect, Characterize, and Monitor the COVID-19 Pandemic in Rocky Mountain Tribal Communities

OBJECTIVE

Data were essential to public health decision-making during the COVID-19 pandemic, yet no single data source was adequate for Tribes in Montana and Wyoming. We outlined data access, availability, and limitations for COVID-19 pandemic surveillance response to improve future data exchange.

MATERIALS AND METHODS

The Rocky Mountain Tribal Epidemiology Center (RMTEC) used various data sources to deliver data on the number of COVID-19 cases, deaths, and vaccinations at local, state, and regional levels to inform Tribes in Montana and Wyoming. RMTEC reviewed state, federal, and public datasets and then attached a score to each dataset for completeness of demographic information, including race, geographic level, and refresh rate.

RESULTS

The RMTEC COVID-19 response team shared data weekly on the number of COVID-19 cases, deaths, and vaccinations distributed and the percentage of the population vaccinated with Tribal health departments in Montana and Wyoming. The Indian Health Service Epidemiology Data Mart dataset scored the highest (24 of 30), followed by datasets from Montana (18 of 30) and Wyoming (22 of 30). Publicly available datasets scored low largely due to data aggregation across larger geographic areas and lack of demographic variables.

PRACTICE IMPLICATIONS

The absence of data on race and ethnicity from publicly available data and lack of access to real-time data limited RMTEC's ability to provide Tribal-specific updates on COVID-19 cases, deaths, and vaccinations to Tribal health departments. RMTEC should be fully funded to provide the necessary resources for data management and the capacity to respond to data requests from Tribal health departments and their programs to address current and future pandemics. Federal and state agencies should also be educated on Tribal Epidemiology Centers' public health authority status to improve access to infectious disease data among those agencies.

COVID-19: An Overview of SARS-CoV-2 Variants-The Current Vaccines and Drug Development

The world is presently in crisis facing an outbreak of a health-threatening microorganism known as COVID-19, responsible for causing uncommon viral pneumonia in humans. The virus was first reported in Wuhan, China, in early December 2019, and it quickly became a global concern due to the pandemic. Challenges in this regard have been compounded by the emergence of several variants such as B.1.1.7, B.1.351, P1, and B.1.617, which show an increase in transmission power and resistance to therapies and vaccines. Ongoing researches are focused on developing and manufacturing standard treatment strategies and effective vaccines to control the pandemic. Despite developing several vaccines such as Pfizer/BioNTech and Moderna approved by the U.S. Food and Drug Administration (FDA) and other vaccines in phase 4 clinical trials, preventive measures are mandatory to control the COVID-19 pandemic. In this review, based on the latest findings, we will discuss different types of drugs as therapeutic options and confirmed or developing vaccine candidates against SARS-CoV-2. We also discuss in detail the challenges posed by the variants and their effect on therapeutic and preventive interventions.

Does Vaccine Confidence Mediate the Relationship between Vaccine Literacy and Influenza Vaccination? Exploring Determinants of Vaccination among Staff Members of Nursing Homes in Tuscany, Italy, during the COVID-19 Pandemic

BACKGROUND

Low coverage of influenza vaccination in nursing home (NH) staff may be attributed to factors such as vaccine confidence (VC) and vaccine literacy (VL). Our study aimed to evaluate the role of VL and VC in predicting the intention to get the influenza vaccine in a sample of employees of NHs in Tuscany, Italy.

METHODS

Data from staff members in Tuscany were collected using an online questionnaire that examined influenza vaccination history, intentions, demographic information, health status, and VL. Statistical analyses explored the relationships between VC, VL, and vaccination intentions.

RESULTS

The study included 1794 respondents, (86.3%) and assistants/aides (58.1%), with a median age of 46 years. The intention to get vaccinated was significantly higher among those with health risk conditions, and there was a positive association between VC and VL, specifically its interactive/critical component. The mediation analysis showed that VC completely mediated the relationship between VL and the intention to get vaccinated, with significant effects observed in different subgroups.

CONCLUSIONS

VC is a key factor that mediates the effect of VL on vaccine intention. These results suggest that interventions aimed at improving VL alone may not be sufficient to increase vaccine uptake unless VC is also addressed.

Age-dependent immune responses in COVID-19-mediated liver injury: focus on cytokines

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is potentially pathogenic and causes severe symptoms; in addition to respiratory syndromes, patients might experience other severe conditions such as digestive complications and liver complications injury. The abnormality in the liver is manifested by hepatobiliary dysfunction and enzymatic elevation, which is associated with morbidity and mortality. The direct cytopathic effect, immune dysfunction, cytokine storm, and adverse effects of therapeutic regimens have a crucial role in the severity of liver injury. According to aging and immune system alterations, cytokine patterns may also change in the elderly. Moreover, hyperproduction of cytokines in the inflammatory response to SARS-CoV-2 can lead to multi-organ dysfunction. The mortality rate in elderly patients, particularly those with other comorbidities, is also higher than in adults. Although the pathogenic effect of SARS-CoV-2 on the liver has been widely studied, the impact of age and immune-mediated responses at different ages remain unclear. This review discusses the association between immune system responses in coronavirus disease 2019 (COVID-19) patients of different ages and liver injury, focusing on cytokine alterations.

The Impact of Coronavirus Disease 2019 on Viral, Bacterial, and Fungal Respiratory Infections

Although coronavirus disease 2019 (COVID-19) remains an ongoing threat, concerns regarding other respiratory infections remain. Throughout the COVID-19 pandemic various epidemiologic trends have been observed in other respiratory viruses including a reduction in influenza and respiratory syncytial virus infections following onset of the COVID-19 pandemic. Observations suggest that infections with other respiratory viruses were reduced with social distancing, mask wearing, eye protection, and hand hygiene practices. Coinfections with COVID-19 exist not only with other respiratory viruses but also with bacterial pneumonias and other nosocomial and opportunistic infections. Coinfections have been associated with increased severity of illness and other adverse outcomes.

A point-of-care biosensor for rapid detection and differentiation of COVID-19 virus (SARS-CoV-2) and influenza virus using subwavelength grating micro-ring resonator

In the context of continued spread of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 and the emergence of new variants, the demand for rapid, accurate, and frequent detection is increasing. Moreover, the new predominant strain, Omicron variant, manifests more similar clinical features to those of other common respiratory infections. The concurrent detection of multiple potential pathogens helps distinguish SARS-CoV-2 infection from other diseases with overlapping symptoms, which is significant for providing tailored treatment to patients and containing the outbreak. Here, we report a lab-on-a-chip biosensing platform for SARS-CoV-2 detection based on the subwavelength grating micro-ring resonator. The sensing surface is functionalized by specific antibody against SARS-CoV-2 spike protein, which could produce redshifts of resonant peaks by antigen-antibody combination, thus achieving quantitative detection. Additionally, the sensor chip is integrated with a microfluidic chip featuring an anti-backflow Y-shaped structure that enables the concurrent detection of two analytes. In this study, we realized the detection and differentiation of COVID-19 and influenza A H1N1. Experimental results indicate that the limit of detection of our device reaches 100 fg/ml (1.31 fM) within 15 min detecting time, and cross-reactivity tests manifest the specificity of the optical diagnostic assay. Furthermore, the integrated packaging and streamlined workflow facilitate its use for clinical applications. Thus, the biosensing platform presents a promising approach for attaining highly sensitive, selective, multiplexed, and quantitative point-of-care diagnosis and distinction between COVID-19 and influenza.

Application of Hybridization Chain Reaction/CRISPR-Cas12a for the Detection of SARS-CoV-2 Infection

Globally, the emergence of the coronavirus disease (COVID-19) has had a significant impact on life. The need for ongoing SARS-CoV-2 screening employing inexpensive and quick diagnostic approaches is undeniable, given the ongoing pandemic and variations in vaccine administration in resource-constrained regions. This study presents results as proof of concept to use hybridization chain reaction (HCR) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a complex for detecting SARS-CoV-2. HCR hairpin probes were designed using the NUPACK web-based program and further used to amplify the SARS-CoV-2 N gene in archived nasopharyngeal samples. The results were visualized using agarose gels and CRISPR Cas12a-based lateral flow strips. The assay was evaluated using the gold standard, real-time polymerase chain reaction (RT-PCR), as recommended by the World Health Organization (WHO). The results show the comparative efficiency of HCR to RT-PCR. This study shows that HCR and CRISPR are viable alternatives for diagnosing SARS-CoV-2 in samples.

Evaluation of the interaction between tumor growth factor-β and interferon type I pathways in patients with COVID-19: focusing on ages 1 to 90 years

BACKGROUND

Evidence revealed that age could affect immune responses in patients with the acute respiratory syndrome of coronavirus 2 (SARS-CoV-2) infection. This study investigated the impact of age on immune responses, especially on the interaction between the tumor growth factor-β (TGF-β) and interferon type-I (IFN-I) axes in the pathogenesis of novel coronavirus disease 2019 (COVID-19).

METHODS

This age-matched case-control investigation enrolled 41 COVID-19 patients and 40 healthy controls categorized into four groups, including group 1 (up to 20 years), group 2 (20-40 years), group 3 (40-60 years), and group 4 (over 60 years). Blood samples were collected at the time of admission. The expression of TGF-βRI, TGF-βRII, IFNARI, IFNARII, interferon regulatory factor 9 (IRF9), and SMAD family member 3 (SMAD3) was measured using the real-time PCR technique. In addition, serum levels of TGF-β, IFN-α, and SERPINE1 were measured by the enzyme-linked immunosorbent assay (ELISA) technique. All biomarkers were measured and analyzed in the four age studies groups.

RESULTS

The expression of TGF-βRI, TGF-βRII, IFNARI, IFNARII, IRF9, and SMAD3 was markedly upregulated in all age groups of patients compared with the matched control groups. Serum levels of IFN-α and SERPINE1 were significantly higher in patient groups than in control groups. While TGF-β serum levels were only significantly elevated in the 20 to 40 and over 60 years patient group than in matched control groups.

CONCLUSIONS

These data showed that the age of patients, at least at the time of admission, may not significantly affect TGF-β- and IFN-I-associated immune responses. However, it is possible that the severity of the disease affects these pathway-mediated responses, and more studies with a larger sample size are needed to verify it.

An insight overview on COVID-19 mRNA vaccines: Advantageous, pharmacology, mechanism of action, and prospective considerations

The worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has urged scientists to present some novel vaccine platforms during this pandemic to provide a rather prolonged immunity against this respiratory viral infection. In spite of many campaigns formed against the administration of mRNA-based vaccines, those platforms were the most novel types, which helped us meet the global demand by developing protection against COVID-19 and reducing the development of severe forms of this respiratory viral infection. Some societies are worry about the COVID-19 mRNA vaccine administration and the potential risk of genetic integration of inoculated mRNA into the human genome. Although the efficacy and long-term safety of mRNA vaccines have not yet been fully clarified, obviously their application has switched the mortality and morbidity of the COVID-19 pandemic. This study describes the structural features and technologies used in producing of COVID-19 mRNA-based vaccines as the most influential factor in controlling this pandemic and a successful pattern for planning to produce other kind of genetic vaccines against infections or cancers.

A Comparison of Etiology, Pathogenesis, Vaccinal and Antiviral Drug Development between Influenza and COVID-19

Influenza virus and coronavirus, two kinds of pathogens that exist widely in nature, are common emerging pathogens that cause respiratory tract infections in humans. In December 2019, a novel coronavirus SARS-CoV-2 emerged, causing a severe respiratory infection named COVID-19 in humans, and raising a global pandemic which has persisted in the world for almost three years. Influenza virus, a seasonally circulating respiratory pathogen, has caused four global pandemics in humans since 1918 by the emergence of novel variants. Studies have shown that there are certain similarities in transmission mode and pathogenesis between influenza and COVID-19, and vaccination and antiviral drugs are considered to have positive roles as well as several limitations in the prevention and control of both diseases. Comparative understandings would be helpful to the prevention and control of these diseases. Here, we review the study progress in the etiology, pathogenesis, vaccine and antiviral drug development for the two diseases.

A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the way to understanding any complex system in more approachable ways. We developed a logical and predictive model of DC function that integrates the heterogeneity of DCs population, APC function, and cell-cell interaction, spanning molecular to population levels. Our logical model consists of 281 components that connect environmental stimuli with various layers of the cell compartments, including the plasma membrane, cytoplasm, and nucleus to represent the dynamic processes within and outside the DC, such as signaling pathways and cell-cell interactions. We also provided three sample use cases to apply the model in the context of studying cell dynamics and disease environments. First, we characterized the DC response to Sars-CoV-2 and influenza co-infection by in-silico experiments and analyzed the activity level of 107 molecules that play a role in this co-infection. The second example presents simulations to predict the crosstalk between DCs and T cells in a cancer microenvironment. Finally, for the third example, we used the Kyoto Encyclopedia of Genes and Genomes enrichment analysis against the model's components to identify 45 diseases and 24 molecular pathways that the DC model can address. This study presents a resource to decode the complex dynamics underlying DC-derived APC communication and provides a platform for researchers to perform in-silico experiments on human DC for vaccine design, drug discovery, and immunotherapies.

SARS-CoV-2 versus Influenza A Virus: Characteristics and Co-Treatments

For three years, the novel coronavirus disease 2019 (COVID-19) pandemic, caused by infection of the SARS-CoV-2 virus, has completely changed our lifestyles and prepared us to live with this novel pneumonia for years to come. Given that pre-existing flu is caused by the influenza A virus, we have begun unprecedently co-coping with two different respiratory diseases at the same time. Hence, we draw a comparison between SARS-CoV-2 and influenza A virus based on the general characteristics, especially the main variants’ history and the distribution of the two viruses. SARS-CoV-2 appeared to mutate more frequently and independently of locations than the influenza A virus. Furthermore, we reviewed present clinical trials on combined management against COVID-19 and influenza in order to explore better solutions against both at the same time.

The Impact of LEP rs7799039 Polymorphism and Obesity on the Severity of Coronavirus Disease-19

BACKGROUND AND AIMS

SARS-CoV-2 infection has been recorded in 230 countries to date. Obesity has a negative impact on one's quality of life and is one of the main causes of mortality globally. Obesity affects the immune system, making the host more susceptible to infectious infections. Also, obesity commonly provokes the severity of respiratory diseases so the correlation of LEP rs7799039 Polymorphism in corpulent patients with COVID-19 infection was clearly investigated in the current study.

METHODS

A total of 232 patients were recruited, 116 patients were obese with COVID-19 infection, and 116 patients were non obese COVID-19. Fasting blood glucose test (FBG), hemoglobin A1C (HbA1C), complete blood count (CBC), international normalized ratio (INR), urea, alanine transaminase (ALT), aspartate aminotransferase (AST), D dimer and C-reactive protein (CRP) were estimated. C.T. scan was performed for each patient, and C.T. severity score was calculated. Genotyping for the leptin rs7799039 SNPs was performed by TaqMan^® (Applied Biosystems Step One ^TM Real-time PCR).

RESULTS

Regarding LEP polymorphism, all individuals of non-obese groups significantly had the homozygous allele GG (100%), whereas only 56% of obese groups had GG alleles (P = 0.001). The severity scores significantly (P = 0.001) varied regarding LEP polymorphism regarding Rs7799039, where the largest proportion of those with Grade IV had the homozygous allele AA (57.1%).

CONCLUSION

There was a correlation between the leptin gene allelic discrimination and COVID-19 CT brutality in obese patients. The A allele was considered a risk factor for severity in COVID-19 patients while the G allele contributes to decreasing that risk.

Global dynamics of IAV/SARS-CoV-2 coinfection model with eclipse phase and antibody immunity

Coronavirus disease 2019 (COVID-19) and influenza are two respiratory infectious diseases of high importance widely studied around the world. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while influenza is caused by one of the influenza viruses, A, B, C, and D. Influenza A virus (IAV) can infect a wide range of species. Studies have reported several cases of respiratory virus coinfection in hospitalized patients. IAV mimics the SARS-CoV-2 with respect to the seasonal occurrence, transmission routes, clinical manifestations and related immune responses. The present paper aimed to develop and investigate a mathematical model to study the within-host dynamics of IAV/SARS-CoV-2 coinfection with the eclipse (or latent) phase. The eclipse phase is the period of time that elapses between the viral entry into the target cell and the release of virions produced by that newly infected cell. The role of the immune system in controlling and clearing the coinfection is modeled. The model simulates the interaction between nine compartments, uninfected epithelial cells, latent/active SARS-CoV-2-infected cells, latent/active IAV-infected cells, free SARS-CoV-2 particles, free IAV particles, SARS-CoV-2-specific antibodies and IAV-specific antibodies. The regrowth and death of the uninfected epithelial cells are considered. We study the basic qualitative properties of the model, calculate all equilibria, and prove the global stability of all equilibria. The global stability of equilibria is established using the Lyapunov method. The theoretical findings are demonstrated via numerical simulations. The importance of considering the antibody immunity in the coinfection dynamics model is discussed. It is found that without modeling the antibody immunity, the case of IAV and SARS-CoV-2 coexistence will not occur. Further, we discuss the effect of IAV infection on the dynamics of SARS-CoV-2 single infection and vice versa.

Coronavirus diagnosis using cough sounds: Artificial intelligence approaches

Introduction

The Coronavirus disease 2019 (COVID-19) pandemic has caused irreparable damage to the world. In order to prevent the spread of pathogenicity, it is necessary to identify infected people for quarantine and treatment. The use of artificial intelligence and data mining approaches can lead to prevention and reduction of treatment costs. The purpose of this study is to create data mining models in order to diagnose people with the disease of COVID-19 through the sound of coughing.

Method

In this research, Supervised Learning classification algorithms have been used, which include Support Vector Machine (SVM), random forest, and Artificial Neural Networks, that based on the standard "Fully Connected" neural network, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) recurrent neural networks have been established. The data used in this research was from the online site sorfeh.com/sendcough/en, which has data collected during the spread of COVID-19.

Result

With the data we have collected (about 40,000 people) in different networks, we have reached acceptable accuracies.

Conclusion

These findings show the reliability of this method for using and developing a tool as a screening and early diagnosis of people with COVID-19. This method can also be used with simple artificial intelligence networks so that acceptable results can be expected. Based on the findings, the average accuracy was 83% and the best model was 95%.

Polymeric Materials as Indispensable Tools to Fight RNA Viruses: SARS-CoV-2 and Influenza A

Towards the end of 2019 in Wuhan, suspicions of a new dangerous virus circulating in the air began to arise. It was the start of the world pandemic coronavirus disease 2019 (COVID-19). Since then, considerable research data and review papers about this virus have been published. Hundreds of researchers have shared their work in order to achieve a better comprehension of this disease, all with the common goal of overcoming this pandemic. The coronavirus is structurally similar to influenza A. Both are RNA viruses and normally associated with comparable infection symptoms. In this review, different case studies targeting polymeric materials were appraised to highlight them as an indispensable tool to fight these RNA viruses. In particular, the main focus was how polymeric materials, and their versatile features could be applied in different stages of viral disease, i.e., in protection, detection and treatment.

Hamlet-Pattern-Based Automated COVID-19 and Influenza Detection Model Using Protein Sequences

SARS-CoV-2 and Influenza-A can present similar symptoms. Computer-aided diagnosis can help facilitate screening for the two conditions, and may be especially relevant and useful in the current COVID-19 pandemic because seasonal Influenza-A infection can still occur. We have developed a novel text-based classification model for discriminating between the two conditions using protein sequences of varying lengths. We downloaded viral protein sequences of SARS-CoV-2 and Influenza-A with varying lengths (all 100 or greater) from the NCBI database and randomly selected 16,901 SARS-CoV-2 and 19,523 Influenza-A sequences to form a two-class study dataset. We used a new feature extraction function based on a unique pattern, HamletPat, generated from the text of Shakespeare's Hamlet, and a signum function to extract local binary pattern-like bits from overlapping fixed-length (27) blocks of the protein sequences. The bits were converted to decimal map signals from which histograms were extracted and concatenated to form a final feature vector of length 1280. The iterative Chi-square function selected the 340 most discriminative features to feed to an SVM with a Gaussian kernel for classification. The model attained 99.92% and 99.87% classification accuracy rates using hold-out (75:25 split ratio) and five-fold cross-validations, respectively. The excellent performance of the lightweight, handcrafted HamletPat-based classification model suggests that it can be a valuable tool for screening protein sequences to discriminate between SARS-CoV-2 and Influenza-A infections.

Association of Clinical and Laboratory Findings in COVID-19 Patients with Thromboembolic Complications

Background: COVID-19 is associated with dangerous thromboembolic complications, such as stroke, heart attack, pulmonary embolism, and arterial and venous thromboembolism (VTE). Early diagnosis and even prediction of thromboembolic complications using biomarkers could facilitate the treatment and decrease the mortality rate. Objectives: This study evaluated and compared the clinical and laboratory findings of COVID-19 patients with thrombotic events with other COVID-19 patients. Methods: A total of 114 confirmed COVID-19 patients referred to Taleghani Hospital, Tehran, Iran, between February and September 2020 were included in this cross-sectional study. Those with a history of thromboembolic disease were excluded. The laboratory data, including the levels of lactate dehydrogenase (LDH), D-dimer, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and counts of lymphocyte and neutrophil, along with clinical findings (such as oxygen saturation and lung involvement percentage), were retrospectively collected from the patients’ clinical files. The incidence of thrombotic events was evaluated in patients. Results: The prevalence of thrombosis in the right and left main pulmonary arteries, right and left sub-segmental pulmonary arteries, and right and left deep veins was 2.7%, 3.5%, 7%, 7.9%, 4.4%, and 1.8% of all patients, respectively. The results showed that thromboembolic complications were significantly associated with mortality (P < 0.001). Besides, it was found that LDH (P < 0.001) and neutrophil (P = 0.002) levels in thromboembolic COVID-19 patients were respectively higher and lower than those without thromboembolic manifestations. Conclusions: High LDH and neutropenia might serve as biomarkers for thromboembolism in COVID-19 patients.

Comparison of Fragments in Human Hemostatic Proteins That Mimics Fragments in Proteins of A/H1N1 Viruses and Coronaviruses

Objective: To compare the repertoire of proteins of the human hemostatic system and fragments mimicking these proteins in the proteins of influenza A/H1N1 viruses and coronaviruses. Material and methods. Influenza viruses A/H1N1 (A/Brevig Mission/1/18), A/St. Petersburg /RII04/2016 (H1N1)pdm09, coronaviruses SARS-CoV and SARS-CoV-2 (strain Wuhan-Hu-1) were used for comparative computer analysis. The sources of the primary structures of proteins of the analyzed viruses and 41 proteins of the human hemostatic system were publicly available Internet databases, respectively, www.ncbi.nlm.nih.gov and www.nextprot.org. The search for homologous sequences in the structure of viral proteins and hemostatic proteins was carried out by comparing fragments of 12 amino acids in length, taking as related those that showed identity at ≥8 positions. Results. Comparative analysis of the repertoire of cellular proteins of the hemostatic system and fragments mimicking these proteins in the structure of proteins of viruses A/H1N1 1918, A(H1N1)pdm09 isolated in 2016, SARS-CoV and SARS-CoV-2, showed a significant difference between SARS-CoV-2 and analyzed viruses. In the protein structure of the SARS-CoV-2 virus, mimicry was revealed for almost all analyzed hemostasis proteins. As for the comparison of viruses A/H1N1 1918, A(H1N1)pdm09 2016 and SARS-CoV, the influenza virus A/H1N1 1918 and SARS-CoV are the closest in the repertoire of hemostatic proteins. Conclusion. Obtained bioinformatic analysis data can serve as a basis for further study of the role of homologous fragments in the regulation of hemostasis of the host organism.

Role of CCL2/CCR2 axis in the pathogenesis of COVID-19 and possible Treatments: All options on the Table

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is cause of the novel coronavirus disease (COVID-19). In the last two years, SARS-CoV-2 has infected millions of people worldwide with different waves, resulting in the death of many individuals. The evidence disclosed that the host immune responses to SARS-CoV-2 play a pivotal role in COVID-19 pathogenesis and clinical manifestations. In addition to inducing antiviral immune responses, SARS-CoV-2 can also cause dysregulated inflammatory responses characterized by the noticeable release of proinflammatory mediators in COVID-19 patients. Among these proinflammatory mediators, chemokines are considered a subset of cytokines that participate in the chemotaxis process to recruit immune and non-immune cells to the site of inflammation and infection. Researchers have demonstrated that monocyte chemoattractant protein-1 (MCP-1/CCL2) and its receptor (CCR2) are involved in the recruitment of monocytes and infiltration of these cells into the lungs of patients suffering from COVID-19. Moreover, elevated levels of CCL2 have been reported in the bronchoalveolar lavage fluid (BALF) obtained from patients with severe COVID-19, initiating cytokine storm and promoting CD163+ myeloid cells infiltration in the airways and further alveolar damage. Therefore, CCL2/CCR axis plays a key role in the immunopathogenesis of COVID-19 and targeted therapy of involved molecules in this axis can be a potential therapeutic approach for these patients. This review discusses the biology of the CCL2/CCR2 axis as well as the role of this axis in COVID-19 immunopathogenesis, along with therapeutic options aimed at inhibiting CCL2/CCR2 and modulating dysregulated inflammatory responses in patients with severe SARS-CoV-2 infection.

How the COVID 19 pandemic will shape influenza public health initiatives: The UK experience

Although caused by different pathogens, COVID-19 and influenza share many clinical features, as well as the potential for inflammatory, cardiovascular, and other long-term complications. During the 2020-2021 influenza season, COVID-19 mitigation efforts and a robust influenza vaccination campaign led to an unprecedented reduction in influenza cases. The lack of exposure to influenza, along with antigenic changes, may have reduced population immunity to influenza and set the stage for a high severity influenza season in 2021-2022. For the second consecutive season, the UK Department of Health and Social Care has expanded influenza vaccine eligibility to mitigate the impact of both COVID-19 and influenza. Continuation of clear policy decisions, as well as ongoing coordination between manufacturers, distributors, health authorities, and healthcare providers, is key to reducing the burden of influenza and COVID-19 and preventing large numbers of severe cases that can overwhelm the healthcare system.

Performance Evaluation of the Microfluidic Antigen LumiraDx SARS-CoV-2 and Flu A/B Test in Diagnosing COVID-19 and Influenza in Patients with Respiratory Symptoms

Introduction

Coronavirus disease 2019 (COVID-19) and influenza share similar symptoms, which hampers diagnosis. Given that they require different containment and treatment strategies, fast and accurate distinction between the two infections is needed. This study evaluates the sensitivity and specificity of the microfluidic antigen LumiraDx SARS-CoV-2 and Flu A/B Test for simultaneous detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/B from a single nasal swab.

Methods

Nasal samples were collected from patients as part of the ASPIRE (NCT04557046) and INSPIRE (NCT04288921) studies at point-of-care testing sites in the USA. ASPIRE study participants were included after developing COVID-19 symptoms in the last 14 days or following a positive SARS-CoV-2 test in the last 48 h. INSPIRE study participants were included after developing influenza symptoms in the last 4 days. Samples were extracted into proprietary buffer and analysed using the LumiraDx SARS-CoV-2 and Flu A/B Test. A reference sample was taken from each subject, placed into universal transport medium and tested using reference SARS-CoV-2 and influenza reverse transcription polymerase chain reaction (RT-PCR) tests. The test and reference samples were compared using the positive percent agreement (PPA) and negative percent agreement (NPA), together with their 95% confidence intervals (CIs).

Results

Analysis of the data from the ASPIRE (N = 124) and INSPIRE (N = 159) studies revealed high levels of agreement between the LumiraDx SARS-CoV-2 and Flu A/B Test and the reference tests in detecting SARS-CoV-2 (PPA = 95.5% [95% CI 84.9%, 98.7%]; NPA = 96.0% [95% CI 90.9%, 98.3%]), influenza A (PPA = 83.3% [95% CI 66.4%, 92.7%]; NPA = 97.7% [95% CI 93.4%, 99.2%]) and influenza B (PPA = 80.0% [95% CI 62.7%, 90.5%]; NPA = 95.3% [95% CI 90.2%, 97.9%]).

Conclusions

The LumiraDx SARS-CoV-2 and Flu A/B Test shows a high agreement with the reference RT-PCR tests while simultaneously detecting and differentiating between SARS-CoV-2 and influenza A/B.

Trial Registration

ClinicalTrials.gov identifiers NCT04557046 and NCT04288921.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40121-022-00696-8.

Dual-mode SERS-based lateral flow assay strips for simultaneous diagnosis of SARS-CoV-2 and influenza a virus

Since COVID-19 and flu have similar symptoms, they are difficult to distinguish without an accurate diagnosis. Therefore, it is critical to quickly and accurately determine which virus was infected and take appropriate treatments when a person has an infection. This study developed a dual-mode surface-enhanced Raman scattering (SERS)-based LFA strip that can diagnose SARS-CoV-2 and influenza A virus with high accuracy to reduce the false-negative problem of the commercial colorimetric LFA strip. Furthermore, using a single strip, it is feasible to detect SARS-CoV-2 and influenza A virus simultaneously. A clinical test was performed on 39 patient samples (28 SARS-CoV-2 positives, 6 influenza A virus positives, and 5 negatives), evaluating the clinical efficacy of the proposed dual-mode SERS-LFA strip. Our assay results for clinical samples show that the dual-mode LFA strip significantly reduced the false-negative rate for both SARS-CoV-2 and influenza A virus.

Clinical Characteristics, Outcomes and Prognostic Factors for Critical Illness in Hospitalized COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

BACKGROUND

A good understanding of the possible risk factors for coronavirus disease 19 (COVID-19) severity could help clinicians in identifying patients who need prioritized treatment to prevent disease progression and adverse outcome. In the present study, we aimed to correlate clinical and laboratory characteristics of hospitalized COVID-19 patients to disease outcome in Saudi Arabia.

MATERIALS AND METHODS

The present study included 199 COVID-19 patients admitted to King Fahd Specialist Hospital, Buraydah, Qassim, Saudi Arabia, from April to December 2020. Patients were followed-up until discharge either for recovery or death. Demographic data, clinical data and laboratory results were retrieved from electronic patient records.

RESULTS

Critical COVID-19 cases showed higher mean of age and higher prevalence of co-morbid conditions. Fifty-five patients died during the observation period. Risk factors for in hospital death for COVID 19 patients were leukocytosis (OR 1.89, 95% CI 1.008-3.548, p = 0.081), lymphocytopenia (OR 2.152, 95% CI 1.079-4.295, p = 0.020), neutrophilia (OR 1.839, 95% CI 0.951-3.55, p = 0.047), thrombocytopenia (OR 2.152, 95% CI 0.852-5.430, p = 0.085), liver injury (OR 2.689, 95% CI 1.373-4.944, p = 0.003), acute kidney injury (OR 1.248, 95% CI 0.631-2.467 p = 0.319), pancreatic injury (OR 1.973, 95% CI 0.939-4.144, p = 0.056) and high D dimer (OR 2.635, 95% CI 0.747-9.287, p = 0.091).

CONCLUSION

Clinical and laboratory data of COVID-19 patients may help understanding the pathogenesis of the disease and subsequently improve of the outcome of patients by determination of the associated risk factors and recognition of high risk group who are more liable for complications and in hospital death. The present study put an eye on some parameters (laboratory and clinical) that should be alarming signs that the patient is at high risk bad prognosis.

Post-COVID-19 Parkinsonism and Parkinson's Disease Pathogenesis: The Exosomal Cargo Hypothesis

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease after Alzheimer's disease, globally. Dopaminergic neuron degeneration in substantia nigra pars compacta and aggregation of misfolded alpha-synuclein are the PD hallmarks, accompanied by motor and non-motor symptoms. Several viruses have been linked to the appearance of a post-infection parkinsonian phenotype. Coronavirus disease 2019 (COVID-19), caused by emerging severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, has evolved from a novel pneumonia to a multifaceted syndrome with multiple clinical manifestations, among which neurological sequalae appear insidious and potentially long-lasting. Exosomes are extracellular nanovesicles bearing a complex cargo of active biomolecules and playing crucial roles in intercellular communication under pathophysiological conditions. Exosomes constitute a reliable route for misfolded protein transmission, contributing to PD pathogenesis and diagnosis. Herein, we summarize recent evidence suggesting that SARS-CoV-2 infection shares numerous clinical manifestations and inflammatory and molecular pathways with PD. We carry on hypothesizing that these similarities may be reflected in exosomal cargo modulated by the virus in correlation with disease severity. Travelling from the periphery to the brain, SARS-CoV-2-related exosomal cargo contains SARS-CoV-2 RNA, viral proteins, inflammatory mediators, and modified host proteins that could operate as promoters of neurodegenerative and neuroinflammatory cascades, potentially leading to a future parkinsonism and PD development.

Immunogenicity and safety of a SARS-CoV-2 inactivated vaccine (CoronaVac) co-administered with an inactivated quadrivalent influenza vaccine: A randomized, open-label, controlled study in healthy adults aged 18 to 59 years in China

BACKGROUND

Studies are needed for evidence of inactivated COVID-19 vaccine co-administered with influenza vaccine.

METHODS

A randomized, open-label, controlled study was conducted in Zhejiang Province, China. Eligible healthy adults aged 18-59 years underwent randomization at a ratio of 1:1:2 to receive inactivated quadrivalent influenza vaccine (IIV4) either concomitantly with the first (C1 subgroup) or the second (C2 subgroup) dose of CoronaVac, or 14 days after the first dose of CoronaVac (S group). The primary purpose of the study was to prove the non-inferiority in seroconversion rate of antibody against SARS-CoV-2.

RESULTS

Overall, 480 participants were enrolled, with 120, 120, and 240 randomly assigned to the C1, C2, and S groups, respectively. As lower bound of the two-sided 95% confidence interval (CI) of the difference for the seroconversion rate of antibodies against SARS-CoV-2 was over -10%, the immune response for CoronaVac in the C group (93.1% [89.0, 96.0]) was non-inferior to that in the S group (95.2% [91.5, 97.6]) in the per-protocol set. A lower GMT of antibody against SARS-CoV-2 was observed in the C group as compared to the S group (27.5 vs. 38.1, P = 0.0001). Decrease of immune response to CoronaVac was mainly observed in participants received IIV4 concomitantly with their second dose of CoronaVac (C2 subgroup), with a seroconversion rate of 89.7% (95CI: 82.6%-94.5%) and a GMT of 23.3. The occurrences of vaccine related adverse reactions were no more than 20% and comparable among different groups. Most of the adverse reactions were mild and moderate.

CONCLUSION

Co-administration of inactivated COVID-19 vaccine and seasonal influenza vaccine, especially the administration regimen that the seasonal influenza vaccine co-administered with the first dose of the inactivated COVID-19 vaccine, would be feasible.

Factors Affecting Perceived Effectiveness of Government Response towards COVID-19 Vaccination in Occidental Mindoro, Philippines

The COVID-19 pandemic has caused several developing countries to fall behind on vaccination at the onset of the pandemic, thus affecting the mobility of easing restrictions and lowering virus transmission. The current study integrated the Protection Motivation Theory (PMT) and extended the Theory of Planned Behavior (TPB) to evaluate factors affecting the perceived effectiveness of government response towards COVID-19 vaccination in Occidental Mindoro. A total of 400 respondents from the municipalities of Occidental Mindoro answered the online questionnaires, which contained 61 questions. This study outlined the relationship between the dependent and independent variables using structural equation modeling (SEM). The results indicated that knowledge of COVID-19 vaccination had significant direct effects on its perceived severity. Subjective standards had significant adverse effects on willingness to follow. In addition, perceived behavioral control was discovered to impact willingness to follow positively. It also showed that perceived government response was significantly affected by adaptive behavior and actual behavior regarding the perceived government response. Meanwhile, it was found that the perceived government response had significant effects on perceived effectiveness. The current study is one of the first to study the factors that affect the perceived effectiveness of government response toward COVID- 19 vaccination.

Type-I interferons in the immunopathogenesis and treatment of Coronavirus disease 2019

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), is currently the major global health problem. Still, it continues to infect people globally and up to the end of February 2022, over 436 million confirmed cases of COVID-19, including 5.95 million deaths, were reported to the world health organization (WHO). No specific treatment is currently available for COVID-19, and the discovery of effective therapeutics requires understanding the effective immunologic and immunopathologic mechanisms behind this infection. Type-I interferons (IFN-Is), as the critical elements of the immediate immune response against viral infections, can inhibit the replication and spread of the viruses. However, the available evidence shows that the antiviral IFN-I response is impaired in patients with the severe form of COVID-19. Moreover, the administration of exogenous IFN-I in different phases of the disease can lead to various outcomes. Therefore, understanding the role of IFN-I molecules in COVID-19 development and its severity can provide valuable information for better management of this disease. This review summarizes the role of IFN-Is in the pathogenesis of COIVD-19 and discusses the importance of autoantibodies against this cytokine in the spreading of SARS-CoV-2 and control of the subsequent excessive inflammation.

A Game of Infection - Song of Respiratory Viruses and Interferons

Humanity has experienced four major pandemics since the twentieth century, with the 1918 Spanish flu, the 2002 severe acute respiratory syndrome (SARS), the 2009 swine flu, and the 2019 coronavirus disease (COVID)-19 pandemics having the most important impact in human health. The 1918 Spanish flu caused unprecedented catastrophes in the recorded human history, with an estimated death toll between 50 - 100 million. While the 2002 SARS and 2009 swine flu pandemics caused approximately 780 and 280,000 deaths, respectively, the current COVID-19 pandemic has resulted in > 6 million deaths globally at the time of writing. COVID-19, instigated by the SARS - coronavirus-2 (SARS-CoV-2), causes unprecedented challenges in all facets of our lives, and never before brought scientists of all fields together to focus on this singular topic. While for the past 50 years research have been heavily focused on viruses themselves, we now understand that the host immune responses are just as important in determining the pathogenesis and outcomes of infection. Research in innate immune mechanisms is crucial in understanding all aspects of host antiviral programmes and the mechanisms underpinning virus-host interactions, which can be translated to the development of effective therapeutic avenues. This review summarizes what is known and what remains to be explored in the innate immune responses to influenza viruses and SARS-CoVs, and virus-host interactions in driving disease pathogenesis. This hopefully will encourage discussions and research on the unanswered questions, new paradigms, and antiviral strategies against these emerging infectious pathogens before the next pandemic occurs.

COVID-19-Associated Fungal Infections: An Urgent Need for Alternative Therapeutic Approach?

Secondary fungal infections may complicate the clinical course of patients affected by viral respiratory diseases, especially those admitted to intensive care unit. Hospitalized COVID-19 patients are at increased risk of fungal co-infections exacerbating the prognosis of disease due to misdiagnosis that often result in treatment failure and high mortality rate. COVID-19-associated fungal infections caused by predominantly Aspergillus and Candida species, and fungi of the order Mucorales have been reported from several countries to become significant challenge for healthcare system. Early diagnosis and adequate antifungal therapy is essential to improve clinical outcomes, however, drug resistance shows a rising trend highlighting the need for alternative therapeutic agents. The purpose of this review is to summarize the current knowledge on COVID-19-associated mycoses, treatment strategies and the most recent advancements in antifungal drug development focusing on peptides with antifungal activity.