A Comparative Systematic Review of COVID-19 and Influenza

Comparison of inflammatory markers, coagulation indicators and outcomes between influenza and COVID-19 infection amongst children: A systematic review and meta-analysis

Background

Influenza and COVID-19 patients share similar features and outcomes amongst adults. However, the difference between these diseases is not explored in paediatric age group especially in terms of inflammatory markers, coagulation profile and outcomes. Hence, we did this review to compare the inflammatory, coagulation features and outcomes between influenza and COVID-19 infected children.

Methods

Literature search was done in PubMed Central, Scopus, EMBASE, CINAHL, Cochrane library, Google Scholar & ScienceDirect from November 2019 to May 2022. Risk of bias assessment was done through Newcastle Ottawa scale. Meta-analysis was done using random-effects model and the final pooled estimate was reported as pooled odds ratio (OR) or standardized mean difference (SMD) along with 95 % confidence interval (CI) depending on the type of outcome.

Results

About 16 studies were included with most studies having higher risk of bias. Influenza paediatric patients had significantly higher erythrocyte sedimentation rate (ESR) (pooled SMD = 0.60; 95%CI: 0.30-0.91; I2 = 0 %), lactate dehydrogenase (LDH) (pooled SMD = 2.01; 95%CI: 0.37-3.66; I2 = 98.4 %) and prothrombin time (PT) (pooled SMD = 2.12; 95%CI: 0.44-3.80; I2 = 98.3 %) when compared to paediatric COVID-19 patients. There was no significant difference in terms of features like CRP, procalcitonin, serum albumin, aPTT, mortality and need for mechanical ventilation.

Conclusion

Inflammatory markers like ESR, LDH and PT was significantly higher in influenza patients when compared to COVID-19 in children, while rest of the markers and adverse clinical outcomes were similar between both the groups. Identification of these biomarkers has helped in understanding the distinctness of COVID-19 and influenza virus and develop better management strategies.

Investigating epidemiological distribution (temporality and intensity) of respiratory pathogens following COVID-19 de-escalation process in Catalonia, September 2016-June 2021: Analysis of regional surveillance data

BACKGROUND

Following the low incidence rates of non-SARS-CoV-2 respiratory viruses registered during the strict lockdown enforced in the pandemic, a resurgence of several endemic viruses in Catalonia (Spain) was noted during the early summer of 2021.

OBJECTIVES

In this study, we investigated whether the circulation of non-SARS-CoV-2 respiratory viruses in Catalonia, assessed by Microbiological Reporting System of Catalonia (MRSC) and the Epidemiological Surveillance Network of Catalonia, was affected by the strict lockdown measures, as well as, the implication of the Coronavirus Disease 19 (COVID-19) de-escalation process in the late season outbreaks registered during the 2020-2021 season.

STUDY DESIGN

A retrospective comparison of epidemic patterns in the respiratory viruses' incidence, using regional public health surveillance data from MRSC, was performed between weeks 26/2016 to week 27/2021. Data were expressed as the weekly total number of test positivity for individual viruses. A segmented negative binomial regression model was conducted, with two parameters included (level and trend) for each segment of the time series (2020 pre-lockdown, 2020 post-lockdown and 2021). Results were reported as a unit changed in the strict lockdown.

RESULTS

A total of 51588 confirmed cases of the different respiratory viruses were included in the analysis, the majority were influenza cases (63.7%). An immediate reduction in the weekly number of cases was observed in 2020 after the COVID-19 outbreak for human adenovirus virus (HAdV) (β2 = -2.606; P <0.01), human parainfluenza virus (HPIV) (β2 = -3.023; P <0.01), influenza virus (IFV) (β2 = -1.259; P <0.01), but not for respiratory syncytial virus (RSV), where the number of cases remained unchanged. During 2020, a significant negative trend was found for RSV (β3 = -0.170, P <0.01), and a positive trend for HAdV (β3 = 0.075, P <0.01). During 2021, a significant reduction in the weekly number of cases was also observed for all respiratory viruses, and a borderline non-significant reduction for HPIV (β3 = -0.027; P = 0.086). Moreover, significant positive trends were found for each viral pathogen, except for influenza during 2020-2021 season, where cases remained close to zero. The respiratory viruses increased activity and their late season epidemic start particularly affected children under 6 years old.

CONCLUSIONS

Our data not only provides evidence that occurrence of different respiratory virus infections was affected by the strict lockdown taken against SARS-CoV-2 but it also shows a late resurgence of seasonal respiratory viruses' cases during the 2020-2021 season following the relaxation of COVID-19-targeted non-pharmaceutical interventions.

Comparing COVID-19 and influenza: Epidemiology, clinical characteristics, outcomes and mortality in the ICU

RATIONALE

Several authors have compared COVID-19 infection with influenza in the ICU.

OBJECTIVE

This study aimed to compare the baseline clinical profiles, care procedures, and mortality outcomes of patients admitted to the intensive care unit, categorized by infection status (Influenza vs. COVID-19).

METHODS

Retrospective observational study. Data were extracted from the Toulouse University Hospital from March 2014 to March 2021. To compare survival curves, we plotted the survival at Day-90 using the Kaplan-Meier curve and conducted a log-rank test. Additionally, we performed propensity score matching to adjust for confounding factors between the COVID-19 and influenza groups. Furthermore, we use the CART model for multivariate analysis.

RESULTS

The study included 363 patients admitted to the ICU due to severe viral pneumonia: 152 patients (41.9 %) with influenza and 211 patients (58.1 %) with COVID-19. COVID-19 patients exhibited a higher prevalence of cardiovascular risk factors, whereas influenza patients had significantly higher severity scores (SOFA: 10 [6-12] vs. 6 [3-9], p<0.01 and SAPS II: 51 [35-67] vs. 37 [29-50], p<0.001). Overall mortality rates were comparable between the two groups (27.6 % (n = 42) in the influenza group vs. 21.8 % (n = 46) in the COVID-19 group, p=NS). Mechanical ventilation was more commonly employed in the influenza group (76.3 % (n = 116) vs. 59.7 % (n = 126), p<0.001); however, COVID-19 patients required longer durations of mechanical ventilation (18 [9-29] days vs. 13 [5-24] days, p<0.006) and longer hospital stays (23 [13-34] days vs. 18.5 [9-34.5] days, p = 0.009). The CART analysis revealed that the use of extra renal replacement therapy was the most influential prognostic factor in the influenza group, while the PaO2/FiO2-PEEP ratio played a significant role in the COVID-19 group.

CONCLUSIONS

Despite differences in clinical presentation and prognostic factors, the mortality rates at 90 days, after adjusting for confounding factors, were similar between COVID-19 and influenza patients.

Epidemiological, clinical and laboratory profile of patients presenting with severe acute respiratory syndrome (SARS-CoV-2) in Ethiopia

INTRODUCTION

Data regarding patients presenting with severe acute respiratory syndrome (SARS-CoV-2) illness have not adequately been documented which provides distinct insights into low-resource settings like Ethiopia. Thus, the study aimed to compare epidemiological, clinical and laboratory profiles of patients presenting with acute respiratory syndrome illness in Addis Ababa Ethiopia.

METHODS

We used a comparative cross-sectional study design among patients with SARS-CoV-2 illness at St. Paul's Hospital Millennium Medical College (SPHMMC), Addis Ababa, Ethiopia from October 2020 to September 2021. Using a structured questionnaire a consecutive sampling technique was applied to collect socio-demographic data. Additionally, nasal swabs were collected to confirm SARS-CoV-2 infection using a Real-Time Polymerase Chain Reaction. Blood samples were also collected from the participants for laboratory profiles (hematological tests like; white blood cell count, hematocrit, and platelet count; and biochemical and enzymatic tests like; aspartate transaminase (AST), creatinine, etc) analysis. Data were entered and analyzed using SPSS version 23.0 and p-values ≤0.05 were considered as statistically significant.

RESULTS

Of the total 413 participants presenting with SARS-CoV-2 illness, 250 (60.5%) participants tested positive for COVID-19 disease. COVID-19 patients were less likely to use an alcohol-based method of hand washing (12.5% vs 87.5%; p = 0.048). The COVID-19 patients had a higher proportion of headache (67.3% vs 32.7%, p = 0.001), sore throat (72.5% vs 27.5%, p = 0.001), and loss of sense of taste (74.4% vs 25.6%, p = 0.002). Patients with COVID-19 have significantly higher neutrophil than their counterparts (68.2% vs 31.8%; p = 0.001). Similarly, creatinine (64.9% vs 35.1%, p = 0.001) from renal function and alkaline phosphatase (66.8% vs 33.2%, p = 0.046) in the liver function tests were significantly higher in the COVID-19 patients.

CONCLUSION

Our findings suggest the need to substantially consider headache, sore throat, and loss of taste as potential clinical diagnostic symptoms for early screening and testing. Elevation of neutrophil, creatinine, alkaline phosphatase profiles are also used for potential diagnostic biomarkers in screening and testing suspected patients.

COVID-19

COVID-19, the illness caused by SARS-CoV-2, became a worldwide pandemic in 2020. Initial clinical manifestations range from asymptomatic infection to mild upper respiratory illness but may progress to pulmonary involvement with hypoxemia and, in some cases, multiorgan involvement, shock, and death. Older adults, pregnant persons, those with common comorbidities, and those with immunosuppression are at greatest risk for progression. Vaccination is effective in preventing symptomatic infection and reducing risk for severe disease, hospitalization, and death. Antiviral treatment and immunomodulators have been shown to benefit certain patients. This article summarizes current recommendations on prevention, diagnosis, management, and treatment of COVID-19.

Bibliometric analysis of publication trends and topics of influenza-related encephalopathy from 2000 to 2022

BACKGROUND

Influenza-related encephalopathy is a rapidly progressive encephalopathy that usually presents during the early phase of influenza infection and primarily manifests as central nervous system dysfunction. This study aimed to analyze the current research status and hotspots of influenza-related encephalopathy since 2000 through bibliometrics analysis.

METHODS

The Web of Science Core Collection (WOSCC) was used to extract global papers on influenza-related encephalopathy from 2000 to 2022. Meanwhile, the VOSviewer and CiteSpace software were used for data processing and result visualization.

RESULTS

A total of 561 published articles were included in the study. Japan was the country that published the most articles, with 205 articles, followed by the United States and China. Okayama University and Tokyo Medical University published the most articles, followed by Nagoya University, Tokyo University, and Juntendo University. Based on the analysis of keywords, four clusters with different research directions were identified: "Prevalence of H1N1 virus and the occurrence of neurological complications in different age groups," "mechanism of brain and central nervous system response after influenza virus infection," "various acute encephalopathy" and "diagnostic indicators of influenza-related encephalopathy."

CONCLUSIONS

The research progress, hotspots, and frontiers on influenza-related encephalopathy after 2000 were described through the visualization of bibliometrics. The findings will lay the groundwork for future studies and provide a reference for influenza-related encephalopathy. Research on influenza-related encephalopathy is basically at a stable stage, and the number of research results is related to outbreaks of the influenza virus.

A mathematical model for the co-dynamics of COVID-19 and tuberculosis

In this study, we formulated and analyzed a deterministic mathematical model for the co-infection of COVID-19 and tuberculosis, to study the co-dynamics and impact of each disease in a given population. Using each disease's corresponding reproduction number, the existence and stability of the disease-free equilibrium were established. When the respective threshold quantities R C , and R T are below unity, the COVID-19 and TB-free equilibrium are said to be locally asymptotically stable. The impact of vaccine (i.e., efficacy and vaccinated proportion) and the condition required for COVID-19 eradication was examined. Furthermore, the presence of the endemic equilibria of the sub-models is analyzed and the criteria for the phenomenon of backward bifurcation of the COVID-19 sub-model are presented. To better understand how each disease condition impacts the dynamics behavior of the other, we investigate the invasion criterion of each disease by computing the threshold quantity known as the invasion reproduction number. We perform a numerical simulation to investigate the impact of threshold quantities ( R C , R T ) with respect to their invasion reproduction number, co-infection transmission rate ( β c t ) , and each disease transmission rate ( β c , β t ) on disease dynamics. The outcomes established the necessity for the coexistence or elimination of both diseases from the communities. Overall, our findings imply that while COVID-19 incidence decreases with co-infection prevalence, the burden of tuberculosis on the human population increases.

Next-Generation Vaccines Against COVID-19 Variants: Beyond the Spike Protein

Vaccines are among the most effective medical countermeasures against infectious diseases. The current Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spurred the scientific strategies to fight against the disease. Since 2020, a great number of vaccines based on different platforms have been in development in response to the pandemic, among which mRNA, adenoviral vector, and subunit vaccines have been clinically approved for use in humans. These first-generation COVID-19 vaccines largely target the viral spike (S) protein and aim for eliciting potent neutralizing antibodies. With the emergence of SARS-CoV-2 variants, especially the highly transmissible Omicron strains, the S-based vaccine strategies have been faced constant challenges due to strong immune escape by the variants. The coronavirus nucleocapsid (N) is one of the viral proteins that induces strong T-cell immunity and is more conserved across different SARS-CoV-2 variants. Inclusion of N in the development of COVID-19 vaccines has been reported. Here, we briefly reviewed and discussed COVID-19 disease, current S-based vaccine strategies, and focused on the immunobiology of N protein in SARS-CoV-2 host immunity, as well as the next-generation vaccine strategies involving N protein, to combat current and emerging SARS-CoV-2 variants.

Electrochemical Capillary Driven Immunoassay for Detection of SARS-CoV-2

The COVID-19 pandemic focused attention on a pressing need for fast, accurate, and low-cost diagnostic tests. This work presents an electrochemical capillary driven immunoassay (eCaDI) developed to detect SARS-CoV-2 nucleocapsid (N) protein. The low-cost flow device is made of polyethylene terephthalate (PET) and adhesive films. Upon addition of a sample, reagents and washes are sequentially delivered to an integrated screen-printed carbon electrode for detection, thus automating a full sandwich immunoassay with a single end-user step. The modified electrodes are sensitive and selective for SARS-CoV-2 N protein and stable for over 7 weeks. The eCaDI was tested with influenza A and Sindbis virus and proved to be selective. The eCaDI was also successfully applied to detect nine different SARS-CoV-2 variants, including Omicron.

Is there a diurnal variation of COVID-19 patients warranting presentation to the health centre? A chronobiological observational cross-sectional study

BACKGROUND

The circadian clock regulates the function of the immune system, the replication of viruses, and the magnitude of infections. The aim of this study was to analyse whether hospital attendance in Coronavirus disease 2019 (COVID-19) patients presents a diurnal variation.

METHODS

Data from the electronic medical records of 1094 COVID-19 patients who presented to a Health Centre in Qatar during the month of July 2020 was retrospectively analysed. The following demographic (i.e. time of day (TOD), sex, age), clinical (i.e. cycle threshold (CT), temperature, oxy-haemoglobin saturation and resting heart-rate), biochemical (i.e. uraemia, glycaemia and albuminia) and haematological (i.e. leukocytes, erythrocytes ad platelets) parameters were collected.

RESULTS

Univariate analysis showed a significant effect of TOD on hospital admission (p < 0.001), with patients attending the health care centre more during the active behavioural phase (08h00-00h00) compared to the resting phase (00h00-08h00). COVID-19 infection blunted the circadian rhythms of core body temperature, neutrophils and leukocytes family and shifted the circadian rhythms of resting heart-rate and uraemia. Correlation analysis showed a near perfect negative correlation between the age of patients and the TOD (r=-0.97), with older patients attending the care centre earlier during the day.

CONCLUSION

COVID-19 infection affected the circadian rhythms of the host through disrupting the circadian rhythms of core temperature and innate immunity mediators. Old patients attend the health care centre earlier compared to younger ones. However, CT during polymerase chain reaction-test was unaffected by the TOD, which limits the conclusion that COVID-19 viral infection exhibits diurnal variation.

Nonlinear optimal control strategies for a mathematical model of COVID-19 and influenza co-infection

Infectious diseases have remained one of humanity's biggest problems for decades. Multiple disease infections, in particular, have been shown to increase the difficulty of diagnosing and treating infected people, resulting in worsening human health. For example, the presence of influenza in the population is exacerbating the ongoing COVID-19 pandemic. We formulate and analyze a deterministic mathematical model that incorporates the biological dynamics of COVID-19 and influenza to effectively investigate the co-dynamics of the two diseases in the public. The existence and stability of the disease-free equilibrium of COVID-19-only and influenza-only sub-models are established by using their respective threshold quantities. The result shows that the COVID-19 free equilibrium is locally asymptotically stable when R C < 1 , whereas the influenza-only model, is locally asymptotically stable when R F < 1 . Furthermore, the existence of the endemic equilibria of the sub-models is examined while the conditions for the phenomenon of backward bifurcation are presented. A generalized analytical result of the COVID-19-influenza co-infection model is presented. We run a numerical simulation on the model without optimal control to see how competitive outcomes between-hosts and within-hosts affect disease co-dynamics. The findings established that disease competitive dynamics in the population are determined by transmission probabilities and threshold quantities. To obtain the optimal control problem, we extend the formulated model by including three time-dependent control functions. The maximum principle of Pontryagin was used to prove the existence of the optimal control problem and to derive the necessary conditions for optimum disease control. A numerical simulation was performed to demonstrate the impact of different combinations of control strategies on the infected population. The findings show that, while single and twofold control interventions can be used to reduce disease, the threefold control intervention, which incorporates all three controls, will be the most effective in reducing COVID-19 and influenza in the population.

Clinical progress in MSC-based therapies for the management of severe COVID-19

Considering the high impact that severe Coronavirus disease 2019 (COVID-19) cases still pose on public health and their complex pharmacological management, the search for new therapeutic alternatives is essential. Mesenchymal stromal cells (MSCs) could be promising candidates as they present important immunomodulatory and anti-inflammatory properties that can combat the acute severe respiratory distress syndrome (ARDS) and the cytokine storm occurring in COVID-19, two processes that are mainly driven by an immunological misbalance. In this review, we provide a comprehensive overview of the intricate inflammatory process derived from the immune dysregulation that occurs in COVID-19, discussing the potential that the cytokines and growth factors that constitute the MSC-derived secretome present to treat the disease. Moreover, we revise the latest clinical progress made in the field, discussing the most important findings of the clinical trials conducted to date, which follow 2 different approaches: MSC-based cell therapy or the administration of the secretome by itself, as a cell-free therapy.

Clinical and Epidemiological Presentation of COVID-19 among Children in Conflict Setting

Background: This study aims to describe the observable symptoms of children with COVID-19 infection and analyze access to real-time polymerase chain reaction (RT-PCR) testing among children seeking care in Yemen. Method: In the period of March 2020−February 2022, data were obtained from 495 children suspected to have been infected with COVID-19 (from a larger register of 5634 patients) from the Diseases Surveillance and Infection Control Department at the Ministry of Public Health and Population in Aden, Yemen. Results: Overall, 21.4% of the children with confirmed COVID-19 infection were asymptomatic. Fever (71.4%) and cough (67.1%) were the most frequently reported symptoms among children, and children were less likely to have fever (p < 0.001), sore throat (p < 0.001) and cough (p < 0.001) compared to adults. A lower frequency of COVID-19-associated symptoms was reported among children with positive RT-PCR tests compared to children with negative tests. A lower rate of testing was conducted among children (25%) compared to adults (61%). Fewer tests were carried out among children <5 years (11%) compared to other age groups (p < 0.001), for children from other nationalities (4%) compared to Yemeni children (p < 0.001) and for girls (21%) compared to boys (30%) (p < 0.031). Conclusion: Understanding and addressing the cause of these disparities and improving guidelines for COVID-19 screening among children will improve access to care and control of the COVID-19 pandemic.

Comparison of laboratory parameters, clinical symptoms and clinical outcomes of COVID-19 and influenza in pediatric patients: A systematic review and meta-analysis

BACKGROUND

New and more severe clinical manifestations associated with the coronavirus disease 2019 (COVID-19) are emerging constantly in the pediatric age group. Patients in this age group are also primary carriers of the influenza virus and are at a higher risk of developing severe infection. However, studies comparing influenza and COVID-19 to show which condition causes a more severe form of disease amongst the pediatric age group are scarce.

AIM

To compare the laboratory results, clinical symptoms and clinical outcomes in pediatric patients with COVID-19 and influenza.

METHODS

A systematic and comprehensive search was carried out in databases and search engines, including EMBASE, Cochrane, MEDLINE, ScienceDirect and Google Scholar from 1964 until January 2022. A meta-analysis was carried out using a random-effects model and pooled odds ratio (OR) or standardized mean difference (SMD) and 95%CI.

RESULTS

A total of 16 studies satisfied the inclusion criteria. Pediatric COVID-19 patients had a significantly reduced risk of cough (pooled OR = 0.16; 95%CI: 0.09 to 0.27), fever (pooled OR = 0.23; 95%CI: 0.12 to 0.43), and dyspnea (pooled OR = 0.54; 95%CI: 0.33 to 0.88) compared to influenza patients. Furthermore, total hemoglobin levels (pooled SMD = 1.22; 95%CI: 0.29 to 2.14) in COVID-19 patients were significantly higher as compared to pediatric influenza patients. There was no significant difference in symptoms such as sore throat, white blood cell count, platelets, neutrophil and lymphocytes levels, and outcomes like mortality, intensive care unit admission, mechanical ventilation or length of hospital stay.

CONCLUSION

COVID-19 is associated with a significantly lower rate of clinical symptoms and abnormal laboratory indexes compared to influenza in the pediatric age group. However, further longitudinal studies of the outcomes between influenza and COVID-19 pediatric patients are needed.

The impact of COVID-19 on a Malaria dominated region: A mathematical analysis and simulations

One of society’s major concerns that have continued for a long time is infectious diseases. It has been demonstrated that certain disease infections, in particular multiple disease infections, make it more challenging to identify and treat infected individuals, thus deteriorating human health. As a result, a COVID-19-malaria co-infection model is developed and analyzed to study the effects of threshold quantities and co-infection transmission rate on the two diseases’ synergistic relationship. This allowed us to better understand the co-dynamics of the two diseases in the population. The existence and stability of the disease-free equilibrium of each single infection were first investigated by using their respective reproduction number. The COVID-19 and malaria-free equilibrium are locally asymptotically stable when the individual threshold quantities RC and RM are below unity. Additionally, the occurrence of the malaria prevalent equilibrium is examined, and the requirements for the backward bifurcation’s existence are provided. Sensitivity analysis reveals that the two main parameters that influence the spread of COVID-19 infection are the disease transmission rate (βc) and the fraction of the exposed individuals becoming symptomatic (ψ), while malaria transmission is influenced by the abundance of vector population, which is driven by recruitment rate (πv) with an increase in the effective biting rate (b), probability of malaria transmission per mosquito bite (βm), and probability of malaria transmission from infected humans to vectors (βv). The findings from the numerical simulation of the model show that COVID-19 will predominate in the populace and drives malaria to extinction when RM<1<RC, whereas malaria will dominate in the population and drives COVID-19 into extinction when RC<1<RM. At the disease’s endemic equilibrium, the two diseases will coexist with the one with the highest reproduction number predominating but not eradicating the other. It was demonstrated in particular that COVID-19 will invade a population where malaria is endemic if the invasion reproduction number exceeds unity. The findings also demonstrate that when the two diseases are at endemic equilibrium, the prevalence of co-infection increases COVID-19’s burden on the population while decreasing malaria incidence.

Influenza and COVID-19 Co-infection

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A Low-Cost Handheld Impedimetric Biosensing System for Rapid Diagnostics of SARS-CoV-2 Infections

Current laboratory diagnostic approaches for virus detection give reliable results, but they require a lengthy procedure, trained personnel, and expensive equipment and reagents; hence, they are not a suitable choice for home monitoring purposes. This paper addresses this challenge by developing a portable impedimetric biosensing system for the identification of COVID-19 patients. This sensing system has two main parts: a throwaway two-working electrode (2-WE) strip and a novel read-out circuit, specifically designed for simultaneous signal acquisition from both working electrodes. Highly reliable electrochemical signal tracking from multiplex immunosensors provides a potential for flexible and portable multi-biomarker detection. The electrodes' surfaces were functionalized with SARS-CoV-2 Nucleocapsid Antibody enabling the selective detection of Nucleocapsid protein (N-protein) along with self-validation in the clinical nasopharyngeal swab specimens. The proposed programmable highly sensitive impedance read-out system allows for a wide dynamic detection range, which makes the sensor capable of detecting N-protein concentrations between 0.116 and 10,000 pg/mL. This lightweight and economical read-out arrangement is an ideal prospect for being mass-produced, especially during urgent pandemic situations. Also, such an impedimetric sensing platform has the potential to be redesigned for targeting not only other infectious diseases but also other critical disorders.

Differential diagnosis of COVID-19 and influenza

This study uses two existing data sources to examine how patients' symptoms can be used to differentiate COVID-19 from other respiratory diseases. One dataset consisted of 839,288 laboratory-confirmed, symptomatic, COVID-19 positive cases reported to the Centers for Disease Control and Prevention (CDC) from March 1, 2019, to September 30, 2020. The second dataset provided the controls and included 1,814 laboratory-confirmed influenza positive, symptomatic cases, and 812 cases with symptomatic influenza-like-illnesses. The controls were reported to the Influenza Research Database of the National Institute of Allergy and Infectious Diseases (NIAID) between January 1, 2000, and December 30, 2018. Data were analyzed using case-control study design. The comparisons were done using 45 scenarios, with each scenario making different assumptions regarding prevalence of COVID-19 (2%, 4%, and 6%), influenza (0.01%, 3%, 6%, 9%, 12%) and influenza-like-illnesses (1%, 3.5% and 7%). For each scenario, a logistic regression model was used to predict COVID-19 from 2 demographic variables (age, gender) and 10 symptoms (cough, fever, chills, diarrhea, nausea and vomiting, shortness of breath, runny nose, sore throat, myalgia, and headache). The 5-fold cross-validated Area under the Receiver Operating Curves (AROC) was used to report the accuracy of these regression models. The value of various symptoms in differentiating COVID-19 from influenza depended on a variety of factors, including (1) prevalence of pathogens that cause COVID-19, influenza, and influenza-like-illness; (2) age of the patient, and (3) presence of other symptoms. The model that relied on 5-way combination of symptoms and demographic variables, age and gender, had a cross-validated AROC of 90%, suggesting that it could accurately differentiate influenza from COVID-19. This model, however, is too complex to be used in clinical practice without relying on computer-based decision aid. Study results encourage development of web-based, stand-alone, artificial Intelligence model that can interview patients and help clinicians make quarantine and triage decisions.

Comparison of clinical characteristics and outcomes of hospitalized patients with seasonal coronavirus infection and COVID-19: a retrospective cohort study

BACKGROUND

Unlike SARS-CoV and MERS-C0V, SARS-CoV-2 has the potential to become a recurrent seasonal infection; hence, it is essential to compare the clinical spectrum of COVID-19 to the existent endemic coronaviruses. We conducted a retrospective cohort study of hospitalized patients with seasonal coronavirus (sCoV) infection and COVID-19 to compare their clinical characteristics and outcomes.

METHODS

A total of 190 patients hospitalized with any documented respiratory tract infection and a positive respiratory viral panel for sCoV from January 1, 2011, to March 31, 2020, were included. Those patients were compared with 190 hospitalized adult patients with molecularly confirmed symptomatic COVID-19 admitted from March 1, 2020, to May 25, 2020.

RESULTS

Among 190 patients with sCoV infection, the Human Coronavirus-OC93 was the most common coronavirus with 47.4% of the cases. When comparing demographics and baseline characteristics, both groups were of similar age (sCoV: 74 years vs. COVID-19: 69 years) and presented similar proportions of two or more comorbidities (sCoV: 85.8% vs. COVID-19: 81.6%). More patients with COVID-19 presented with severe disease (78.4% vs. 67.9%), sepsis (36.3% vs. 20.5%), and developed ARDS (15.8% vs. 2.6%) compared to patients with sCoV infection. Patients with COVID-19 had an almost fourfold increased risk of in-hospital death than patients with sCoV infection (OR 3.86, CI 1.99-7.49; p < .001).

CONCLUSION

Hospitalized patients with COVID-19 had similar demographics and baseline characteristics to hospitalized patients with sCoV infection; however, patients with COVID-19 presented with higher disease severity, had a higher case-fatality rate, and increased risk of death than patients with sCoV. Clinical findings alone may not help confirm or exclude the diagnosis of COVID-19 during high acute respiratory illness seasons. The respiratory multiplex panel by PCR that includes SARS-CoV-2 in conjunction with local epidemiological data may be a valuable tool to assist clinicians with management decisions.

The host response in different aetiologies of community-acquired pneumonia

BACKGROUND

Community-acquired pneumonia (CAP) can be caused by a variety of pathogens, of which Streptococcus pneumoniae, Influenza and currently SARS-CoV-2 are the most common. We sought to identify shared and pathogen-specific host response features by directly comparing different aetiologies of CAP.

METHODS

We measured 72 plasma biomarkers in a cohort of 265 patients hospitalized for CAP, all sampled within 48 hours of admission, and 28 age-and sex matched non-infectious controls. We stratified the biomarkers into several pathophysiological domains- antiviral response, vascular response and function, coagulation, systemic inflammation, and immune checkpoint markers. We directly compared CAP caused by SARS-CoV-2 (COVID-19, n=39), Streptococcus pneumoniae (CAP-strep, n=27), Influenza (CAP-flu, n=22) and other or unknown pathogens (CAP-other, n=177). We adjusted the comparisons for age, sex and disease severity scores.

FINDINGS

Biomarkers reflective of a stronger cell-mediated antiviral response clearly separated COVID-19 from other CAPs (most notably granzyme B). Biomarkers reflecting activation and function of the vasculature showed endothelial barrier integrity was least affected in COVID-19, while glycocalyx degradation and angiogenesis were enhanced relative to other CAPs. Notably, markers of coagulation activation, including D-dimer, were not different between the CAP groups. Ferritin was most increased in COVID-19, while other systemic inflammation biomarkers such as IL-6 and procalcitonin were highest in CAP-strep. Immune checkpoint markers showed distinctive patterns in viral and non-viral CAP, with highly elevated levels of Galectin-9 in COVID-19.

INTERPRETATION

Our investigation provides insight into shared and distinct pathophysiological mechanisms in different aetiologies of CAP, which may help guide new pathogen-specific therapeutic strategies.

FUNDING

This study was financially supported by the Dutch Research Council, the European Commission and the Netherlands Organization for Health Research and Development.

Influenza is More Severe than Our Newest Enemy (COVID-19) in Hospitalized Children: Experience from a Tertiary Center

Understanding differences in terms of clinical phenotypes and outcomes of coronavirus disease 2019 (COVID‐19) compared with influenza is vital to optimizing the management of patients and planning healthcare. Herein, we aimed to investigate the clinical differences and outcomes in hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and influenza. We performed a retrospective study of hospitalized children who were positive for SARS‐CoV‐2 between March 2020 and March 2021 and for influenza between January 2016 and February 2020 in respiratory samples. The primary outcome of this study was pediatric intensive care unit (PICU) admission, and the secondary outcome was the need for respiratory support. A total of 74 patients with influenza and 71 who were positive for SARS‐CoV‐2 were included. The distribution among the sexes was similar, but patients with COVID‐19 were older than patients with influenza (96 vs. 12, p < 0.001). In terms of underlying chronic diseases, the frequency was 26.7% in the COVID‐19 group and 54% in the influenza group (p = 0.001). The comparison of symptoms revealed that fatigue, headache, nausea, vomiting, and abdominal pain occurred more frequently with COVID‐19 (for all p < 0.05) and runny nose with influenza (p = 0.002). The frequency of admission to the PICU was relatively higher (18.9%) in the influenza group than with COVID‐19 (2.8%) with a significant ratio (p = 0.001), secondary bacterial infections were observed more frequently in the influenza group (20.2% vs. 4.2%, p = 0.003). Some 88.7% of patients with COVID‐19 did not need respiratory support, whereas 59.4% of patients with influenza did require respiratory support (p < 0.001). This study noted that influenza caused more frequent admissions to the PICU and a greater need for respiratory support in hospitalized pediatric patients than COVID‐19.

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Background

Descriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to enhance the understanding of people of this disease.

Methods

In this retrospective cohort study, a total of 1,067 COVID-19 cases were enrolled. Symptom clustering patterns were first explored by a text clustering method. Then, a multinomial logistic regression was applied to reveal the population characteristics of different symptom groups. In addition, time intervals between symptoms onset and the first visit were analyzed to consider the effect of time interval extension on the progression of symptoms.

Results

Based on text clustering, the symptoms were summarized into four groups. Group 1: no-obvious symptoms; Group 2: mainly fever and/or dry cough; Group 3: mainly upper respiratory tract infection symptoms; Group 4: mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms. Apart from Group 1 with no obvious symptoms, the most frequent symptom combinations were fever only (64 cases, 47.8%), followed by dry cough only (42 cases, 31.3%) in Group 2; expectoration only (21 cases, 19.8%), followed by expectoration complicated with fever (10 cases, 9.4%) in Group 3; fatigue complicated with fever (12 cases, 4.2%), followed by headache complicated with fever was also high (11 cases, 3.8%) in Group 4. People aged 45–64 years were more likely to have symptoms of Group 4 than those aged 65 years or older (odds ratio [OR] = 2.66, 95% CI: 1.21–5.85) and at the same time had longer time intervals.

Conclusions

Symptoms of COVID-19 could be divided into four clustering groups with different symptom combinations. The Group 4 symptoms (i.e., mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms) happened more frequently in COVID-19 than in influenza. This distinction could help deepen the understanding of this disease. The middle-aged people have a longer time interval for medical visit and was a group that deserve more attention, from the perspective of medical delays.

Influenza

Seasonal influenza epidemics of variable severity pose challenges to public health. Annual vaccination is the primary way to prevent influenza, and a wide range of vaccines are available, including inactivated or live attenuated standard-dose, recombinant vaccines, as well as adjuvanted or high-dose vaccines for persons aged 65 years or older. Persons at increased risk for influenza complications include young children, persons with underlying medical conditions, and older adults. Prompt diagnosis of influenza can facilitate early initiation of antiviral treatment that provides the greatest clinical benefit. This article summarizes recommendations for providers on influenza vaccination, diagnostic testing, and antiviral treatment.

[COVID-19: neurological manifestations-update : What we know so far]

Beyond pulmonary presentation, COVID-19 infection can manifest with a variety of both acute and chronic neurologic and neuropsychiatric (concomitant) symptoms and diseases. Nonspecific symptoms such as headache, fatigue, olfactory and gustatory disturbance have been reported more frequently, and severe disease such as encephalopathy, encephalitis, and cerebrovascular events have been reported relatively rarely. The heterogeneity of neurologic and neuropsychiatric presentations is large, as well as the range of recorded prevalences. Older patients, pre-existing neurologic and non neurologic comorbidities and severe COVID-19 disease were associated with increased risk of severe neurologic complications and higher in-hospital mortality. Probable neurotropic pathomechanisms of SARS-CoV‑2 have been discussed, but a multifactorial genesis of neurologic/neuropsychiatric symptoms and disease beyond these is likely.