A Pathology-based Case Series of Influenza- and COVID-19-associated Pulmonary Aspergillosis: The Proof Is in the Tissue.

RATIONALE: Invasive pulmonary aspergillosis has emerged as a frequent coinfection in severe COVID-19, similarly to influenza; yet the clinical invasiveness is more debated. OBJECTIVES: We investigated the invasive nature of pulmonary aspergillosis in histology specimens of influenza and COVID-19 intensive care unit (ICU) fatalities in a tertiary care center. METHODS: In this monocentric, descriptive, retrospective case series we included adult ICU patients with PCR-proven influenza/COVID-19 respiratory failure that underwent postmortem examination and/or tracheobronchial biopsy during ICU admission from September 2009 until June 2021. Diagnosis of probable/proven viral-associated pulmonary aspergillosis (VAPA) was made based on the ICM-IAPA and ECMM/ISHAM-CAPA consensus criteria. All respiratory tissues were independently reviewed by two experienced pathologists. MEASUREMENTS AND MAIN RESULTS: In the 44 patients of the autopsy-verified cohort, 6 proven influenza-associated and 6 proven COVID-19-associated pulmonary aspergillosis diagnoses were identified. Fungal disease was identified as missed-diagnosis upon autopsy in 8% of proven cases (n=1/12), yet most frequently found as confirmation of probable antemortem diagnosis (n=11/21, 52%) despite receiving antifungal treatment. Bronchoalveolar lavage galactomannan testing showed highest sensitivity for VAPA diagnosis. Among both viral entities, an impeded fungal growth was the predominant histologic pattern of pulmonary aspergillosis. Fungal tracheobronchitis was histologically indistinguishable in influenza (n=3) and COVID-19 (n=3) cases, yet macroscopically more extensive at bronchoscopy in influenza setting. CONCLUSIONS: Proven invasive pulmonary aspergillosis diagnosis was found regularly and with a similar histological pattern in influenza and in COVID-19 ICU case-fatalities. Our findings highlight an important need for VAPA awareness with an emphasis on mycological bronchoscopic work-up. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

'Most children's hospitals are struggling'...John Nickens

The article focuses on the challenges facing children's hospitals in the U.S. Topics discussed include the problem on shortage in medical professionals at these hospitals, events that have affected children's hospitals in the country, an increase in the number of child patients in the emergency room, and the conversion of hospital rooms to navigate capacity issues.

Comparing antibiotic prescriptions in primary care between SARS-CoV-2 and influenza: a retrospective observational study.

BACKGROUND: Antibiotics are frequently prescribed during viral respiratory infection episodes in primary care. There is limited information about antibiotic prescription during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in primary care and its association with risk factors for an adverse course. AIM: To compare the proportion of antibiotic prescriptions between patients with COVID-19 and influenza or influenza-like symptoms, and to assess the association between antibiotic prescriptions and risk factors for an adverse course of COVID-19. DESIGN & SETTING: An observational cohort study using pseudonymised and coded routine healthcare data extracted from 85 primary care practices in the Netherlands. METHOD: Adult patients with influenza and influenza-like symptoms were included from the 2017 influenza season to the 2020 season. Adult patients with suspected or confirmed COVID-19 were included from the first (15 February 2020-1 August 2020) and second (1 August 2020-1 January 2021) SARS-CoV-2 waves. Proportions of antibiotic prescriptions were calculated for influenza and COVID-19 patients. Odds ratios (ORs) were used to compare the associations of antibiotic prescriptions in COVID-19 patients with risk factors, hospital admission, intensive care unit (ICU) admission, and mortality. RESULTS: The proportion of antibiotic prescriptions during the first SARS-CoV-2 wave was lower than during the 2020 influenza season (9.6% versus 20.7%), difference 11.1% (95% confidence interval [CI] = 8.7 to 13.5). During the second SARS-CoV-2 wave, antibiotic prescriptions were associated with being aged ≥70 years (OR 2.05; 95% CI = 1.43 to 2.93), the number of comorbidities (OR 1.46; 95% CI = 1.18 to 1.82), and admission to hospital (OR 3.19; 95% CI = 2.02 to 5.03) or ICU (OR 4.64; 95% CI = 2.02 to 10.62). CONCLUSION: Antibiotic prescription was less common during the SARS-CoV-2 pandemic than during influenza seasons, and was associated with an adverse course and its risk factors. The findings suggest a relatively targeted prescription policy of antibiotics in primary care during COVID-19.

A Population-Based Susceptible, Infected, Recovered Simulation Model of the Spread of Influenza-Like-Illness in the Homeless versus Non-Homeless Population.

PURPOSE: To examine the prevalence and characteristics of influenza-like illness (ILI) related presentations among people experiencing homelessness compared to the general population as well as to use the Susceptible, Infected, Recovered (SIR) simulation model parameters ß and γ to model infectious interactivity, recovery rate, and population-level basic reproduction number (R0). METHODS: Using administrative health data from emergency department (ED) visits in the province of Ontario, Canada from 2010 to 2017, an SIR model was used to calculate the R0 for ILI in both the general population and the population of homeless individuals. RESULTS: From 2010 to 2017, a total of 17,056 homeless and 85,553 non-homeless individuals presented with an ILI to an ED in Ontario. The estimated infectious interactivity (ß) was lower while the recovery rate (γ) was longer for infected people experiencing homelessness. CONCLUSIONS: Our results suggest that infections of ILI will result in more secondary cases in the homeless population compared to the homed population. This evaluation of the dynamics of ILI spread in the homeless population provides insight into how illnesses such as COVID-19 may be much more infectious in this population compared to the homed population.

Scientific publication speed and retractions of COVID-19 pandemic original articles.

Objective: To describe the editorial processing time of published COVID-19 research articles and compare this with a similar topic, human influenza, and analyze the number of publications, withdrawals, and retractions. Methods: A descriptive-analytical study using PubMed on research articles with the MeSH terms human influenza and COVID-19. Time to acceptance (from submission to acceptance) and time to publication (from acceptance to publication) were compared. Retractions and withdrawals were reviewed both qualitatively and quantitatively. Results: There were 31 319 research articles on COVID-19 and 4 287 on human influenza published during 2020. The median time to acceptance for COVID-19 was lower than that for human influenza (8 vs. 92 days). The median time to publication for COVID-19 articles was shorter than those on human influenza (12 vs. 16 days); 47.0% of COVID-19 research articles were accepted within the first week of submission, and 19.5% within one day. There were 82 retractions and withdrawals for COVID-19 articles, 1 for human influenza, and 5 for articles that contain both terms; these were mainly related to ethical misconduct, and 27 (31.0%) were published by the same group of authors in one highest-quartile journal. Conclusions: The conundrum between fast publishing and adequate standards is shown in this analysis of COVID-19 research articles. The speed of acceptance for COVID-19 manuscripts was 11.5 times faster than for human influenza. The high number of acceptances within a day or week of submission and the number of retractions and withdrawals of COVID-19 papers might be a warning sign about the possible lack of a quality control process in scientific publishing and the peer review process.

The 2022/23 flu vaccination season: a return to normality?

The article reports on the signs showing a return to normality in England, including the publication by National Health Service (NHS) England and NHS Improvement of the flu vaccination letter for the 2022/2023 season.

Lineage-matched versus mismatched influenza B vaccine effectiveness following seasons of marginal influenza B circulation.

BACKGROUND: Several countries have recently transitioned from the trivalent inactivated influenza vaccine (TIV) to the quadrivalent inactivated influenza vaccine (QIV) in order to outweigh influenza B vaccine-mismatch. However, few studies thus far evaluated its benefits versus the TIV in a systematic manner. Our objective was to compare the QIV VE with lineage-mismatched TIV VE. METHODS: We estimated the 2015-2016, 2017-2018, 2019-2020 end-of season influenza B VE against laboratory-confirmed influenza-like illness (ILI) among community patients, using the test-negative design. VE was estimated for pre-determined age groups and for moving age intervals of 15 years. RESULTS: Since 2011-2012 season, alternate seasons in Israel were dominated by influenza B circulation. Compared with the lineage-mismatched TIV used during the 2015-2016 and 2017-2018 seasons, the 2019-2020 QIV showed the highest all-ages VE, with VE estimates of 56.9 (95% CI 30.1 to 73.4), 16.5 (95% CI -22.5 to 43.1) and -25.8 (95% CI -85.3 to 14.6) for the 2019-2020, 2017-2018 and 2015-2016 seasons, respectively. The 2019-2020 VE point estimated were the highest for the 0.5-4, 5-17 and 18-44 years age groups and for more 15-year age intervals as compared to the other seasons. CONCLUSIONS: Our results support the rapid transition from the TIV to the QIV.

Responses against infectious disease pandemics: a narrative review on COVID-19

Currently, the world is facing the coronavirus disease 2019 (COVID-19) pandemic. With this, an emerging infectious disease pandemic in the absence of effective antiviral agents and vaccines for a novel virus is no different from the 1918 influenza pandemic, which became a great disaster for humankind. We also experienced a global lockdown with a stringent implementation of social distancing, which is a first for mankind living in the present day, and has led to enormous economic damage and restrictions on individual freedom. The microorganism that will cause the next pandemic may be a highly fatal avian influenza virus, another coronavirus, or a completely different microorganism. This COVID-19 pandemic is an enormous lesson for humankind and is tantamount to a vaccine in preparation for the next pandemic. Important and urgent undertakings were given to each country in terms of complementing laws and regulations for a stronger and more resilient healthcare system, such as investment in research and development for new rapid diagnostic technologies, vaccines, new therapeutic agents, among others.

Can laboratory evaluation differentiate between coronavirus disease-2019, influenza, and respiratory syncytial virus infections? A retrospective cohort study

AIM: To identify clinical and laboratory parameters that can assist in the differential diagnosis of coronavirus disease 2019 (COVID-19), influenza, and respiratory syncytial virus (RSV) infections. METHODS: In this retrospective cohort study, we obtained basic demographics and laboratory data from all 685 hospitalized patients confirmed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza virus, or RSV from 2018 to 2020. A multiple logistic regression was employed to investigate the relationship between COVID-19 and laboratory parameters. RESULTS: SARS-CoV-2 patients were significantly younger than RSV (P=0.001) and influenza virus (P=0.022) patients. SARS-CoV-2 patients also displayed a significant male predominance over influenza virus patients (P=0.047). They also had significantly lower white blood cell count (median 6.3x106 cells/mu) compared with influenza virus (P<0.001) and RSV (P=0.001) patients. Differences were also observed in other laboratory values but were insignificant in a multivariate analysis. CONCLUSIONS: Male sex, younger age, and low white blood cell count can assist in the diagnosis of COVID-19 over other viral infections. However, the differences between the groups were not substantial enough and would probably not suffice to distinguish between the viral illnesses in the emergency department.

Promoting hauora during COVID-19: Time to listen to the narratives of Māori nurses and leaders

The authors reflect on the efforts by Maori nurses to promote hauora Maori in their respective communities in New Zealand during the Covid-19 pandemic. Topics include how the nurses used the kaupapa Maori principles in responding to emergencies like the pandemic and the legacy of influential Maori leader Te Puea Herangi in restoring the honour and strength of her Tainui people.

Feasibility of Radiomics to Differentiate Coronavirus Disease 2019 (COVID-19) from H1N1 Influenza Pneumonia on Chest Computed Tomography: A Proof of Concept.

BACKGROUND: Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and influenza can be challenging when seasonal influenza concurs with the COVID-19 pandemic. This study was conducted to test the ability of radiomics-artificial intelligence (AI) to perform this task. METHODS: In this retrospective study, chest CT images from 47 patients with COVID-19 (after February 2020) and 19 patients with H1N1 influenza (before September 2019) pneumonia were collected from three hospitals affiliated with Arak University of Medical Sciences, Arak, Iran. All pulmonary lesions were segmented on CT images. Multiple radiomics features were extracted from the lesions and used to develop support-vector machine (SVM), k-nearest neighbor (k-NN), decision tree, neural network, adaptive boosting (AdaBoost), and random forest. RESULTS: The patients with COVID-19 and H1N1 influenza were not significantly different in age and sex (P=0.13 and 0.99, respectively). Nonetheless, the average time between initial symptoms/hospitalization and chest CT was shorter in the patients with COVID-19 (P=0.001 and 0.01, respectively). After the implementation of the inclusion and exclusion criteria, 453 pulmonary lesions were included in this study. On the harmonized features, random forest yielded the highest performance (area under the curve=0.97, sensitivity=89%, precision=90%, F1 score=89%, and classification accuracy=89%). CONCLUSION: In our preliminary study, radiomics feature extraction, conjoined with AI, especially random forest and neural network, appeared to yield very promising results in the differentiation between COVID-19 and H1N1 influenza on chest CT.

Determinants of seasonal influenza vaccination hesitancy among healthcare personnel: An integrative review.

AIMS AND OBJECTIVES: To explore the determinants of and behaviour change models for seasonal influenza vaccination compliance among healthcare personnel. BACKGROUND: COVID-19 vaccine hesitancy among healthcare personnel may be better understood by exploring determinants of seasonal influenza vaccine hesitancy. DESIGN: Integrative literature review. METHODS: A systematic search was conducted in accordance with PRISMA guidelines. Six thousand and forty-eight articles were screened. Seventy-eight met inclusion criteria. Due to the heterogeneity of included articles, a narrative synthesis was conducted utilising a conceptual matrix to identify thematic categories. RESULTS: Six thematic categories were identified as influencing HCP SIV compliance: 'perceived vulnerability', 'trust', 'past behaviour', 'professional duty', 'access and convenience' and 'knowledge and experience'. The Health Belief Model (HBM) was the most commonly utilised health behaviour change model within the seasonal influenza vaccination context. Few studies have examined seasonal influenza vaccine acceptance and uptake within the Australian HCP context, particularly involving community care and aged care. CONCLUSIONS: Factors that appear to relate to influenza vaccination compliance among HCP can be grouped according to several thematic categories, and they also appear influential in COVID-19 vaccine uptake. In particular, an emerging focus on 'trust' or the more emotive considerations of decision-making around health-protective behaviours requires further exploration in the context of a pandemic. Efforts to influence these domains to increase compliance, however, are likely to be impeded by a lack of a well-developed and tested behaviour change model. RELEVANCE TO CLINICAL PRACTICE: Healthcare personnel (HCP) face high levels of occupational exposure to seasonal influenza every year. An emerging focus on 'trust' and the more emotive considerations of decision-making around health-protective behaviours requires further exploration in the context of a pandemic.

Survival in influenza virus-related pneumonia by viral subtype: 2016-2020.

BACKGROUND: Influenza remains a common cause of morbidity and mortality worldwide, and viral subtype-related differences in disease outcomes have been documented. OBJECTIVE: To characterize the survival experience of adult inpatients with influenza virus-associated pneumonia by viral subtype during five consecutive flu seasons. METHOD: We performed a retrospective cohort study; data from 4,678 adults were analyzed using the Kaplan-Meier method. A multivariate Cox proportional hazard regression model was fitted. RESULTS: The overall in-hospital mortality rate was 25.0 per 1,000 hospital days. The survival probabilities from pneumonia patients went from 93.4% (95% CI 92.6-94.1%) by day three to 43.3% (95% CI 39.2-47.4%) by day 30 from hospital admission. In general, the lowest survival rates were observed in patients with AH1N1 infection. In multiple models, after adjusting for comorbidities and when compared with A non-subtyped virus, pneumonia patients with AH3N2 or B strains had a significantly decreased risk of a non-favorable disease outcome. The association of other strains was not significant. CONCLUSIONS: Our findings suggest that the survival of inpatients with influenza virus-associated pneumonia varies according to the pathogenic viral subtype; the lowest survival rates were observed in patients with AH1N1 infection. This effect was independent of the patients' gender, age, and the analyzed underlying health conditions.

Effects of weather-related social distancing on city-scale transmission of respiratory viruses: a retrospective cohort study.

BACKGROUND: Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses. METHODS: Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits. RESULTS: Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase. CONCLUSION: High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths.

Just a bad flu? Tackling the "infodemic" in Ireland through a comparative analysis of hospitalised cases of COVID-19 and influenza.

OBJECTIVES: COVID-19 infection has been compared to seasonal influenza as an argument against non-pharmacological population-based infection control measures known as "lockdowns". Our study sought to compare disease severity measures for patients in Ireland hospitalised with COVID-19 against those hospitalised with seasonal influenza. STUDY DESIGN: This is a retrospective population-based cohort study. METHODS: COVID-19 hospital episodes and seasonal influenza hospital episodes were identified using relevant International Classification of Disease (ICD-10) codes from the Irish national hospitalisation dataset. The occurrences of key metrics of disease severity, length of stay, intensive care admission, ventilatory support, haemodialysis and in-hospital mortality were measured and compared between the two groups using odds ratios with 95% confidence intervals (CIs), stratified by age. RESULTS: Hospitalised COVID-19 episodes had a mean length of stay more than twice as long as hospitalised influenza episodes (17.7 days vs 8.3 days). The likelihood of all measures of disease severity was greater in COVID-19 episodes, and the odds of in-hospital mortality were five-fold higher in this group compared with seasonal influenza episodes (OR 5.07, 95% CI 4.29-5.99, P < 0.001). Greater likelihood of increased disease severity was observed for COVID-19 episodes in most age groups. CONCLUSIONS: COVID-19 is a more severe illness than seasonal influenza in hospitalised cohorts. It is imperative that public health professionals ensure that evidence-based advocacy is part of the response to COVID-19 to tackle a dangerous "infodemic" that can undermine public health control measures.