Influenza testing, diagnosis, and treatment in the emergency department in 2009-2010 and 2010-2011

Dearth of influenza among older adults admitted with respiratory symptoms in Malaysia during the coronavirus disease 2019 pandemic in 2021

Introduction

Influenza is a common respiratory virus which leads to over 400,000 annual deaths globally. Mortality from influenza is highest among those aged 75 years and over living in Africa and Southeast Asia.

Objective

To determine the burden of influenza among older adults presenting to public hospitals with severe acute respiratory infection (SARI) during the coronavirus disease 2019 (COVID-19) pandemic.

Methods

This multi-center, prospective, observational study recruited individuals aged 65 years and over who presented to four Malaysian hospitals with SARI from 1 January to 31 December 2021. Those with prior confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection were excluded. SARS-CoV-2 was detected through real-time polymerase chain reaction (PCR) with routine diagnostic kits. Influenza A, influenza B and respiratory syncytial virus (RSV) viruses were detected with Xpress Flu/RSV kits using the GeneXpert rapid real-time PCR system (Cepheid, USA).

Results

Samples were obtained from 512 participants, comprising 296 (57.8%) men and 216 (42.2%) women, with a mean age (SD) of 74.0 (7.1) years. Inpatient death occurred in 48 (9.6%) individuals. Significant differences existed in age, ethnicity, and comorbidities across study sites. One (0.2%) case of influenza A, two (0.4%) cases of RSV and 63 (12.5%) cases of SARS-CoV-2 infection were detected over the 1-year period. Cases of COVID-19 mirrored national trends derived from open source data, while the dearth of influenza cases mirrored national and global Flunet figures.

Conclusion

Our observational study conducted during the COVID-19 pandemic detected only one case of influenza, alongside a high SARS-CoV-2 positivity rate. The poor uptake of influenza vaccination nationally, worsened by the recent pandemic restrictions, could lead to waning immunity from the absence of seasonal exposure. Potentially deadly outbreaks may then occur when lockdown and infection control measures are eventually removed.

Influenza Antiviral Prescribing Practices and the Influence of Rapid Testing Among Primary Care Providers in the US, 2009-2016

Background

Early influenza antiviral treatment within 2 days of illness onset can reduce illness severity and duration. Reliance on low sensitivity rapid influenza diagnostic tests (RIDTs) to guide antiviral prescribing has been reported. We describe antiviral prescribing practices among primary care providers from a large surveillance network in the United States.

Methods

From 2009-2016, a network of 36 to 68 outpatient clinics per year collected respiratory specimens and clinical data for patients with influenza-like illness (ILI). Specimens were tested for influenza using polymerase chain reaction (PCR). We used multivariable logistic regression to assess factors influencing antiviral prescribing.

Results

Among 13 540 patients with ILI, 2766 (20%) were prescribed antivirals. In age groups recommended to receive empiric antiviral treatment for suspected influenza, 11% of children <2 years and 23% of adults ≥65 years received a prescription. Among 3681 patients with a positive PCR test for influenza, 40% tested negative by RIDT. In multivariable analysis, prescription receipt was strongly associated with a positive RIDT (adjusted odds ratio [aOR] 12, 95% CI 11-14) and symptom onset ≤2 days before visit (aOR 4.3, 95% CI 3.8-4.9). Antiviral prescribing was also more frequent among pediatric and private family practice clinics compared with community health centers (aOR 1.9, 95% CI 1.6-2.2, and 1.3, 95% CI 1.1-1.5, respectively).

Conclusion

Primary care providers were more likely to prescribe antivirals to patients with a positive RIDT, but antivirals were prescribed infrequently even to patients in high-risk age groups. Understanding patient and provider characteristics associated with antiviral prescribing is important for communicating treatment recommendations.

Impact of the 2014-2015 influenza season on the activity of an academic emergency department

The morbidity and mortality of the 2014-2015 influenza season were more important than those in previous years. We assessed the impact of the 2014-2015 influenza season on the length of stay (LOS) and workload in an academic emergency department (ED). This is a monocentric retrospective study. The database of the microbiology laboratory was used to identify influenza nasal swabs performed during the influenza seasons from 2010 to 2015. Patients admitted to the ED during these periods were identified through the administrative database and cross-checked with patients who underwent an influenza nasal swab in the ED. Median LOS was used to estimate the impact of the isolation procedures on ED LOS. Bed occupancy rate and mean LOS in the ED were calculated as proxy of the ED workload. During the 2014-2015 influenza season, 55.9% of ED patients (n = 123) with confirmed influenza were hospitalised. In terms of workload, despite that influenza patients represented only 2.2% of all ED patients during the season, they occupied 28% of ED beds with respiratory isolation during the delay to realise and obtain the test results, as well as during the delay before being discharged home or transferred to a hospital ward. The median ED LOS for influenza-confirmed patients was significantly longer in comparison with all ED patients (21.6 h vs 4.0 for ambulatory patients and 24.7 h vs 12.3 for hospitalised patients). The 2014-2015 influenza season had significant consequences in terms of ED LOS and bed use. It dramatically increased the workload in the ED.

Diagnostic accuracy of the real-time PCR cobas® Liat® Influenza A/B assay and the Alere i Influenza A&B NEAR isothermal nucleic acid amplification assay for the detection of influenza using adult nasopharyngeal specimens

BACKGROUND

Accurate detection of influenza requires diagnostic testing; however, methods such as RADTs and central laboratory-based tests are limited by low sensitivity and time constraints, respectively.

OBJECTIVE

To compare the performances of the cobas^® Liat^® Influenza A/B and Alere™ i Influenza A&B point-of-care (POC) assays for detecting influenza A and B viruses using fresh nasopharyngeal specimens with the GenMark Dx^® Respiratory Viral Panel as the reference method, a FDA cleared IVD PCR test.

STUDY DESIGN

A total of 87 samples collected in viral transport medium from adults ≥18 years of age were re-tested on both POC assays (based on the reference PCR method, 29 were influenza A and 18 were influenza B virus positive).

RESULTS

The overall sensitivity and specificity of the cobas Influenza A/B for the detection of influenza A and B relative to reference PCR was 97.9% (95% confidence interval [CI] 88.9%, 99.6%) and 97.5% (95% CI: 87.1%, 99.6%), respectively, while the sensitivity of the Alere i Influenza A&B assay relative to the reference PCR method was 63.8% (95% CI: 49.5%, 76.0%) and the specificity was 97.5% (95% CI: 87.1%, 99.6%). The individual sensitivities and specificities of the cobas Influenza A/B assay for influenza A alone and influenza B alone were comparable to those of the reference PCR method (influenza A: sensitivity of 100% [95% CI: 88.3%, 100.0%] and specificity of 98.3% [95% CI: 90.9%, 99.7%]; influenza B: sensitivity of 94.4% [95% CI: 74.2%, 99.0%] and specificity of 100% [95% CI: 94.7%, 100.0%]). For the Alere i Influenza A&B assay, the individual specificities for influenza A and B were comparable to those of the reference PCR method (98.3% [95% CI: 90.9%, 99.7%] and 97.1% [95% CI: 90.0%, 99.2%], respectively), while the individual sensitivities were low relative to reference PCR (55.2% [95% CI: 37.5%, 71.6%] and 72.2% [95% CI: 49.1%, 87.5%], respectively).

CONCLUSION

The cobas Influenza A/B assay demonstrated performance equivalent to laboratory-based PCR, and could replace rapid antigen tests.

Clinical Mimics: An Emergency Medicine-Focused Review of Influenza Mimics

BACKGROUND

Influenza viruses are a significant cause of morbidity and mortality in the United States. Given the wide range of symptoms, emergency physicians must maintain a broad differential diagnosis in the evaluation and treatment of patients presenting with influenza-like illnesses.

OBJECTIVE

This review addresses objective and subjective symptoms commonly associated with influenza and discusses important mimics of influenza viruses, while offering a practical approach to their clinical evaluation and treatment.

DISCUSSION

Influenza-like symptoms are common in the emergency department (ED), and influenza accounts for > 200,000 hospitalizations annually. The three predominant types are A, B, and C, and these viruses are commonly transmitted through aerosolized viral particles with a wide range of symptoms. The most reliable means of identifying influenza in the ED is rapid antigen detection, although consideration of local prevalence is required. High-risk populations include children younger than 4 years, adults older than 50 years, adults with immunosuppression or chronic comorbidities, pregnancy, obesity, residents of long-term care facilities, and several others. The Centers for Disease Control and Prevention recommends treatment with neuraminidase inhibitors in these populations. However, up to 70% of patients with these symptoms may have a mimic. These mimics include infectious and noninfectious sources. The emergency physician must be aware of life-threatening mimics and assess for these conditions while beginning resuscitation and treatment.

CONCLUSIONS

The wide range of symptoms associated with influenza overlap with several life-threatening conditions. Emergency physicians must be able to rapidly identify patients at risk for complications and those who require immediate resuscitation.

Predictors of Influenza Diagnosis Among Patients With Laboratory-Confirmed Influenza

OBJECTIVE

This study was performed to determine predictors of clinical influenza diagnosis among patients with laboratory-confirmed influenza.

METHODS

Prospective, laboratory-confirmed surveillance for influenza was conducted among patients of all ages who were hospitalized or presented to the emergency department with fever and respiratory symptoms during 2009-2013. We evaluated all enrolled persons who had influenza confirmed by viral culture and/or polymerase chain reaction and received any discharge diagnosis. The primary outcome, clinical influenza diagnosis, was defined as (1) a discharge diagnosis of influenza, (2) a prescription of neuraminidase inhibitor, or (3) a rapid test positive for influenza virus. Bivariate analyses and multiple logistic regression modeling were performed.

RESULTS

Influenza was diagnosed for 29% of 504 enrolled patients with laboratory-confirmed influenza and for 56% of 236 patients with high-risk conditions. Overall, clinical influenza diagnosis was predicted by race/ethnicity, insurance status, year, being hospitalized, having high-risk conditions, and receiving no diagnosis of bacterial infection. Being diagnosed with a bacterial infection reduced the odds of receiving an influenza diagnosis by >3-fold for all patients and for patients with high-risk conditions.

CONCLUSIONS

Many influenza virus-positive patients, including those with high-risk conditions, do not receive a clinical diagnosis of influenza. The pattern of clinical diagnoses among influenza virus-positive patients suggests preferential consideration of bacterial diseases as a diagnosis.

Multi-scale modeling for the transmission of influenza and the evaluation of interventions toward it

Mathematical modeling of influenza epidemic is important for analyzing the main cause of the epidemic and finding effective interventions towards it. The epidemic is a dynamic process. In this process, daily infections are caused by people's contacts, and the frequency of contacts can be mainly influenced by their cognition to the disease. The cognition is in turn influenced by daily illness attack rate, climate, and other environment factors. Few existing methods considered the dynamic process in their models. Therefore, their prediction results can hardly be explained by the mechanisms of epidemic spreading. In this paper, we developed a heterogeneous graph modeling approach (HGM) to describe the dynamic process of influenza virus transmission by taking advantage of our unique clinical data. We built social network of studied region and embedded an Agent-Based Model (ABM) in the HGM to describe the dynamic change of an epidemic. Our simulations have a good agreement with clinical data. Parameter sensitivity analysis showed that temperature influences the dynamic of epidemic significantly and system behavior analysis showed social network degree is a critical factor determining the size of an epidemic. Finally, multiple scenarios for vaccination and school closure strategies were simulated and their performance was analyzed.