Point‐of‐care testing for influenza in a university emergency department: A prospective study

BackgroundSeasonal influenza is a burden for emergency departments (ED). The aim of this study was to investigate whether point‐of‐care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures.ObjectivesThe aim of this study was to investigate whether point‐of‐care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures.MethodsUsing a cross‐over design, the cobas® Liat® Influenza A/B POC PCR test (Liat) was compared with standard clinical practice during the 2019/2020 influenza season. All adult patients (aged ≥ 18 years) with fever (≥38°C) and respiratory symptoms were included. Primary end points were the prevalence of influenza infections in the ED and staff sick days. Secondary end points were frequency of antiviral and antibacterial therapy, time between admission and test result or treatment initiation, patient disposition, ED length of stay (LOS), and for inpatients mortality and LOS. Nurses were interviewed about handling and integration of POC testing. The occurrence of SARS‐CoV‐2 infections coincided with the second half of the study.ResultsA total of 828 patients were enrolled in the study. All 375 patients of the intervention group were tested with Liat, and 103 patients of them (27.6%) tested positive. During the intervention period, staff sick days were reduced by 34.4% (P = .023). Significantly, more patients in the intervention group received antiviral therapy with neuraminidase inhibitors (7.2% vs 3.8%, P = .028) and tested patients received antibiotics more frequently (40.0% vs 31.6%, P = .033). Patients with POC test were transferred to external hospitals significantly more often (5.6% vs 1.3%, P = .01).ConclusionWe conclude that POC testing for influenza is useful in the ED, especially if it is heavily frequented by patients with respiratory symptoms.     

Vaccine‐preventable disease hospitalized patients with heart failure with reduced ejection fraction

BackgroundOver five million Americans suffer from heart failure (HF), and this is associated with multiple chronic comorbidities and recurrent decompensation. Currently, there is an increased incidence in vaccine‐preventable diseases (VPDs). We aim to investigate the impact of HF with reduced ejection fraction (HFrEF) in patients hospitalized with VPDs.HypothesisPatient with HFrEF are at higher risk for VPDs and they carry a higher risk for in‐hospital complications.MethodsRetrospective analysis from all hospital admissions from the 2016‐2018 National Inpatient Sample (NIS) using the ICD‐10CM codes for patients admitted with a primary diagnosis of VPDs with HFrEF and those without reduced ejection fraction. Outcomes evaluated were in‐hospital mortality, length of stay (LOS), healthcare utilization, frequency of admissions, and in‐hospital complications. Multivariate regression analysis was conducted to adjust for confounders.ResultsOut of 317 670 VPDs discharges, we identified 12 130 (3.8%) patients with HFrEF as a comorbidity. The most common admission diagnosis for VPDs was influenza virus (IV) infection (75.0% vs. 64.1%; p < .01), followed by pneumococcal pneumonia (PNA) (13% vs. 9.4%; p < .01). After adjusting for confounders, patients with HFrEF had higher odds of having diagnosis of IV (adjusted [aOR], 1.42; p < .01) and PNA (aOR, 1.27; p < .01). Patients with VPDs and HFrEF had significantly higher odds of mortality (aOR, 1.76; p < .01), LOS, respiratory failure requiring mechanical ventilation, and mechanical ventilation for less than 96 h.ConclusionInfluenza and PNA were the most common VPDs admitted to the hospital in patients with a concomitant diagnosis of HFrEF. They were associated with increased mortality and in‐hospital complications.     

Absence of association between 2019‐20 influenza vaccination and COVID‐19: Results of the European I‐MOVE‐COVID‐19 primary care project,March‐August 2020

BackgroundClaims of influenza vaccination increasing COVID‐19 risk are circulating. Within the I‐MOVE‐COVID‐19 primary care multicentre study, we measured the association between 2019‐20 influenza vaccination and COVID‐19.MethodsWe conducted a multicentre test‐negative case‐control study at primary care level, in study sites in five European countries, from March to August 2020. Patients presenting with acute respiratory infection were swabbed, with demographic, 2019‐20 influenza vaccination and clinical information documented. Using logistic regression, we measured the adjusted odds ratio (aOR), adjusting for study site and age, sex, calendar time, presence of chronic conditions. The main analysis included patients swabbed ≤7 days after onset from the three countries with <15% of missing influenza vaccination. In secondary analyses, we included five countries, using multiple imputation with chained equations to account for missing data.ResultsWe included 257 COVID‐19 cases and 1631 controls in the main analysis (three countries). The overall aOR between influenza vaccination and COVID‐19 was 0.93 (95% CI: 0.66‐1.32). The aOR was 0.92 (95% CI: 0.58‐1.46) and 0.92 (95% CI: 0.51‐1.67) among those aged 20‐59 and ≥60 years, respectively. In secondary analyses, we included 6457 cases and 69 272 controls. The imputed aOR was 0.87 (95% CI: 0.79‐0.95) among all ages and any delay between swab and symptom onset.ConclusionsThere was no evidence that COVID‐19 cases were more likely to be vaccinated against influenza than controls. Influenza vaccination should be encouraged among target groups for vaccination. I‐MOVE‐COVID‐19 will continue documenting influenza vaccination status in 2020‐21, in order to learn about effects of recent influenza vaccination.     

Predicting virologically confirmed influenza using school absences in Allegheny County,Pennsylvania, USA during the 2007‐2015 influenza seasons

BackgroundChildren are important in community‐level influenza transmission. School‐based monitoring may inform influenza surveillance.MethodsWe used reported weekly confirmed influenza in Allegheny County during the 2007 and 2010‐2015 influenza seasons using Pennsylvania''s Allegheny County Health Department all‐age influenza cases from health facilities, and all‐cause and influenza‐like illness (ILI)‐specific absences from nine county school districts. Negative binomial regression predicted influenza cases using all‐cause and illness‐specific absence rates, calendar week, average weekly temperature, and relative humidity, using four cross‐validations.ResultsSchool districts reported 2 184 220 all‐cause absences (2010‐2015). Three one‐season studies reported 19 577 all‐cause and 3012 ILI‐related absences (2007, 2012, 2015). Over seven seasons, 11 946 confirmed influenza cases were reported. Absences improved seasonal model fits and predictions. Multivariate models using elementary school absences outperformed middle and high school models (relative mean absolute error (relMAE) = 0.94, 0.98, 0.99). K‐5 grade‐specific absence models had lowest mean absolute errors (MAE) in cross‐validations. ILI‐specific absences performed marginally better than all‐cause absences in two years, adjusting for other covariates, but markedly worse one year.ConclusionsOur findings suggest seasonal models including K‐5th grade absences predict all‐age‐confirmed influenza and may serve as a useful surveillance tool.     

Association of admission blood glucose level and clinical outcomes in elderly community‐acquired pneumonia patients with or without diabetes

IntroductionCommunity‐acquired pneumonia (CAP) is the major cause of infection‐related mortality worldwide. Patients with CAP frequently present with admission hyperglycemia.ObjectivesThe aim of this study was to evaluate the association between admission blood glucose (ABG) level and clinical outcomes in elderly CAP patients (≥80 years of age) with or without diabetes.MethodsIn this single center retrospective study, 290 elderly patients diagnosed with CAP were included. Demographic and clinical information were collected and compared. The associations between admission blood glucose level and the 30‐day mortality as well as intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) in elderly CAP patients with or without diabetes were assessed.ResultsOf the 290 eligible patients with CAP, 159 (66.5%) patients were male, and 64 (22.1%) had a known history of diabetes at hospital admission. After adjusting for age and sex, the logistic regression analysis had identified several risk factors that might be associated with clinical outcomes in elderly patients with CAP. Multivariable logistic regression analysis revealed that admission glucose level > 11.1 mmol/L was significant associated with ICU admission, IMV, and 30‐day mortality both in non‐diabetic and diabetic patients. Furthermore, Kaplan–Meier analysis indicated that patients with higher admission glucose level were correlated statistically significantly with 30‐day mortality in patients with CAP (P < 0.001).ConclusionAdmission blood glucose is correlated with 30‐day hospital mortality, ICU admission, and IMV of CAP in elderly patients with and without diabetes. Specially, admission glucose > 11.1 mmol/L was a significant risk factor for 30‐day hospital mortality.     

Viral co‐infections are associated with increased rates of hospitalization in those with influenza

BackgroundInfluenza causes significant morbidity and mortality in the United States. Among patients infected with influenza, the presence of bacterial co‐infection is associated with worse clinical outcomes; less is known regarding the clinical importance of viral co‐infections. The objective of this study was to determine rates of viral co‐infections in emergency department (ED) patients with confirmed influenza and association of co‐infection with disease severity.MethodsSecondary analysis of a biorepository and clinical database from a parent study where rapid influenza testing was implemented in four U.S. academic EDs, during the 2014–2015 influenza season. Patients were systematically tested for influenza virus using a validated clinical decision guideline. Demographic and clinical data were extracted from medical records; nasopharyngeal specimens from influenza‐positive patients were tested for viral co‐infections (ePlex, Genmark Diagnostics). Patterns of viral co‐infections were evaluated using chi‐square analysis. The association of viral co‐infection with hospital admission was assessed using univariate and multivariate regression.ResultsThe overall influenza A/B positivity rate was 18.1% (1071/5919). Of the 999 samples with ePlex results, the prevalence of viral co‐infections was 7.9% (79/999). The most common viral co‐infection was rhinovirus/enterovirus (RhV/EV), at 3.9% (39/999). The odds of hospital admission (OR 2.33, 95% CI: 1.01–5.34) increased significantly for those with viral co‐infections (other than RhV/EV) versus those with influenza A infection only.ConclusionPresence of viral co‐infection (other than RhV/EV) in ED influenza A/B positive patients was independently associated with increased risk of hospital admission. Further research is needed to determine clinical utility of ED multiplex testing.     

Changes in characteristics and case‐severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves—England, 2009–2010

BackgroundDuring 2009‐2010, pandemic influenza A (H1N1) pdm09 virus (pH1N1) infections in England occurred in two epidemic waves. Reasons for a reported increase in case‐severity during the second wave are unclear.MethodsWe analysed hospital‐based surveillance for patients with pH1N1 infections in England during 2009‐2010 and linked national data sets to estimate ethnicity, socio‐economic status and death within 28 days of admission. We used multivariable logistic regression to assess whether changes in demographic, clinical and management characteristics of patients could explain an increase in ICU admission or death, and accounted for missing values using multiple imputation.ResultsDuring the first wave, 54/960 (6%) hospitalised patients required intensive care and 21/960 (2%) died; during the second wave 143/1420 (10%) required intensive care and 55/1420 (4%) died. In a multivariable model, during the second wave patients were less likely to be from an ethnic minority (OR 0.33, 95% CI 0.26‐0.42), have an elevated deprivation score (OR 0.75, 95% CI 0.68‐0.83), have known comorbidity (OR 0.78, 95% CI 0.63‐0.97) or receive antiviral therapy ≤2 days before onset (OR 0.72, 95% CI 0.56‐0.92). Increased case‐severity during the second wave was not explained by changes in demographic, clinical or management characteristics.ConclusionsMonitoring changes in patient characteristics could help target interventions during multiple waves of COVID‐19 or a future influenza pandemic. To understand and respond to changes in case‐severity, surveillance is needed that includes additional factors such as admission thresholds and seasonal coinfections.     

Costs of a clinical pathway with point‐of‐care testing during influenza epidemic in a Dutch hospital

Our study aim was to determine how a new clinical pathway, including PCR‐based influenza point‐of‐care test (POCT), influences the hospitalisation costs of patients suspected of influenza presenting at the emergency department of a Dutch hospital during two consecutive influenza epidemics (2016‐2017 and 2017‐2018). Compared to mean costs per patient of €3661 in 2016‐2017, the implementation of this new clinical pathway with influenza POCT in 2017 was associated with mean costs per influenza‐positive patient of €2495 in 2017‐2018 (P = .3). Our study suggests favourable economic results regarding a new clinical pathway with influenza POCT, reflecting a more efficient care of patients suspected of influenza presenting at the emergency department.     

Prognostic implications of biventricular strain measurement in COVID‐19 patients by speckle‐tracking echocardiography

BackgroundRecent reports have indicated the beneficial role of strain measurement in COVID‐19 patients.HypothesisTo determine the association between right and left global longitudinal strain (RVGLS, LVGLS) and COVID‐19 patients'' outcomes.MethodsHospitalized COVID‐19 patients between June and August 2020 were included. Two‐dimensional echocardiography and biventricular global longitudinal strain measurement were performed. The outcome measure was defined as mortality, ICU admission, and need for intubation. Appropriate statistical tests were used to compare different groups.ResultsIn this study 207 patients (88 females) were enrolled. During 64 ± 4 days of follow‐up, 22 (10.6%) patients died. Mortality, ICU admission, and intubation were significantly associated with LVGLS and RVGLS tertiles. LVGLS tertiles could predict poor outcome with significant odds ratios in the total population (OR = 0.203, 95% CI: 0.088–0.465; OR = 0.350, 95% CI: 0.210–0.585; OR = 0.354, 95% CI: 0.170–0.736 for mortality, ICU admission, and intubation). Although odds ratios of LVGLS for the prediction of outcome were statistically significant among hypertensive patients, these odds ratios did not reach significance among non‐hypertensive patients. RVGLS tertiles revealed significant odds ratios for the prediction of mortality (OR = 0.322, 95% CI: 0.162–0.640), ICU admission (OR = 0.287, 95% CI: 0.166–0.495), and need for intubation (OR = 0.360, 95% CI: 0.174–0.744). Odds ratios of RVGLS remained significant even after adjusting for hypertension when considering mortality and ICU admission.ConclusionRVGLS and LVGLS can be acceptable prognostic factors to predict mortality, ICU admission, and intubation in hospitalized COVID‐19 patients. However, RVGLS seems more reliable, as it is not confounded by hypertension.     

Influenza A viruses dual and multiple infections with other respiratory viruses and risk of hospitalisation and mortality

Please cite this paper as: Goka et al. (2013) Influenza A viruses dual and multiple infections with other respiratory viruses and risk of hospitalisation and mortality. Influenza and Other Respiratory Viruses 7(6), 1079–1087. Introduction Recent literature suggests that dual or multiple virus infections may affect disease severity. However, few studies have investigated the effect of co‐infection with influenza A viruses. Objectives To identify the association between influenza A and respiratory viruses co‐infections with disease outcome. Methodology Data for samples from North West England tested between January 2007 and June 2011 was analysed for patterns of co‐infection between influenza A viruses and eight respiratory viruses. Risk of hospitalisation to ICU or general ward in single versus co‐infections was assessed using logistic regression. Results Of the 25 596 samples analysed for respiratory viruses 40·7% (10 501) were positive for any virus. Co‐infections were detected in 4·7% (137/2879) of all patients with influenza A(H1N1)pdm09, and 7·3% (57/779) of those with other influenza A virus infections. Co‐infection between seasonal influenza A viruses and influenza B virus was associated with a significant increase in the risk of admission to ICU/death (OR: 22·0, 95% CI: 2·21–219·8, P = 0·008). Respiratory syncytial virus/influenza A (RSV/Flu A) co‐infection also increased this risk but was not statistically significant. For influenza A(H1N1)pdm09, RSV and AdV co‐infection increased risk of hospitalisation to general ward whereas Flu B increased risk of admission to ICU, but none of these were statistically significant. Conclusion Co‐infection is a significant predictor of disease outcome; combined treatment, introduction of an integrated vaccine for all respiratory viruses and development of multi‐target rapid diagnostic tests is recommended. Integration of respiratory viruses’ co‐infections into public health reports could also contribute to the accumulation of evidence.     

Predictors of all‐cause mortality among patients hospitalized with influenza,respiratory syncytial virus,or SARS‐CoV‐2

BackgroundShared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen.MethodsWe conducted a retrospective cohort study to identify predictors of 30‐day all‐cause mortality following hospitalization with influenza (N = 45,749; 2010‐09 to 2019‐05), respiratory syncytial virus (RSV; N = 24 345; 2010‐09 to 2019‐04), or severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2; N = 8988; 2020‐03 to 2020‐12; pre‐vaccine) using population‐based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality.ResultsA total of 3186 (7.0%), 697 (2.9%), and 1880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS‐CoV‐2, respectively. Shared predictors of increased mortality included older age, male sex, residence in a long‐term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS‐CoV‐2. Few comorbidities were associated with mortality among patients with SARS‐CoV‐2 as compared with those with influenza or RSV.ConclusionsOur findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.     

Symptoms and recovery among adult outpatients with and without COVID‐19 at 11 healthcare facilities—July 2020, United States

BackgroundSymptoms of mild COVID‐19 illness are non‐specific and may persist for prolonged periods. Effects on quality of life of persistent poor physical or mental health associated with COVID‐19 are not well understood.MethodsAdults aged ≥18 years with laboratory‐confirmed COVID‐19 and matched control patients who tested negative for SARS‐CoV‐2 infection at outpatient facilities associated with 11 medical centers in the United States were interviewed to assess symptoms, illness duration, and health‐related quality of life. Duration of symptoms, health‐related quality of life measures, and days of poor physical health by symptoms experienced during illness were compared between case patients and controls using Wilcoxon rank‐sum tests. Symptoms associated with COVID‐19 case status were evaluated by multivariable logistic regression.ResultsAmong 320 participants included, 157 were COVID‐19 cases and 163 were SARS‐CoV‐2 negative controls. Loss of taste or smell was reported by 63% of cases and 6% of controls and was strongly associated with COVID‐19 in logistic regression models (adjusted odds ratio [aOR] = 32.4; 95% confidence interval [CI], 12.6‐83.1). COVID‐19 cases were more likely than controls to have experienced fever, body aches, weakness, or fatigue during illness, and to report ≥1 persistent symptom more than 14 days after symptom onset (50% vs 32%, P < .001). Cases reported significantly more days of poor physical health during the past 14 days than controls (P < .01).ConclusionsDifferentiating COVID‐19 from other acute illnesses will require widespread diagnostic testing, especially during influenza seasons. Persistent COVID‐19‐related symptoms may negatively affect quality of life, even among those initially presenting with mild illness.     

The value of ECG changes in risk stratification of COVID‐19 patients

BackgroundThere is growing evidence of cardiac injury in COVID‐19. Our purpose was to assess the prognostic value of serial electrocardiograms in COVID‐19 patients.MethodsWe evaluated 269 consecutive patients admitted to our center with confirmed SARS‐CoV‐2 infection. ECGs available at admission and after 1 week from hospitalization were assessed. We evaluated the correlation between ECGs findings and major adverse events (MAE) as the composite of intra‐hospital all‐cause mortality or need for invasive mechanical ventilation. Abnormal ECGs were defined if primary ST‐T segment alterations, left ventricular hypertrophy, tachy or bradyarrhythmias and any new AV, bundle blocks or significant morphology alterations (e.g., new Q pathological waves) were present.ResultsAbnormal ECG at admission (106/216) and elevated baseline troponin values were more common in patients who developed MAE (p = .04 and p = .02, respectively). Concerning ECGs recorded after 7 days (159), abnormal findings were reported in 53.5% of patients and they were more frequent in those with MAE (p = .001). Among abnormal ECGs, ischemic alterations and left ventricular hypertrophy were significantly associated with a higher MAE rate. The multivariable analysis showed that the presence of abnormal ECG at 7 days of hospitalization was an independent predictor of MAE (HR 3.2; 95% CI 1.2–8.7; p = .02). Furthermore, patients with abnormal ECG at 7 days more often required transfer to the intensive care unit (p = .01) or renal replacement therapy (p = .04).ConclusionsPatients with COVID‐19 should receive ECG at admission but also during their hospital stay. Indeed, electrocardiographic alterations during hospitalization are associated with MAE and infection severity.     

Increased risk of rhinovirus infection in children during the coronavirus disease‐19 pandemic

BackgroundCoronavirus disease (COVID‐19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), was first detected in Japan in January 2020 and has spread throughout the country. Previous studies have reported that viral interference among influenza virus, rhinovirus, and other respiratory viruses can affect viral infections at the host and population level.MethodsTo investigate the impact of COVID‐19 on influenza and other respiratory virus infections, we analyzed clinical specimens collected from 2244 patients in Japan with respiratory diseases between January 2018 and September 2020.ResultsThe frequency of influenza and other respiratory viruses (coxsackievirus A and B; echovirus; enterovirus; human coronavirus 229E, HKU1, NL63, and OC43; human metapneumovirus; human parainfluenza virus 1, 2, 3, and 4; human parechovirus; human respiratory syncytial virus; human adenovirus; human bocavirus; human parvovirus B19; herpes simplex virus type 1; and varicella‐zoster virus) was appreciably reduced among all patients during the COVID‐19 pandemic except for that of rhinovirus in children younger than 10 years, which was appreciably increased. COVID‐19 has not spread among this age group, suggesting an increased risk of rhinovirus infection in children.ConclusionsRhinovirus infections should be continuously monitored to understand their increased risk during the COVID‐19 pandemic and viral interference with SARS‐CoV‐2.     

Lipid goal attainment in post‐acute coronary syndrome patients in China: Results from the 6‐month real‐world dyslipidemia international study II

BackgroundDyslipidemia International Study II (DYSIS II)‐China was conducted to determine the low‐density lipoprotein cholesterol (LDL‐C) goal (<1.8 mmol/L) attainment rate in patients with post‐acute coronary syndrome (ACS).HypothesisCompliance with treatment guideline recommendations improves the LDL‐C goal attainment rate in post‐ACS patients.MethodsThis multicenter prospective observational study conducted at 28 tertiary hospitals determined the LDL‐C goal attainment rates at admission and 6‐month follow‐up in patients on lipid‐lowering treatment (LLT) for ≥3 months and those not on LLT (LLT‐naive or off LLT for ≥3 months) at admission. Predictors of goal attainment at 6 months were identified using multivariate logistic regression.ResultsThe LDL‐C goal attainment rate at admission in 1102/1103 enrolled patients was 17.1%; it was 41.2% among 752 patients with available lipid results at 6 months. The distance to goal was 0.7 mmol/L at 6 months. Statin monotherapy was the most prescribed LLT. Only 7.7% of patients were receiving statin + ezetimibe and 8.4% of patients were receiving an atorvastatin‐equivalent dose of ≥40 mg/day at 6 months. Being male (odds ratio [OR] 1.7, 95% confidence interval [CI] 1.1–2.6) and undergoing percutaneous coronary intervention during index hospitalization (OR 1.5, 95% CI 1.1 to 2.1) were the independent predictors for LDL‐C goal attainment.ConclusionsThis real‐world DYSIS II study in China reports a low LDL‐C goal attainment rate in post‐ACS patients even after 6 months of LLT. Lack of intensification of statin therapy and underutilization of combinations suggest gaps between real‐world treatment practices and guideline recommendations.     

Influenza C virus–associated community‐acquired pneumonia in children

To evaluate the impact of influenza C (ICV) infection in children with community‐acquired pneumonia (CAP), all of the children consecutively seen during 4 influenza seasons with respiratory symptoms and radiographically confirmed CAP were prospectively evaluated. ICV was identified in the respiratory secretions of five of 391 patients (1·3%). In children with ICV‐associated CAP, clinical data were similar to those observed in children with IAV‐associated CAP and worse than those observed in children with IBV‐associated. The phylogenetic tree showed that the sequenced strains clustered in two of the six ICV lineages. These findings highlight that ICV can be a cause of CAP of children and that this can be severe enough to require hospitalization.     

Epidemiology and burden of illness of seasonal influenza among the elderly in Japan: A systematic literature review and vaccine effectiveness meta‐analysis

BackgroundElderly populations are particularly vulnerable to influenza and often require extensive clinical support. In Japan, nationwide passive surveillance monitors seasonal influenza but does not capture the full disease burden. We synthesized existing evidence on the epidemiology, vaccine effectiveness (VE), and economic burden of seasonal influenza in the elderly population.MethodsPubMed, EMBASE, and ICHUSHI were searched for articles on seasonal influenza in Japan, published between 1997 and 2018, in English or Japanese. Grey literature was also assessed. A random‐effects meta‐analysis characterized VE of influenza vaccines among studies reporting this information.ResultsOf 1,147 identified articles, 143 met inclusion criteria. Reported incidence rates varied considerably depending on study design, season, study setting and, most importantly, case definition. In nursing homes, the maximum reported attack rate was 55.2% and in the 16 articles reporting mortality rates, case fatality rates varied from 0.009% to 14.3%. Most hospitalizations were in people aged >60; healthcare costs were partially mitigated by vaccine administration. Meta‐analysis estimated overall VE of 19.1% (95% CI: 2.3% ‐ 33.0%) with a high proportion of heterogeneity (I²: 89.1%). There was a trend of lower VE in older people (40.1% [−57.3‐77.2] in the <65 group; 12.9% [−8.0‐29.8] in those 65; P = .21).ConclusionsDespite differences between studies that make comparisons challenging, the influenza burden in elderly Japanese is significant. While vaccines are effective, current vaccination programs offer suboptimal protection. Health economic data and cost‐effectiveness analyses were limited and represent areas for policy‐relevant future research.     

Evidence for an increase in the intensity of inter‐seasonal influenza,Queensland, Australia, 2009‐2019

BackgroundInter‐seasonal influenza cases have been increasing in Australia. Studies of influenza seasonality typically focus on seasonal transmission in temperate regions, leaving our understanding of inter‐seasonal epidemiology limited. We aimed to improve understanding of influenza epidemiology during inter‐seasonal periods across climate zones, and explored influenza intensity and strain dominance patterns over time.MethodsQueensland state‐wide laboratory‐confirmed influenza notifications and public laboratory influenza test data from 2009‐2019 were described by demographics, time period, region and strain type. We compared influenza intensity over time using the WHO Average Curve method to provide thresholds for seasonal and inter‐seasonal periods.ResultsAmong the 243 830 influenza notifications and 490 772 laboratory tests reported in Queensland between 2009 and 2019, 15% of notifications and 40% of tests occurred during inter‐seasonal periods, with 6.3% of inter‐seasonal tests positive. Inter‐seasonal notifications and tests substantially increased over time and increases in weekly proportions positive and intensity classifications suggested gradual increases in virus activity. Tropical inter‐seasonal activity was higher with periods of marked increase. Influenza A was dominant, although influenza B represented up to 72% and 42% of notifications during some seasonal and inter‐seasonal periods, respectively.ConclusionsUsing notification and testing data, we have demonstrated a gradual increase in inter‐seasonal influenza over time. Our findings suggest this increase results from an interplay between testing, activity and intensity, and strain circulation. Seasonal intensity and strain circulation appeared to modify subsequent period intensity. Routine year‐round surveillance data would provide a better understanding of influenza epidemiology during this infrequently studied inter‐seasonal time period.     

Factors associated with COVID‐19 related hospitalisation,critical care admission and mortality using linked primary and secondary care data

BackgroundIt is important that population cohorts at increased risk of hospitalisation and death following a COVID‐19 infection are identified and protected.ObjectivesWe identified risk factors associated with increased risk of hospitalisation, intensive care unit (ICU) admission and mortality in inner North East London (NEL) during the first UK COVID‐19 wave.MethodsMultivariate logistic regression analysis on linked primary and secondary care data from people aged 16 or older with confirmed COVID‐19 infection between 01/02/2020 and 30/06/2020 determined odds ratios (OR), 95% confidence intervals (CI) and P‐values for the association between demographic, deprivation and clinical factors with COVID‐19 hospitalisation, ICU admission and mortality.ResultsOver the study period, 1781 people were diagnosed with COVID‐19, of whom 1195 (67%) were hospitalised, 152 (9%) admitted to ICU and 400 (23%) died. Results confirm previously identified risk factors: being male, or of Black or Asian ethnicity, or aged over 50. Obesity, type 2 diabetes and chronic kidney disease (CKD) increased the risk of hospitalisation. Obesity increased the risk of being admitted to ICU. Underlying CKD, stroke and dementia increased the risk of death. Having learning disabilities was strongly associated with increased risk of death (OR = 4.75, 95% CI = [1.91, 11.84], P = .001). Having three or four co‐morbidities increased the risk of hospitalisation (OR = 2.34, 95% CI = [1.55, 3.54], P < .001; OR = 2.40, 95% CI = [1.55, 3.73], P < .001 respectively) and death (OR = 2.61, 95% CI = [1.59, 4.28], P < .001; OR = 4.07, 95% CI = [2.48, 6.69], P < .001 respectively).ConclusionsWe confirm that age, sex, ethnicity, obesity, CKD and diabetes are important determinants of risk of COVID‐19 hospitalisation or death. For the first time, we also identify people with learning disabilities and multi‐morbidity as additional patient cohorts that need to be actively protected during COVID‐19 waves.