Excess mortality associated with influenza epidemics in Portugal, 1980 to 2004

Influenza-Associated Excess Mortality and Hospitalization in Germany from 1996 to 2018

INTRODUCTION

Influenza-associated excess mortality and morbidity is commonly estimated using statistical methods. In Germany, the Robert Koch Institute (RKI) uses the relative mortality distribution method (RMDM) to estimate influenza-associated excess mortality without reporting age-specific values. In order to better differentiate the distribution of the disease burden, a distinction by age is of high relevance. Therefore, we aimed to revise the existing excess mortality model and provide age-specific excess mortality estimates over multiple seasons. We also used the model to determine influenza-associated excess hospitalizations, since the RKI excess hospitalization model is currently based on another approach (i.e., combination of excess physician visits and hospitalized proportion).

METHODS

This study was a retrospective data analysis based on secondary data of the German population from 1996-2018. We adapted the RKI's method of estimating influenza-associated excess mortality with the RMDM and also applied this approach to excess hospitalizations. We calculated the number of excess deaths/hospitalizations using weekly and age-specific data.

RESULTS

Data available in Germany are suitable for addressing the restrictions of the RKI's mortality model. In total, we estimated 175,858 (176,482 with age stratification) influenza-associated excess all cause deaths between 1995-1996 and 2017-2018 ranging from 0 (17 with age stratification) in 2005-2006 to 25,599 (25,527 with age stratification) in 2017-2018. Total influenza-associated excess deaths were comparable to RKI's estimates in most seasons. Most excess deaths/hospitalizations occurred in patients aged ≥ 60 years (95.42%/57.49%) followed by those aged 35-59 years (3,80%/24,98%). Compared with our model, the RKI hospitalization model implies a substantial underestimation of excess hospitalizations (828,090 vs. 374,200 over all seasons).

CONCLUSION

This is the first study that provides age-specific estimates of influenza-associated excess mortality in Germany. The results clearly show that the main burden of influenza is in the elderly, for whom prevention and control measures should be prioritized.

Meaning and prediction of 'excess mortality': a comparison of Covid-19 and pre-Covid-19 mortality data in 31 Eurostat countries from 1965 to 2021

Determining 'excess mortality' makes it possible to compare the burden of disasters between countries and over time, and thus also to evaluate the success of mitigation measures. However, the debate on coronavirus disease 2019 (Covid-19) has exposed that calculations of excess mortalities vary considerably depending on the method and its specification. Moreover, it is often unclear what exactly is meant by 'excess mortality'. We define excess mortality as the excess over the number of deaths that would have been expected counter-factually, that is without the catastrophic event in question. Based on this definition, we use a very parsimonious calculation method, namely the linear extrapolation of death figures from previous years to determine the excess mortality during the Covid-19 pandemic. But unlike most other literature on this topic, we first evaluated and optimized the specification of our method using a larger historical data set in order to identify and minimize estimation errors and biases. The result shows that excess mortality rates in the literature are often inflated. Moreover, they would have exhibited considerable excess mortalities in the period before Covid-19, if this value had already been of public interest at that time. Three conclusions can be drawn from this study and its findings: (i) All calculation methods for current figures should first be evaluated against past figures. (ii) To avoid alarm fatigue, thresholds should be introduced which would differentiate between 'usual fluctuations' and 'remarkable excess'. (iii) Statistical offices could provide more realistic estimates.

Uncovering the burden of Influenza in children in Portugal, 2008-2018

BACKGROUND

Despite their higher risk of developing severe disease, little is known about the burden of influenza in Portugal in children aged < 5 years old. This study aims to cover this gap by estimating the clinical and economic burden of severe influenza in children, in Portugal, during ten consecutive influenza seasons (2008/09-2017/18).

METHODS

We reviewed hospitalizations in children aged < 5 years old using anonymized administrative data covering all public hospitals discharges in mainland Portugal. The burden of hospitalization and in-hospital mortality directly coded as due to influenza was supplemented by the indirect burden calculated from excess hospitalization and mortality (influenza-associated), estimated for four groups of diagnoses (pneumonia or influenza, respiratory, respiratory or cardiovascular, and all-cause), through cyclic regression models integrating the incidence of influenza. Means were reported excluding the H1N1pdm09 pandemic (2009/10).

RESULTS

The mean annual number of hospitalizations coded as due to influenza was 189 (41.3 cases per 100,000 children aged < 5 years old). Hospitalization rates decreased with increasing age. Nine-in-ten children were previously healthy, but the presence of comorbidities increased with age. Children stayed, on average, 6.1 days at the hospital. Invasive mechanical ventilation was used in 2.4% of hospitalizations and non-invasive in 3.1%. Influenza-associated excess hospitalizations between 2008 and 2018 were estimated at 1,850 in pneumonia or influenza, 1,760 in respiratory, 1,787 in respiratory or cardiovascular, and 1,879 in all-cause models. A total of 95 influenza-associated excess deaths were estimated in all-cause, 14 in respiratory or cardiovascular, and 9 in respiratory models. Over ten years, influenza hospitalizations were estimated to have cost the National Health Service at least €2.9 million, of which 66.5% from healthy children.

CONCLUSIONS

Influenza viruses led to a high number of hospitalizations in children. Most were previously healthy. Results should lead to a reflection on the adequate preventive measures to protect this age group.

Examining the Negative Sentiments Related to Influenza Vaccination from 2017 to 2022: An Unsupervised Deep Learning Analysis of 261,613 Twitter Posts

Several countries are witnessing significant increases in influenza cases and severity. Despite the availability, effectiveness and safety of influenza vaccination, vaccination coverage remains suboptimal globally. In this study, we examined the prevailing negative sentiments related to influenza vaccination via a deep learning analysis of public Twitter posts over the past five years. We extracted original tweets containing the terms 'flu jab', '#flujab', 'flu vaccine', '#fluvaccine', 'influenza vaccine', '#influenzavaccine', 'influenza jab', or '#influenzajab', and posted in English from 1 January 2017 to 1 November 2022. We then identified tweets with negative sentiment from individuals, and this was followed by topic modelling using machine learning models and qualitative thematic analysis performed independently by the study investigators. A total of 261,613 tweets were analyzed. Topic modelling and thematic analysis produced five topics grouped under two major themes: (1) criticisms of governmental policies related to influenza vaccination and (2) misinformation related to influenza vaccination. A significant majority of the tweets were centered around perceived influenza vaccine mandates or coercion to vaccinate. Our analysis of temporal trends also showed an increase in the prevalence of negative sentiments related to influenza vaccination from the year 2020 onwards, which possibly coincides with misinformation related to COVID-19 policies and vaccination. There was a typology of misperceptions and misinformation underlying the negative sentiments related to influenza vaccination. Public health communications should be mindful of these findings.

Factors of influenza vaccine inoculation and non-inoculation behavior of community-dwelling residents in Japan: suggestions for vaccine policy and public health ethics after COVID-19

The aim of this study is to provide basic information that contributes to vaccine inoculation policy after COVID-19. We used the secondary data of the influenza vaccine inoculation behavior survey for community-dwelling adults conducted in 2011, before the COVID-19 pandemic, but after the 2009 novel influenza A (H1N1) pdm 09 pandemic. All factors such as socio-demographic characteristics, health-related behaviors, family environment, physical and social environment, and area of residence were adjusted, and factors related to vaccine inoculation behavior were analyzed. Those living with pregnant women had a significantly higher odds ratio of inoculation; this was self-evident in that those people considered infection to their family. Regarding the social environment, those aged 20–64 years with a significantly higher adjusted odds ratio of inoculation were those with “at least five people with which they interacted in the neighborhood”. This result can be interpreted in two ways relating to altruism in Japan. Finally, we indicated the importance of learning from the past, including the case of 2009.

Evaluation of Cardiac Biomarkers and Expression Analysis of IL-1, IL-6, IL-10, IL-17, and IL-25 among COVID-19 Patients from Pakistan

Coronavirus disease 19 (COVID-19) is caused by viral infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Where upregulation of several important biomarkers and multiple organ dysfunction occurs, this study aimed to evaluate the association of cardiac biomarkers and CS induced acute lung damage with disease severity and mortality in survival of COVID-19 patients. A total of 500 COVID-19 patients with elevated cardiac biomarkers were studied for the analysis of myocardial abnormality through cardiac enzymes, inflammatory biomarkers, and the expression analysis of various cytokines, including IL-1, IL-6, IL-10, IL-17, and IL-25 genes. The elevation of various cardiac enzymes including LDH (87%), CK (78.4%), TNI (80.4%), CK-MB (83%), and D-dimer (80.8%) were found correlated (p < 0.001) with COVID-19 infection. Cardiac enzyme elevation was highly associated with an increased level of inflammatory biomarkers such as CRP (14.2%), SAA (11.4%) and erythrocyte sedimentation rate (ESR) (7.8%) (p = 0.001 for all). The quantitative expression analysis of IL-10, 1L-17, and 1L-25 were found to be high, while those of IL-1 and IL-6 were moderately elevated. The death-to-live ratio of COVID-19 patients was 457:43 indicating that the patients having elevated levels of both CKMB, D-dimer, CK and IL-1, IL-6, IL-10 and D-dimer, Troponin, CK and IL-1, IL-10 had high fatality rate (73% and 12% respectively). The current finding concludes that the evaluation of cardiac biomarkers with cytokine storm plays a significant role in COVID-19-associated anatomical organ damage, myocardial injury, and mortality. Physicians should pay special attention to cardiac biomarkers in patients with old age, inflammation, and comorbidities among COVID-19 infections.

Age-dependent and sex-dependent differences in mortality from influenza-associated cardiovascular diseases among older adults in Shanghai, China: a population-based study

OBJECTIVES

Influenza epidemics lead to substantial morbidity and mortality among older adults. This study aimed to analyse and assess the age-specific and sex-specific differences in mortality rates for cardiovascular disease (CVD) associated with influenza in older adults.

DESIGN

We obtained weekly data on mortality from CVD in adults≥60 years, categorised into five age groups. We used a quasi-Poisson model and adjusted for long-term and seasonal trends and absolute humidity as confounding factors. The male-to-female ratio (M/F ratio) was an indicator for assessing sex differences.

SETTING

Shanghai, China.

PARTICIPANT

We analysed 440 107 CVD deaths in adults aged ≥60 years, including 44 913 cases positive for influenza and 1 927 487 outpatient visits for influenza-like illness from 2010 to 2019.

MAIN OUTCOME MEASURES

Age-specific and sex-specific excess CVD mortality rates in older adults for various combinations of CVDs and influenza viruses.

RESULTS

Variations were observed in the excess mortality from CVD, ischaemic heart disease (IHD) and stroke depending on the influenza types/subtypes in different age and sex categories. The ≥85 years group had the highest excess mortality rates per 100 000 persons for CVD, IHD and stroke, while influenza A (H3N2) virus accounted for the highest mortality from CVD, IHD and stroke in people aged ≥65 years. Older men had a significantly lower influenza-associated IHD mortality rate than women, with an M/F ratio of 0.77 (p<0.05).

CONCLUSIONS

Excess mortality rates for CVDs associated with influenza increased with age in older adults. The risk for influenza-associated IHD mortality was significantly higher in older women than men. Our findings will help implement targeted health strategies, including the promotion of influenza vaccination and early therapeutic intervention for the older population with CVD, to curb the influenza burden effectively.

Mathematical modeling in perspective of vector-borne viral infections: a review

Background

Viral diseases are highly widespread infections caused by viruses. These viruses are passing from one human to other humans through a certain medium. The medium might be mosquito, animal, reservoir and food, etc. Here, the population of both human and mosquito vectors are important.

Main body of the abstract

The main objectives are here to introduce the historical perspective of mathematical modeling, enable the mathematical modeler to understand the basic mathematical theory behind this and present a systematic review on mathematical modeling for four vector-borne viral diseases using the deterministic approach. Furthermore, we also introduced other mathematical techniques to deal with vector-borne diseases. Mathematical models could help forecast the infectious population of humans and vectors during the outbreak.

Short conclusion

This study will be helpful for mathematical modelers in vector-borne diseases and ready-made material in the review for future advancement in the subject. This study will not only benefit vector-borne conditions but will enable ideas for other illnesses.

What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks

Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an alternative retrospective baseline derived from the lowest weekly death rates achieved in previous years and a within-year baseline based on the average of the 13 lowest weekly death rates within the same year. These baselines express normative levels of the lowest feasible target death rates. The excess death rates calculated from these baselines are not distorted by past mortality peaks and do not treat non-pandemic winter mortality excesses as inevitable.

We obtained weekly series for 35 industrialized countries from the Human Mortality Database for 2000–2020. Observed, baseline and excess mortalities were measured by age-standardized death rates. We assessed weekly and annual excess death rates driven by the COVID-19 pandemic in 2020 and those related to seasonal respiratory infections in earlier years. There was a distinct geographic pattern with high excess death rates in Eastern Europe followed by parts of the UK, and countries of Southern and Western Europe. Some Asia-Pacific and Scandinavian countries experienced lower excess mortality. In 2020 and earlier years, the alternative retrospective and the within-year excess mortality figures were higher than estimates based on conventional metrics. While the latter were typically negative or close to zero in years without extraordinary epidemics, the alternative estimates were substantial. Cumulation of this "usual" excess over 2–3 years results in human losses comparable to those caused by COVID-19.

Challenging the view that non-pandemic seasonal winter mortality is inevitable would focus attention on reducing premature mortality in many countries. As SARS-CoV-2 is unlikely to be the last respiratory pathogen with the potential to cause a pandemic, such measures would also strengthen global resilience in the face of similar threats in the future.

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Conventional estimates of excess mortality underestimate potentially avoidable losses.

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We propose metrics based on best weeks in the same and in earlier years.

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Our alternative metrics estimate higher annual excess mortality in 2020 and 2005-19.

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Mortality peaks in non-pandemic years should be regarded as potentially avoidable.

Public Reporting on the Quality of Care in Patients with Acute Myocardial Infarction: The Korean Experience

Public reporting is a way to promote quality of healthcare. However, evidence supporting improved quality of care using public reporting in patients with acute myocardial infarction (AMI) is disputed. This study aims to describe the impact of public reporting of AMI care on hospital quality improvement in Korea. Patients with AMI admitted to the emergency room with ICD-10 codes of I21.0 to I21.9 as the primary or secondary diagnosis were identified from the national health insurance claims data (2007-2012). Between 2007 and 2012, 43,240/83,378 (51.9%) patients manifested ST segment elevation myocardial infarction (STEMI). Timely reperfusion rate increased (β = 2.78, p = 0.001). The mortality rate of STEMI patients was not changed (β = -0.0098, p = 0.384) but that of NSTEMI patients decreased (β = -0.465, p = 0.001). Public reporting has a substantial impact on the process indicators of AMI in Korea because of the increased reperfusion rate. However, the outcome indicators such as mortality did not significantly change, suggesting that public reporting did not necessarily improve the quality of care.

Cost-effectiveness of baloxavir marboxil compared with laninamivir for the treatment of influenza in patients at high risk for complications in Japan

OBJECTIVE

Baloxavir marboxil (baloxavir) is a single-dose antiviral which was previously found to be a cost-effective alternative to laninamivir in otherwise healthy adults in Japan. This study aimed at investigating the cost-effectiveness of baloxavir versus laninamivir in patients with influenza at high risk for complications.

METHODS

A decision tree was utilized to estimate costs and health gains associated with the use of antivirals. A lifetime horizon was applied to capture the long-term impact of influenza complications, and other events with associated costs and health outcomes were accounted for one influenza season. The study population was stratified into three categories: adolescents and non-elderly adults with high-risk conditions (HRC), elderly without other HRC, and elderly with other HRC. The cost-effectiveness was assessed from a public healthcare payer's perspective. The duration of influenza symptoms, probabilities of complications and probabilities of adverse events were obtained from a clinical trial and network meta-analysis. The costs of influenza and adverse events management were derived from the JammNet claims database. Utility values were informed by the clinical trial data and literature. Sensitivity analyses were also performed.

RESULTS

The baloxavir strategy was associated with higher costs (+¥144) and higher quality-adjusted life-years (QALYs) in adults with HRC, elderly without HRC and elderly with HRC (+0.00078, +0.00183 and +0.00350 respectively). The overall incremental cost/QALY for baloxavir versus laninamivir was ¥68,855, which was below the willingness-to-pay threshold of ¥5 million/QALY gained. Key drivers of the model results were the probability of pneumonia and bronchitis. The probability of baloxavir being cost-effective was 72%.

CONCLUSIONS

This study suggests that influenza treatment with baloxavir is cost-effective compared with laninamivir in the adult high-risk population in Japan.

Global short-term forecasting of COVID-19 cases

The continuously growing number of COVID-19 cases pressures healthcare services worldwide. Accurate short-term forecasting is thus vital to support country-level policy making. The strategies adopted by countries to combat the pandemic vary, generating different uncertainty levels about the actual number of cases. Accounting for the hierarchical structure of the data and accommodating extra-variability is therefore fundamental. We introduce a new modelling framework to describe the pandemic's course with great accuracy and provide short-term daily forecasts for every country in the world. We show that our model generates highly accurate forecasts up to seven days ahead and use estimated model components to cluster countries based on recent events. We introduce statistical novelty in terms of modelling the autoregressive parameter as a function of time, increasing predictive power and flexibility to adapt to each country. Our model can also be used to forecast the number of deaths, study the effects of covariates (such as lockdown policies), and generate forecasts for smaller regions within countries. Consequently, it has substantial implications for global planning and decision making. We present forecasts and make all results freely available to any country in the world through an online Shiny dashboard.

Prognostic value of cardiac biomarkers in COVID-19 infection

Multiple Biomarkers have recently been shown to be elevated in COVID-19, a respiratory infection with multi-organ dysfunction; however, information regarding the prognostic value of cardiac biomarkers as it relates to disease severity and cardiac injury are inconsistent. The goal of this meta-analysis was to summarize the evidence regarding the prognostic relevance of cardiac biomarkers from data available in published reports. PubMed, Embase and Web of Science were searched from inception through April 2020 for studies comparing median values of cardiac biomarkers in critically ill versus non-critically ill COVID-19 patients, or patients who died versus those who survived. The weighted mean differences (WMD) and 95% confidence interval (CI) between the groups were calculated for each study and combined using a random effects meta-analysis model. The odds ratio (OR) for mortality based on cardiac injury was combined from studies reporting it. Troponin levels were significantly higher in COVID-19 patients who died or were critically ill versus those who were alive or not critically ill (WMD 0.57, 95% CI 0.43-0.70, p < 0.001). Additionally, BNP levels were also significantly higher in patients who died or were critically ill (WMD 0.45, 95% CI - 0.21-0.69, p < 0.001). Cardiac injury was independently associated with significantly increased odds of mortality (OR 6.641, 95% CI 1.26-35.1, p = 0.03). A significant difference in levels of D-dimer was seen in those who died or were critically ill. CK levels were only significantly higher in those who died versus those who were alive (WMD 0.79, 95% CI 0.25-1.33, p = 0.004). Cardiac biomarkers add prognostic value to the determination of the severity of COVID-19 and can predict mortality.

Excess Winter Mortality (EWM) as a Dynamic Forensic Tool: Where, When, Which Conditions, Gender, Ethnicity and Age

To investigate the dynamic issues behind intra- and international variation in EWM (Excess Winter Mortality) using a rolling monthly EWM calculation. This is used to reveal seasonal changes in the EWM calculation and is especially relevant nearer to the equator where EWM does not reach a peak at the same time each year. In addition to latitude country specific factors determine EWM. Females generally show higher EWM. Differences between the genders are highly significant and seem to vary according to the mix of variables active each winter. The EWM for respiratory conditions in England and Wales ranges from 44% to 83%, which is about double the all-cause mortality equivalent. A similar magnitude of respiratory EWM is observed in other temperate countries. Even higher EWM can be seen for specific respiratory conditions. Age has a profound effect on EWM with a peak at puberty and then increases EWM at older ages. The gap between male and female EWM seems to act as a diagnostic tool reflecting the infectious/metrological mix in each winter. Difference due to ethnicity are also observed. An EWM equivalent calculation for sickness absence demonstrates how other health-related variables can be linked to EWM. Midway between the equator and the poles show the highest EWM since such areas tend to neglect the importance of keeping dwellings warm in the winter. Pandemic influenza does not elevate EWM, although seasonal influenza plays a part each winter. Pandemic influenza and changes in influenza strain/variant mix do, however, create structural breaks in the time series and this implies that comparing EWM between studies conducted over different times can be problematic. Cancer is an excellent example of the usefulness of rolling method since cancer EWM drifts each year, in some years increasing winter EWM and in other years diminishing it. In addition, analysis of sub-national EWM in the UK reveals high spatiotemporal granularity indicating roles for infectious outbreaks. The rolling method gives greater insight into the dynamic nature of EWM, which otherwise lies concealed in the current static method.

An open-sourced, web-based application to analyze weekly excess mortality based on the Short-term Mortality Fluctuations data series

The COVID-19 pandemic stimulated the interest of scientists, decision makers and the general public in short-term mortality fluctuations caused by epidemics and other natural or man-made disasters. To address this interest and provide a basis for further research, in May 2020, the Short-term Mortality Fluctuations data series was launched as a new section of the Human Mortality Database. At present, this unique data resource provides weekly mortality death counts and rates by age and sex for 38 countries and regions. The main objective of this paper is to detail the web-based application for visualizing and analyzing the excess mortality based on the Short-term Mortality Fluctuation data series. The application yields a visual representation of the database that enhances the understanding of the underlying data. Besides, it enables the users to explore data on weekly mortality and excess mortality across years and countries. The contribution of this paper is twofold. First, to describe a visualization tool that aims to facilitate research on short-term mortality fluctuations. Second, to provide a comprehensive open-source software solution for demographic data to encourage data holders to promote their datasets in a visual framework.

SBDiEM: A new mathematical model of infectious disease dynamics

A worldwide multi-scale interplay among a plethora of factors, ranging from micro-pathogens and individual or population interactions to macro-scale environmental, socio-economic and demographic conditions, entails the development of highly sophisticated mathematical models for robust representation of the contagious disease dynamics that would lead to the improvement of current outbreak control strategies and vaccination and prevention policies. Due to the complexity of the underlying interactions, both deterministic and stochastic epidemiological models are built upon incomplete information regarding the infectious network. Hence, rigorous mathematical epidemiology models can be utilized to combat epidemic outbreaks. We introduce a new spatiotemporal approach (SBDiEM) for modeling, forecasting and nowcasting infectious dynamics, particularly in light of recent efforts to establish a global surveillance network for combating pandemics with the use of artificial intelligence. This model can be adjusted to describe past outbreaks as well as COVID-19. Our novel methodology may have important implications for national health systems, international stakeholders and policy makers.

Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect

IntroductionEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges.AimIn a modelling study we combined environmental, epidemiological and laboratory surveillance data to estimate influenza-attributable mortality in Greece, over four seasons (2013/14 to 2016/17), specifically addressing the lag dimension and the confounding effect of temperature.MethodsAssociations of influenza type/subtype-specific incidence proxies and of daily mean temperature with mortality were estimated with a distributed-lag nonlinear model with 30 days of maximum lag, separately by age group (all ages, 15-64 and ≥ 65 years old). Total and weekly deaths attributable to influenza and cold temperatures were calculated.ResultsOverall influenza-attributable mortality was 23.6 deaths per 100,000 population per year (95% confidence interval (CI): 17.8 to 29.2), and varied greatly between seasons, by influenza type/subtype and by age group, with the vast majority occurring in persons aged ≥ 65 years. Most deaths were attributable to A(H3N2), followed by influenza B. During periods of A(H1N1)pdm09 circulation, weekly attributable mortality to this subtype among people ≥ 65 years old increased rapidly at first, but then fell to zero and even negative, suggesting a mortality displacement (harvesting) effect. Mortality attributable to cold temperatures was much higher than that attributable to influenza.ConclusionsStudies of influenza-attributable mortality need to consider distributed-lag effects, stratify by age group and adjust both for circulating influenza virus types/subtypes and daily mean temperatures, in order to produce reliable estimates. Our approach addresses these issues, is readily applicable in the context of influenza surveillance, and can be useful for other countries.

Prognostic value of Cardiac Biomarkers in COVID-19 Infection: A Meta-analysis

Background

Multiple Biomarkers have recently been shown to be elevated in COVID-19, a respiratory infection with multi-organ dysfunction; however, information regarding the prognostic value of cardiac biomarkers as it relates to disease severity and cardiac injury are inconsistent.

Research Question

The goal of this meta-analysis was to summarize the evidence regarding the prognostic relevance of cardiac biomarkers from data available in published reports.

Study Design and Methods

PubMed was searched from inception through April 2020 for studies comparing median values of cardiac biomarkers in critically ill versus non-critically ill COVID-19 patients, or patients who died versus those who survived. The weighted mean differences (WMD) and 95% confidence interval (CI) between the groups were calculated for each study and combined using a random effects meta-analysis model. The odds ratio (OR) for mortality based on cardiac injury was combined from studies reporting it.

Results

Troponin levels were significantly higher in COVID-19 patients who died or were critically ill versus those who were alive or not critically ill (WMD 0.58, 95% CI 0.42–0.71, p<0.001). Cardiac injury was independently associated with significantly increased odds of mortality (OR 6.641, 95% CI 1.26 – 35.1, p=0.03). No difference in BNP was seen between the two groups. A significant difference in levels of D-dimer was seen in those who died or were critically ill. CK levels were only significantly higher in those who died versus those who were alive (WMD 0.47 95% CI 0.09–0.84, p=0.014).

Interpretation

Cardiac biomarkers add prognostic value to the determination of the severity of COVID-19 and can predict mortality.

Impact of national influenza vaccination strategy in severe influenza outcomes among the high-risk Portuguese population

BACKGROUND

All aged individuals with a chronic condition and those with 65 and more years are at increased risk of severe influenza post-infection complications. There is limited research on cases averted by the yearly vaccination programs in high-risk individuals. The objective was to estimate the impact of trivalent seasonal influenza vaccination on averted hospitalizations and death among the high-risk population in Portugal.

METHODS

The impact of trivalent seasonal influenza vaccination was estimated using vaccine coverage, vaccine effectiveness and the number of influenza-related hospitalizations and deaths. The number of averted events (NAE), prevented fraction (PF) and number needed to vaccinate (NVN) were estimated for seasons 2014/15 to 2016/17.

RESULTS

The vaccination strategy averted on average approximately 1833 hospitalizations and 383 deaths per season. Highest NAE was observed in the ≥65 years population (85% of hospitalizations and 95% deaths) and in the 2016/17 season (1957 hospitalizations and 439 deaths). On average, seasonal vaccination prevented 21% of hospitalizations in the population aged 65 and more, and 18.5% in the population with chronic conditions. The vaccination also prevented 29% and 19.5% of deaths in each group of the high-risk population. It would be needed to vaccinate 3360 high-risk individuals, to prevent one hospitalization and 60,471 high-risk individuals to prevent one death.

CONCLUSION

The yearly influenza vaccination campaigns had a sustained positive benefit for the high-risk population, reducing hospitalizations and deaths. These results can support public health plans toward increased vaccine coverage in high-risk groups.

Estimating Influenza-associated Mortality in Korea: The 2009-2016 Seasons

OBJECTIVES

Estimating influenza-associated mortality is important since seasonal influenza affects persons of all ages, causing severe illness or death. This study aimed to estimate influenza-associated mortality, considering both periodic changes and age-specific mortality by influenza subtypes.

METHODS

Using the Microdata Integrated Service from Statistics Korea, we collected weekly mortality data including cause of death. Laboratory surveillance data of respiratory viruses from 2009 to 2016 were obtained from the Korea Centers for Disease Control and Prevention. After adjusting for the annual age-specific population size, we used a negative binomial regression model by age group and influenza subtype.

RESULTS

Overall, 1 859 890 deaths were observed and the average rate of influenza virus positivity was 14.7% (standard deviation [SD], 5.8), with the following subtype distribution: A(H1N1), 5.0% (SD, 5.8); A(H3N2), 4.4% (SD, 3.4); and B, 5.3% (SD, 3.7). As a result, among individuals under 65 years old, 6774 (0.51%) all-cause deaths, 2521 (3.05%) respiratory or circulatory deaths, and 1048 (18.23%) influenza or pneumonia deaths were estimated. Among those 65 years of age or older, 30 414 (2.27%) all-cause deaths, 16 411 (3.42%) respiratory or circulatory deaths, and 4906 (6.87%) influenza or pneumonia deaths were estimated. Influenza A(H3N2) virus was the major contributor to influenza-associated all-cause and respiratory or circulatory deaths in both age groups. However, influenza A(H1N1) virus-associated influenza or pneumonia deaths were more common in those under 65 years old.

CONCLUSIONS

Influenza-associated mortality was substantial during this period, especially in the elderly. By subtype, influenza A(H3N2) virus made the largest contribution to influenza-associated mortality.

Trend of mortality from ischemic heart disease and influenza vaccination in older adults in São Paulo

Abstract The aim of the present study was to analyze the mortality trend due to ischemic heart disease (IHD) among older adults, identify changes in the trend and determine the correlation with influenza vaccine coverage (2000 to 2012) in the state of São Paulo between 1980 and 2012. An ecological time series study was conducted involving secondary data from Brazilian information systems. Linear and polynomial regression models as well as joinpoint regression were used to estimate the trends. Pearson’s correlation coefficient was used to evaluate the correlation between age-standardized mortality coefficients and vaccine coverage. A decreasing tendency in mortality due to IHD occurred in both sexes, higher mortality rates were found for males and greater reductions were found in the period after the vaccination campaigns. However, no statistically significant changes occurred in the year coinciding with or near the onset of the campaigns. In the overall sample, no evidence of a linear correlation was found between the mortality coefficients and vaccination coverage. Other factors directly associated with morbidity and mortality due to ischemic heart disease may have influenced the trend.

[Mortality due to cerebrovascular disease among the elderly and vaccination against influenza: São Paulo State, Brazil, 1980-2012]

This study describes the trend of the coefficients of mortality due to cerebrovascular diseases (CbVD) among the elderly in São Paulo State, Brazil, from 1980 to 2012, before and after influenza vaccination campaigns, and identifies change points. It is an ecological, time-series study carried out with death data from the Health Ministry's Mortality Information System and population data from the Brazilian Institute of Geography and Statistics. We used linear, polynomial and joinpoint regression models in the data analysis. Between 1980 and 2012, there were 480,955 deaths due to CbVD. The mean mortality coefficients decreased for both sexes in all age groups we analyzed, with the greatest reduction in the older ages and male sex. We observed a significant reduction in the mortality trend in 1998 for male sex in the age group 60-69 years (annual percent change - APC = -3%, 95%CI: -4.3; -1.6) and for all elderly (APC = -3.8%, 95%CI: -4.4; -3.1). Considering the period as a whole, we did not observe change points for the age group 70-79 (average annual percent change - AAPC = -3.3%, 95%CI: -3.5; -3.1) and, for male sex, for the group ≥ 80 years (AAPC = -2.9%, 95%CI: -3.1; -2.6). For all elderly, the mean percentage reduction was of 3.1% per year (AAPC = -3.1%, 95%CI: -3.5; -2.7). Results show a reduction in the mortality due to CbVD in the period, with different percentage variations in coefficient reduction. The study's findings add information to the debate regarding possible effects of vaccination campaigns in reducing mortality due to CbVD among the elderly.

Factors influencing seasonal influenza vaccination uptake among health care workers in an adult tertiary care hospital in Singapore: A cross-sectional survey

BACKGROUND

This study aimed to evaluate the factors influencing seasonal influenza vaccination uptake among different health care professional groups.

METHODS

A single-center, cross-sectional survey using a standardized anonymous, self-administered questionnaire to assess knowledge, attitudes, and uptake of seasonal influenza vaccination was used. Associations between respective health care groups and vaccination acceptance were then assessed.

RESULTS

In total, 3,873 health care workers completed the questionnaire. Of these, 7% were administrative staff, 17% were allied health staff, 7% were ancillary staff, 11% were medical staff, and 58% were nursing staff. The overall vaccination rate for the Southern Hemisphere 2015 influenza season was 82%. In a multivariate logistic regression model, after controlling for gender and presence of chronic disease, associated factors for accepting influenza vaccination were age, education level of bachelor degree or higher, preference for vaccination provided by mobile teams, having 1-50 patient contacts per week, and belief in the potential severity of influenza and vaccine safety (P < .05). In contrast, factors negatively associated with vaccination acceptance included being a medical staff member or allied health staff member, living with family members under the age of 16, fear of adverse reactions, and disbelief in vaccination effectiveness (P < .05).

CONCLUSIONS

Although vaccine coverage in Singapore has been high, our findings provide guidance for the development of strategies to further improve vaccine coverage among different groups of health care workers.

Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India

The factors that drive spatial heterogeneity and diffusion of pandemic influenza remain debated. We characterized the spatiotemporal mortality patterns of the 1918 influenza pandemic in British India and studied the role of demographic factors, environmental variables, and mobility processes on the observed patterns of spread. Fever-related and all-cause excess mortality data across 206 districts in India from January 1916 to December 1920 were analyzed while controlling for variation in seasonality particular to India. Aspects of the 1918 autumn wave in India matched signature features of influenza pandemics, with high disease burden among young adults, (moderate) spatial heterogeneity in burden, and highly synchronized outbreaks across the country deviating from annual seasonality. Importantly, we found population density and rainfall explained the spatial variation in excess mortality, and long-distance travel via railroad was predictive of the observed spatial diffusion of disease. A spatiotemporal analysis of mortality patterns during the 1918 influenza pandemic in India was integrated in this study with data on underlying factors and processes to reveal transmission mechanisms in a large, intensely connected setting with significant climatic variability. The characterization of such heterogeneity during historical pandemics is crucial to prepare for future pandemics.

Estimation of exposure-attributable fractions from time series: A simulation study

Burden analysis in public health often involves the estimation of exposure-attributable fractions from observed time series. When the entire population is exposed, the association between the exposure and outcome must be carefully modelled before the attributable fractions can be estimated. This article derives asymptotic convergences for the estimation of attributable fractions for commonly used time series models (ARMAX, Poisson, negative binomial, and Serfling), using for the most part the delta method. For the Poisson regression, the estimation of the attributable fraction is achieved by a Monte Carlo algorithm, taking into account both an estimation and a prediction error. A simulation study compares these estimations in the case of an epidemic exposure and highlights the importance of thorough analysis of the data: When the outcome is generated under an additive model, the additive models are satisfactory, and the multiplicative models are poor, and vice versa. However, the Serfling model performs poorly in all cases. Of note, a misspecification in the form or delay of the association between the exposure and the outcome leads to mediocre estimation of the attributable fraction. An application to the fraction of French outpatient antibiotic use attributable to influenza between 2003 and 2010 illustrates the asymptotic convergences. This study suggests that the Serfling model should be avoided when estimating attributable fractions while the model of choice should be selected after careful investigation of the association between the exposure and outcome.

Estimates of global seasonal influenza-associated respiratory mortality: a modelling study

BACKGROUND

Estimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250 000-500 000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015.

METHODS

We estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and ≥75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods.

FINDINGS

EMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0·1 to 6·4 per 100 000 individuals for people younger than 65 years, 2·9 to 44·0 per 100 000 individuals for people aged between 65 and 74 years, and 17·9 to 223·5 per 100 000 for people older than 75 years. We estimated that 291 243-645 832 seasonal influenza-associated respiratory deaths (4·0-8·8 per 100 000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2·8-16·5 per 100 000 individuals), southeast Asia (3·5-9·2 per 100 000 individuals), and among people aged 75 years or older (51·3-99·4 per 100 000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105 690 influenza-associated respiratory deaths occur annually.

INTERPRETATION

These global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated.

FUNDING

None.

Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review

Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from -0.3-1.3 and 0.6-8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4-119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No "average" estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.

Excess of Mortality in Adults and Elderly and Circulation of Subtypes of Influenza Virus in Southern Brazil

Purpose

In the elderly population, the influenza infection and its clinical complications are important causes of hospitalization and death, particularly, in longer-lived age. The objective of this study is to analyze the impact of influenza virus circulation on mortality in the elderly and adults, in years with different predominant virus strains.

Methods

We performed a time trend study to evaluated excess of mortality for pneumonia and influenza, respiratory disease, and all-causes in southern region of Brazil, from 2002 to 2015. After considering other models, we opted for Serfling regression. Excess of death rates per 100,000 inhabitants were analyzed in specific age groups (24–59, 60–69, 70–79, ≥80 years) and by year of occurrence. Mortality information were taken from Brazilian Mortality Information System and etiological data were accessed in Sentinel Virological Surveillance database, getting the weekly positivity of the immunofluorescence tests for influenza A (H1N1, H3N2), and B.

Results

In southern Brazil, there is an evident seasonal pattern of all death outcomes among different age groups in the dry and cold season (April–September). The highest excess mortality rates occurs among older, particularly in years of circulation of influenza AH3N2, especially among people ≥80 years, in 2003 and 2007—years of great severity of influenza activity. After 2009, with the introduction of the pandemic influenza AH1N1, we observed a lower impact on the mortality of the elderly compared to <60 years.

Discussion

A cross reactivity antibody response from past exposure probably provided protection against disease in the elderly. Despite not controlling for comorbidities, climate, and vaccination, for the >70 years, ratio of respiratory diseases excess mortality rates between AH1N1 (2009) and severe year of H3N2 (2007) shows protection in the pandemic year and great vulnerability during AH3N2 virus predominance.

Conclusion

The reduced immune response to infection, and to vaccination, and presence of comorbidities recommend a special attention to this age group in Brazil. Besides medical assistance, the timeliness of vaccine campaigns, its composition, and etiological surveillance of respiratory diseases are some of the preventive and public health measures.

Excess pneumonia and influenza hospitalizations associated with influenza epidemics in Portugal from season 1998/1999 to 2014/2015

BACKGROUND

The aim of this study was to estimate excess pneumonia and influenza (P&I) hospitalizations during influenza epidemics and measure their correlation with influenza vaccine coverage in the 65 and more years old, according to the type/subtype of influenza virus.

METHODS

The study period comprised week 40/1998-40/2015. Age-specific weekly P&I hospitalizations (ICD-9: 480-487) as main diagnosis were extracted from the National Hospital Discharge database. Age-specific baseline hospitalization rates were estimated by autoregressive integrated moving average (ARIMA) model without time periods with excess hospitalizations. Excess hospitalizations were calculated by subtracting expected hospitalization rates from the observed during influenza epidemic periods. Correlation between excess P&I hospitalizations and influenza vaccine coverage in the elderly was measured with Pearson correlation coefficient.

RESULTS

The average excess P&I hospitalizations/season was 19.4/105 (range 0-46.1/105 ), and higher excess was observed in young children with <2 years (79.8/105 ) and ≥65 years (68.3/105 ). In epidemics with A(H3) dominant, the highest excess hospitalizations were observed among 65 and over. Seasons which influenza B or A(H1)pdm09 dominance the highest excess was observed in children with <2 years. High negative correlation was estimated between excess hospitalizations associated with A(H3) circulation and vaccine coverage in the elderly (r = -.653; 95% CI: -0.950 to -0.137).

CONCLUSION

Over 80% of the influenza epidemics were associated with excess hospitalizations. However, excess P&I hospitalizations pattern differed from age group and circulating virus. This ecologic approach also identified a reduction in excess P&I associated with A(H3) circulation with increasing vaccine coverage in the elderly.

Influenza-associated mortality in Yancheng, China, 2011-15

INTRODUCTION

The Yangtze river delta in eastern China, centered on Shanghai, is one of the most populated regions of the world with more than 100 million residents. We examined the impact of influenza on excess mortality in Yancheng, a prefecture-level city with 8.2 million population located 250 km north of Shanghai, during 2011-2015.

METHODS

We obtained individual data on deaths by date, age, sex, and cause in Yancheng from the Chinese Centers for Disease Control and Prevention, and used these to derive weekly rates of mortality from respiratory causes, respiratory and cardiovascular causes combined, and all causes. We used data on influenza-like illnesses and laboratory detections of influenza to construct a proxy measure of the weekly incidence of influenza virus infections in the community. We used regression models to estimate the association of influenza activity with mortality and excess mortality by age, cause, and influenza type/subtype.

RESULTS

We estimated that an annual average of 4.59 (95% confidence interval: 3.94, 7.41) excess respiratory deaths per 100 000 persons were associated with influenza, which was 4.6% of all respiratory deaths in the years studied. Almost all influenza-associated excess deaths occurred in persons ≥65 years. Influenza A(H3N2) had the greatest impact on mortality and was associated with around 50% of the influenza-associated respiratory deaths in the 5 years studied.

CONCLUSIONS

Influenza has a substantial impact on respiratory mortality in Yancheng, mainly in older adults. Influenza vaccination has the potential to reduce disease burden, and cost-effectiveness analysis could be used to compare policy options.

Excess all-cause and influenza-attributable mortality in Europe, December 2016 to February 2017

Since December 2016, excess all-cause mortality was observed in many European countries, especially among people aged ≥ 65 years. We estimated all-cause and influenza-attributable mortality in 19 European countries/regions. Excess mortality was primarily explained by circulation of influenza virus A(H3N2). Cold weather snaps contributed in some countries. The pattern was similar to the last major influenza A(H3N2) season in 2014/15 in Europe, although starting earlier in line with the early influenza season start.

Translation of the UK Pediatric Influenza Vaccination Programme in Primary Schools to 13 European Countries Using a Dynamic Transmission Model

Objectives: To simulate the impact of a pediatric influenza vaccination programme using quadrivalent live attenuated influenza vaccine (QLAIV) in Europe by applying coverage rates achieved in the United Kingdom during the 2014-2015 season and to compare the model outcomes to the UK results. Methods: We used a deterministic, age-structured, dynamic transmission model adapted to the demography, contact patterns and influenza incidence of 13 European countries, with a 10-year horizon. The reference strategy was the unchanged country-specific coverage rate, using quadrivalent inactivated vaccine (assumed efficacy against infection from 45% in 1-year-old children to 60% in healthy adults). In the evaluated strategy, 56.8% of 5-10-year-old children were additionally vaccinated with QLAIV (assumed efficacy 80%), as was the case in 2014-2015 in the United Kingdom's primary school pilot areas. Symptomatic influenza cases and associated medical resources (primary care consultations [PCC], hospitalization, intensive care unit [ICU] admissions) were calculated. The evaluated versus reference strategies were compared using odds ratios (ORs) for PCC in the target (aged 5-10-years) and non-target adult (aged >17 years) populations as well as number needed to vaccinate (NNV) with QLAIV to avert one PCC, hospitalization or ICU admission. Model outcomes, averaged over 10 seasons, were compared with published real-life data from the United Kingdom for the 2014-2015 season. Results: Over 13 countries and 10 years, the evaluated strategy prevented 32.8 million of symptomatic influenza cases (172.3 vs 205.2 million). The resulting range of ORs for PCC was 0.18-0.48 among children aged 5-10-years, and the published OR in the United Kingdom was 0.06 (95% confidence interval [0.01; 0.62]). In adults, the range of ORs for PCC was 0.60-0.91 (UK OR=0.41 [0.19; 0.86]). NNV ranges were 6-19 per averted PCC (UK NNV=16), 530-1524 per averted hospitalization (UK NNV=317) and 5298-15 241 per averted ICU admission (UK NNV=2205). Conclusions: Across a range of European countries, our model shows the beneficial direct and indirect impact of a paediatric vaccination programme using QLAIV in primary school-aged children, consistent with what was observed during a single season in the United Kingdom. Recommendations for the implementation of pediatric vaccination programmes are, therefore, supported in Europe.

Direct and Indirect Protection with Pediatric Quadrivalent Live-Attenuated Influenza Vaccination in Europe Estimated by a Dynamic Transmission Model

Objectives: To estimate the public health impact of annual vaccination of children with a quadrivalent live-attenuated influenza vaccine (QLAIV) across Europe. Methods: A deterministic, age-structured, dynamic model was used to simulate influenza transmission across 14 European countries, comparing current vaccination coverage using a quadrivalent inactivated vaccine (QIV) to a scenario whereby vaccination coverage was extended to 50% of 2-17 year-old children, using QLAIV. Differential equations described demographic changes, exposure to infectious individuals, recovery and immunity dynamics. For each country, the basic reproduction number (R0) was calibrated to published influenza incidence statistics. Assumed vaccine efficacy for children was 80% (QLAIV) and 59% (QIV). Symptomatic cases cumulated over 10 years were calculated per 100 000 person-years. One-way sensitivity analyses were conducted on QLAIV efficacy in 7-17 year-olds (59% instead of 80%), durations of natural (±3 years; base case: 6, 12 years for influenza A, B respectively) and QLAIV vaccine-induced immunity (100% immunity loss after 1 season; base case: 30%), and R0 (+/-10% around all-year average value). Results: Across countries, annual QLAIV vaccination additionally prevents 1366-3604 symptomatic cases per 100 000 population (average 2495 /100 000, ie, a reduction of 47.6% of the cases which occur in the reference scenario with QIV vaccination only). Among children (2-17 years), QLAIV prevents 551-1555 cases per 100 000 population (average 990 /100 000, ie, 67.2% of current cases). Among adults, QLAIV indirectly prevents 726-2047 cases per 100 000 population (average 1466 /100 000, ie, 40.0% of current cases). The most impactful drivers of total protection were duration of natural immunity against influenza A, R0 and QLAIV immunity duration and efficacy. In all evaluated scenarios, there was a large direct and even larger indirect protection compared with the reference scenario. Conclusions: The model highlights direct and indirect protection benefits when vaccinating healthy children with QLAIV in Europe, across a range of demographic structures, contact patterns and vaccination coverage rates.

Estimating influenza and respiratory syncytial virus-associated mortality in Western Kenya using health and demographic surveillance system data, 2007-2013

Background

Influenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa.

Methods

We used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007–2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths.

Results

Using the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0–93.3) and 17.1 (95% CI 0.0–111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0–28.5) and 7.3 (95% CI 0.0–27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0–122.7]); and with RSV were among <5 years. Using the rate-difference method, the excess mortality rate for influenza and RSV was 44.8 (95% CI 36.8–54.4) and 19.7 (95% CI 14.7–26.5) per 100,000 PY, respectively, for all-cause deaths; and 9.6 (95% CI 6.3–14.7) and 6.6 (95% CI 3.9–11.0) per 100,000 PY, respectively, for respiratory deaths.

Conclusions

Our study shows a substantial excess mortality associated with influenza and RSV in Western Kenya, especially among children <5 years and older persons with TB, supporting recommendations for influenza vaccination and efforts to develop RSV vaccines.

Modelled seasonal influenza mortality shows marked differences in risk by age, sex, ethnicity and socioeconomic position in New Zealand

OBJECTIVES

Influenza is responsible for a large number of deaths which can only be estimated using modelling methods. Such methods have rarely been applied to describe the major socio-demographic characteristics of this disease burden.

METHODS

We used quasi Poisson regression models with weekly counts of deaths and isolates of influenza A, B and respiratory syncytial virus for the period 1994 to 2008.

RESULTS

The estimated average mortality rate was 13.5 per 100,000 people which was 1.8% of all deaths in New Zealand. Influenza mortality differed markedly by age, sex, ethnicity and socioeconomic position. Relatively vulnerable groups were males aged 65-79 years (Rate ratio (RR) = 1.9, 95% CI: 1.9, 1.9 compared with females), Māori (RR = 3.6, 95% CI: 3.6, 3.7 compared with European/Others aged 65-79 years), Pacific (RR = 2.4, 95% CI: 2.4, 2.4 compared with European/Others aged 65-79 years) and those living in the most deprived areas (RR = 1.8, 95% CI: 1.3, 2.4) for New Zealand Deprivation (NZDep) 9&10 (the most deprived) compared with NZDep 1&2 (the least deprived).

CONCLUSIONS

These results support targeting influenza vaccination and other interventions to the most vulnerable groups, in particular Māori and Pacific people and men aged 65-79 years and those living in the most deprived areas.

Beliefs and attitudes towards the influenza vaccine in high-risk individuals

Societal and economic impact of influenza is mainly due to influenza infection of specific groups, who are at higher risk of health complications leading up to hospitalisation or death. In this study we applied the health belief model (HBM) to evaluate beliefs and attitudes towards influenza disease and vaccine in community-dwelling high-risk individuals (aged 65 or more or having a chronic disease). We conducted a mixed-method study using data collected through a telephone survey of a household unit sample. We used thematic analysis to map responses to HBM dimensions and Poisson regression to model vaccine non-uptake prevalence. The main self-reported reason not to take the vaccine referred to the susceptibility dimension: 'considering oneself to be a healthy person' (29·8%, (95% confidence interval (CI) 22·1-38·7)). Bad experiences after vaccination - barriers dimension - were also commonly reported (17·0%, (95% CI 10·8-23·8)). Vaccine non-uptake prevalence was 22% higher in those who did not consider themselves susceptible to contract flu (Prevalence Ratio (PR) = 1·22, (95% CI 1·0-1·5)) and 18% lower in those who did not consider that the vaccine causes flu symptoms (PR = 0·82, (95% CI 0·68-0·99)). Results suggest that high-risk individuals do not think of themselves susceptible to influenza infection and fear adverse events following immunisation.

The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities

It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1-2-day delay, reaching maximum increased risk of death after 6-7 days and lasting up to 20-28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.

Correlates of influenza vaccine uptake among community-dwelling older adults in Brazil

This study aimed at assessing the factors associated with vaccine uptake in a representative sample of community-dwelling Brazilian older adults, specifically focusing on differences in socioeconomic factors among the country regions. We conducted a cross-sectional, population-based study, using a probabilistic household sample in 2013. Individuals aged 60 years or more answered a structured questionnaire informing on vaccination status and sociodemographic and behavioral covariates. Associations between variables were evaluated using prevalence ratios estimated by Poisson regression models. The overall vaccination coverage (72.6%) in older adults ranked lower than the goal of 80% stipulated by the Brazilian health authority; vaccine uptake differed significantly among the country regions. The prevalence of vaccination was lower in black individuals in Brazil than that in their white counterparts. The prevalence of vaccine uptake was significantly associated with covariates on current life style, use of health care, and socioeconomic determinants. Compared with individuals with 0-3 years of education, more schooled individuals had higher prevalence of vaccine uptake in the North, Northeast, and South regions of the country. This study showed that there is room for increasing vaccination coverage among the elderly in Brazil. The knowledge previously obtained on factors significantly associated with vaccine uptake has not prevented them to continue influencing this outcome. The socioeconomic inequality in vaccination in some Brazilian regions reinforces the need of targeting the intervention toward the most vulnerable groups.

Influenza-Associated Excess Mortality in South Korea

INTRODUCTION

It is important to determine the health impact of influenza in order to calibrate public health measures. The objective of this study was to estimate excess mortality associated with influenza in Korea in 2003-2013.

METHODS

The authors constructed multiple linear regression models in 2014 with weekly mortality rates stratified by age, region, and cause of death against weekly surveillance data on influenza virus collected in 2003-2013. Excess mortality rates were estimated using the difference between predicted mortality rates from the fitted model versus predicted mortality rates with the influenza covariate for each strain set to 0.

RESULTS

During the study period, influenza was associated with an average of 2,900 excess deaths per year. The impact of influenza on mortality was significantly higher in older people; the overall all-cause excess annual mortality rate per 100,000 people was 5.97 (95% CI=4.89, 7.19), whereas it was 46.98 (95% CI=36.40, 55.82) for adults aged ≥65 years. It also greatly varied from year to year, ranging from 2.04 in 2009-2010 to 18.76 in 2011-2012.

CONCLUSIONS

The impact of influenza on mortality in Korea is substantial, particularly among the elderly and the rural population. More-comprehensive studies may be needed to estimate the full impact of influenza.

Deaths associated with respiratory syncytial and influenza viruses among persons ≥5 years of age in HIV-prevalent area, South Africa, 1998-2009(1)

We estimated deaths attributable to influenza and respiratory syncytial virus (RSV) among persons >5 years of age in South Africa during 1998-2009 by applying regression models to monthly deaths and laboratory surveillance data. Rates were expressed per 100,000 person-years. The mean annual number of seasonal influenza-associated deaths was 9,093 (rate 21.6). Persons >65 years of age and HIV-positive persons accounted for 50% (n = 4,552) and 28% (n = 2,564) of overall seasonal influenza-associated deaths, respectively. In 2009, we estimated 4,113 (rate 9.2) influenza A(H1N1)pdm09-associated deaths. The mean of annual RSV-associated deaths during the study period was 511 (rate 1.2); no RSV-associated deaths were estimated in persons >45 years of age. Our findings support the recommendation for influenza vaccination of older persons and HIV-positive persons. Surveillance for RSV should be strengthened to clarify the public health implications and severity of illness associated with RSV infection in South Africa.

Enhanced Estimates of the Influenza Vaccination Effect in Preventing Mortality: A Prospective Cohort Study

Mortality is a major end-point in the evaluation of influenza vaccine effectiveness. However, this effect is not well known, since most previous studies failed to show good control of biases. We aimed to estimate the effectiveness of influenza vaccination in preventing all-cause mortality in community-dwelling seniors.Since 2009, a population-based cohort study using healthcare databases has been conducted in Navarra, Spain. In 2 late influenza seasons, 2011/2012 and 2012/2013, all-cause mortality in the period January to May was compared between seniors (65 years or over) who received the trivalent influenza vaccine and those who were unvaccinated, adjusting for demographics, major chronic conditions, dependence, previous hospitalization, and pneumococcal vaccination.The cohort included 103,156 seniors in the 2011/2012 season and 105,140 in the 2012/2013 season (58% vaccinated). Seniors vaccinated in the previous season who discontinued vaccination (6% of the total) had excess mortality and were excluded to prevent frailty bias. The final analysis included 80,730 person-years and 2778 deaths. Vaccinated seniors had 16% less all-cause mortality than those unvaccinated (adjusted rate ratio [RR] = 0.84; 95% confidence interval 0.76-0.93). This association disappeared in the post-influenza period (adjusted RR = 0.96; 95% confidence interval 0.85-1.09). A similar comparison did not find an association in January to May of the 2009/2010 pandemic season (adjusted RR = 0.98; 95% confidence interval 0.84-1.14), when no effect of the seasonal vaccine was expected. On average, 1 death was prevented for every 328 seniors vaccinated: 1 for every 649 in the 65 to 74 year age group and 1 for every 251 among those aged 75 and over.These results suggest a moderate preventive effect and a high potential impact of the seasonal influenza vaccine against all-cause mortality. This reinforces the recommendation of annual influenza vaccination in seniors.

Excess Mortality Associated with Influenza among Tuberculosis Deaths in South Africa, 1999-2009

Background

Published data on the interaction between influenza and pulmonary tuberculosis (PTB) are limited. We aimed to estimate the influenza-associated mortality among individuals with PTB in South Africa from 1999–2009.

Methods

We modelled the excess influenza-associated mortality by applying Poisson regression models to monthly PTB and non-tuberculosis respiratory deaths, using laboratory-confirmed influenza as a covariate.

Results

PTB deaths increased each winter, coinciding with influenza virus circulation. Among individuals of any age, mean annual influenza-associated PTB mortality rate was 164/100,000 person-years (n = 439). The rate of non-tuberculosis respiratory deaths was 27/100,000 (n = 1125) for HIV-infected and 5/100,000 (n = 2367) for HIV-uninfected individuals of all ages. Among individuals aged <65 years, influenza-associated PTB mortality risk was elevated compared to influenza-associated non-tuberculosis respiratory deaths in HIV-infected (relative risk (RR): 5.2; 95% CI: 4.6–5.9) and HIV-uninfected individuals (RR: 61.0; CI: 41.4–91.0). Among individuals aged ≥65 years, influenza-associated PTB mortality risk was elevated compared to influenza-associated non-tuberculosis respiratory deaths in HIV-uninfected individuals (RR: 13.0; 95% CI: 12.0–14.0).

Conclusion

We observed an increased risk of influenza-associated mortality in persons with PTB compared to non-tuberculosis respiratory deaths. If confirmed in other settings, our findings may support recommendations for active inclusion of patients with TB for influenza vaccination and empiric influenza anti-viral treatment of patients with TB during influenza epidemics.

Deaths averted by influenza vaccination in the U.S. during the seasons 2005/06 through 2013/14

BACKGROUND

Excess mortality due to seasonal influenza is substantial, yet quantitative estimates of the benefit of annual vaccination programs on influenza-associated mortality are lacking.

METHODS

We estimated the numbers of deaths averted by vaccination in four age groups (0.5 to 4, 5 to 19, 20 to 64 and ≥65 yrs.) for the nine influenza seasons from 2005/6 through 2013/14. These estimates were obtained using a Monte Carlo approach applied to weekly U.S. age group-specific estimates of influenza-associated excess mortality, monthly vaccination coverage estimates and summary seasonal influenza vaccine effectiveness estimates to obtain estimates of the number of deaths averted by vaccination. The estimates are conservative as they do not include indirect vaccination effects.

RESULTS

From August, 2005 through June, 2014, we estimated that 40,127 (95% confidence interval [CI] 25,694 to 59,210) deaths were averted by influenza vaccination. We found that of all studied seasons the most deaths were averted by influenza vaccination during the 2012/13 season (9398; 95% CI 2,386 to 19,897) and the fewest during the 2009/10 pandemic (222; 95% CI 79 to 347). Of all influenza-associated deaths averted, 88.9% (95% CI 83 to 92.5%) were in people ≥65 yrs. old.

CONCLUSIONS

The estimated number of deaths averted by the US annual influenza vaccination program is considerable, especially among elderly adults and even when vaccine effectiveness is modest, such as in the 2012/13 season. As indirect effects ("herd immunity") of vaccination are ignored, these estimates represent lower bound estimates and are thus conservative given valid excess mortality estimates.

Technical guidelines for the application of seasonal influenza vaccine in China (2014-2015)

Influenza, caused by the influenza virus, is a respiratory infectious disease that can severely affect human health. Influenza viruses undergo frequent antigenic changes, thus could spread quickly. Influenza causes seasonal epidemics and outbreaks in public gatherings such as schools, kindergartens, and nursing homes. Certain populations are at risk for severe illness from influenza, including pregnant women, young children, the elderly, and people in any ages with certain chronic diseases.

Using winter 2009-2010 to assess the accuracy of methods which estimate influenza-related morbidity and mortality

We used the winter of 2009-2010, which had minimal influenza circulation due to the earlier 2009 influenza A(H1N1) pandemic, to test the accuracy of ecological trend methods used to estimate influenza-related deaths and hospitalizations. We aggregated weekly counts of person-time, all-cause deaths, and hospitalizations for pneumonia/influenza and respiratory/circulatory conditions from seven healthcare systems. We predicted the incidence of the outcomes during the winter of 2009-2010 using three different methods: a cyclic (Serfling) regression model, a cyclic regression model with viral circulation data (virological regression), and an autoregressive, integrated moving average model with viral circulation data (ARIMAX). We compared predicted non-influenza incidence with actual winter incidence. All three models generally displayed high accuracy, with prediction errors for death ranging from -5% to -2%. For hospitalizations, errors ranged from -10% to -2% for pneumonia/influenza and from -3% to 0% for respiratory/circulatory. The Serfling and virological models consistently outperformed the ARIMAX model. The three methods tested could predict incidence of non-influenza deaths and hospitalizations during a winter with negligible influenza circulation. However, meaningful mis-estimation of the burden of influenza can still result with outcomes for which the contribution of influenza is low, such as all-cause mortality.

Are influenza-associated morbidity and mortality estimates for those ≥ 65 in statistical databases accurate, and an appropriate test of influenza vaccine effectiveness?

PURPOSES

To assess the accuracy of estimates using statistical databases of influenza-associated morbidity and mortality, and precisely measure influenza vaccine effectiveness.

PRINCIPAL RESULTS

Laboratory testing of influenza is incomplete. Death certificates under-report influenza. Statistical database models are used as an alternative to randomised controlled trials (RCTs) to assess influenza vaccine effectiveness. Evidence of the accuracy of influenza morbidity and mortality estimates was sought from: (1) Studies comparing statistical models. For four studies Poisson and ARIMA models produced higher estimates than Serfling, and Serfling higher than GLM. Which model is more accurate is unknown. (2) Studies controlling confounders. Fourteen studies mostly controlled one confounder (one controlled comorbidities), and limited control of confounders limits accuracy.

EVIDENCE FOR VACCINE EFFECTIVENESS WAS SOUGHT FROM

(1) Studies of regions with increasing vaccination rates. Of five studies two controlled for confounders and one found a positive vaccination effect. Three studies did not control confounders and two found no effect of vaccination. (2) Studies controlling multiple confounders. Of thirteen studies only two found a positive vaccine effect and no mortality differences between vaccinees and non-vaccinees in non-influenza seasons, showing confounders were controlled. Key problems are insufficient testing for influenza, using influenza-like illness, heterogeneity of seasonal and pandemic influenza, population aging, and incomplete confounder control (co-morbidities, frailty, vaccination history) and failure to demonstrate control of confounders by proving no mortality differences between vaccinees and non-vaccinees in non-influenza seasons.

MAJOR CONCLUSIONS

Improving model accuracy requires proof of no mortality differences in pre-influenza periods between the vaccinated and non-vaccinated groups, and reduction in influenza morbidity and mortality in seasons with a good vaccine match, more virulent strains, in the younger elderly with less immune senescence, and specific outcomes (laboratory-confirmed outcomes, pneumonia deaths). Proving influenza vaccine effectiveness requires appropriately powered RCTs, testing participants with RT-PCR tests, and comprehensively monitoring morbidity and mortality.