The role of influenza in the epidemiology of pneumonia

Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review

Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation.

Cost-effectiveness of influenza vaccination with a high dose quadrivalent vaccine of the elderly population in Belgium, Finland, and Portugal

BACKGROUND

Seasonal influenza may result in severe outcomes, resulting in a significant increase of hospitalizations during the winter. To improve the protection provided by the standard dose influenza quadrivalent vaccine (SDQIV), a high-dose vaccine (HDQIV) has been developed specifically for adults aged 60 and older who are at higher risk of life-threatening complications.

OBJECTIVES

The aim of this study was to determine the cost-effectiveness of HD QIV vs. SD-QIV in the recommended population of three European countries: Belgium, Finland and Portugal.

METHODS

A cost-utility analysis comparing HDQIV vs. SDQIV was conducted using a decision tree estimating health outcomes conditional on influenza: cases, general practitioner and emergency department visits, hospitalizations and deaths. To account for the full benefit of the vaccine, an additional outcome-hospitalizations attributable to influenza-was also evaluated. Demographic, epidemiological and economic inputs were based on the respective local data. HDQIV relative vaccine efficacy vs. SDQIV was obtained from a phase IV efficacy randomized clinical trial. The incremental cost-effectiveness ratios (ICER) were computed for each country, and a probabilistic sensitivity analysis (1,000 simulations per country) was performed to assess the robustness of the results.

RESULTS

In the base case analysis, HDQIV resulted in improved health outcomes (visits, hospitalizations, and deaths) compared to SDQIV. The ICERs computed were 1,397, 9,581, and 15,267 €/QALY, whereas the PSA yielded 100, 100, and 84% of simulations being cost-effective at their respective willingness-to-pay thresholds, for Belgium, Finland, and Portugal, respectively.

CONCLUSION

In three European countries with different healthcare systems, HD-QIV would contribute to a significant improvement in the prevention of influenza health outcomes while being cost-effective.

Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths

Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.

Virucidal Activity of Essential Oils From Citrus x aurantium L. Against Influenza A Virus H1N1:Limonene as a Potential Household Disinfectant Against Virus

This work explored the compositions of a crude extract of peels of Citrus x aurantium using a gas chromatography-mass spectrometry (GC-MS) technique. The crude extract of peels of C. ×  aurantium was analyzed by GC-MS revealing the presence of limonene as the major compound, accounting for 93.7% of the total. Virucidal activity of the oil of C. x aurantium peels against influenza A virus H1N1 was evaluated by the ASTM E1053-20 method. Moreover, the virucidal activity was also investigated of D-limonene, the major terpene in essential oils of C. x aurantium, and its enantiomer L-limonene. The essential oil of the C. x aurantium peels produced a log reduction of 1.9 to 2.0, accounting for 99% reduction of the virus, while D- and L-limonene exhibited virucidal activity with a log reduction of 3.70 to 4.32 at concentrations of 125 and 250.0 µg/mL, thus reducing the virus by 99.99%. Previous work found that D-limonene exhibited antiviral activity against herpes simplex virus, but L-limonene, an enantiomer of D-limonene, has never been reported for antiviral activity. This work demonstrates the antiviral activity of L-limonene for the first time. Moreover, this work suggests that concentrations of 0.0125% to 0.025% of either D- or L-limonene can possibly be used as a disinfectant against viruses, probably in the form of essential oil sprays, which may be useful disinfectants against the airborne transmission of viruses, such as influenza and COVID-19.

Cost-utility analysis of influenza vaccination in a population aged 65 years or older in Spain with a high-dose vaccine versus an adjuvanted vaccine

BACKGROUND

The normal ageing process is accompanied by immunosenescence and a progressive weakening of the immune system. High-dose inactivated influenza quadrivalent vaccine (HD-QIV) has shown greater immunogenicity, relative efficacy, and effectiveness than the standard-dose inactivated quadrivalent vaccine (SD-QIV). The aim of the study was to assess the cost-utility of an HD-QIV strategy compared with an adjuvanted trivalent inactivated vaccine (aTIV) strategy in the population above 65 years of age in Spain.

METHODS

We evaluated the public health and economic benefits of alternatives by using a decision-tree model, which included influenza cases, visits to the general practitioner (GP), visits to the emergency department (ED), hospitalisations, and mortality related to influenza. We performed deterministic and probabilistic sensitivity analyses to account for both epidemiological and economical sources of uncertainty.

RESULTS

Our results show that switching from aTIV strategy to HD-QIV would prevent 36,476 cases of influenza, 5,143 visits to GP, 1,054 visits to the ED, 9,193 episodes of hospitalisation due to influenza or pneumonia, and 357 deaths due to influenza - increasing 3,514 life-years and 3,167 quality-adjusted life-years (QALYs). Healthcare costs increase by €78,874,301, leading to an incremental cost-effectiveness ratio (ICER) of €24,353/QALY. The sensitivity analysis indicates that the results are rather robust.

CONCLUSION

Our analysis shows that HD-QIV in people over 65 years of age is an influenza-prevention strategy that is at least cost-effective, if not dominant, in Spain. It reduces cases of influenza, GP visits, hospitalisations, deaths, and associated healthcare costs.

Burden of pneumonia in patients with viral and bacterial coinfection in Spain during six consecutive influenza seasons, from 2009-10 to 2014-15

PURPOSE

Lower respiratory infections remain the most lethal communicable disease worldwide. Viral and bacterial coinfections (VBC) are common complications in patients with seasonal influenza and are associated with around 25% of all influenza-related deaths. The burden of pneumonia in patients with VBC in Spain is poorly characterized. To address this question, we aimed to provide population data over a period of six consecutive influenza seasons, from 2009-10 to 2014-15.

METHODS

We used the discharge report from the Minimum Basic Data Set (MBDS), published annually by the Spanish Ministry of Health, to retrospectively analyse hospital discharge data in individuals aged ≥60 years with a diagnosis of pneumonia and influenza, based on the International Classification of Diseases (ICD-9-CM codes 480-486 and 487-488, respectively), from 1 October 2009 to 30 September 2015.

RESULTS

In total, 1933 patients ≥60 years old were hospitalized for pneumonia and influenza, of whom 55.2% were male. The median age was 74 years (interquartile range [IRQ] 15); half of the patients were ≥75 years old. Influenza was the main diagnosis in 64.4% of the patients, and all-cause pneumonia in 15.8%, half of whom were assigned a diagnostic code for pneumococcal pneumonia. The mean annual hospitalization rate was 2.99 per 100,000 population (95% CI 2.9-3.1) throughout the study period, while the highest rate, 5.6 per 100,000 population (95% CI 5.2-6.0), was observed in the 2013-14 season. The mean annual mortality rate was 0.5 deaths per 100,000 population (95% CI 0.4-0.6) and in-hospital case fatality rate was 16.1% (95% CI 14.5-17.8).

CONCLUSIONS

In Spain, community-acquired pneumonia and influenza continue to be an important cause of hospitalization and mortality in patients over 60 years of age. There is an urgent need to further develop prevention strategies such as joint vaccination for both pathologies.

Overview of Viral Pneumonia Associated With Influenza Virus, Respiratory Syncytial Virus, and Coronavirus, and Therapeutics Based on Natural Products of Medicinal Plants

Viral pneumonia has been a serious threat to global health, especially now we have dramatic challenges such as the COVID-19 pandemic. Approximately six million cases of community-acquired pneumonia occur every year, and over 20% of which need hospital admission. Influenza virus, respiratory virus, and coronavirus are the noteworthy causative agents to be investigated based on recent clinical research. Currently, anaphylactic reaction and inflammation induced by antiviral immunity can be incriminated as causative factors for clinicopathological symptoms of viral pneumonia. In this article, we illustrate the structure and related infection mechanisms of these viruses and the current status of antiviral therapies. Owing to a set of antiviral regiments with unsatisfactory clinical effects resulting from side effects, genetic mutation, and growing incidence of resistance, much attention has been paid on medicinal plants as a natural source of antiviral agents. Previous research mainly referred to herbal medicines and plant extracts with curative effects on viral infection models of influenza virus, respiratory virus, and coronavirus. This review summarizes the results of antiviral activities of various medicinal plants and their isolated substances, exclusively focusing on natural products for the treatment of the three types of pathogens that elicit pneumonia. Furthermore, we have introduced several useful screening tools to develop antiviral lead compounds.

Ambient particulate matter (PM1, PM2.5, PM10) and childhood pneumonia: The smaller particle, the greater short-term impact?

BACKGROUND

Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia.

AIMS

We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), respectively.

METHODS

Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM₁, PM_2.5, PM₁₀, and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed.

RESULTS

For each 10 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM₁ effects, while PM_2.5 and PM₁₀ effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM₁, but PM_2.5 and PM₁₀ were only associated with children aged 1-4 years. Furthermore, PM₁ effects were greater in autumn and winter, while greater PM_2.5 and PM₁₀ effects were evident only in autumn.

CONCLUSION

This study suggests a greater short-term impact on childhood pneumonia from PM₁ in comparison to PM_2.5 and PM₁₀. Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.

Interrupted time-series analyses of routine vaccination program for elderly pneumonia patients in Japan; an ecological study using aggregated nationwide inpatient data

A national routine pneumococcal pneumonia immunization program started in Japan in 2014. It targeted the population aged ≥65 years and used a 23-valent pneumococcal polysaccharide vaccine; PPSV23. However, its effectiveness was not well defined because of the lack of a comprehensive database on the PPSV23 vaccination status of each subject. We used interrupted time-series analyses to assess the changes in the incidence and prognosis of elderly patients hospitalized for pneumonia before and after initiation of the program. First, we estimated the PPSV23 coverage rates in subjects aged ≥65 years based on the number of shipped PPSV23 syringes and the estimated population in each prefecture. The estimated coverage rates reached around 40% in 2014 for the 3 Tohoku prefectures, while those in the other prefectures remained below 20%. After the national routine immunization program started, the estimated coverage rate increased significantly in every prefecture and exceeded 40% in 2017. Next, we aggregated the data extracted from the Japanese Diagnosis Procedure Combination database from April 2011 through February 2017 for hospitalized pneumonia patients aged ≥65 years. The data included data from 655,746 patients, excluding those in the 3 Tohoku prefectures. Interrupted time-series analyses found no change in the incidence of hospitalized pneumonia patients and in-hospital mortality after the vaccination program, but there was a decrease in the in-hospital mortality of pneumonia patients with severe comorbidities defined by the modified Charlson comorbidity index. These results suggest an association between the vaccination program and an improved outcome in hospitalized elderly pneumonia patients with severe comorbidities in Japan.

Pneumococcal nasopharyngeal carriage among Bhutanese children hospitalized with clinical pneumonia: serotypes and viral co-infection

BACKGROUND

Pneumococcal nasopharyngeal colonization (PNC) generally precedes pneumococcal disease. The purpose of this study was to determine the prevalence of PNC and to identify the pneumococcal serotypes circulating among Bhutanese children under five years of age admitted with clinical pneumonia, before the introduction of pneumococcal conjugate vaccine (PCV13) in the country. We also aimed to contribute to the understanding of the interplay between PNC and viral co-infection among this population.

METHODS

This was a prospective study conducted at the Jigme Dorji Wangchuck National Referral Hospital in Bhutan over 12 consecutive months. Children aged 2 to 59 months admitted with WHO-defined clinical pneumonia were eligible for recruitment. We collected blood for bacterial culture and molecular identification of S. pneumoniae, and nasopharyngeal washing for screening of respiratory viruses, and for the detection and capsular typing of S. pneumoniae by real-time polymerase chain reaction (RT-PCR).

RESULTS

Overall, 189 children were recruited, and PNC was tested in 121 of them (64.0%). PNC was found in 76/121 children (62.8%) and S. pneumoniae was identified in blood (both by culture and RT-PCR) in a single child. Respiratory viruses were detected in a similar proportion among children with (62/70; 88.6%) and without PNC (36/40; 90.0%; p = 1.000), but rhinovirus detection was less common among children with PNC (20/70; 28.6% versus 19/40; 47.5%; p = 0.046). Capsular typing identified 30 different serotypes. Thirty-nine children (51.3%) were colonised with two to five different serotypes. A third of the children presented with serotypes considered highly invasive. Over half of the children (44/76; 57.9%) were carrying at least one serotype included in PCV13.

CONCLUSIONS

This study provides baseline information on the status of PNC among Bhutanese children admitted with clinical pneumonia prior to the introduction of PCV13, which is valuable to monitor its potential impact. PCV13 could theoretically have averted up to 58% of the pneumococcal infections among the children in this study, suggesting a future role for the vaccine to significantly reduce the burden associated with S. pneumoniae in Bhutan.

miR-29a is a negative regulator of influenza virus infection through targeting of the frizzled 5 receptor

Influenza A virus (IAV) infections result in a large number of deaths and substantial economic losses each year. MicroRNAs repress gene expression and are involved in virus-host interactions. miR-29a is known to have anti-tumor and anti-fibrotic effects. However, the role of miR-29a in IAV infection is unclear. In the present study, we investigated the effect of miR-29a on IAV infection and the mechanisms by which it functions. IAV infection was found to cause decreased miR-29a expression in lung epithelial A549 cells and mouse lungs. Overexpression of miR-29a reduced IAV mRNA and protein levels and progeny virus production in HEK293 and A549 cells. Inhibition of IAV infection by miR-29a was observed with different strains of IAV, including A/PR/8/34, A/WSN/1933, and clinical isolates A/OK/3052/09 and A/OK/309/06 H3N2. Knockout of miR-29a using CRISPR/Cas9 resulted in an increase in viral mRNA and protein levels, confirming that miR-29a suppresses IAV infection. A 3' untranslated region (3'-UTR) reporter assay showed that miR-29a had binding sites in the 3'-UTR of the Wnt-Ca²⁺ signaling receptor frizzled 5 gene, and overexpression of miR-29a reduced the level of the endogenous frizzled 5 protein. Wnt5a treatment of HEK293 and A549 cells enhanced IAV infection. Our results suggest that miR-29a inhibits IAV infection, probably via the frizzled 5 receptor.

Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance

Influenza and pneumonia independently lead to high morbidity and mortality annually among the human population globally; however, a glaring fact is that influenza pneumonia coinfection is more vicious and it is a threat to public health. Emergence of antiviral resistance is a major impediment in the control of the coinfection. In this paper, a deterministic mathematical model illustrating the transmission dynamics of influenza pneumonia coinfection is formulated having incorporated antiviral resistance. Optimal control theory is then applied to investigate optimal strategies for controlling the coinfection using prevalence reduction and treatment as the system control variables. Pontryagin's maximum principle is used to characterize the optimal control. The derived optimality system is solved numerically using the Runge-Kutta-based forward-backward sweep method. Simulation results reveal that implementation of prevention measures is sufficient to eradicate influenza pneumonia coinfection from a given population. The prevention measures could be social distancing, vaccination, curbing mutation and reassortment, and curbing interspecies movement of the influenza virus.

Humanized Mice for Live-Attenuated Vaccine Research: From Unmet Potential to New Promises

Live-attenuated vaccines (LAV) represent one of the most important medical innovations in human history. In the past three centuries, LAV have saved hundreds of millions of lives, and will continue to do so for many decades to come. Interestingly, the most successful LAVs, such as the smallpox vaccine, the measles vaccine, and the yellow fever vaccine, have been isolated and/or developed in a purely empirical manner without any understanding of the immunological mechanisms they trigger. Today, the mechanisms governing potent LAV immunogenicity and long-term induced protective immunity continue to be elusive, and therefore hamper the rational design of innovative vaccine strategies. A serious roadblock to understanding LAV-induced immunity has been the lack of suitable and cost-effective animal models that can accurately mimic human immune responses. In the last two decades, human-immune system mice (HIS mice), i.e., mice engrafted with components of the human immune system, have been instrumental in investigating the life-cycle and immune responses to multiple human-tropic pathogens. However, their use in LAV research has remained limited. Here, we discuss the strong potential of LAVs as tools to enhance our understanding of human immunity and review the past, current and future contributions of HIS mice to this endeavor.

Quantifying the consequences of measles-induced immune modulation for whooping cough epidemiology

Measles, an acute viral disease, continues to be an important cause of childhood mortality worldwide. Infection with the measles virus is thought to be associated with a transient but profound period of immune suppression. Recently, it has been claimed that measles-induced immune manipulation lasts for about 30 months and results in increased susceptibility to other co-circulating infectious diseases and more severe disease outcomes upon infection. We tested this hypothesis using model-based inference applied to parallel historical records of measles and whooping cough mortality and morbidity. Specifically, we used maximum likelihood to fit a mechanistic transmission model to incidence data from three different eras, spanning mortality records from 1904 to 1912 and 1922 to 1932 and morbidity records from 1946 to 1956. Our aim was to quantify the timing, severity and pathogenesis impacts of measles-induced immune modulation and their consequences for whooping cough epidemiology across a temporal gradient of measles transmission. We identified an increase in susceptibility to whooping cough following recent measles infection by approximately 85-, 10- and 36-fold for the three eras, respectively, although the duration of this effect was variable. Overall, while the immune impacts of measles may be strong and clearly evident at the individual level, their epidemiological signature in these data appears both modest and inconsistent. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Age-Related Differences in Hospitalization Rates, Clinical Presentation, and Outcomes Among Older Adults Hospitalized With Influenza-U.S. Influenza Hospitalization Surveillance Network (FluSurv-NET)

BACKGROUND

Rates of influenza hospitalizations differ by age, but few data are available regarding differences in laboratory-confirmed rates among adults aged ≥65 years.

METHODS

We evaluated age-related differences in influenza-associated hospitalization rates, clinical presentation, and outcomes among 19 760 older adults with laboratory-confirmed influenza at 14 FluSurv-NET sites during the 2011-2012 through 2014-2015 influenza seasons using 10-year age groups.

RESULTS

There were large stepwise increases in the population rates of influenza hospitalization with each 10-year increase in age. Rates ranged from 101-417, 209-1264, and 562-2651 per 100 000 persons over 4 influenza seasons in patients aged 65-74 years, 75-84 years, and ≥85 years, respectively. Hospitalization rates among adults aged 75-84 years and ≥85 years were 1.4-3.0 and 2.2-6.4 times greater, respectively, than rates for adults aged 65-74 years. Among patients hospitalized with laboratory-confirmed influenza, there were age-related differences in demographics, medical histories, and symptoms and signs at presentation. Compared to hospitalized patients aged 65-74 years, patients aged ≥85 years had higher odds of pneumonia (aOR, 1.2; 95% CI, 1.0-1.3; P = .01) and in-hospital death or transfer to hospice (aOR, 2.1; 95% CI, 1.7-2.6; P < .01).

CONCLUSIONS

Age-related differences in the incidence and severity of influenza hospitalizations among adults aged ≥65 years can inform prevention and treatment efforts, and data should be analyzed and reported using additional age strata.

Estimating age-stratified influenza-associated invasive pneumococcal disease in England: A time-series model based on population surveillance data

BACKGROUND

Measures of the contribution of influenza to Streptococcus pneumoniae infections, both in the seasonal and pandemic setting, are needed to predict the burden of secondary bacterial infections in future pandemics to inform stockpiling. The magnitude of the interaction between these two pathogens has been difficult to quantify because both infections are mainly clinically diagnosed based on signs and symptoms; a combined viral-bacterial testing is rarely performed in routine clinical practice; and surveillance data suffer from confounding problems common to all ecological studies. We proposed a novel multivariate model for age-stratified disease incidence, incorporating contact patterns and estimating disease transmission within and across groups.

METHODS AND FINDINGS

We used surveillance data from England over the years 2009 to 2017. Influenza infections were identified through the virological testing of samples taken from patients diagnosed with influenza-like illness (ILI) within the sentinel scheme run by the Royal College of General Practitioners (RCGP). Invasive pneumococcal disease (IPD) cases were routinely reported to Public Health England (PHE) by all the microbiology laboratories included in the national surveillance system. IPD counts at week t, conditional on the previous time point t-1, were assumed to be negative binomially distributed. Influenza counts were linearly included in the model for the mean IPD counts along with an endemic component describing some seasonal background and an autoregressive component mimicking pneumococcal transmission. Using age-specific counts, Akaike information criterion (AIC)-based model selection suggested that the best fit was obtained when the endemic component was expressed as a function of observed temperature and rainfall. Pneumococcal transmission within the same age group was estimated to explain 33.0% (confidence interval [CI] 24.9%-39.9%) of new cases in the elderly, whereas 50.7% (CI 38.8%-63.2%) of incidence in adults aged 15-44 years was attributed to transmission from another age group. The contribution of influenza on IPD during the 2009 pandemic also appeared to vary greatly across subgroups, being highest in school-age children and adults (18.3%, CI 9.4%-28.2%, and 6.07%, CI 2.83%-9.76%, respectively). Other viral infections, such as respiratory syncytial virus (RSV) and rhinovirus, also seemed to have an impact on IPD: RSV contributed 1.87% (CI 0.89%-3.08%) to pneumococcal infections in the 65+ group, whereas 2.14% (CI 0.87%-3.57%) of cases in the group of 45- to 64-year-olds were attributed to rhinovirus. The validity of this modelling strategy relies on the assumption that viral surveillance adequately represents the true incidence of influenza in the population, whereas the small numbers of IPD cases observed in the younger age groups led to significant uncertainty around some parameter estimates.

CONCLUSIONS

Our estimates suggested that a pandemic wave of influenza A/H1N1 with comparable severity to the 2009 pandemic could have a modest impact on school-age children and adults in terms of IPD and a small to negligible impact on infants and the elderly. The seasonal impact of other viruses such as RSV and rhinovirus was instead more important in the older population groups.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

Project Tycho 2.0: a repository to improve the integration and reuse of data for global population health

Objective

In 2013, we released Project Tycho, an open-access database comprising 3.6 million counts of infectious disease cases and deaths reported for over a century by public health surveillance in the United States. Our objective is to describe how Project Tycho version 1 (v1) data has been used to create new knowledge and technology and to present improvements made in the newly released version 2.0 (v2).

Materials and Methods

We analyzed our user database and conducted online searches to analyze the use of Project Tycho v1 data. For v2, we added new US data and dengue data for other countries, and grouped data into 360 datasets, each with a digital object identifier and rich metadata. In addition, we used standard vocabularies to encode data where possible, improving compliance with FAIR (findable, accessible, interoperable, reusable) guiding principles for data management.

Results

Since release, 3174 people have registered to use Project Tycho data, leading to 18 new peer-reviewed papers and 27 other creative works, such as conference papers, student theses, and software applications. Project Tycho v2 comprises 5.7 million counts of infectious diseases in the United States and of dengue-related conditions in 98 additional countries.

Discussion

Project Tycho v2 contributes to improving FAIR compliance of global health data, but more work is needed to develop community-accepted standard representations for global health data.

Conclusion

FAIR principles are a valuable guide for improving the integration and reuse of data in global health to improve disease control and save lives.

Ecology and evolution of facilitation among symbionts

Facilitation occurs when one species positively impacts the fitness of another, and has predominantly been studied in free-living species like plants. Facilitation can also occur among symbiont (mutualistic or parasitic) species or strains, but equivalent studies are scarce. To advance an integrated view of the effect of facilitation on symbiont ecology and evolution, we review empirical evidence and their underlying mechanisms, explore the factors favouring its emergence, and discuss its consequences for virulence and transmission. We argue that the facilitation concept can improve understanding of the evolutionary forces shaping symbiont communities and their effects on hosts.

Characterizing and Comparing the Seasonality of Influenza-Like Illnesses and Invasive Pneumococcal Diseases Using Seasonal Waveforms

The seasonalities of influenza-like illnesses (ILIs) and invasive pneumococcal diseases (IPDs) remain incompletely understood. Experimental evidence indicates that influenza-virus infection predisposes to pneumococcal disease, so that a correspondence in the seasonal patterns of ILIs and IPDs might exist at the population level. We developed a method to characterize seasonality by means of easily interpretable summary statistics of seasonal shape-or seasonal waveforms. Nonlinear mixed-effects models were used to estimate those waveforms based on weekly case reports of ILIs and IPDs in 5 regions spanning continental France from July 2000 to June 2014. We found high variability of ILI seasonality, with marked fluctuations of peak amplitudes and peak times, but a more conserved epidemic duration. In contrast, IPD seasonality was best modeled by a markedly regular seasonal baseline, punctuated by 2 winter peaks in late December to early January and January to February. Comparing ILI and IPD seasonal waveforms, we found indication of a small, positive correlation. Direct models regressing IPDs on ILIs provided comparable results, even though they estimated moderately larger associations. The method proposed is broadly applicable to diseases with unambiguous seasonality and is well-suited to analyze spatially or temporally grouped data, which are common in epidemiology.

Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is ("Isolate-Inactivate-Inject") Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview

Vaccines are public health interventions aimed at preventing infections-related mortality, morbidity, and disability. While vaccines have been successfully designed for those infectious diseases preventable by preexisting neutralizing specific antibodies, for other communicable diseases, additional immunological mechanisms should be elicited to achieve a full protection. “New vaccines” are particularly urgent in the nowadays society, in which economic growth, globalization, and immigration are leading to the emergence/reemergence of old and new infectious agents at the animal–human interface. Conventional vaccinology (the so-called “vaccinology 1.0”) was officially born in 1796 thanks to the contribution of Edward Jenner. Entering the twenty-first century, vaccinology has shifted from a classical discipline in which serendipity and the Pasteurian principle of the three Is (isolate, inactivate, and inject) played a major role to a science, characterized by a rational design and plan (“vaccinology 3.0”). This shift has been possible thanks to Big Data, characterized by different dimensions, such as high volume, velocity, and variety of data. Big Data sources include new cutting-edge, high-throughput technologies, electronic registries, social media, and social networks, among others. The current mini-review aims at exploring the potential roles as well as pitfalls and challenges of Big Data in shaping the future vaccinology, moving toward a tailored and personalized vaccine design and administration.

Modeling and inference for infectious disease dynamics: a likelihood-based approach

Likelihood-based statistical inference has been considered in most scientific fields involving stochastic modeling. This includes infectious disease dynamics, where scientific understanding can help capture biological processes in so-called mechanistic models and their likelihood functions. However, when the likelihood of such mechanistic models lacks a closed-form expression, computational burdens are substantial. In this context, algorithmic advances have facilitated likelihood maximization, promoting the study of novel data-motivated mechanistic models over the last decade. Reviewing these models is the focus of this paper. In particular, we highlight statistical aspects of these models like overdispersion, which is key in the interface between nonlinear infectious disease modeling and data analysis. We also point out potential directions for further model exploration.

Influenza B virus reverse genetic backbones with improved growth properties in the EB66® cell line as basis for vaccine seed virus generation

Vaccination remains the best available prophylaxis to prevent influenza virus infections, yet current inadequacies in influenza virus vaccine manufacturing often lead to vaccine shortages at times when the vaccine is most needed, as it was the case during the last influenza virus pandemic. Novel influenza virus vaccine production systems will be crucial to improve public health and safety. Here we report the optimization of influenza B virus growth in the proprietary EB66® cell line, currently in use for human vaccine production. To this end, we collected, curated and sequenced 71 influenza B viruses selected for high diversity in date of isolation and lineage. This viral collection was tested for ability to enter and replicate within EB66® cells in a single cycle assay and appears to readily infect these cells. When the collection was tested for viral progeny production in a multi-cycle assay, we found a large variation from strain to strain. The strains with the top growth characteristics from the B/Victoria and B/Yamagata lineages were selected for vaccine backbone generation using a reverse genetics system. We then showed that these backbones maintain their desirable growth within EB66® cells when the HA and NA from poorly growing strains were substituted for the parental segments, indicating that the selected backbones are viable options for vaccine production in EB66®. Finally, we show that compounds previously reported to enhance influenza virus growth in cell culture also increase virus production in the EB66® cell line.

Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling

Evidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, which have become critical in public health decision-making. Yet models usually focus on influenza virus acquisition and infection alone, thereby making broad oversimplifications of pathogen ecology. Herein, we report evidence of influenza virus interactions with bacteria and viruses and systematically review the modelling studies that have incorporated interactions. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitidis, respiratory syncytial virus (RSV), human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. The notable exception is the pneumococcus-influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approach to test biological hypotheses on interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and possible misinterpretation, and we illustrate the impact of interactions on public health surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures. Finally, we identify the public health, surveillance, modelling, and biological challenges and propose avenues of research for the coming years.

Efficacy of Maternal Influenza Vaccination Against All-Cause Lower Respiratory Tract Infection Hospitalizations in Young Infants: Results From a Randomized Controlled Trial

Background

Influenza immunization of pregnant women protects their young infants against laboratory-confirmed influenza infection. Influenza infection might predispose to subsequent bacterial infections that cause severe pneumonia. In a secondary analysis of a randomized clinical trial (RCT), we evaluated the effect of maternal vaccination on infant hospitalizations for all-cause acute lower respiratory tract infection (ALRI).

Methods

Infants born to women who participated in a double-blind placebo-controlled RCT in 2011 and 2012 on the efficacy of trivalent inactivated influenza vaccine (IIV) during pregnancy were followed during the first 6 months of life.

Results

The study included 1026 infants born to IIV recipients and 1023 born to placebo recipients. There were 52 ALRI hospitalizations (median age, 72 days). The incidence (per 1000 infant-months) of ALRI hospitalizations was lower in infants born to IIV recipients (3.4 [95% confidence interval {CI}, 2.2-5.4]; 19 cases) compared with placebo recipients (6.0 [95% CI, 4.3-8.5]; 33 cases) with a vaccine efficacy of 43.1% (P = .050). Thirty of the ALRI hospitalizations occurred during the first 90 days of life, 9 in the IIV group (3.0 [95% CI, 1.6-5.9]) and 21 in the placebo group (7.2 [95% CI, 4.7-11.0]) (incidence rate ratio, 0.43 [95% CI, .19-.93]) for a vaccine efficacy of 57.5% (P = .032). The incidence of ALRI hospitalizations was similar in the IIV and placebo group for infants >3 months of age. Forty-four of the hospitalized infants were tested for influenza virus infection and 1 tested positive.

Conclusions

Using an RCT as a vaccine probe, influenza vaccination during pregnancy decreased all-cause ALRI hospitalization during the first 3 months of life, suggesting possible protection against subsequent bacterial infections that influenza infection might predispose to.

Clinical Trial Registration

NCT01306669.

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

INTRODUCTION

Influenza-Like Illness is a leading cause of hospitalization in children. Disease burden due to influenza and other respiratory viral infections is reported on a population level, but clinical scores measuring individual changes in disease severity are urgently needed. Areas covered: We present a composite clinical score allowing individual patient data analyses of disease severity based on systematic literature review and WHO-criteria for uncomplicated and complicated disease. The 22-item ViVI Disease Severity Score showed a normal distribution in a pediatric cohort of 6073 children aged 0-18 years (mean age 3.13; S.D. 3.89; range: 0 to 18.79). Expert commentary: The ViVI Score was correlated with risk of antibiotic use as well as need for hospitalization and intensive care. The ViVI Score was used to track children with influenza, respiratory syncytial virus, human metapneumovirus, human rhinovirus, and adenovirus infections and is fully compliant with regulatory data standards. The ViVI Disease Severity Score mobile application allows physicians to measure disease severity at the point-of care thereby taking clinical trials to the next level.

A Narrative Review of Influenza: A Seasonal and Pandemic Disease

Influenza is an acute respiratory disease caused by the influenza A or B virus. It often occurs in outbreaks and epidemics worldwide, mainly during the winter season. Significant numbers of influenza virus particles are present in the respiratory secretions of infected persons, so infection can be transmitted by sneezing and coughing via large particle droplets. The mean duration of influenza virus shedding in immunocompetent adult patients is around 5 days but may continue for up to 10 days or more-particularly in children, elderly adults, patients with chronic illnesses, and immunocompromised hosts. Influenza typically begins with the abrupt onset of high-grade fever, myalgia, headache, and malaise. These manifestations are accompanied by symptoms of respiratory tract illnesses such as nonproductive cough, sore throat, and nasal discharge. After a typical course, influenza can affect other organs such as the lungs, brain, and heart more than it can affect the respiratory tract and cause hospitalization. The best way to prevent influenza is to administer annual vaccinations. Among severely ill patients, an early commencement of antiviral treatment (<2 d from illness onset) is associated with reduced morbidity and mortality, with greater benefits allied to an earlier initiation of treatment. Given the significance of the disease burden, we reviewed the latest findings in the diagnosis and management of influenza.

Hajj vaccinations-facts, challenges, and hope

Vaccination is an effective preventive measure that has been used in the unique Hajj pilgrimage setting to control the transmission of infectious diseases. The current vaccination policy applied during Hajj is reviewed herein, highlighting the effectiveness of the approaches applied and identifying research gaps that need to be filled in order to improve the development and dissemination of Hajj vaccination strategies.