Evaluation of coseasonality of influenza and invasive pneumococcal disease: results from prospective surveillance

The pathogenesis of ventilator-associated pneumonia: old and new mechanisms

INTRODUCTION

Ventilator-associated pneumonia (VAP), defined as a lung infection that occurs in patients after 48 hours on mechanical ventilation, is among the most frequently found nosocomial infections in intensive care units around the world and is associated with increased morbidity, mortality, and economic burden.

AREAS COVERED

We review the classical mechanisms of VAP development and explore more recent ones, such as dysbiosis, which has changed our view of the pathogenesis of the disease; whereas in the past the lower respiratory tract was classically considered a sterile organ, the use of new diagnostic techniques has shown that the lungs of healthy humans are inhabited by a large, dynamic ecosystem of microorganisms. Dysbiosis is the disruption of this ecosystem and is a key factor in the development of VAP. Recent findings have demonstrated that host immunity is microbiome-regulated and, consequently, is profoundly affected by dysbiosis. In this paper the significance of the microbiome-immunity crosstalk in the pathophysiology of VAP will be discussed.

EXPERT OPINION

A deeper understanding of mechanisms of VAP pathogenesis should help to devise new preventive, diagnostic and therapeutic strategies for reducing the incidence of this condition and for improving patient prognosis.

A cooperativity between virus and bacteria during respiratory infections

Respiratory tract infections remain the leading cause of morbidity and mortality worldwide. The burden is further increased by polymicrobial infection or viral and bacterial co-infection, often exacerbating the existing condition. Way back in 1918, high morbidity due to secondary pneumonia caused by bacterial infection was known, and a similar phenomenon was observed during the recent COVID-19 pandemic in which secondary bacterial infection worsens the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) condition. It has been observed that viruses paved the way for subsequent bacterial infection; similarly, bacteria have also been found to aid in viral infection. Viruses elevate bacterial infection by impairing the host's immune response, disrupting epithelial barrier integrity, expression of surface receptors and adhesion proteins, direct binding of virus to bacteria, altering nutritional immunity, and effecting the bacterial biofilm. Similarly, the bacteria enhance viral infection by altering the host's immune response, up-regulation of adhesion proteins, and activation of viral proteins. During co-infection, respiratory bacterial and viral pathogens were found to adapt and co-exist in the airways of their survival and to benefit from each other, i.e., there is a cooperative existence between the two. This review comprehensively reviews the mechanisms involved in the synergistic/cooperativity relationship between viruses and bacteria and their interaction in clinically relevant respiratory infections.

The effects of the COVID-19 pandemic on community respiratory virus activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused substantial global morbidity and deaths, leading governments to turn to non-pharmaceutical interventions to slow down the spread of infection and lessen the burden on health care systems. These policies have evolved over the course of the COVID-19 pandemic, including after the availability of COVID-19 vaccines, with regional and country-level differences in their ongoing use. The COVID-19 pandemic has been associated with changes in respiratory virus infections worldwide, which have differed between virus types. Reductions in respiratory virus infections, including by influenza virus and respiratory syncytial virus, were most notable at the onset of the COVID-19 pandemic and continued in varying degrees through subsequent waves of SARS-CoV-2 infections. The decreases in community infection burden have resulted in reduced hospitalizations and deaths associated with non-SARS-CoV-2 respiratory infections. Respiratory virus evolution relies on the maintaining of a diverse genetic pool, but evidence of genetic bottlenecking brought on by case reduction during the COVID-19 pandemic has resulted in reduced genetic diversity of some respiratory viruses, including influenza virus. By describing the differences in these changes between viral species across different geographies over the course of the COVID-19 pandemic, we may better understand the complex factors involved in community co-circulation of respiratory viruses.

Association of Influenza Activity and Environmental Conditions With the Risk of Invasive Pneumococcal Disease

IMPORTANCE

Streptococcus pneumoniae is the most commonly identified cause of bacterial pneumonia, and invasive pneumococcal disease (IPD) has a high case fatality rate. The wintertime coseasonality of influenza and IPD in temperate countries has suggested that pathogen-pathogen interaction or environmental conditions may contribute to IPD risk.

OBJECTIVES

To evaluate the short-term associations of influenza activity and environmental exposures with IPD risk in temperate countries and to examine the generalizability of such associations across multiple jurisdictions.

DESIGN, SETTING, AND PARTICIPANTS

This case-crossover analysis of 19 566 individuals with IPD from 1998 to 2011 combined individual-level outcomes of IPD and population-level exposures. Participants lived in 12 jurisdictions in Canada (the province of Alberta and cities of Toronto, Vancouver, and Halifax), Australia (Perth, Sydney, Adelaide, Brisbane, and Melbourne), and the United States (Baltimore, Providence, and Philadelphia). Data were analyzed in 2019.

EXPOSURES

Influenza activity, mean temperature, absolute humidity, and UV radiation at delays of 1 to 3 weeks before case occurrence in each jurisdiction.

MAIN OUTCOMES AND MEASURES

Matched odds ratios (ORs) for IPD associated with changes in exposure variables, estimated using multivariable conditional logistic regression models. Heterogeneity in effects across jurisdictions were evaluated using random-effects meta-analytic models.

RESULTS

This study included 19 566 patients: 9629 from Australia (mean [SD] age, 42.8 [30.8] years; 5280 [54.8%] men), 8522 from Canada (only case date reported), and 1415 from the United States (only case date reported). In adjusted models, increased influenza activity was associated with increases in IPD risk 2 weeks later (adjusted OR [aOR] per SD increase, 1.07; 95% CI, 1.01-1.13). Increased humidity was associated with decreased IPD risk 1 week later (aOR per 1 g/m3, 0.98; 95% CI, 0.96-1.00). Other associations were heterogeneous; metaregression suggested that combinations of environmental factors might represent unique local risk signatures. For example, the heterogeneity in effects of UV radiation and humidity at a 2-week lag was partially explained by variation in temperature (UV index: coefficient, 0.0261; 95% CI, 0.0078 to 0.0444; absolute humidity: coefficient, -0.0077; 95% CI, -0.0125 to -0.0030).

CONCLUSIONS AND RELEVANCE

In this study, influenza was associated with increased IPD risk in temperate countries. This association was not explained by coseasonality or case characteristics and appears generalizable. Absolute humidity was associated with decreased IPD risk in the same jurisdictions. The generalizable nature of these associations has important implications for influenza control and advances the understanding of the seasonality of this important disease.

Influenza increases invasive meningococcal disease risk in temperate countries

OBJECTIVES

Invasive meningococcal disease (IMD) is a severe bacterial infection that displays wintertime seasonality in temperate countries. Mechanisms driving seasonality are poorly understood and may include environmental conditions and/or respiratory virus infections. We evaluated the contribution of influenza and environmental conditions to IMD risk, using standardized methodology, across multiple geographical regions.

METHODS

We evaluated 3276 IMD cases occurring between January 1999 and December 2011 in 11 jurisdictions in Australia, Canada, France and the United States. Effects of environmental exposures and normalized weekly influenza activity on IMD risk were evaluated using a case-crossover design. Meta-analytic methods were used to evaluate homogeneity of effects and to identify sources of between-region heterogeneity.

RESULTS

After adjustment for environmental factors, elevated influenza activity at a 2-week lag was associated with increased IMD risk (adjusted odds ratio (OR) per standard deviation increase 1.29; 95% confidence interval, 1.04-1.59). This increase was homogeneous across the jurisdictions studied. By contrast, although associations between environmental exposures and IMD were identified in individual jurisdictions, none was generalizable.

CONCLUSIONS

Using a self-matched design that adjusts for both coseasonality and case characteristics, we found that surges in influenza activity result in an acute increase in population-level IMD risk. This effect is seen across diverse geographic regions in North America, France and Australia. The impact of influenza infection on downstream meningococcal risk should be considered a potential benefit of influenza immunization programmes.

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.

Unraveling the seasonal epidemiology of pneumococcus

Infections caused by Streptococcus pneumoniae-including invasive pneumococcal diseases (IPDs)-remain a significant public health concern worldwide. The marked winter seasonality of IPDs is a striking, but still enigmatic aspect of pneumococcal epidemiology in nontropical climates. Here we confronted age-structured dynamic models of carriage transmission and disease with detailed IPD incidence data to test a range of hypotheses about the components and the mechanisms of pneumococcal seasonality. We find that seasonal variations in climate, influenza-like illnesses, and interindividual contacts jointly explain IPD seasonality. We show that both the carriage acquisition rate and the invasion rate vary seasonally, acting in concert to generate the marked seasonality typical of IPDs. We also find evidence that influenza-like illnesses increase the invasion rate in an age-specific manner, with a more pronounced effect in the elderly than in other demographics. Finally, we quantify the potential impact of seasonally timed interventions, a type of control measures that exploit pneumococcal seasonality to help reduce IPDs. Our findings shed light on the epidemiology of pneumococcus and may have notable implications for the control of pneumococcal infections.

Predictors of yearly influenza vaccination in hospitalized and community based patients

Background

Understanding positive and negative influences on adult immunization status can help healthcare providers to better identify and target patients who are likely to need immunization. Our aim was to assess and compare influenza and pneumococcal (IV/PV) immunisation rates to identify vaccination predictors in Malta.

Method

One group consisted of all medical patients discharged from Mater Dei Hospital (MDH) over a one week period in February 2013. Patients were administered a phone questionnaire. A second group of patients receiving community-based care at local health centres over a one week period in March 2013 were interviewed, identifying vaccination eligibility as per 2010 WHO recommendations.

Results

A total of 150 community (Mean age 61.5 SD 15.8, Male 60%) and 149 hospitalised (Mean age 66.8, SD 13.6%, Male 48.3%) patients in whom influenza vaccine was indicated were recruited. In the current year, 44 and 48.3% received the seasonal influenza vaccine, while 32.0, and 49% vaccinated yearly respectively. Pneumococcal vaccination advice was less than 5% in both groups. On stepwise binary regression, vaccination predictors for the current year were regular yearly influenza vaccination (OR 93.62, CI: 31.8-275.5, p < 0.001) and vaccination reminders (OR 27.5, CI: 9.63-78.31, p < 0.001). Nursing home residence (OR 5.78, CI: 1.22-27.4,p = 0.011), congestive cardiac failure (OR 2.11, CI: 1.1-4.08, p = 0.02) and diabetes mellitus (OR 1.68, CI: 1.04-2.72, p = 0.034) were all predictors for vaccination on exclusion of the strongest two predictors. For successive yearly vaccination, influenza vaccine recommendation by healthcare professionals (OR 12.35, CI: 4.5-33.91, p < 0.001) and vaccination reminders (OR 5.99, CI: 3.13-11.45, p < 0.01) were main predictors. Congestive cardiac failure (OR 2.37, CI: 1.20-4.7, p = 0.13) and nursing home residence (OR 7.07, CI: 1.45-34.5, p = 0,005) were also positive predictors. Male gender was a negative predictor (OR 0.51, CI: 0.31-0.83, p = 0.006). Some of those who did not vaccinate were unaware of such need (40.5% of community and 15.6% of hospitalised patients).

Conclusions

Just under half of the patient population received the IV during 2012-2013 period. Hospitalized patients are more likely to vaccinate regularly while a large proportion of community patients are unaware of the indication to vaccinate.

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.

Association of seasonal viral acute respiratory infection with pneumococcal disease: a systematic review of population-based studies

OBJECTIVE

Animal and in vitro studies suggest that viral acute respiratory infection (VARI) can predispose to pneumococcal infection. These findings suggest that the prevention of VARI can yield additional benefits for the control of pneumococcal disease (PD). In population-based studies, however, the evidence is not in accordance, possibly due to a variety of methodological challenges and problems in these studies. We aimed to summarise and critically review the methods and results from these studies in order to inform future studies.

METHODS

We conducted a systematic review of population-based studies that analysed the association between preceding seasonal VARI and subsequent PD. We searched MEDLINE, Embase and Global Health databases using tailored search strategies.

RESULTS

A total of 28 studies were included. After critically reviewing the methodologies and findings, 11 studies did not control for seasonal factors shared by VARI and PD. This, in turn, could lead to an overestimation of the association between the two illnesses. One case-control study was limited by its small sample size (n case=13). The remaining 16 studies that controlled for seasonal factors suggested that influenza and/or respiratory syncytial virus (RSV) infections were likely to be associated with the subsequent occurrence of PD (influenza: 12/14 studies; RSV: 4/5 studies). However, these 16 studies were unable to conduct individual patient data-based analyses. Nevertheless, these studies suggested the association between VARI and subsequent PD was related to additional factors such as virus type and subtype, age group, comorbidity status, presentation of PD and pneumococcal serotype.

CONCLUSIONS

Population-based studies do not give consistent support for an association between preceding seasonal VARI and subsequent PD incidence. The main methodological challenges of existing studies include the failure to use individual patient data, control for seasonal factors of VARI and PD, or include other factors related to the association (eg, virus, age, comorbidity and pneumococcal serotype).

[Influenzae and pneumococcal vaccination rate in an internal medicine ward]

INTRODUCTION

Vaccination against influenza virus and Streptococcus pneumoniae is a global health priority and authorities, on the basis of recent publications, have recently updated French recommendations. The aim of this study was to describe the influenzae and pneumococcal vaccination's rate in an internal medicine ward.

MATERIAL AND METHODS

All patients consecutively hospitalized during a 10 week-period in an internal medicine ward were included. The reasons for non-vaccination and the impact of an educational program for corrective measures were reported.

RESULTS

Overall, 198 consecutive patients were included; 93 (47%) were immunocompromised; 142 (71.2%) had an indication for pneumococcal vaccination and 171 (86.4%) for influenza vaccination but only 16.2% and 55% of them were vaccinated against these microorganisms, respectively. Prior pneumococcal vaccination was more frequently observed in immunocompromised patients than in non-immunocompromised patients (21.1 versus 6.4%; P=0.029), but no significant difference was observed for influenza vaccine. Corrective measures were initiated in 46 patients (39%), non-immunized against S. pneumoniae.

CONCLUSION

These results underline the very low prevalence of pneumococcal vaccination rate in at-risk hospitalized patients, as compared with influenza, despite recent recommendations.

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.

Increased incidence of adult pneumococcal pneumonia during school holiday periods

Child contact is a recognised risk factor for adult pneumococcal disease. Peaks in invasive pneumococcal disease incidence observed during winter holidays may be related to changes in social dynamics. This analysis was conducted to examine adult pneumococcal community-acquired pneumonia (CAP) incidence during school holiday periods.

Between September 2008 and 2013, consecutive adults admitted to hospitals covering the Greater Nottingham area with a diagnosis of CAP were studied. Pneumococcal pneumonia was detected using culture and antigen detection methods.

Of 2221 adults studied, 575 (25.9%) were admitted during school holidays and 643 (29.0%) had pneumococcal CAP. CAP of pneumococcal aetiology was significantly more likely in adults admitted during school holidays compared to term time (35.3% versus 26.7%; adjusted OR 1.38, 95% CI 1.11–1.72, p=0.004). Over the 5-year period, the age-adjusted incidence of hospitalised pneumococcal CAP was higher during school holidays compared to term time (incident rate ratio 1.35, 95% CI 1.14–1.60, p<0.001); there was no difference in rates of all-cause CAP or non-pneumococcal CAP. Reported child contact was higher in individuals with pneumococcal CAP admitted during school holidays compared to term time (42.0% versus 33.7%, OR 1.43, 95% CI 1.00–2.03, p=0.046).

Further study of transmission dynamics in relation to these findings and to identify appropriate intervention strategies is warranted.

School holiday periods are associated with an increased incidence of adult pneumococcal community-acquired pneumoniahttp://ow.ly/JiAb3089Gii

Temporal cross-correlation between influenza-like illnesses and invasive pneumococcal disease in The Netherlands

Background

While the burden of community‐acquired pneumonia and invasive pneumococcal disease (IPD) is still considerable, there is little insight in the factors contributing to disease. Previous research on the lagged relationship between respiratory viruses and pneumococcal disease incidence is inconclusive, and studies correcting for temporal autocorrelation are lacking.

Objectives

To investigate the temporal relation between influenza‐like illnesses (ILI) and IPD, correcting for temporal autocorrelation.

Methods

Weekly counts of ILI were obtained from the Sentinel Practices of NIVEL Primary Care Database. IPD data were collected from the Dutch laboratory‐based surveillance system for bacterial meningitis from 2004 to 2014. We analysed the correlation between time series, pre‐whitening the dependent time series with the best‐fit seasonal autoregressive integrated moving average (SARIMA) model to the independent time series. We performed cross‐correlations between ILI and IPD incidences, and the (pre‐whitened) residuals, in the overall population and in the elderly.

Results

We found significant cross‐correlations between ILI and IPD incidences peaking at lags ‐3 overall and at 1 week in the 65+ population. However, after pre‐whitening, no cross‐correlations were apparent in either population group.

Conclusion

Our study suggests that ILI occurrence does not seem to be the major driver of IPD incidence in The Netherlands.

Increased Invasive Pneumococcal Disease, North East England, UK

Since April 2014, invasive pneumococcal disease incidence has increased substantially across North East England, United Kingdom, reversing the decline that followed the 2006 introduction of pneumococcal conjugate vaccines. Significant increases occurred in 23-valent polysaccharide vaccine serotypes and nonvaccine serotypes. Trends in other regions and long-term effects of multivalent vaccines require further investigation.

The role of influenza in the epidemiology of pneumonia

Interactions arising from sequential viral and bacterial infections play important roles in the epidemiological outcome of many respiratory pathogens. Influenza virus has been implicated in the pathogenesis of several respiratory bacterial pathogens commonly associated with pneumonia. Though clinical evidence supporting this interaction is unambiguous, its population-level effects-magnitude, epidemiological impact and variation during pandemic and seasonal outbreaks-remain unclear. To address these unknowns, we used longitudinal influenza and pneumonia incidence data, at different spatial resolutions and across different epidemiological periods, to infer the nature, timing and the intensity of influenza-pneumonia interaction. We used a mechanistic transmission model within a likelihood-based inference framework to carry out formal hypothesis testing. Irrespective of the source of data examined, we found that influenza infection increases the risk of pneumonia by ~100-fold. We found no support for enhanced transmission or severity impact of the interaction. For model-validation, we challenged our fitted model to make out-of-sample pneumonia predictions during pandemic and non-pandemic periods. The consistency in our inference tests carried out on several distinct datasets, and the predictive skill of our model increase confidence in our overall conclusion that influenza infection substantially enhances the risk of pneumonia, though only for a short period.

Many respiratory viruses have temporal association with meningococcal disease

BACKGROUND

Previous ecological studies have shown a temporal and spatial association between influenza epidemics and meningococcal disease (MNG); however, none have examined more than two respiratory viruses.

METHODS

Data were obtained in Chile between 2000 and 2005 on confirmed cases of MNG and all confirmed cases of respiratory viruses (influenza A and B; parainfluenza; adenovirus; and respiratory syncytial virus [RSV]). Both variables were divided by epidemiological weeks, age range, and regions. Models of transference functions were run for rates of MNG.

RESULTS

In this period, 1022 reported cases of MNG and 34,737 cases of respiratory virus were identified (25,137 RSV; 4300 parainfluenza; 2527 influenza-A; 356 influenza-B; and 2417 adenovirus). RSV was the major independent virus temporally associated to MNG (it appears one week before MNG), followed by parainfluenza, influenza-B, adenovirus, and influenza-A.

CONCLUSIONS

The rate of MNG in Chile is temporally associated to all of the respiratory viruses studied, but with variability according age range, and regions.

Malaria incidence from 2005-2013 and its associations with meteorological factors in Guangdong, China

BACKGROUND

The temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population's susceptibility in Guangdong, China.

METHODS

The Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population's susceptibility to meteorological effects by malaria type, gender, and age group.

RESULTS

An incidence rate of 1.1 cases per 1,000,000 people was detected in Guangdong from 2005-2013. High temperature was associated with an observed increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI): 1.06-2.33) by comparing 30°C to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI: 1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation increased malaria incidence after four weeks with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI: 1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.

CONCLUSION

Temperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were distinct among sub-groups. This study provided helpful information for predicting malaria incidence and developing the future warning system.

Pneumococcal vaccination in older adults in the era of childhood vaccination: Public health insights from a Norwegian statistical prediction study

Two different vaccines, a 23-valent polysaccharide vaccine (PPV23) and a 13-valent conjugate vaccine (PCV13), are available for prevention of invasive pneumococcal disease (IPD) in the population aged 65 years and older (65+). The IPD epidemiology in the 65+ is undergoing change due to indirect effects of childhood immunisation. Vaccine recommendations for the 65+ must take into account these trends in epidemiology. We therefore explored the preventive potential of vaccination strategies to prevent IPD in the 65+, including PPV23, PCV13 or PCV13 + PPV23 in 2014-2019. Quasi-Poisson regression models were fitted to 2004-2014 population-wide surveillance data and used to predict incidences for vaccine-type and non-vaccine type IPD. We determined the number of people needed to be vaccinated to prevent one case per season (NNV) for each strategy and estimated the public health impact on the IPD case counts from increasing the vaccine uptake to 28-45%. Our results indicate that PCV13-IPD will decrease by 71% from 58 (95% prediction interval 55-61) cases in 2014/15 to 17 (6-52) in 2018/19 and PPV23-IPD by 32% from 168 (162-175) to 115 (49-313) cases. The NNV will increase over time for all strategies because of a decreasing vaccine-type IPD incidence. In 2018/19, the PCV13-NNV will be 5.3 times higher than the PPV23-NNV. Increasing the vaccine uptake will lead to a larger public health impact for all scenarios. Combining PCV13 and PPV23 is most effective, but the additional effect of PCV13 will decrease and is only marginal in 2018/19. Our study demonstrates the importance of increasing PPV23 uptake and of developing vaccines that confer broader immunity.

Impact of influenza season and environmental factors on the clinical presentation and outcome of invasive pneumococcal disease

Influenza and meteorological factors have been associated with increases in the incidence of invasive pneumococcal disease (IPD). However, scant data regarding the impact of influenza and the environment on the clinical presentation of IPD are available. An observational study of all adults hospitalized with IPD was performed between 1996 and 2012 in our hospital. The incidence of IPD correlated with the incidence rates of influenza and with environmental data. A negative binominal regression was used to assess the relationship between these factors. Clinical presentation of IPD during the influenza and non-influenza periods was compared. During the study, 1,150 episodes of IPD were diagnosed. After adjusting for confounding variables, factors correlating with the rates of IPD were the incidence of influenza infection (IRR 1.229, 95% CI 1.025-1.472) and the average ambient temperature (IRR 0.921, 95% CI 0.88-0.964). Patients with IPD during the influenza period had a worse respiratory status. A greater proportion of patients had respiratory failure (45.6% vs 52%, p = 0.032) and higher requirements for ICU admission (19.3% vs 24.7%, p = 0.018) and mechanical ventilation (11% vs 15.1%, p = 0.038). When we stratified by invasiveness of pneumococcal serotypes and the presence of comorbid conditions, the increase in the severity of clinical presentation was focused on healthy adults with IPD caused by nonhighly invasive serotypes. Beyond the increase in the burden of IPD associated with influenza, a more severe clinical pattern of pneumococcal disease was observed in the influenza period. This effect varied according to pneumococcal serotype, host comorbidities, and age.

Disseminated Infections

The ability of microorganisms to cause infection is governed by multiple different factors – some linked to the microorganisms itself and others to the host or environment. In this chapter we explore some of these factors and provide an overview of disseminated infections examining some important manifestations such as toxic shock syndrome and sepsis as well as examining some of molecular aspects including host receptors and bacterial antigens. A brief discussion will also follow about disseminated infections in specific populations such as neonates and the immunosuppressed.

Risk factors for invasive pneumococcal disease among children less than 5 years of age in a high HIV prevalence setting, South Africa, 2010 to 2012

BACKGROUND

Invasive pneumococcal disease (IPD) causes significant disease burden, especially in developing countries, even in the era of pneumococcal conjugate vaccine and maternal-to-child HIV transmission prevention programs. We evaluated factors that might increase IPD risk in young children in a high HIV prevalence setting.

METHODS

We conducted a case-control study using IPD cases identified at 24 Group for Enteric, Respiratory and Meningeal disease Surveillance-South Africa program sites (2010-2012). At least 4 controls were matched by age, HIV status and hospital to each case. Potential risk factors were evaluated using multivariable conditional logistic regression.

RESULTS

In total, 486 age-eligible cases were enrolled. Factors associated with IPD in HIV-uninfected children (237 cases, 928 controls) included siblings <5 years [adjusted odds ratio (aOR) = 1.68, 95% confidence interval (CI): 1.16-2.46], underlying medical conditions (aOR = 1.99, CI 1.22-3.22), preceding upper respiratory tract infection (aOR = 1.79, CI 1.19-2.69), day-care attendance (aOR = 1.58, CI 1.01-2.47), perinatal HIV exposure (aOR = 1.62, CI 1.10-2.37), household car ownership (aOR = 0.45, CI 0.25-0.83) and ≥2 7-valent pneumococcal conjugate vaccine doses (aOR = 0.67, CI 0.46-0.99). Among HIV-infected children (124 cases, 394 controls), IPD-associated factors included malnutrition (aOR = 2.68, CI 1.40-5.14), upper respiratory tract infection (aOR = 3.49, CI 1.73-7.03), tuberculosis in the last 3 months (aOR = 5.12, CI 1.69-15.50) and current antiretroviral treatment (aOR = 0.13, CI 0.05-0.38).

CONCLUSION

Previously identified factors related to poverty, poor health and intense exposure continue to be risk factors for IPD in children. Ensuring delivery of pneumococcal conjugate vaccine and antiretroviral treatment are important for improving disease prevention.

Association between respiratory syncytial virus activity and pneumococcal disease in infants: a time series analysis of US hospitalization data

BACKGROUND

The importance of bacterial infections following respiratory syncytial virus (RSV) remains unclear. We evaluated whether variations in RSV epidemic timing and magnitude are associated with variations in pneumococcal disease epidemics and whether changes in pneumococcal disease following the introduction of seven-valent pneumococcal conjugate vaccine (PCV7) were associated with changes in the rate of hospitalizations coded as RSV.

METHODS AND FINDINGS

We used data from the State Inpatient Databases (Agency for Healthcare Research and Quality), including >700,000 RSV hospitalizations and >16,000 pneumococcal pneumonia hospitalizations in 36 states (1992/1993-2008/2009). Harmonic regression was used to estimate the timing of the average seasonal peak of RSV, pneumococcal pneumonia, and pneumococcal septicemia. We then estimated the association between the incidence of pneumococcal disease in children and the activity of RSV and influenza (where there is a well-established association) using Poisson regression models that controlled for shared seasonal variations. Finally, we estimated changes in the rate of hospitalizations coded as RSV following the introduction of PCV7. RSV and pneumococcal pneumonia shared a distinctive spatiotemporal pattern (correlation of peak timing: ρ = 0.70, 95% CI: 0.45, 0.84). RSV was associated with a significant increase in the incidence of pneumococcal pneumonia in children aged <1 y (attributable percent [AP]: 20.3%, 95% CI: 17.4%, 25.1%) and among children aged 1-2 y (AP: 10.1%, 95% CI: 7.6%, 13.9%). Influenza was also associated with an increase in pneumococcal pneumonia among children aged 1-2 y (AP: 3.2%, 95% CI: 1.7%, 4.7%). Finally, we observed a significant decline in RSV-coded hospitalizations in children aged <1 y following PCV7 introduction (-18.0%, 95% CI: -22.6%, -13.1%, for 2004/2005-2008/2009 versus 1997/1998-1999/2000). This study used aggregated hospitalization data, and studies with individual-level, laboratory-confirmed data could help to confirm these findings.

CONCLUSIONS

These analyses provide evidence for an interaction between RSV and pneumococcal pneumonia. Future work should evaluate whether treatment for secondary bacterial infections could be considered for pneumonia cases even if a child tests positive for RSV. Please see later in the article for the Editors' Summary.

Geographical variability in the likelihood of bloodstream infections due to gram-negative bacteria: correlation with proximity to the equator and health care expenditure

OBJECTIVE

Infections due to Gram-negative bacteria exhibit seasonal trends, with peak infection rates during warmer months. We hypothesized that the likelihood of a bloodstream infection due to Gram-negative bacteria increases with proximity to the equator. We tested this hypothesis and identified geographical, climatic and social factors associated with this variability.

DESIGN

We established a network of 23 international centers in 22 cities.

SETTING

De-identified results of positive blood cultures from 2007-2011 and data sources for geographic, climatic and socioeconomic factors were assembled for each center.

PARTICIPANTS

Patients at the 23 centers with positive blood cultures.

MAIN OUTCOME

Due to variability in the availability of total culture volumes across sites, our primary outcome measure was the fraction of positive blood cultures that yielded Gram-negative bacteria; sources of variability in this outcome measure were explored using meta-regression techniques.

RESULTS

The mean fraction of bacteremia associated with Gram-negative bacteria was 48.4% (range 26.4% to 61.8%). Although not all sites displayed significant seasonality, the overall P-value for seasonal oscillation was significant (P<0.001). In univariate meta-regression models, temperature, latitude, latitude squared, longitude, per capita gross domestic product and percent of gross domestic product spent on healthcare were all associated with the fraction of bacteremia due to Gram-negative bacteria. In multivariable models, only percent of gross domestic product spent on healthcare and distance from the equator (ie. latitude squared) were significantly associated with the fraction of bacteremia due to Gram-negative bacteria.

CONCLUSIONS

The likelihood of bacteremia due to Gram-negative bacteria varies markedly between cities, in a manner that appears to have both geographic (latitude) and socioeconomic (proportion gross domestic product devoted to health spending) determinants. Thus, the optimal approach to initial management of suspected bacteremia may be geographically specific. The rapid emergence of highly antibiotic-resistant Gram-negative pathogens may have geographically specific impacts.

Bacterial and viral infections associated with influenza

Influenza‐associated bacterial and viral infections are responsible for high levels of morbidity and death during pandemic and seasonal influenza episodes. A review was undertaken to assess and evaluate the incidence, epidemiology, aetiology, clinical importance and impact of bacterial and viral co‐infection and secondary infection associated with influenza. A review was carried out of published articles covering bacterial and viral infections associated with pandemic and seasonal influenza between 1918 and 2009 (and published through December 2011) to include both pulmonary and extra‐pulmonary infections. While pneumococcal infection remains the predominant cause of bacterial pneumonia, the review highlights the importance of other co‐ and secondary bacterial and viral infections associated with influenza, and the emergence of newly identified dual infections associated with the 2009 H1N1 pandemic strain. Severe influenza‐associated pneumonia is often bacterial and will necessitate antibiotic treatment. In addition to the well‐known bacterial causes, less common bacteria such as Legionella pneumophila may also be associated with influenza when new influenza strains emerge. This review should provide clinicians with an overview of the range of bacterial and viral co‐ or secondary infections that could present with influenza illness.

No effect of season of birth on risk of type 1 diabetes, cancer, schizophrenia and ischemic heart disease, while some variations may be seen for pneumonia and multiple sclerosis

Background: The risk of type 1 diabetes (T1DM), infections, cancer, schizophrenia and multiple sclerosis (MS) has been associated with environmental factors including vitamin D status.

Materials and Methods: Data were obtained from all children born in Denmark in 1940 (n = 72,839), 1977 (n = 89,570), and 1996 (n = 74,015). Information on contacts to hospitals (1977–2009) was obtained from the National Hospital Discharge Register. The main exposure variable was season of birth as a proxy variable for vitamin D status (summer: April–September and winter: October–March).

Results: No associations between season of birth and risk of MS were seen in the 1940 cohort or the 1996 cohort. In the 1977 cohort, there was a borderline statistically significant decreased risk of MS in those born during wintertime compared with those born during summertime (HR = 0.70, 95% CI: 0.47–1.04, p = 0.07). There were no significant differences within the groups regarding season and risk of T1DM at any age, T1DM before 10 y, infection, any type of cancer, schizophrenia and myocardial infarction. In the 1977 cohort the risk of pneumonia was significantly lower among those born in the summer compared with the winter at any age (HR 0.91, 95% CI 0.85–0.97, p < 0.01) and at age < 10 y (HR 0.90, 95% CI 0.84–0.97, p < 0.01).

Conclusion: MS and pneumonia in young subjects may be related to season of birth and thus maternal vitamin D exposure. Low sunlight exposure in the winter time leading to low vitamin D levels during pregnancy may be a potential explanation.

Examining rainfall and cholera dynamics in Haiti using statistical and dynamic modeling approaches

Haiti has been in the midst of a cholera epidemic since October 2010. Rainfall is thought to be associated with cholera here, but this relationship has only begun to be quantitatively examined. In this paper, we quantitatively examine the link between rainfall and cholera in Haiti for several different settings (including urban, rural, and displaced person camps) and spatial scales, using a combination of statistical and dynamic models. Statistical analysis of the lagged relationship between rainfall and cholera incidence was conducted using case crossover analysis and distributed lag nonlinear models. Dynamic models consisted of compartmental differential equation models including direct (fast) and indirect (delayed) disease transmission, where indirect transmission was forced by empirical rainfall data. Data sources include cholera case and hospitalization time series from the Haitian Ministry of Public Health, the United Nations Water, Sanitation and Health Cluster, International Organization for Migration, and Hôpital Albert Schweitzer. Rainfall data was obtained from rain gauges from the U.S. Geological Survey and Haiti Regeneration Initiative, and remote sensing rainfall data from the National Aeronautics and Space Administration Tropical Rainfall Measuring Mission. A strong relationship between rainfall and cholera was found for all spatial scales and locations examined. Increased rainfall was significantly correlated with increased cholera incidence 4-7 days later. Forcing the dynamic models with rainfall data resulted in good fits to the cholera case data, and rainfall-based predictions from the dynamic models closely matched observed cholera cases. These models provide a tool for planning and managing the epidemic as it continues.

Additive preventive effect of influenza and pneumococcal vaccines in the elderly: results of a large cohort study

Elderly people are at increased risk of influenza and pneumococcal diseases. Influenza increases clinical pneumococcal disease incidence. Pneumococcal vaccination could therefore be a supplement to influenza vaccination. This study evaluated all-cause mortality and antibiotic consumption according to elderly people's influenza and pneumococcal vaccination status. Its goal was to demonstrate that vaccination with both Influenza and pneumococcal vaccines decrease all-cause mortality and antibiotic consumption. From 2004-10-01 to 2004-12-31 (3 mo), elderly people (≥ 65 y) who lived in the Gard department (South of France) were offered both vaccinations. Among the 68,897 subjects followed-up one year after this vaccination campaign, 21,303 (30.9%) were vaccinated with both vaccines, 18,651 (27.1%) with influenza vaccine alone, 3,769 (5.5%) with pneumococcal vaccine alone; 25,174 (36.5%) subjects were unvaccinated. Mortality rate (per 1,000 inhabitants-year) adjusted on gender, age and prior underlying chronic disease was 17.9 (95% CI: 16.3-19.6), 20.8 (19.0-22.8), 22.5 (19.0-26.6) and 24.7 (22.7-26.8), respectively. It was 42.1 (38.8-45.8) in elderly people with underlying chronic disease who received both vaccines vs. 58.1 (53.7-62.9) in unvaccinated elderly people. The decrease in mortality rate was 27.0% (20.0-34.0) in subjects who received both vaccines and 16.0% (6.0-24.0) in those who received influenza vaccine. No significant reduction in mortality rate was seen with the pneumococcal vaccine alone. Influenza and/or pneumococcal vaccinations did not decrease antibiotic consumption that drastically increases during the winter period. An additive effect was observed in the prevention of all-cause mortality with influenza and pneumococcal vaccines given together in elderly people, including in those with underlying chronic disease.

Serotype-specific effect of influenza on adult invasive pneumococcal pneumonia

BACKGROUND

 Influenza affects host susceptibility to pneumococcus. We sought to evaluate whether this relationship varies by pneumococcal serotype using a large epidemiological database covering 3 decades.

METHODS

 Weekly rates of invasive pneumococcal pneumonia (IPP) were obtained from the Danish National Laboratory Surveillance System, and influenza-like illness (ILI) data were collected from Danish sentinel surveillance, Statens Serum Institut, 1977-2007. We fit Poisson regression models for each age and comorbidity group, with predictors for seasonality and secular changes, ILI activity, and serotype.

RESULTS

 Among individuals with low levels of comorbidities, influenza had the largest impact on IPP incidence among low-invasiveness serotypes (influenza attributable percent: 17.9%, 95% confidence interval [CI], 13.6-21.9) as compared with high-invasiveness serotypes (6.7%, 95% CI, 3.8%-11.7%). Among those with higher levels of comorbidities, the effect of influenza was smaller, but high-invasiveness serotypes increased more than low-invasiveness serotypes (8.9% [95% CI, 6.6-11.8] vs. 1.3% [95% CI, -1.6-5.4].

CONCLUSIONS

Influenza was associated with the greatest increases in the incidence of disease caused by serotypes with lower invasive potential and among individuals with low levels of comorbid conditions. The importance of influenza for adult IPP varies by serotype and host comorbidity.

Time and dose-dependent risk of pneumococcal pneumonia following influenza: a model for within-host interaction between influenza and Streptococcus pneumoniae

A significant fraction of seasonal and in particular pandemic influenza deaths are attributed to secondary bacterial infections. In animal models, influenza virus predisposes hosts to severe infection with both Streptococcus pneumoniae and Staphylococcus aureus. Despite its importance, the mechanistic nature of the interaction between influenza and pneumococci, its dependence on the timing and sequence of infections as well as the clinical and epidemiological consequences remain unclear. We explore an immune-mediated model of the viral-bacterial interaction that quantifies the timing and the intensity of the interaction. Taking advantage of the wealth of knowledge gained from animal models, and the quantitative understanding of the kinetics of pathogen-specific immunological dynamics, we formulate a mathematical model for immune-mediated interaction between influenza virus and S. pneumoniae in the lungs. We use the model to examine the pathogenic effect of inoculum size and timing of pneumococcal invasion relative to influenza infection, as well as the efficacy of antivirals in preventing severe pneumococcal disease. We find that our model is able to capture the key features of the interaction observed in animal experiments. The model predicts that introduction of pneumococcal bacteria during a 4-6 day window following influenza infection results in invasive pneumonia at significantly lower inoculum size than in hosts not infected with influenza. Furthermore, we find that antiviral treatment administered later than 4 days after influenza infection was not able to prevent invasive pneumococcal disease. This work provides a quantitative framework to study interactions between influenza and pneumococci and has the potential to accurately quantify the interactions. Such quantitative understanding can form a basis for effective clinical care, public health policies and pandemic preparedness.

Identifying the interaction between influenza and pneumococcal pneumonia using incidence data

The association between influenza virus and the bacterium Streptococcus pneumoniae (pneumococcus) has been proposed as a polymicrobial system, whereby transmission and pathogenicity of one pathogen (the bacterium) are affected by interactions with the other (the virus). However, studies focusing on different scales of resolution have painted an inconsistent picture: Individual-scale animal experiments have unequivocally demonstrated an association, whereas epidemiological support in human populations is, at best, inconclusive. We integrate weekly incidence reports and a mechanistic transmission model within a likelihood-based inference framework to characterize the nature, timing, and magnitude of this interaction. We find support for a strong but short-lived interaction, with influenza infection increasing susceptibility to pneumococcal pneumonia ~100-fold. We infer modest population-level impacts arising from strong processes at the level of an individual, thereby resolving the dichotomy in seemingly inconsistent observations across scales. An accurate characterization of the influenza-pneumococcal interaction can form a basis for more effective clinical care and public health measures for pneumococcal pneumonia.

Assessing pneumococcal meningitis association with viral respiratory infections and antibiotics: insights from statistical and mathematical models

Pneumococcus is an important human pathogen, highly antibiotic resistant and a major cause of bacterial meningitis worldwide. Better prevention requires understanding the drivers of pneumococcal infection incidence and antibiotic susceptibility. Although respiratory viruses (including influenza) have been suggested to influence pneumococcal infections, the underlying mechanisms are still unknown, and viruses are rarely considered when studying pneumococcus epidemiology. Here, we propose a novel mathematical model to examine hypothetical relationships between Streptococcus pneumoniae meningitis incidence (SPMI), acute viral respiratory infections (AVRIs) and antibiotic exposure. French time series of SPMI, AVRI and penicillin consumption over 2001-2004 are analysed and used to assess four distinct virus-bacteria interaction submodels, ascribing the interaction on pneumococcus transmissibility and/or pathogenicity. The statistical analysis reveals strong associations between time series: SPMI increases shortly after AVRI incidence and decreases overall as the antibiotic-prescription rate rises. Model simulations require a combined impact of AVRI on both pneumococcal transmissibility (up to 1.3-fold increase at the population level) and pathogenicity (up to threefold increase) to reproduce the data accurately, along with diminished epidemic fitness of resistant pneumococcal strains causing meningitis (0.97 (0.96-0.97)). Overall, our findings suggest that AVRI and antibiotics strongly influence SPMI trends. Consequently, vaccination protecting against respiratory virus could have unexpected benefits to limit invasive pneumococcal infections.

Influenza and RSV make a modest contribution to invasive pneumococcal disease incidence in the UK

Objectives

The common seasonality of incidence of invasive pneumococcal disease (IPD) and viral respiratory infections has long been recognized, however, the extent to which this affects the association between the pathogens is unknown. We have analysed weekly surveillance data of IPD, influenza and respiratory syncytial virus (RSV), using ambient temperature and hours of sunshine as measures of seasonality.

Methods

Reported cases of influenza, IPD and RSV, were collected in England and Wales, from week 1 (January) 1996 to week 23 (June) 2009. The associations between IPD and respiratory viral infections were analysed using several statistical methods, including correlation coefficients and both additive and multiplicative regression models.

Results

6–7.5% of cases of IPD are attributable to influenza and 3–4% attributable to RSV. Correlation coefficients reported considerably stronger associations between IPD and the viral infections compared to regression models.

Conclusions

A small but potentially important percentage of IPD may be attributable to influenza and RSV when adjusted for seasonality by temperature. Jointly these viral infections may lead to over 10% of IPD cases. Therefore, prevention of viral respiratory infections may offer some additional benefit in reducing invasive pneumococcal infections.

Respiratory viral and pneumococcal coinfection of the respiratory tract: implications of pneumococcal vaccination

The interactions between Streptococcus pneumoniae and other respiratory pathogens have been studied in vitro, in animal models and in humans - including epidemiologic and vaccine probe studies. Interactions of pneumococcus with respiratory viruses are common, and many mechanisms have been suggested to explain this phenomenon. The aim of this review is to explore pneumococcal interactions with respiratory viruses and consider the potential role that the pneumococcal polysaccharide-protein conjugate vaccine may play in modifying pneumococcal-respiratory viral interactions.

Interactions between Streptococcus pneumoniae and influenza virus: a mutually beneficial relationship?

Historically, most research on infectious diseases has focused on infections with single pathogens. However, infections with pathogens often occur in the context of pre-existing viral and bacterial infections. Clinically, this is of particular relevance for coinfections with Streptococcus pneumoniae and influenza virus, which together are an important cause of global morbidity and mortality. In recent years new evidence has emerged regarding the underlying mechanisms of influenza virus-induced susceptibility to secondary pneumococcal infections, in particular regarding the sustained suppression of innate recognition of S. pneumoniae. Conversely, it is also increasingly being recognized that there is not a unidirectional effect of the virus on S. pneumoniae, but that asymptomatic pneumococcal carriage may also affect subsequent influenza virus infection and the clinical outcome. Here, we will review both aspects of pneumococcal influenza virus infection, with a particular focus on the age-related differences in pneumococcal colonization rates and invasive pneumococcal disease.

Seasonality of viral infections: mechanisms and unknowns

Seasonality is a long-recognized attribute of many viral infections of humans, but the mechanisms underlying seasonality, particularly for person-to-person communicable diseases, remain poorly understood. Better understanding of drivers of seasonality could provide insights into the relationship between the physical environment and infection risk, which is particularly important in the context of global ecological change in general, and climate change in particular. In broad terms, seasonality represents oscillation in pathogens' effective reproductive number, which, in turn, must reflect oscillatory changes in infectiousness, contact patterns, pathogen survival, or host susceptibility. Epidemiological challenges to correct identification of seasonal drivers of risk include failure to adjust for predictable correlation between disease incidence and seasonal exposures, and unmeasured confounding. The existing evidence suggests that the seasonality of some enteric and respiratory viral pathogens may be driven by enhanced wintertime survival of pathogens, and also by increased host susceptibility resulting from relative 'wintertime immune suppression'. For vector-borne diseases and zoonoses, environmental influences on vector or reservoir abundance, and vector biting rates, are probably more important. However, numerous areas of uncertainty exist, making this an exciting area for future research.