Intense co-circulation of non-influenza respiratory viruses during the first wave of pandemic influenza pH1N1/2009: a cohort study in Reunion Island

Evaluation of the cobas Liat detection test for SARS-CoV-2 and influenza viruses following the emergence of the SARS-CoV-2 Omicron variant

OBJECTIVES

This study assessed the clinical performance of the cobas Liat SARS‑CoV‑2 & Influenza A/B assay (LiatCOVID/flu) for the detection of both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses during the SARS-CoV-2 Omicron outbreak.

METHODS

Residual nasopharyngeal swab samples (NPS) previously tested with cobas SARS-CoV-2 & Influenza A/B for SARS-CoV-2 and with the Allplex Respiratory Panel 1 for influenza viruses were collected. All samples were submitted to the LiatCOVID/flu assay.

RESULTS

A total of 1147 samples were collected comprising 167 SARS-CoV-2-positive, 556 SARS-CoV-2-negative, 224 influenza-positive, and 200 influenza-negative cases. The positive percent agreement (PPA)/negative percent agreement (NPA) of LiatCOVID/flu for SARS-CoV-2 and influenza viruses compared to the previously tested methods were 100% of 100% and 99.6% of 100%, respectively.

CONCLUSIONS

The LiatCOVID/flu assay shows an acceptable performance in the detection of SARS-CoV-2 and influenza viruses using NPS samples.

Virus-virus interactions of febrile respiratory syndrome among patients in China based on surveillance data from February 2011 to December 2020

BACKGROUND

The burden of acute respiratory infections is still considerable, and virus-virus interactions may affect their epidemics, but previous evidence is inconclusive.

OBJECTIVE

To quantitatively investigate the interactions among respiratory viruses at both the population and individual levels.

METHODS

Cases tested for influenza virus (IV), respiratory syncytial virus (RSV), human parainfluenza virus (PIV), human Adenovirus (AdV), human coronavirus (CoV), human bocavirus (BoV) and rhinoviruses (RV) were collected from the pathogen surveillance for febrile respiratory syndrome (FRS) in China from February 2011 to December 2020. We used spearman's rank correlation coefficients and binary logistic regression models to analyze the interactions between any two of the viruses at the population and individual levels, respectively.

RESULTS

Among 120,237 cases, 4.5% were co-infected with two or more viruses. Correlation coefficients showed 7 virus pairs were positively correlated, namely: IV and RSV, PIV and AdV, PIV and CoV, PIV and BoV, PIV and RV, AdV and BoV, CoV and RV. Regression models showed except for the negative interaction between IV and RV (OR=0.70, 95%CI: 0.61-0.81), all other virus pairs had positive interactions.

CONCLUSION

Most of the respiratory viruses interact positively, while IV and RV interact negatively. This article is protected by copyright. All rights reserved.

Epidemiological Consequences of Viral Interference: A Mathematical Modeling Study of Two Interacting Viruses

Some viruses have the ability to block or suppress growth of other viruses when simultaneously present in the same host. This type of viral interference or viral block has been suggested as a potential interaction between some respiratory viruses including SARS-CoV-2 and other co-circulating respiratory viruses. We explore how one virus' ability to block infection with another within a single host affects spread of the viruses within a susceptible population using a compartmental epidemiological model. We find that population-level effect of viral block is a decrease in the number of people infected with the suppressed virus. This effect is most pronounced when the viruses have similar epidemiological parameters. We use the model to simulate co-circulating epidemics of SARS-CoV-2 and influenza, respiratory syncytial virus (RSV), and rhinovirus, finding that co-circulation of SARS-CoV-2 and RSV causes the most suppression of SARS-CoV-2. Paradoxically, co-circulation of SARS-CoV-2 and influenza or rhinovirus results in almost no change in the SARS-CoV-2 epidemic, but causes a shift in the timing of the influenza and rhinovirus epidemics.

In vitro and genetic screening of probiotic properties of lactic acid bacteria isolated from naturally fermented cow-milk and yak-milk products of Sikkim, India

A total of 272 isolates of lactic acid bacteria (LAB) were isolated from 22 samples of naturally fermented milk products of Sikkim in India viz. dahi, soft-variety chhurpi, hard-variety chhurpi, mohi and philu, out of which, 68 LAB isolates were randomly grouped on the basis of phenotypic characteristics, and were identified by 16S rRNA gene sequence analysis. Leuconostoc mesenteroides was the most dominant genus, followed by Leuc. mesenteroides subsp. jonggajibkimchii, Lactococcus lactis subsp. cremoris, Lc. lactis, Lc. lactis subsp. hordniae, Lc. lactis subsp. tructae, Enterococcus faecalis, E. italicus and E. pseudoavium. LAB strains were tested for probiotics attributes by in vitro and genetic screening, based on marker genes. LAB strains showed tolerance to pH 3.0, bile salt, resistance to lysozyme and β-galactosidase activity. Enterococcus faecalis YS4-11 and YS4-14 and Lactococcus lactis subsp. cremoris SC3 showed more than 85% of hydrophobicity. Genes clp L and tdc encoding for low pH tolerance, agu A and Ir1516 encoding for bile tolerance, LBA1446 gene encoding for BSH activity, map A, apf, mub 1 and msa encoding for mucosal binding property were detected. Gene mesY for bacteriocin production was detected only in Leuconostoc spp. Based on the in vitro and genetic screening of probiotic attributes, Leuc. mesenteroides; Leuc. mesenteroides subsp. jonggajibkimchii and Lc. lactis subsp. cremoris were tentatively selected for possible probiotic candidates.

SARS-CoV-2 infection in children in Moscow in 2020: clinical features and impact on circulation of other respiratory viruses: SARS-CoV-2 infection in children in Moscow in 2020

Objectives

This study aimed to estimate the impact of the COVID-19 pandemic on the circulation of non-SARS-CoV-2 respiratory viruses and the clinical characteristics of COVID-19 in hospitalized children.

Methods

A total of 226 and 864 children admitted to the Children's City Clinical Hospital with acute respiratory infection in September to November of 2018 and 2020 in Moscow were tested for respiratory viruses using multiplex polymerase chain reaction (PCR) and Mycoplasma pneumoniae/Chlamydia pneumoniae using enzyme-linked immunosorbent assay.

Results

The detection rate of non-SARS-CoV-2 viruses in 2020 was lower than in 2018, 16.9% versus 37.6%. An increase in the median age of children with respiratory viruses was observed during the pandemic (3 years vs 1 year). There was no significant difference in the frequency of intensive care unit (ICU) admission in children with SARS-CoV-2 and other respiratory virus infections (2.7% vs 2.9%). SARS-CoV-2 and human rhinoviruses, human metapneumoviruses, and human adenoviruses showed significantly lower than expected co-detection rates during co-circulation. An increase in body mass index (BMI) or bacterial coinfection leads to an increased risk of ICU admission and a longer duration of COVID-19 in children.

Conclusions

The COVID-19 pandemic led to significant changes in the epidemiological characteristics of non-SARS-CoV-2 respiratory viruses during the autumn peak of the 2020 pandemic, compared with the same period in 2018.

Dual respiratory virus detection in adult patients with acute respiratory illness

BACKGROUND

Nonrandom multiple respiratory virus (RV) detection provides evidence for viral interference among respiratory viruses. However, little is known as to whether it occurs randomly.

METHODS

The prevalence of dual RV detection (DRVD) in patients with acute respiratory illnesses (ARIs) at 4 academic medical centers was investigated; data about the prevalence of 8 RVs were collected from the Korean national RV surveillance dataset. Linear regression analysis was performed to assess the correlation between observed and estimated prevalence of each type of DRVD.

RESULTS

In total, 108 patients with ARIs showing DRVD were included in this study between 2011 and 2017. In several types of regression analysis, a strong correlation was observed between the observed and estimated prevalence of each type of DRVD. Excluding three DRVD types (influenza/picornavirus, influenza/human metapneumovirus, and adenovirus/respiratory syncytial virus), the slope of the regression line was higher than that of the line of random occurrence (1.231 > 1.000) and the 95% confidence interval of the regression line was located above the line of random occurrence.

CONCLUSIONS

Contrary to the results of previous epidemiologic studies, most types of DRVD occur more frequently than expected from the prevalence rates of individual RV, except for three underrepresented pairs above.

Competition between RSV and influenza: Limits of modelling inference from surveillance data

Respiratory Syncytial Virus (RSV) and Influenza cause a large burden of disease. Evidence of their interaction via temporary cross-protection implies that prevention of one could inadvertently lead to an increase in the burden of the other. However, evidence for the public health impact of such interaction is sparse and largely derives from ecological analyses of peak shifts in surveillance data. To test the robustness of estimates of interaction parameters between RSV and Influenza from surveillance data we conducted a simulation and back-inference study. We developed a two-pathogen interaction model, parameterised to simulate RSV and Influenza epidemiology in the UK. Using the infection model in combination with a surveillance-like stochastic observation process we generated a range of possible RSV and Influenza trajectories and then used Markov Chain Monte Carlo (MCMC) methods to back-infer parameters including those describing competition. We find that in most scenarios both the strength and duration of RSV and Influenza interaction could be estimated from the simulated surveillance data reasonably well. However, the robustness of inference declined towards the extremes of the plausible parameter ranges, with misleading results. It was for instance not possible to tell the difference between low/moderate interaction and no interaction. In conclusion, our results illustrate that in a plausible parameter range, the strength of RSV and Influenza interaction can be estimated from a single season of high-quality surveillance data but also highlights the importance to test parameter identifiability a priori in such situations.

Probiotic properties of lactic acid bacteria isolated from traditionally prepared dry starters of the Eastern Himalayas

The Himalayan people prepare dry and oval to round-shaped starter cultures to ferment cereals into mild-alcoholic beverages, which contain lactic acid bacteria (LAB) as one of the essential microbiota. There is no report on probiotic characters of LAB isolated from dry starters. Hence, we screened the probiotic and some functional properties of 37 LAB strains isolated from dry starters of the Eastern Himalayas viz. marcha, phab, paa, pee and phut. About 38% of the LAB strains showed high survival rate (> 50%) at pH 3 and 0.3% bile salts. Enterococcus durans BPB21 and SMB7 showed the highest hydrophobicity percentage of 98%. E. durans DMB4 and SMB7 showed maximum cholesterol assimilation activity. About 65% of the LAB strains showed the ability to produce β galactosidase. Majority of the strains showed phytase activity, whereas none of the strain showed amylase activity. About 86% of LAB strains showed an optimum tolerance of 10% ethanol concentration. Genetic screening of some probiotic and functional marker genes have also been analysed. The occurrence of clp L gene, agu A gene (survival of gastrointestinal tract conditions), apf, mub1 and map A gene (adhesion genes) was higher compared to other genes. The occurrence of bsh gene (bile salt tolerance) was detected in Pediococcus pentosaceus SMB13-1 and Enterococcus faecium BPB11. Gene ped B for pediocin with amplicon size of 375 bp was detected in E. durans DMB13 and Pediococcus acidilactici AKB3. Detection of nutritional marker gene rib A and fol P in some strains showed the potential ability to synthesize riboflavin and folic acid. LAB with probiotic and functional properties may be explored for food industry in future.

Outbreak of severe acute respiratory infection in Southern Province, Sri Lanka in 2018: a cross-sectional study

OBJECTIVES

To determine aetiology of illness among children and adults presenting during outbreak of severe respiratory illness in Southern Province, Sri Lanka, in 2018.

DESIGN

Prospective, cross-sectional study.

SETTING

1600-bed, public, tertiary care hospital in Southern Province, Sri Lanka.

PARTICIPANTS

410 consecutive patients, including 371 children and 39 adults, who were admitted with suspected viral pneumonia (passive surveillance) or who met case definition for acute respiratory illness (active surveillance) in May to June 2018.

RESULTS

We found that cocirculation of influenza A (22.6% of cases), respiratory syncytial virus (27.8%) and adenovirus (AdV) (30.7%; type B3) was responsible for the outbreak. Mortality was noted in 4.5% of paediatric cases identified during active surveillance. Virus type and viral coinfection were not significantly associated with mortality.

CONCLUSIONS

This is the first report of intense cocirculation of multiple respiratory viruses as a cause of an outbreak of severe acute respiratory illness in Sri Lanka, and the first time that AdV has been documented as a cause of a respiratory outbreak in the country. Our results emphasise the need for continued vigilance in surveying for known and emerging respiratory viruses in the tropics.

Dynamics and predisposition of respiratory viral co-infections in children and adults

OBJECTIVES

The epidemiology of respiratory co-infection pairings is poorly understood. Here we assess the dynamics of respiratory viral co-infections in children and adults and determine predisposition for or against specific viral pairings.

METHODS

Over five respiratory seasons from 30 November 2013 through 6 June 2018, the mono-infection and co-infection prevalence of 13 viral pathogens was tabulated at The Cleveland Clinic. Employing a model to proportionally distribute viral pairs using individual virus co-infection rate with prevalence patterns of concurrent co-circulating viruses, we compared predicted occurrence with observed occurrence of 132 viral pairing permutations using binomial analysis.

RESULTS

Of 30 535 respiratory samples, 9843 (32.2%) were positive for at least one virus and 1018 (10.8%) of these were co-infected. Co-infected samples predominantly originated from children. Co-infection rate in paediatric population was 35.0% (2068/5906), compared with only 5.8% (270/4591) in adults. Adenovirus C (ADVC) had the highest co-infection rate (426/623, 68.3%) while influenza virus B had the lowest (55/546, 10.0%). ADVC-rhinovirus (HRV), respiratory syncytial virus A (RSVA)-HRV and RSVB-HRV pairings occurred at significantly higher frequencies than predicted by the proportional distribution model (p < 0.05). Additionally, several viral pairings had fewer co-infections than predicted by our model: notably metapneumovirus (hMPV)-parainfluenza virus 3, hMPV-RSVA and RSVA-RSVB.

CONCLUSIONS

This is one of the largest studies on respiratory viral co-infections in children and adults. Co-infections are substantially more common in children, especially under 5 years of age, and the most frequent pairings occurred at a higher frequency than would be expected by random. Specific pairings occur at altered rates compared with those predicted by proportional distribution, suggesting either direct or indirect interactions result between specific viral pathogens.

Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models

It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.

Disease-causing microorganisms, including viruses, bacteria, protozoa and fungi, form complex communities within animals and plants. These microorganisms can coexist harmoniously or even beneficially, or they may competitively interact for host resources. Well-studied examples include interactions between viruses and bacteria in the respiratory tract. Whilst ecological studies have revealed that some pathogens do interact within their hosts, identifying interactions from available population scale data from health authorities is challenging. This is exacerbated by a lack of large-scale data describing the infection patterns of multiple pathogens within single populations over long time frames. Furthermore, methods for evaluating whether infection frequencies of different pathogens fluctuate together or not over time cannot readily account for alternative explanations. For example, human pathogens may have related seasonal patterns depending on the age groups they infect and the weather conditions they survive in, and not because they are interacting. We developed a robust statistical framework to identify pathogen-pathogen interactions from population scale diagnostic data. This framework serves as a crucial step in identifying such important interactions and will guide new studies to elucidate their underpinning mechanisms. This will have important consequences for public health preparedness and the design of effective disease control interventions.

Using routine testing data to understand circulation patterns of influenza A, respiratory syncytial virus and other respiratory viruses in Victoria, Australia

Several studies have reported evidence of interference between respiratory viruses: respiratory viruses rarely reach their epidemic peak concurrently and there appears to be a negative association between infection with one respiratory virus and co-infection with another. We used results spanning 16 years (2002-2017) of a routine diagnostic multiplex panel that tests for nine respiratory viruses to further investigate these interactions in Victoria, Australia. Time series analyses were used to plot the proportion positive for each virus. The seasonality of all viruses included was compared with respiratory syncytial virus (RSV) and influenza A virus using cross-correlations. Logistic regression was used to explore the likelihood of co-infection with one virus given infection with another. Seasonal peaks were observed each year for influenza A and RSV and less frequently for influenza B, coronavirus and parainfluenza virus. RSV circulated an average of 6 weeks before influenza A. Co-infection with another respiratory virus was less common with picornavirus, RSV or influenza A infection. Our findings provide further evidence of a temporal relationship in the circulation of respiratory viruses. A greater understanding of the interaction between respiratory viruses may enable better prediction of the timing and magnitude of respiratory virus epidemics.

[Etiological structure of influenza and other ARVI in St. Petersburg during epidemic seasons 2012-2016.]

The etiological structure of influenza and other acute respiratory viral infections including their rate of incidence in St. Petersburg and Leningrad region during 4 epidemic seasons has been studied. Seasonality of some respiratory viruses was shown and peaks of circulation of RSV, adenovirus, parainfluenza viruses, rhinovirus, bocavirus, metapneumovirus and coronavirus were marked. The interference of influenza A viruses and RSV, RSV and rhinoviruses was highlighted. A high incidence of adenovirus infection in organized communities and RSV infection in children was revealed.

Attenuation of Influenza A Virus Disease Severity by Viral Coinfection in a Mouse Model

Influenza viruses and rhinoviruses are responsible for a large number of acute respiratory viral infections in human populations and are detected as copathogens within hosts. Clinical and epidemiological studies suggest that coinfection by rhinovirus and influenza virus may reduce disease severity and that they may also interfere with each other's spread within a host population. To determine how coinfection by these two unrelated respiratory viruses affects pathogenesis, we established a mouse model using a minor serogroup rhinovirus (rhinovirus strain 1B [RV1B]) and mouse-adapted influenza A virus (A/Puerto Rico/8/1934 [PR8]). Infection of mice with RV1B 2 days before PR8 reduced the severity of infection by a low or medium, but not high, dose of PR8. Disease attenuation was associated with an early inflammatory response in the lungs and enhanced clearance of PR8. However, coinfection by RV1B did not reduce PR8 viral loads early in infection or inhibit replication of PR8 within respiratory epithelia or in vitro Inflammation in coinfected mice remained focal compared to diffuse inflammation and damage in the lungs of mice infected by PR8. The timing of RV1B coinfection was a critical determinant of protection, suggesting that sufficient time is needed to induce this response. Finally, disease attenuation was not unique to RV1B: dose-dependent coinfection by a murine coronavirus (mouse hepatitis virus strain 1 [MHV-1]) also reduced the severity of PR8 infection. Unlike RV1B, coinfection with MHV-1 reduced early PR8 replication, which was associated with upregulation of beta interferon (IFN-β) expression. This model is critical for understanding the mechanisms responsible for influenza disease attenuation during coinfection by unrelated respiratory viruses.IMPORTANCE Viral infections in the respiratory tract can cause severe disease and are responsible for a majority of pediatric hospitalizations. Molecular diagnostics have revealed that approximately 20% of these patients are infected by more than one unrelated viral pathogen. To understand how viral coinfection affects disease severity, we inoculated mice with a mild viral pathogen (rhinovirus or murine coronavirus), followed 2 days later by a virulent viral pathogen (influenza A virus). This model demonstrated that rhinovirus can reduce the severity of influenza A virus, which corresponded with an early but controlled inflammatory response in the lungs and early clearance of influenza A virus. We further determined the dose and timing parameters that were important for effective disease attenuation and showed that influenza disease is also reduced by coinfection with a murine coronavirus. These findings demonstrate that coinfecting viruses can alter immune responses and pathogenesis in the respiratory tract.

Epidemiology of viral respiratory infections in Australian working-age adults (20–64 years): 2010–2013

Acute respiratory infections cause significant morbidity and mortality accounting for 5.8 million deaths worldwide. In Australia, influenza-like illness (ILI), defined as cough, fever and fatigue is a common presentation in general practice and results in reduced productivity and lost working days. Little is known about the epidemiology of ILI in working-age adults. Using data from the ASPREN influenza surveillance network in Australia (2010–2013) we found that working-age adults made up 45.2% of all ILI notifications with 55% of samples positive for at least one respiratory virus. Viruses most commonly detected in our study included influenza A (20.6%), rhinovirus (18.6%), influenza B (6.2%), human meta-pneumovirus (3.4%), respiratory syncytial virus (3.1%), para-influenza virus (2.6%) and adenovirus (1.3%). We also demonstrated that influenza A is the predominant virus that increases ILI (by 1.2% per month for every positive influenza A case) in working-age adults during autumn–winter months while other viruses are active throughout the year. Understanding the epidemiology of viral respiratory infections through a year will help clinicians make informed decisions about testing, antibiotic and antiviral prescribing and when the beginning of the ‘flu season’ can be more confidently predicted.

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.

Acute respiratory infections in hospitalized children in Vientiane, Lao PDR - the importance of Respiratory Syncytial Virus

The Human respiratory syncytial virus (RSV) is one of the most important viral pathogens, causing epidemics of acute respiratory infection (ARI), especially bronchiolitis and pneumonia, in children worldwide. To investigate the RSV burden in Laos, we conducted a one-year study in children <5 years old admitted to Mahosot Hospital, Vientiane Capital, to describe clinical and epidemiological characteristics and predictive factors for severity of RSV-associated ARI. Pooled nasal and throat swabs were tested using multiplex real-time PCR for 33 respiratory pathogens (FTD® kit). A total of 383 patients were included, 277 (72.3%) of whom presented with pneumonia. 377 (98.4%) patients were positive for at least one microorganism, of which RSV was the most common virus (41.0%), with a peak observed between June and September, corresponding to the rainy season. Most RSV inpatients had pneumonia (84.1%), of whom 35% had severe pneumonia. Children <3-months old were a high-risk group for severe pneumonia, independently of RSV infection. Our study suggests that RSV infection is frequent in Laos and commonly associated with pneumonia in hospitalized young children. Further investigations are required to provide a better overall view of the Lao nationwide epidemiology and public health burden of RSV infection over time.

Viral interference and the live-attenuated intranasal influenza vaccine: Results from a pediatric cohort with cystic fibrosis

BACKGROUND

The objective of this study was to explore the effects of viral co-detection in individuals recently vaccinated with the live-attenuated intranasal influenza virus vaccine (LAIV) on the detection of influenza RNA.

METHODS

Before the 2013-2014 influenza season, nasal swabs were obtained from 59 pediatric participants with cystic fibrosis (CF) and 17 of their healthy siblings immediately before vaccination and 4 times during the week of follow-up. Real-time RT-PCR assays were used to detect influenza RNA. Co-detection of a non-influenza respiratory virus (NIRV) at the time of vaccination was determined by a multiplex RT-PCR assay. Differences in the proportions and rates of influenza detection and their 95% credible intervals (CrI) were estimated.

RESULTS

Influenza RNA was detected in 16% fewer participants (95% CrI: -7, 39%) throughout follow-up in the NIRV-positive group compared with the NIRV-negative group (59% vs. 75%). This was also observed in participants with CF alone (66% vs. 74%; RD = 8% 95% CrI: -16, 33%) as well as in healthy participants only (75% vs. 30%; RD = 45%, 95% CrI: -2, 81%). Influenza was detected in NIRV-negative subjects for 0.49 d more compared with NIRV-positive subjects (95% CrI: -0.37, 1.26).

CONCLUSION

The observed proportion of subjects in whom influenza RNA was detected and the duration of detection differed slightly between NIRV- positive and -negative subjects. However, wide credible intervals for the difference preclude definitive conclusions. If true, this observed association may be related to a recent viral respiratory infection, a phenomenon known as viral interference.

Prevalence of non-influenza respiratory viruses in acute respiratory infection cases in Mexico

Background

Acute respiratory infections are the leading cause of morbidity and mortality worldwide. Although a viral aetiological agent is estimated to be involved in up to 80% of cases, the majority of these agents have never been specifically identified. Since 2009, diagnostic and surveillance efforts for influenza virus have been applied worldwide. However, insufficient epidemiological information is available for the many other respiratory viruses that can cause Acute respiratory infections.

Methods

This study evaluated the presence of 14 non-influenza respiratory viruses in 872 pharyngeal exudate samples using RT-qPCR. All samples met the operational definition of a probable case of an influenza-like illness or severe acute respiratory infection and had a previous negative result for influenza by RT-qPCR.

Results

The presence of at least one non-influenza virus was observed in 312 samples (35.8%). The most frequent viruses were rhinovirus (RV; 33.0%), human respiratory syncytial virus (HRSV; 30.8%) and human metapneumovirus (HMPV; 10.6%). A total of 56 cases of co-infection (17.9%) caused by 2, 3, or 4 viruses were identified. Approximately 62.5% of all positive cases were in children under 9 years of age.

Conclusion

In this study, we identified 13 non-influenza respiratory viruses that could occur in any season of the year. This study provides evidence for the prevalence and seasonality of a wide range of respiratory viruses that circulate in Mexico and constitute a risk for the population. Additionally, our data suggest that including these tests more widely in the diagnostic algorithm for influenza may reduce the use of unnecessary antibiotics, reduce the hospitalisation time, and enrich national epidemiological data with respect to the infections caused by these viruses.

Etiology of Influenza-Like Illnesses from Sentinel Network Practitioners in Réunion Island, 2011-2012

In Réunion Island, despite an influenza surveillance established since 1996 by the sentinel general practitioner’s network, little is known about the etiology of Influenza like-illness (ILI) that differs from influenza viruses in a tropical area. We set up a retrospective study using nasal swabs collected by sentinel GPs from ILI patients in 2011 and 2012. A total of 250 swabs were randomly selected and analyzed by multiplex reverse transcriptase polymerase chain reaction (RT-PCR) including research of 18 viruses and 4 bacteria. We detected respiratory viruses in 169/222 (76.1%) samples, mostly rhinovirus (23.4%), influenza A virus (21.2%), influenza B virus (12.6%), coronavirus (4.9%) and Human metapneumovirus (3.6%). Nine swabs (5.3% of positive swabs) revealed co-infections with two viruses identified, among which six concerned co-infections with influenza viruses. We observed important seasonal differences, with circulation of Human Metapneumoviruses, RSV A and B and coronavirus only during summer; whereas parainfluenza viruses were identified only during winter. In conclusion, this study highlights a substantial circulation of multiple respiratory pathogens in Réunion Island throughout the year. It shows that ILI are not only attributable to influenza and underlines the need for biological surveillance. As the use of multiplex RT-PCR showed its efficacy, it is now used routinely in the surveillance of ILI.

Theoretical Basis of the Test-Negative Study Design for Assessment of Influenza Vaccine Effectiveness

Influenza viruses undergo frequent antigenic changes. As a result, the viruses circulating change within and between seasons, and the composition of the influenza vaccine is updated annually. Thus, estimation of the vaccine's effectiveness is not constant across seasons. In order to provide annual estimates of the influenza vaccine's effectiveness, health departments have increasingly adopted the "test-negative design," using enhanced data from routine surveillance systems. In this design, patients presenting to participating general practitioners with influenza-like illness are swabbed for laboratory testing; those testing positive for influenza virus are defined as cases, and those testing negative form the comparison group. Data on patients' vaccination histories and confounder profiles are also collected. Vaccine effectiveness is estimated from the odds ratio comparing the odds of testing positive for influenza among vaccinated patients and unvaccinated patients, adjusting for confounders. The test-negative design is purported to reduce bias associated with confounding by health-care-seeking behavior and misclassification of cases. In this paper, we use directed acyclic graphs to characterize potential biases in studies of influenza vaccine effectiveness using the test-negative design. We show how studies using this design can avoid or minimize bias and where bias may be introduced with particular study design variations.

Update on Human Rhinovirus and Coronavirus Infections

Human rhinovirus (HRV) and coronavirus (HCoV) infections are associated with both upper respiratory tract illness (“the common cold”) and lower respiratory tract illness (pneumonia). New species of HRVs and HCoVs have been diagnosed in the past decade. More sensitive diagnostic tests such as reverse transcription-polymerase chain reaction have expanded our understanding of the role these viruses play in both immunocompetent and immunosuppressed hosts. Recent identification of severe acute respiratory syndrome and Middle East respiratory syndrome viruses causing serious respiratory illnesses has led to renewed efforts for vaccine development. The role these viruses play in patients with chronic lung disease such as asthma makes the search for antiviral agents of increased importance.

Early occurrence of influenza A epidemics coincided with changes in occurrence of other respiratory virus infections

BACKGROUND

Viral interaction in which outbreaks of influenza and other common respiratory viruses might affect each other has been postulated by several short studies. Regarding longer time periods, influenza epidemics occasionally occur very early in the season, as during the 2009 pandemic. Whether early occurrence of influenza epidemics impacts outbreaks of other common seasonal viruses is not clear.

OBJECTIVES

We investigated whether early occurrence of influenza outbreaks coincides with shifts in the occurrence of other common viruses, including both respiratory and non-respiratory viruses.

METHODS

We investigated time trends of and the correlation between positive laboratory diagnoses of eight common viruses in the Netherlands over a 10-year time period (2003-2012): influenza viruses types A and B, respiratory syncytial virus (RSV), rhinovirus, coronavirus, norovirus, enterovirus, and rotavirus. We compared trends in viruses between early and late influenza seasons.

RESULTS

Between 2003 and 2012, influenza B, RSV, and coronavirus showed shifts in their occurrence when influenza A epidemics occurred earlier than usual (before week 1). Although shifts were not always consistently of the same type, when influenza type A hit early, RSV outbreaks tended to be delayed, coronavirus outbreaks tended to be intensified, and influenza virus type B tended not to occur at all. Occurrence of rhinovirus, norovirus, rotavirus, and enterovirus did not change.

CONCLUSION

When influenza A epidemics occured early, timing of the epidemics of several respiratory winter viruses usually occurring close in time to influenza A was affected, while trends in rhinoviruses (occurring in autumn) and trends in enteral viruses were not.

Differential Immune Profiles in Two Pandemic Influenza A(H1N1)pdm09 Virus Waves at Pandemic Epicenter

Background and Aims

Severe influenza A(H1N1)pdm2009 virus infection cases are characterized by sustained immune activation during influenza pandemics. Seasonal flu data suggest that immune mediators could be modified by wave-related changes. Our aim was to determine the behavior of soluble and cell-related mediators in two waves at the epicenter of the 2009 influenza pandemic.

Methods

Leukocyte surface activation markers were studied in serum from peripheral blood samples, collected from the 1^st (April–May, 2009) and 2^nd (October 2009–February 2010) pandemic waves. Patients with confirmed influenza A(H1N1)pdm2009 virus infection (H1N1), influenza-like illness (ILI) or healthy donors (H) were analyzed.

Results

Serum IL-6, IL-4 and IL-10 levels were elevated in H1N1 patients from the 2^nd pandemic wave. Additionally, the frequency of helper and cytotoxic T cells was reduced during the 1^st wave, whereas CD69 expression in helper T cells was increased in the 2^nd wave for both H1N1 and ILI patients. In contrast, CD62L expression in granulocytes from the ILI group was increased in both waves but in monocytes only in the 2^nd wave. Triggering Receptor Expressed on Myeloid cells (TREM)-1 expression was elevated only in H1N1 patients at the 1^st wave.

Conclusions

Our results show that during the 2009 influenza pandemic a T cell activation phenotype is observed in a wave-dependent fashion, with an expanded activation in the 2^nd wave, compared to the 1^st wave. Conversely, granulocyte and monocyte activation is infection-dependent. This evidence collected at the pandemic epicenter in 2009 could help us understand the differences in the underlying cellular mechanisms that drive the wave-related immune profile behaviors that occur against influenza viruses during pandemics.

Household Transmission of Influenza Virus

Human influenza viruses cause regular epidemics and occasional pandemics with a substantial public health burden. Household transmission studies have provided valuable information on the dynamics of influenza transmission. We reviewed published studies and found that once one household member is infected with influenza, the risk of infection in a household contact can be up to 38%, and the delay between onset in index and secondary cases is around 3 days. Younger age was associated with higher susceptibility. In the future, household transmission studies will provide information on transmission dynamics, including the correlation of virus shedding and symptoms with transmission, and the correlation of new measures of immunity with protection against infection.

Historically, household cohort studies have provided valuable information on the incidence of respiratory infections and risk factors for infection. However, these studies require substantial resources and can provide limited information on transmission dynamics.

Household transmission studies provide an efficient approach to describing the risk of influenza transmission and factors affecting transmission. In these studies, households with at least one member infected by influenza are eligible and are followed intensively for 1–2 weeks to observe secondary transmission within the household.

Transmission studies also provide a model for evaluation of interventions in randomized controlled trials, and have been used to determine the efficacy of antiviral drugs for treatment and prophylaxis, and nonpharmaceutical interventions such as face masks and hand hygiene.

Cross-immunity between strains explains the dynamical pattern of paramyxoviruses

Viral respiratory tract diseases pose serious public health problems. Our ability to predict and thus, be able to prepare for outbreaks is strained by the complex factors driving the prevalence and severity of these diseases. The abundance of diseases and transmission dynamics of strains are not only affected by external factors, such as weather, but also driven by interactions among viruses mediated by human behavior and immunity. To untangle the complex out-of-phase annual and biennial pattern of three common paramyxoviruses, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus (HPIV), and Human Metapneumovirus (hMPV), we adopt a theoretical approach that integrates ecological and immunological mechanisms of disease interactions. By estimating parameters from multiyear time series of laboratory-confirmed cases from the intermountain west region of the United States and using statistical inference, we show that models of immune-mediated interactions better explain the data than those based on ecological competition by convalescence. The strength of cross-protective immunity among viruses is correlated with their genetic distance in the phylogenetic tree of the paramyxovirus family.

Return of pandemic H1N1 influenza virus

Background

Influenza pandemics are usually caused by the re-assortment of several influenza viruses, results in the emergence of new influenza virus strains that can infect the entire population. These pandemic strains, as well as seasonal influenza viruses, are subjected to extensive antigenic change that has, so far, prevented the generation of a universal vaccine.

Methods

Samples of patients hospitalized due to infection with the pandemic H1N1 influenza virus (A(H1N1)pdm09) from 2009, when the virus first appeared, until 2013 were analyzed.

Results

While many patients were hospitalized in 2009 due to infection with the pandemic H1N1 influenza virus, only small percentages of patients were hospitalized later in 2010–2012. Surprisingly, however in 2012–2013, we noticed that the percentages of patients hospitalized due to the pandemic H1N1 influenza infection increased significantly. Moreover, the ages of hospitalized patients differed throughout this entire period (2009–2013) and pregnant women were especially vulnerable to the infection.

Conclusions

High percentages of patients (especially pregnant women) were hospitalized in 2013 due to the A(H1N1)pdm09 infection, which may have been enabled by an antigenic drift from those which circulated at the onset of the pandemic.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0710-1) contains supplementary material, which is available to authorized users.

Relationships between A(H1N1)pdm09 influenza infection and infections with other respiratory viruses

BACKGROUND

A(H1N1)pdm09, a new influenza pandemic virus emerged in 2009. The A(H1N1)pdm09 infection had several unique characteristics which included rapid transmissibility and high morbidity in obese individuals, pregnant women and individuals suffering from chronic diseases.

OBJECTIVES

To study the relationships between A(H1N1)pdm09 influenza infection and infections with other respiratory viruses such as respiratory syncytial virus (RSV), human metapneumo virus (hMPV), adenovirus and seasonal influenza.

METHODS

Samples (nasopharyngeal swabs or aspirates) collected between 2007 until 2012 from patients of various ages that were hospitalized due to respiratory virus infections were analyzed for the presence of various respiratory viruses, using qRT-PCR.

RESULTS

In 2009-2010, when the pandemic influenza A(H1N1)pdm09 first appeared, two major infection peaks were noted and individuals of various ages were infected. Following the decline of the A(H1N1)pdm09 virus infection, the percentages of patients infected with adenovirus and hMPV increased, while infection frequency with RSV B and with seasonal influenza virus decreased. Furthermore, RSV infections were delayed and very few percentages of patients were co-infected with more than one virus. Interestingly, the A(H1N1)pdm09 virus lost its dominancy when it reappeared in the winter of 2010-2011, and at this time, only the incidence of RSV infections was affected by the A(H1N1)pdm09 virus.

CONCLUSIONS

The A(H1N1)pdm09 virus had distinct effects on other respiratory viruses when it first appeared versus later, when it evolved from being a pandemic to a seasonal virus.

The influenza A (H1N1) pandemic in Reunion Island: knowledge, perceived risk and precautionary behaviour

Background

The effectiveness of preventive measures depends on prevailing attitudes and mindsets within a population. Perceived risk is central to a shift in mindset and behaviour. The present study aims to investigate the perceived severity, vulnerability and precautionary behaviour adopted in response to the influenza A (H1N1) epidemic that broke out in 2009 on Reunion Island (Indian Ocean). As no H1N1 vaccination was available at the time, non-medical interventions appeared of crucial importance to the control of the epidemic.

Methods

A cross sectional survey was conducted in Reunion Island between November 2009 and April 2010 within 2 months of the passage of the influenza A (H1N1) epidemic wave. Individual contacts representing 725 households (one contact per household) were interviewed by telephone using validated questionnaires on perceived risks. Mean scores were calculated for perceived severity, vulnerability, efficacy of preventive measures and precautionary behaviour. Univariate analysis was applied to identify preventive measures and attitudes and multivariate analysis was used to study the determinants of precautionary behaviour.

Results

More than 95% of contacted persons accepted to participate to the survey. Eighty seven percent of respondents believed that prevention was possible. On average, three out of six preventive measures were deemed effective. Spontaneously, 57% of the respondents reported that they took one or more preventive measures. This percentage increased to 87% after the interviewer detailed possible precautions one by one. The main precautions taken were frequent hand washing (59%) and avoidance of crowded places (34%). In multivariate logistic regression analysis the following factors were significantly associated with taking one or more preventive measures: young age, previous vaccination against seasonal influenza, having had seasonal influenza in the last five years, effectiveness of the preventive measures taken and low standards of education.

Conclusion

Inhabitants of Reunion Island have expressed a preventive approach adapted to the realities of the H1N1 pandemic, a feature that likely reflects some preparedness gained after the large and severe chikungunya epidemic that hit the island in 2006. The degree of severity was well assessed despite the initial alarmist messages disseminated by national and international media. Precautions that were undertaken matched the degree of severity of the epidemic and the recommendations issued by health authorities. Further qualitative studies are needed to help adapting public messages to the social and cultural realities of diverse communities and to prevent misconceptions.