Age-specific incidence of A/H1N1 2009 influenza infection in England from sequential antibody prevalence data using likelihood-based estimation.

Estimating the age-specific incidence of an emerging pathogen is essential for understanding its severity and transmission dynamics. This paper describes a statistical method that uses likelihoods to estimate incidence from sequential serological data. The method requires information on seroconversion intervals and allows integration of information on the temporal distribution of cases from clinical surveillance. Among a family of candidate incidences, a likelihood function is derived by reconstructing the change in seroprevalence from seroconversion following infection and comparing it with the observed sequence of positivity among the samples. This method is applied to derive the cumulative and weekly incidence of A/H1N1 pandemic influenza in England during the second wave using sera taken between September 2009 and February 2010 in four age groups (1-4, 5-14, 15-24, 25-44 years). The highest cumulative incidence was in 5-14 year olds (59%, 95% credible interval (CI): 52%, 68%) followed by 1-4 year olds (49%, 95% CI: 38%, 61%), rates 20 and 40 times higher respectively than estimated from clinical surveillance. The method provides a more accurate and continuous measure of incidence than achieved by comparing prevalence in samples grouped by time period

Seroprevalence of influenza A(H1N1)pdm09 virus antibody, England, 2010 and 2011.

The intense influenza activity in England during the 2010-11 winter resulted from a combination of factors. Population-based seroepidemiology confirms that the third wave of influenza A(H1N1)pdm09 virus circulation was associated with a shift in age groups affected, with the highest rate of infection in young adults

Humoral Response to the Influenza A H1N1/09 Monovalent AS03-Adjuvanted Vaccine in Immunocompromised Patients

In this observational study, safety and immunogenicity after one dose of the AS03-adjuvanted influenza H1N1/09 vaccine was overall appropriate in HIV-infected patients and solid-organ transplant recipients. A second dose of the vaccine only moderately improved the antibody respons

Early mucosal events promote distinct mucosal and systemic antibody responses to live attenuated influenza vaccine

Compared to intramuscular vaccines, nasally administered vaccines have the advantage of inducing local mucosal immune responses that may block infection and interrupt transmission of respiratory pathogens. Live attenuated influenza vaccine (LAIV) is effective in preventing influenza in children, but a correlate of protection for LAIV remains unclear. Studying young adult volunteers, we observe that LAIV induces distinct, compartmentalized, antibody responses in the mucosa and blood. Seeking immunologic correlates of these distinct antibody responses we find associations with mucosal IL-33 release in the first 8 hours post-inoculation and divergent CD8+ and circulating T follicular helper (cTfh) T cell responses 7 days post-inoculation. Mucosal antibodies are induced separately from blood antibodies, are associated with distinct immune responses early post-inoculation, and may provide a correlate of protection for mucosal vaccination. This study was registered as NCT04110366 and reports primary (mucosal antibody) and secondary (blood antibody, and nasal viral load and cytokine) endpoint data

Estimation of Seasonal Influenza Attack Rates and Antibody Dynamics in Children Using Cross-Sectional Serological Data.

Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24-60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics

Reproducibility of Serologic Assays for Influenza Virus A (H5N1)

Results for clade 1 viruses were more consistent among laboratories when a standard antibody was used

Haemagglutination inhibition and virus microneutralisation serology assays: use of harmonised protocols and biological standards in seasonal influenza serology testing and their impact on inter-laboratory variation and assay correlation: A FLUCOP collaborative study

Introduction: The haemagglutination inhibition assay (HAI) and the virus microneutralisation assay (MN) are long-established methods for quantifying antibodies against influenza viruses. Despite their widespread use, both assays require standardisation to improve inter-laboratory agreement in testing. The FLUCOP consortium aims to develop a toolbox of standardised serology assays for seasonal influenza. Building upon previous collaborative studies to harmonise the HAI, in this study the FLUCOP consortium carried out a head-to-head comparison of harmonised HAI and MN protocols to better understand the relationship between HAI and MN titres, and the impact of assay harmonisation and standardisation on inter-laboratory variability and agreement between these methods. Methods: In this paper, we present two large international collaborative studies testing harmonised HAI and MN protocols across 10 participating laboratories. In the first, we expanded on previously published work, carrying out HAI testing using egg and cell isolated and propagated wild-type (WT) viruses in addition to high-growth reassortants typically used influenza vaccines strains using HAI. In the second we tested two MN protocols: an overnight ELISA-based format and a 3-5 day format, using reassortant viruses and a WT H3N2 cell isolated virus. As serum panels tested in both studies included many overlapping samples, we were able to look at the correlation of HAI and MN titres across different methods and for different influenza subtypes. Results: We showed that the overnight ELISA and 3-5 day MN formats are not comparable, with titre ratios varying across the dynamic range of the assay. However, the ELISA MN and HAI are comparable, and a conversion factor could possibly be calculated. In both studies, the impact of normalising using a study standard was investigated, and we showed that for almost every strain and assay format tested, normalisation significantly reduced inter-laboratory variation, supporting the continued development of antibody standards for seasonal influenza viruses. Normalisation had no impact on the correlation between overnight ELISA and 3-5 day MN formats.publishedVersio

Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study.

BACKGROUND: Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. METHODS: Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; and a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. RESULTS: The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3-4 of 2018. Estimates for R0 were consistent over time for three of the four models until week 12 of 2018, and there was consistency in the estimation of R0 across the SPC and SS models, and in the ICU attack rates estimated by the ICU and the synthesis model. Estimation and predictions varied according to the assumed levels of pre-season immunity. CONCLUSIONS: This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable