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

Seasonality as a driver of pH1N12009 influenza vaccination campaign impact

Although the most recent respiratory virus pandemic was triggered by a Coronavirus, sustained and elevated prevalence of highly pathogenic avian influenza viruses able to infect mammalian hosts highlight the continued threat of pandemics of influenza A virus (IAV) to global health. Retrospective analysis of pandemic outcomes, including comparative investigation of intervention efficacy in different regions, provide important contributions to the evidence base for future pandemic planning. The swine-origin IAV pandemic of 2009 exhibited regional variation in onset, infection dynamics and annual infection attack rates (IARs). For example, the UK experienced three severe peaks of infection over two influenza seasons, whilst Australia experienced a single severe wave. We adopt a seasonally forced 2-subtype model for the transmission of pH1N12009 and seasonal H3N2 to examine the role vaccination campaigns may play in explaining differences in pandemic trajectories in temperate regions. Our model differentiates between the nature of vaccine- and infection-acquired immunity. In particular, we assume that immunity triggered by infection elicits heterologous cross-protection against viral shedding in addition to long-lasting neutralising antibody, whereas vaccination induces imperfect reduction in susceptibility. We employ an Approximate Bayesian Computation (ABC) framework to calibrate the model using data for pH1N12009 seroprevalence, relative subtype dominance, and annual IARs for Australia and the UK. Heterologous cross-protection substantially suppressed the pandemic IAR over the posterior, with the strength of protection against onward transmission inversely correlated with the initial reproduction number. We show that IAV pandemic timing relative to the usual seasonal influenza cycle influenced the size of the initial waves of pH1N12009 in temperate regions and the impact of vaccination campaigns.

Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010

BACKGROUND

During 2009-2010, pandemic influenza A (H1N1) pdm09 virus (pH1N1) infections in England occurred in two epidemic waves. Reasons for a reported increase in case-severity during the second wave are unclear.

METHODS

We analysed hospital-based surveillance for patients with pH1N1 infections in England during 2009-2010 and linked national data sets to estimate ethnicity, socio-economic status and death within 28 days of admission. We used multivariable logistic regression to assess whether changes in demographic, clinical and management characteristics of patients could explain an increase in ICU admission or death, and accounted for missing values using multiple imputation.

RESULTS

During the first wave, 54/960 (6%) hospitalised patients required intensive care and 21/960 (2%) died; during the second wave 143/1420 (10%) required intensive care and 55/1420 (4%) died. In a multivariable model, during the second wave patients were less likely to be from an ethnic minority (OR 0.33, 95% CI 0.26-0.42), have an elevated deprivation score (OR 0.75, 95% CI 0.68-0.83), have known comorbidity (OR 0.78, 95% CI 0.63-0.97) or receive antiviral therapy ≤2 days before onset (OR 0.72, 95% CI 0.56-0.92). Increased case-severity during the second wave was not explained by changes in demographic, clinical or management characteristics.

CONCLUSIONS

Monitoring changes in patient characteristics could help target interventions during multiple waves of COVID-19 or a future influenza pandemic. To understand and respond to changes in case-severity, surveillance is needed that includes additional factors such as admission thresholds and seasonal coinfections.

Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records

Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic health record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2.

Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco

Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic medical record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2.

The impact of climate and antigenic evolution on seasonal influenza virus epidemics in Australia

Although seasonal influenza viruses circulate globally, prevention and treatment occur at the level of regions, cities, and communities. At these scales, the timing, duration and magnitude of epidemics vary substantially, but the underlying causes of this variation are poorly understood. Here, based on analyses of a 15-year city-level dataset of 18,250 laboratory-confirmed and antigenically-characterised influenza virus infections from Australia, we investigate the effects of previously hypothesised environmental and virological drivers of influenza epidemics. We find that anomalous fluctuations in temperature and humidity do not predict local epidemic onset timings. We also find that virus antigenic change has no consistent effect on epidemic size. In contrast, epidemic onset time and heterosubtypic competition have substantial effects on epidemic size and composition. Our findings suggest that the relationship between influenza population immunity and epidemiology is more complex than previously supposed and that the strong influence of short-term processes may hinder long-term epidemiological forecasts.

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.

Serological surveillance of influenza in an English sentinel network: pilot study protocol

BACKGROUND

Rapidly undertaken age-stratified serology studies can produce valuable data about a new emerging infection including background population immunity and seroincidence during an influenza pandemic. Traditionally seroepidemiology studies have used surplus laboratory sera with little or no clinical information or have been expensive detailed population based studies. We propose collecting population based sera from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), a sentinel network with extensive clinical data.

AIM

To pilot a mechanism to undertake population based surveys that collect serological specimens and associated patient data to measure seropositivity and seroincidence due to seasonal influenza, and create a population based serology bank. METHODS AND ANALYSIS: Setting and Participants: We will recruit 6 RCGP RSC practices already taking nasopharyngeal virology swabs. Patients who attend a scheduled blood test will be consented to donate additional blood samples. Approximately 100-150 blood samples will be collected from each of the following age bands - 18- 29, 30- 39, 40- 49, 50- 59, 60- 69 and 70+ years.

METHODS

We will send the samples to the Public Health England (PHE) Seroepidemiology Unit for processing and storage. These samples will be tested for influenza antibodies, using haemagglutination inhibition assays. Serology results will be pseudonymised, sent to the RCGP RSC and combined using existing processes at the RCGP RSC secure hub. The influenza seroprevalence results from the RCGP cohort will be compared against those from the annual PHE influenza residual serosurvey.

ETHICS AND DISSEMINATION

Ethical approval was granted by the Proportionate Review Sub- Committee of the London - Camden & Kings Cross on 6 February 2018. This study received approval from Health Research Authority on 7 February 2018. On completion the results will be made available via peer-reviewed journals.

Host contact structure is important for the recurrence of Influenza A

An important characteristic of influenza A is its ability to escape host immunity through antigenic drift. A novel influenza A strain that causes a pandemic confers full immunity to infected individuals. Yet when the pandemic strain drifts, these individuals will have decreased immunity to drifted strains in the following seasonal epidemics. We compute the required decrease in immunity so that a recurrence is possible. Models for influenza A must make assumptions on the contact structure on which the disease spreads. By considering local stability of the disease free equilibrium via computation of the reproduction number, we show that the classical random mixing assumption predicts an unrealistically large decrease of immunity before a recurrence is possible. We improve over the classical random mixing assumption by incorporating a contact network structure. A complication of contact networks is correlations induced by the initial pandemic. We provide a novel analytic derivation of such correlations and show that contact networks may require a dramatically smaller loss of immunity before recurrence. Hence, the key new insight in our paper is that on contact networks the establishment of a new strain is possible for much higher immunity levels of previously infected individuals than predicted by the commonly used random mixing assumption. This suggests that stable contacts like classmates, coworkers and family members are a crucial path for the spread of influenza in human populations.

Exploiting routinely collected severe case data to monitor and predict influenza outbreaks

Background

Influenza remains a significant burden on health systems. Effective responses rely on the timely understanding of the magnitude and the evolution of an outbreak. For monitoring purposes, data on severe cases of influenza in England are reported weekly to Public Health England. These data are both readily available and have the potential to provide valuable information to estimate and predict the key transmission features of seasonal and pandemic influenza.

Methods

We propose an epidemic model that links the underlying unobserved influenza transmission process to data on severe influenza cases. Within a Bayesian framework, we infer retrospectively the parameters of the epidemic model for each seasonal outbreak from 2012 to 2015, including: the effective reproduction number; the initial susceptibility; the probability of admission to intensive care given infection; and the effect of school closure on transmission. The model is also implemented in real time to assess whether early forecasting of the number of admissions to intensive care is possible.

Results

Our model of admissions data allows reconstruction of the underlying transmission dynamics revealing: increased transmission during the season 2013/14 and a noticeable effect of the Christmas school holiday on disease spread during seasons 2012/13 and 2014/15. When information on the initial immunity of the population is available, forecasts of the number of admissions to intensive care can be substantially improved.

Conclusion

Readily available severe case data can be effectively used to estimate epidemiological characteristics and to predict the evolution of an epidemic, crucially allowing real-time monitoring of the transmission and severity of the outbreak.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5671-7) contains supplementary material, which is available to authorized users.

Comparative study of lymphocytes from individuals that were vaccinated and unvaccinated against the pandemic 2009-2011 H1N1 influenza virus in Southern Brazil

INTRODUCTION

While no single factor is sufficient to guarantee the success of influenza vaccine programs, knowledge of the levels of immunity in local populations is critical. Here, we analyzed influenza immunity in a population from Southern Brazil, a region with weather conditions that are distinct from those in the rest of country, where influenza infections are endemic, and where greater than 50% of the population is vaccinated annually.

METHODS

Peripheral blood mononuclear cells were isolated from 40 individuals. Of these, 20 had received the H1N1 vaccine, while the remaining 20 were unvaccinated against the disease. Cells were stimulated in vitro with the trivalent post-pandemic influenza vaccine or with conserved major histocompatibility complex I (MHC I) peptides derived from hemagglutinin and neuraminidase. Cell viability was then analyzed by [3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide)]-based colorimetric assay (MTT), and culture supernatants were assayed for helper T type 1 (Th1) and Th2-specific cytokine levels.

RESULTS

Peripheral blood lymphocytes from vaccinated, but not unvaccinated, individuals exhibited significant proliferation in vitro in the presence of a cognate influenza antigen. After culturing with vaccine antigens, cells from vaccinated individuals produced similar levels of interleukin (IL)-10 and interferon (IFN)-γ, while those from unvaccinated individuals produced higher levels of IFN-γ than of IL-10.

CONCLUSIONS

Our data indicate that peripheral blood lymphocytes from vaccinated individuals are stimulated upon encountering a cognate antigen, but did not support the hypothesis that cross-reactive responses related to previous infections can ameliorate the immune response. Moreover, monitoring IL-10 production in vaccinated individuals could comprise a valuable tool for predicting disease evolution.

Recording of Influenza-Like Illness in UK Primary Care 1995-2013: Cohort Study

BACKGROUND

There is a lack of recent studies examining recording of influenza-like illness (ILI) in primary care in the UK over time and according to population characteristics. Our aim was to determine time trends and socio-demographic patterns of ILI recorded consultations in primary care.

METHODS

We used The Health Improvement Network (THIN) UK primary care database and extracted data on all ILI consultations between 1995 and 2013. We estimated ILI recorded consultation rates per 100,000 person-weeks (pw) by age, gender, deprivation and winter season. Negative binomial regression models were used to examine time trends and the effect of socio-demographic characteristics. Trends in ILI recorded consultations were compared to trends in consultations with less specific symptoms (cough or fever) recorded.

RESULTS

The study involved 7,682,908 individuals in 542 general practices. The ILI consultation rate decreased from 32.5/100,000 pw (95% confidence interval (CI) 32.1, 32.9) in 1995-98 to 15.5/100,000 pw (95% CI 15.4, 15.7) by 2010-13. The decrease occurred prior to 2002/3, and rates have remained largely stable since then. Declines were evident in all age groups. In comparison, cough or fever consultation rates increased from 169.4/100,000 pw (95% CI 168.6, 170.3) in 1995-98 to 237.7/100,000 pw (95% CI 237.2, 238.2) in 2010-13. ILI consultation rates were highest among individuals aged 15-44 years, higher in women than men, and in individuals from deprived areas.

CONCLUSION

There is substantial variation in ILI recorded consultations over time and by population socio-demographic characteristics, most likely reflecting changing recording behaviour by GPs. These results highlight the difficulties in using coded information from electronic primary care records to measure the severity of influenza epidemics across time and assess the relative burden of ILI in different population subgroups.

Social class based on occupation is associated with hospitalization for A(H1N1)pdm09 infection. Comparison between hospitalized and ambulatory cases

This study aimed to analyse the existence of an association between social class (categorized by type of occupation) and the occurrence of A(H1N1)pmd09 infection and hospitalization for two seasons (2009-2010 and 2010-2011). This multicentre study compared ambulatory A(H1N1)pmd09 confirmed cases with ambulatory controls to measure risk of infection, and with hospitalized A(H1N1)pmd09 confirmed cases to asses hospitalization risk. Study variables were: age, marital status, tobacco and alcohol use, pregnancy, chronic obstructive pulmonary disease, chronic respiratory failure, cardiovascular disease, diabetes, chronic liver disease, body mass index >40, systemic corticosteroid treatment and influenza vaccination status. Occupation was registered literally and coded into manual and non-manual worker occupational social class groups. A conditional logistic regression analysis was performed. There were 720 hospitalized cases, 996 ambulatory cases and 1062 ambulatory controls included in the study. No relationship between occupational social class and A(H1N1)pmd09 infection was found [adjusted odds ratio (aOR) 0·97, 95% confidence interval (CI) 0·74-1·27], but an association (aOR 1·53, 95% CI 1·01-2·31) between occupational class and hospitalization for A(H1N1)pmd09 was observed. Influenza vaccination was a protective factor for A(H1N1)pmd09 infection (aOR 0·41, 95% CI 0·23-0·73) but not for hospitalization. We conclude that manual workers have the highest risk of hospitalization when infected by influenza than other occupations but they do not have a different probability of being infected by influenza.

Anti-Human H1N1pdm09 and swine H1N1 Virus Antibodies among Swine Workers in Guangdong Province, China

To assess the potential transmission for zoonotic influenza, sero-antibodies against two kinds of influenza viruses—classical swine H1N1 and human H1N1pdm09 virus were detected in persons whose profession involved contact with swine in Guangdong province, China. Compared to the non-exposed control group, a significantly higher proportion of subjects with occupational contact to pigs exhibited positive seroreaction against the classical H1N1 SIV. Participants aged 26–50 years were at high risk of classic swine H1N1 infections. Seropositive rate to 2009 pandemic H1N1 virus among swine workers was similar with controls. The major impact of age was apparent for younger populations. Our present study has documented evidence for swine influenza virus infection among persons with occupational swine exposures. The differences of seroreactivity for the two tested influenza subtypes emphasize the necessity of regular surveillance both in pigs and human.

How sex and age affect immune responses, susceptibility to infections, and response to vaccination

Do men die young and sick, or do women live long and healthy? By trying to explain the sexual dimorphism in life expectancy, both biological and environmental aspects are presently being addressed. Besides age-related changes, both the immune and the endocrine system exhibit significant sex-specific differences. This review deals with the aging immune system and its interplay with sex steroid hormones. Together, they impact on the etiopathology of many infectious diseases, which are still the major causes of morbidity and mortality in people at old age. Among men, susceptibilities toward many infectious diseases and the corresponding mortality rates are higher. Responses to various types of vaccination are often higher among women thereby also mounting stronger humoral responses. Women appear immune-privileged. The major sex steroid hormones exhibit opposing effects on cells of both the adaptive and the innate immune system: estradiol being mainly enhancing, testosterone by and large suppressive. However, levels of sex hormones change with age. At menopause transition, dropping estradiol potentially enhances immunosenescence effects posing postmenopausal women at additional, yet specific risks. Conclusively during aging, interventions, which distinctively consider the changing level of individual hormones, shall provide potent options in maintaining optimal immune functions.

Longevity and determinants of protective humoral immunity after pandemic influenza infection

RATIONALE

Antibodies to influenza hemagglutinin are the primary correlate of protection against infection. The strength and persistence of this immune response influences viral evolution and consequently the nature of influenza epidemics. However, the durability and immune determinants of induction of humoral immunity after primary influenza infection remain unclear.

OBJECTIVES

The spread of a novel H1N1 (A[H1N1]pdm09) virus in 2009 through an unexposed population offered a natural experiment to assess the nature and longevity of humoral immunity after a single primary influenza infection.

METHODS

We followed A(H1N1)pdm09-seronegative adults through two influenza seasons (2009-2011) as they developed A(H1N1)pdm09 influenza infection or were vaccinated. Antibodies to A(H1N1)pdm09 virus were measured by hemagglutination-inhibition assay in individuals with paired serum samples collected preinfection and postinfection or vaccination to assess durability of humoral immunity. Preexisting A(H1N1)pdm09-specific multicytokine-secreting CD4 and CD8 T cells were quantified by multiparameter flow cytometry to test the hypothesis that higher frequencies of CD4(+) T-cell responses predict stronger antibody induction after infection or vaccination.

MEASUREMENTS AND MAIN RESULTS

Antibodies induced by natural infection persisted at constant high titer for a minimum of approximately 15 months. Contrary to our initial hypothesis, the fold increase in A(H1N1)pdm09-specific antibody titer after infection was inversely correlated to the frequency of preexisting circulating A(H1N1)pdm09-specific CD4(+)IL-2(+)IFN-γ(-)TNF-α(-) T cells (r = -0.4122; P = 0.03).

CONCLUSIONS

The longevity of protective humoral immunity after influenza infection has important implications for influenza transmission dynamics and vaccination policy, and identification of its predictive cellular immune correlate could guide vaccine development and evaluation.

Comparison of severely ill patients with influenza A(H1N1)pdm09 infection during the pandemic and post-pandemic periods in Singapore

BACKGROUND/OBJECTIVES

Singapore is a tropical country with influenza seasons occurring bi-annually. We compared the profile of severely ill patients with laboratory confirmed influenza A(H1N1)pdm09 infection in Singapore during the pandemic and post-pandemic periods, and studied their risk factors associated with mortality.

PATIENTS/METHODS

Three periods were defined for this study; pandemic period from 18 June to 29 August 2009, early post-pandemic period from 30 August 2009 to 12 February 2010, and late post-pandemic period from 13 February to 10 August 2010.

RESULTS

A total of 172 severely ill patients were admitted to hospitals from 18 June 2009 to 10 August 2010, of whom 23.8% died. The median age in the late post-pandemic period was significantly older than that in the early post-pandemic period (52 years versus 35 years, P=0.02). The median age of patients who died was significantly older than those who survived (52 years versus 44 years, P<0.01). The median length of stay under intensive care in the late post-pandemic period was twice that in the early post-pandemic (6 days versus 3 days, P=0.045). The proportion who died in the late post-pandemic period was more than 2.5 times that in the early post-pandemic period (29.8% versus 11.1%, P=0.043).

CONCLUSIONS

Severely ill patients were of older age in the late post-pandemic period. Older age was also significantly associated with mortality. It is important to maintain heightened vigilance and continue the surveillance of severely ill patients with influenza post-pandemic, so that patients with suspected infections could be promptly identified for early diagnosis and treatment.

Causal analysis of H1N1pdm09 influenza infection risk in a household cohort

Background

Obtaining a comprehensive quantitative figure of the determinants of influenza infection will help identify priority targets for future influenza mitigation interventions. We developed an original causal model integrating highly diverse factors and their dependencies, to identify the most critical determinants of pandemic influenza infection (H1N1pdm09) during the 2010–2011 influenza season.

Methods

We used data from 601 households (1450 participants) included in a dedicated cohort. Structural equations were used to model direct and indirect relationships between infection and risk perception, compliance with preventive behaviours, social contacts, indoor and outdoor environment, sociodemographic factors and pre-epidemic host susceptibility. Standardised estimates (β_std) were used to assess the strength of associations (ranging from −1 for a completely negative association to 1 for a completely positive association).

Results

Host susceptibility to H1N1pdm09 and compliance with preventive behaviours were the only two factors directly associated with the infection risk (β_std=0.31 and β_std=−0.21). Compliance with preventive behaviours was influenced by risk perception and preventive measures perception (β_std=0.14 and β_std=0.27). The number and duration of social contacts were not associated with H1N1pdm09 infection.

Conclusions

Our findings suggest that influenza vaccination in addition to public health communication campaigns focusing on personal preventive measures should be prioritised as potentially efficient interventions to mitigate influenza epidemics.

The influence of changing host immunity on 1918-19 pandemic dynamics

The sociological and biological factors which gave rise to the three pandemic waves of Spanish influenza in England during 1918-19 are still poorly understood. Symptom reporting data available for a limited set of locations in England indicates that reinfection in multiple waves occurred, suggesting a role for loss of infection-acquired immunity. Here we explore the role that changes in host immunity, driven by a combination of within-host factors and viral evolution, may play in explaining weekly mortality data and wave-by-wave symptomatic attack-rates available for a subset of English cities. Our results indicate that changes in the phenotype of the pandemic virus are likely required to explain the closely spaced waves of infection, but distinguishing between the detailed contributions of viral evolution and changing adaptive immune responses to transmission rates is difficult given the dearth of sero-epidemiological and virological data available even for more contemporary pandemics. We find that a dynamical model in which pre-pandemic protection in older "influenza-experienced" cohorts is lost rapidly prior to the second wave provides the best fit to the mortality and symptom reporting data. Best fitting parameter estimates for such a model indicate that post-infection protection lasted of order months, while other statistical analyses indicate that population-age was inversely correlated with overall mortality during the herald wave. Our results suggest that severe secondary waves of pandemic influenza may be triggered by viral escape from pre-pandemic immunity, and thus that understanding the role of heterosubtypic or cross-protective immune responses to pandemic influenza may be key to controlling the severity of future influenza pandemics.

Incidence of influenza A(H1N1)pdm09 infection, United Kingdom, 2009-2011

We conducted a longitudinal community cohort study of healthy adults in the UK. We found significantly higher incidence of influenza A(H1N1)pdm09 infection in 2010-11 than in 2009-10, a substantial proportion of subclinical infection, and higher risk for infection during 2010-11 among persons with lower preinfection antibody titers.

Antivirals in the 2009 pandemic--lessons and implications for future strategies

The World Health Organization's declaration of an imminent swine-origin influenza A pandemic in April 2009 triggered the global launch of national pandemic preparedness plans. An integral component of pandemic preparedness in many countries was the targeted use of antiviral therapy for containment, disease mitigation, and treatment. The 2009 pandemic marked the first pandemic during which influenza antivirals were available for global use. Although most national pandemic plans included provisions for antiviral treatment, these pre-determined protocols required frequent updating as more information became available about the virus, and its susceptibility to antiviral agents, the epidemiology of infection, and the population groups that were most susceptible to severe disease. National public health agencies in countries with both plans for use of antivirals and pre-existing stockpiles, including those in Japan, the United Kingdom, and the United States, operated distinctly different antiviral distribution and treatment programs from one another. In the 3 years following the pandemic, there is still little comparison of the diversity of national antiviral treatment policies and drug distribution mechanisms that were implemented, whether they had any mitigating effects and which might be most efficient. The purpose of this study is to outline roles of antiviral medicines in a pandemic period, provide insights into the diversity of antiviral treatment and distribution policies applied by selected countries between April 2009-July 2010, and to stimulate discussion on whether these policies remain appropriate for implementation in future pandemics.

Seroprevalence of antibody to influenza A(H1N1)pdm09 attributed to vaccination or infection, before and after the second (2010) pandemic wave in Australia

Objectives

Historical records of influenza pandemics demonstrate variability in incidence and severity between waves. The influenza A(H1N1)pdm09 pandemic was the first in which many countries implemented strain-specific vaccination to mitigate subsequent seasons. Serosurveys provide opportunity to examine the constraining influence of antibody on population disease experience.

Design

Changes in the proportion of adults seropositive to influenza A(H1N1)pdm09over the 2009/10 (summer) interepidemic period and 2010 (winter) influenza season were measured to determine whether there was a temporal relationship with vaccine distribution and influenza activity, respectively.

Setting

Australia.

Sample

Plasma samples were collected from healthy blood donors from seven cities at the end of the first wave (November 2009), and before (March/April 2010) and after (November 2010) the subsequent influenza season.

Main outcome measures

Haemagglutination inhibition (HI) assays were performed to assess reactivity of plasma against A(H1N1)pdm09, and the proportion seropositive (HI titre ≥ 40) compared over time, by age group and location.

Results

Between the 2009 and 2010 influenza seasons, the seropositive proportion rose from 22% to 43%, an increase observed across all ages and sites. Brisbane alone recorded a significant rise in seropositivity over the 2010 influenza season – from a baseline of 35% to 53%. The seropositive proportion elsewhere was ≥40% pre-season, and did not rise over winter.

Conclusions

A vaccine-associated increase in seropositive proportion preceding the influenza season correlated with low levels of disease activity in winter 2010. These observations support the role of immunisation in mitigating the ‘second wave’ of A(H1N1)pdm09, with timing critical to ensure sustained herd protection.

Increased transmissibility explains the third wave of infection by the 2009 H1N1 pandemic virus in England

In the 2009 H1N1 pandemic, the United Kingdom experienced two waves of infection, the first in the late spring and the second in the autumn. Given the low level of susceptibility to the pandemic virus expected to be remaining in the population after the second wave, it was a surprise that a substantial third epidemic occurred in the UK population between November 2010 and February 2011, despite no evidence for any significant antigenic evolution of the pandemic virus. Here, we use a mathematical model of influenza transmission embedded within a Bayesian synthesis inferential framework to jointly analyze syndromic, virological, and serological surveillance data collected in England in 2009-2011 and thereby assess epidemiological mechanisms which might have generated the third wave. We find that substantially increased transmissibility of the H1N1pdm09 virus is required to reproduce the third wave, suggesting that the virus evolved and increased fitness in the human host by the end of 2010, or that the very cold weather experienced in the United Kingdom at that time enhanced transmission rates. We also find some evidence that the preexisting heterologous immunity which reduced attack rates in adults during 2009 had substantially decayed by the winter of 2010, thus increasing the susceptibility of the adult population to infection. Finally, our analysis suggests that a pandemic vaccination campaign targeting adults and school-age children could have mitigated or prevented the third wave even at moderate levels of coverage.