Interim analysis of pandemic influenza (H1N1) 2009 in Australia: surveillance trends, age of infection and effectiveness of seasonal vaccination

Developing a Research Network of Early Warning Systems for Infectious Diseases Transmission Between China and Australia

This article offers a thorough review of current early warning systems (EWS) and advocates for establishing a unified research network for EWS in infectious diseases between China and Australia. We propose that future research should focus on improving infectious disease surveillance by integrating data from both countries to enhance predictive models and intervention strategies. The article highlights the need for standardized data formats and terminologies, improved surveillance capabilities, and the development of robust spatiotemporal predictive models. It concludes by examining the potential benefits and challenges of this collaborative approach and its implications for global infectious disease surveillance. This is particularly relevant to the ongoing project, early warning systems for Infectious Diseases between China and Australia (NetEWAC), which aims to use seasonal influenza as a case study to analyze influenza trends, peak activities, and potential inter-hemispheric transmission patterns. The project seeks to integrate data from both hemispheres to improve outbreak predictions and develop a spatiotemporal predictive modeling system for seasonal influenza transmission based on socio-environmental factors.

A Mathematical Modeling Study: Assessing Impact of Mismatch Between Influenza Vaccine Strains and Circulating Strains in Hajj

The influenza virus causes severe respiratory illnesses and deaths worldwide every year. It spreads quickly in an overcrowded area like the annual Hajj pilgrimage in Saudi Arabia. Vaccination is the primary strategy for protection against influenza. Due to the occurrence of antigenic shift and drift of the influenza virus, a mismatch between vaccine strains and circulating strains of influenza may occur. The objective of this study is to assess the impact of mismatch between vaccine strains and circulating strains during Hajj, which brings together individuals from all over the globe. To this end, we develop deterministic mathematical models of influenza with different populations and strains from the northern and southern hemispheres. Our results show that the existence and duration of an influenza outbreak during Hajj depend on vaccine efficacy. In this concern, we discuss four scenarios: vaccine strains for both groups match/mismatch circulating strains, and vaccine strains match their target strains and mismatch the other strains. Further, there is a scenario where a novel pandemic strain arises. Our results show that as long as the influenza vaccines match their target strains, there will be no outbreak of strain H1N1 and only a small outbreak of strain H3N2. Mismatching for non-target strains causes about 10,000 new H3N2 cases, and mismatching for both strains causes about 2,000 more new H1N1 cases and 6,000 additional H3N2 cases during Hajj. Complete mismatch in a pandemic scenario may infect over 342,000 additional pilgrims (13.75%) and cause more cases in their home countries.

Dynamic Propagation and Impact of Pandemic Influenza A (2009 H1N1) in Children: A Detailed Review

Influenza is a highly contagious respiratory infection caused by the circulating Swine flu virus. According to the World Health Organization (WHO), the unique blending strain of influenza A H1N1 2009 (Swine Flu) is a pandemic affecting several geographical regions, including India. Previous literature indicates that children are "drivers" of influenza pandemics. At present, satisfactory data were not available to accurately estimate the role of children in the spread of influenza (in particular 2009 pandemic influenza). However, the role of children in the spread of pandemics influenza is unclear. Several studies in children have indicated that the immunization program decreased the occurrence of influenza, emphasizing the significance of communities impacted by global immunization programs. This article provides a brief overview on how children are a key contributor to pandemic Influenza A (2009 H1N1) and we would like to draw your attention to the need for a new vaccine for children to improve disease prevention and a positive impact on the community.

COVID-19: Development of a robust mathematical model and simulation package with consideration for ageing population and time delay for control action and resusceptibility

The current global health emergency triggered by the pandemic COVID-19 is one of the greatest challenges we face in this generation. Computational simulations have played an important role to predict the development of the current pandemic. Such simulations enable early indications on the future projections of the pandemic and is useful to estimate the efficiency of control action in the battle against the SARS-CoV-2 virus. The SEIR model is a well-known method used in computational simulations of infectious viral diseases and it has been widely used to model other epidemics such as Ebola, SARS, MERS, and influenza A. This paper presents a modified SEIRS model with additional exit conditions in the form of death rates and resusceptibility, where we can tune the exit conditions in the model to extend prediction on the current projections of the pandemic into three possible outcomes; death, recovery, and recovery with a possibility of resusceptibility. The model also considers specific information such as ageing factor of the population, time delay on the development of the pandemic due to control action measures, as well as resusceptibility with temporal immune response. Owing to huge variations in clinical symptoms exhibited by COVID-19, the proposed model aims to reflect better on the current scenario and case data reported, such that the spread of the disease and the efficiency of the control action taken can be better understood. The model is verified using two case studies based on the real-world data in South Korea and Northern Ireland.

Seasonal Influenza Vaccine Impact on Pandemic H1N1 Vaccine Efficacy

Background

In 2009, a novel influenza A (pH1N1) was identified, resulting in a pandemic with significant morbidity and mortality. A monovalent pH1N1 vaccine was separately produced in addition to the seasonal trivalent influenza vaccine. Formulation of the seasonal influenza vaccine (injectable trivalent inactivated influenza vaccine [TIV] vs. intranasal live, attenuated influenza vaccine [LAIV]) was postulated to have impacted the efficacy of the pH1N1 vaccination.

Methods

We reviewed electronic health and databases, which included vaccination records, and healthcare encounters for influenza-like illness (ILI), influenza, and pneumonia among US military members. We examined rates by vaccination type to identify factors associated with the risk for study outcomes.

Results

Compared with those receiving the seasonal influenza vaccine alone, subjects receiving the pH1N1 vaccine, either alone (RR, 0.49) or in addition to the seasonal vaccine (RR, 0.51), had an approximately 50% reduction in ILI, 88% reduction in influenza (RR, 0.11 and 0.12, respectively), and 63% reduction in pneumonia (RR, 0.37 and 0.35, respectively). There was no clinically significant difference in ILI, influenza, or pneumonia attack rates among those receiving the pH1N1 vaccine with or without presence of the seasonal vaccine. Similarly, there was no clinically relevant difference in pH1N1 effectiveness between seasonal TIV and LAIV recipients.

Conclusions

During the 2009–2010 pandemic, the pH1N1 vaccination was effective in reducing rates of ILI, influenza, and pneumonia. Administration of the seasonal vaccine should continue without concern of potential interference with a novel pandemic vaccine, though more studies are needed to determine if this is applicable to other influenza seasons.

Social Media- and Internet-Based Disease Surveillance for Public Health

Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.

Atypical influenza A(H1N1)pdm09 strains caused an influenza virus outbreak in Saudi Arabia during the 2009-2011 pandemic season

BACKGROUND

The triple assortment influenza A(H1N1) virus emerged in spring 2009 and disseminated worldwide, including Saudi Arabia. This study was carried out to characterize Saudi influenza isolates in relation to the global strains and to evaluate the potential role of mutated residues in transmission, adaptation, and the pathogenicity of the virus.

METHODS

Nasopharyngeal samples (n = 6492) collected between September 2009 to March 2011 from patients with influenza-like illness were screened by PCR for influenza A(H1N1). Phylogenetic and Molecular evolutionary analysis were carried out to place the Saudi strains in relation to the global strains followed by Mutation analysis of surface and internal proteins.

RESULTS

Concatenated whole-genome phylogenetic analysis along with hemagglutinin (HA) signature changes, that is, Aspartic Acid (D) at position 187, P83S, S203T, and R223Q confirmed that the Saudi strains belong to the antigenic category of A/California/07/2009. However, phylogenetic analysis revealed unusual strains of A(H1N1) circulating in Saudi Arabia, not belonging to any of known clades, appearing in five distinct groups well supported by group-specific mutations and novel mutation complexes. These cases had characteristic inter- and intragroup substitution patterns while few of their closest matches showed up as sporadic cases the world over. Specific mutation patterns were detected within the functional domains of internal proteins PB2, PB1, PA, NP, NS1, and M2 having a putative role in viral fitness and virulence. Bayesian coalescent MCMC analysis revealed that Saudi strains belonged to cluster 2 of A(H1N1)pdm09 and spread a month later as compared to other strains of this cluster.

CONCLUSION

Influenza outbreak in Saudi Arabia during 2009-2011 was caused by atypical strains of influenza A(H1N1)pdm09, probably introduced in this community on multiple occasions. To understand the antigenic significance of these novel point mutations and mutation complexes require functional studies, which will be crucial for risk assessment of emergent strains and defining infection control measures.

A severe 2017 influenza season dominated by influenza A(H3N2), Victoria, Australia

Surveillance for influenza-like illness (ILI) and laboratory-confirmed influenza in Victoria, Australia is undertaken jointly by the Victorian Infectious Diseases Reference Laboratory and the Victorian Government Department of Health and Human Services from May to October each year. Surveillance data comprise notifiable laboratory-confirmed influenza and ILI reporting from from two sources – a general practice sentinel surveillance programme and a locum service.

The magnitude of the 2017 influenza season was high in Victoria with widespread circulation of influenza type A(H3N2), which peaked in September. A record number of laboratory-confirmed influenza cases were notified, and the proportion of ILI cases to total consultations from both the general practice and locum service were higher than previous years. Notified cases of influenza A were older than influenza B cases with 25% compared to 17% aged more than 65 years, respectively. The proportion of swabs that were positive for influenza peaked at 58%. Antigenic characterization suggested a good match between the circulating and vaccine strains of influenza A(H3N2).

Most of the increases observed in notified cases of laboratory-confirmed influenza in recent years in Victoria have been attributed to increases in testing. However, that cases of ILI also increased in Victoria in 2017 is suggestive that 2017 was a relatively severe season. The dominance of influenza type A(H3N2), the extended duration of elevated activity, and a potential phylogenetic mismatch of vaccine to circulating strains are likely to have contributed to the relative severity of the 2017 season.

Victoria is Australia’s second most populous state and is the mainland’s southernmost state. It has a temperate climate with an influenza season usually occurring in the cooler months between May and October. The Victorian Infectious Diseases Reference Laboratory (VIDRL), in partnership with the Victorian Government Department of Health and Human Services (DHHS), coordinates influenza-like illness (ILI) and laboratory-confirmed influenza surveillance in Victoria. There are three data sources included in the influenza surveillance system.

Using Web-Based Search Data to Study the Public's Reactions to Societal Events: The Case of the Sandy Hook Shooting

Background

Internet search is the most common activity on the World Wide Web and generates a vast amount of user-reported data regarding their information-seeking preferences and behavior. Although this data has been successfully used to examine outbreaks, health care utilization, and outcomes related to quality of care, its value in informing public health policy remains unclear.

Objective

The aim of this study was to evaluate the role of Internet search query data in health policy development. To do so, we studied the public’s reaction to a major societal event in the context of the 2012 Sandy Hook School shooting incident.

Methods

Query data from the Yahoo! search engine regarding firearm-related searches was analyzed to examine changes in user-selected search terms and subsequent websites visited for a period of 14 days before and after the shooting incident.

Results

A total of 5,653,588 firearm-related search queries were analyzed. In the after period, queries increased for search terms related to “guns” (+50.06%), “shooting incident” (+333.71%), “ammunition” (+155.14%), and “gun-related laws” (+535.47%). The highest increase (+1054.37%) in Web traffic was seen by news websites following “shooting incident” queries whereas searches for “guns” (+61.02%) and “ammunition” (+173.15%) resulted in notable increases in visits to retail websites. Firearm-related queries generally returned to baseline levels after approximately 10 days.

Conclusions

Search engine queries present a viable infodemiology metric on public reactions and subsequent behaviors to major societal events and could be used by policymakers to inform policy development.

Concordance of interim and final estimates of influenza vaccine effectiveness: a systematic review

The World Health Organization's Global Influenza Surveillance and Response System meets twice a year to generate a recommendation for the composition of the seasonal influenza vaccine. Interim vaccine effectiveness (VE) estimates provide a preliminary indication of influenza vaccine performance during the season and may be useful for decision making. We reviewed 17 pairs of studies reporting 33 pairs of interim and final estimates using the test-negative design to evaluate whether interim estimates can reliably predict final estimates. We examined features of the study design that may be correlated with interim estimates being substantially different from their final estimates and identified differences related to change in study period and concomitant changes in sample size, proportion vaccinated and proportion of cases. An absolute difference of no more than 10% between interim and final estimates was found for 18 of 33 reported pairs of estimates, including six of 12 pairs reporting VE against any influenza, six of 10 for influenza A(H1N1)pdm09, four of seven for influenza A(H3N2) and two of four for influenza B. While we identified inconsistencies in the methods, the similarities between interim and final estimates support the utility of generating and disseminating preliminary estimates of VE while virus circulation is ongoing.

Non-neutralizing antibodies induced by seasonal influenza vaccine prevent, not exacerbate A(H1N1)pdm09 disease

The association of seasonal trivalent influenza vaccine (TIV) with increased infection by 2009 pandemic H1N1 (A(H1N1)pdm09) virus, initially observed in Canada, has elicited numerous investigations on the possibility of vaccine-associated enhanced disease, but the potential mechanisms remain largely unresolved. Here, we investigated if prior immunization with TIV enhanced disease upon A(H1N1)pdm09 infection in mice. We found that A(H1N1)pdm09 infection in TIV-immunized mice did not enhance the disease, as measured by morbidity and mortality. Instead, TIV-immunized mice cleared A(H1N1)pdm09 virus and recovered at an accelerated rate compared to control mice. Prior TIV immunization was associated with potent inflammatory mediators and virus-specific CD8 T cell activation, but efficient immune regulation, partially mediated by IL-10R-signaling, prevented enhanced disease. Furthermore, in contrast to suggested pathological roles, pre-existing non-neutralizing antibodies (NNAbs) were not associated with enhanced virus replication, but rather with promoted antigen presentation through FcR-bearing cells that led to potent activation of virus-specific CD8 T cells. These findings provide new insights into interactions between pre-existing immunity and pandemic viruses.

Efficacy of a trivalent influenza vaccine against seasonal strains and against 2009 pandemic H1N1: A randomized, placebo-controlled trial

BACKGROUND

Before pandemic H1N1 vaccines were available, the potential benefit of existing seasonal trivalent inactivated influenza vaccines (IIV3s) against influenza due to the 2009 pandemic H1N1 influenza strain was investigated, with conflicting results. This study assessed the efficacy of seasonal IIV3s against influenza due to 2008 and 2009 seasonal influenza strains and against the 2009 pandemic H1N1 strain.

METHODS

This observer-blind, randomized, placebo-controlled study enrolled adults aged 18-64years during 2008 and 2009 in Australia and New Zealand. Participants were randomized 2:1 to receive IIV3 or placebo. The primary objective was to demonstrate the efficacy of IIV3 against laboratory-confirmed influenza. Participants reporting an influenza-like illness during the period from 14days after vaccination until 30 November of each study year were tested for influenza by real-time reverse transcription polymerase chain reaction.

RESULTS

Over a study period of 2years, 15,044 participants were enrolled (mean age±standard deviation: 35.5±14.7years; 54.4% female). Vaccine efficacy of the 2008 and 2009 IIV3s against influenza due to any strain was 42% (95% confidence interval [CI]: 30%, 52%), whereas vaccine efficacy against influenza due to the vaccine-matched strains was 60% (95% CI: 44%, 72%). Vaccine efficacy of the 2009 IIV3 against influenza due to the 2009 pandemic H1N1 strain was 38% (95% CI: 19%, 53%). No vaccine-related deaths or serious adverse events were reported. Solicited local and systemic adverse events were more frequent in IIV3 recipients than placebo recipients (local: IIV3 74.6% vs placebo 20.4%, p<0.001; systemic: IIV3 46.6% vs placebo 39.1%, p<0.001).

CONCLUSIONS

The 2008 and 2009 IIV3s were efficacious against influenza due to seasonal influenza strains and the 2009 IIV3 demonstrated moderate efficacy against influenza due to the 2009 pandemic H1N1 strain. Funded by CSL Limited, ClinicalTrials.gov identifier NCT00562484.

Identifying influenza-like illness presentation from unstructured general practice clinical narrative using a text classifier rule-based expert system versus a clinical expert

BACKGROUND

We designed and validated a rule-based expert system to identify influenza like illness (ILI) from routinely recorded general practice clinical narrative to aid a larger retrospective research study into the impact of the 2009 influenza pandemic in New Zealand.

METHODS

Rules were assessed using pattern matching heuristics on routine clinical narrative. The system was trained using data from 623 clinical encounters and validated using a clinical expert as a gold standard against a mutually exclusive set of 901 records.

RESULTS

We calculated a 98.2 % specificity and 90.2 % sensitivity across an ILI incidence of 12.4 % measured against clinical expert classification. Peak problem list identification of ILI by clinical coding in any month was 9.2 % of all detected ILI presentations. Our system addressed an unusual problem domain for clinical narrative classification; using notational, unstructured, clinician entered information in a community care setting. It performed well compared with other approaches and domains. It has potential applications in real-time surveillance of disease, and in assisted problem list coding for clinicians.

CONCLUSIONS

Our system identified ILI presentation with sufficient accuracy for use at a population level in the wider research study. The peak coding of 9.2 % illustrated the need for automated coding of unstructured narrative in our study.

Web search activity data accurately predict population chronic disease risk in the USA

BACKGROUND

The WHO framework for non-communicable disease (NCD) describes risks and outcomes comprising the majority of the global burden of disease. These factors are complex and interact at biological, behavioural, environmental and policy levels presenting challenges for population monitoring and intervention evaluation. This paper explores the utility of machine learning methods applied to population-level web search activity behaviour as a proxy for chronic disease risk factors.

METHODS

Web activity output for each element of the WHO's Causes of NCD framework was used as a basis for identifying relevant web search activity from 2004 to 2013 for the USA. Multiple linear regression models with regularisation were used to generate predictive algorithms, mapping web search activity to Centers for Disease Control and Prevention (CDC) measured risk factor/disease prevalence. Predictions for subsequent target years not included in the model derivation were tested against CDC data from population surveys using Pearson correlation and Spearman's r.

RESULTS

For 2011 and 2012, predicted prevalence was very strongly correlated with measured risk data ranging from fruits and vegetables consumed (r=0.81; 95% CI 0.68 to 0.89) to alcohol consumption (r=0.96; 95% CI 0.93 to 0.98). Mean difference between predicted and measured differences by State ranged from 0.03 to 2.16. Spearman's r for state-wise predicted versus measured prevalence varied from 0.82 to 0.93.

CONCLUSIONS

The high predictive validity of web search activity for NCD risk has potential to provide real-time information on population risk during policy implementation and other population-level NCD prevention efforts.

Mannan adjuvants intranasally administered inactivated influenza virus in mice rendering low doses inductive of strong serum IgG and IgA in the lung

BACKGROUND

H1N1 influenza viruses mutate rapidly, rendering vaccines developed in any given year relatively ineffective in subsequent years. Thus it is necessary to generate new vaccines every year, but this is time-consuming and resource-intensive. Should a highly virulent influenza strain capable of human-to-human transmission emerge, these factors will severely limit the number of people that can be effectively immunised against that strain in time to prevent a pandemic. An adjuvant and mode of administration capable of rendering ordinarily unprotective vaccine doses protective would thus be highly advantageous.

METHODS

The carbohydrate mannan was conjugated to whole inactivated H1N1 influenza virus at a range of ratios, and mixed with it at a range of ratios, and various doses of the resulting preparations were administered to mice via the intranasal (IN) route. Serum immunity was assessed via antigen-specific IgG ELISA and the haemagglutination-inhibition (HI) assay, and mucosal immunity was assessed via IgA ELISA of bronchio-alveolar lavages.

RESULTS

IN-administered inactivated H1N1 mixed with mannan induced higher serum IgG and respiratory-tract IgA than inactivated H1N1 conjugated to mannan, and HIN1 alone. Adjuvantation was mannan-dose-dependent, with 100 μg of mannan adjuvanting 1 μg of H1N1 more effectively than 10 or 50 μg of mannan. Serum samples from mice immunised with 1 μg H1N1 adjuvanted with 10 μg mannan did not inhibit agglutination of red blood cells (RBCs) at a dilution factor of 10 in the HI assay, but samples resulting from adjuvantation with 50 and 100 μg mannan inhibited agglutination at dilution factors of ≥ 40. Both serum IgG1 and IgG2a were induced by IN mannan-adjuvanted H1N1 vaccination, suggesting the induction of humoral and cellular immunity.

CONCLUSIONS

Mixing 100 μg of mannan with 1 μg of inactivated H1N1 adjuvanted the vaccine in mice, such that IN immunisation induced higher serum IgG and respiratory tract IgA than immunisation with virus alone. The serum from mice thus immunised inhibited H1N1-mediated RBC agglutination strongly in vitro. If mannan similarly adjuvants low doses of influenza vaccine in humans, it could potentially be used for vaccine 'dose-sparing' in the event that a vaccine shortage arises from an epidemic involving a highly virulent human-to-human transmissable influenza strain.

Description of hospitalized cases of influenza A(H1N1)pdm09 infection on the basis of the national hospitalized-case surveillance, 2009-2010, Japan

This study reports the epidemiological characteristics of hospitalized cases of influenza A(H1N1)pdm09 infection analyzed on the basis of surveillance data collected from July 24, 2009, the date on which the hospital-based surveillance of influenza cases was implemented in Japan, to September 5, 2010. During the study period, 13,581 confirmed cases were reported. Among those cases with information regarding the reason for hospitalization, 39% were admitted to hospitals for non-therapeutic purposes such as medical observation and laboratory testing. The overall hospitalization rate was 5.8 cases per 100,000 population when cases hospitalized for non-therapeutic purposes were excluded. While those aged under 20 years accounted for over 85% of hospitalized cases, the largest proportion of fatal cases was observed in those aged over 65 years. The overall case fatality rate for all hospitalized cases was 1.5%. The year-round surveillance for hospitalized influenza-like illness cases was launched in 2011, and it was expected that this surveillance system could add value by monitoring changes in the epidemiological characteristics of hospitalized cases of seasonal influenza.

The Possible Impact of Vaccination for Seasonal Influenza on Emergence of Pandemic Influenza via Reassortment

BACKGROUND

One pathway through which pandemic influenza strains might emerge is reassortment from coinfection of different influenza A viruses. Seasonal influenza vaccines are designed to target the circulating strains, which intuitively decreases the prevalence of coinfection and the chance of pandemic emergence due to reassortment. However, individual-based analyses on 2009 pandemic influenza show that the previous seasonal vaccination may increase the risk of pandemic A(H1N1) pdm09 infection. In view of pandemic influenza preparedness, it is essential to understand the overall effect of seasonal vaccination on pandemic emergence via reassortment.

METHODS AND FINDINGS

In a previous study we applied a population dynamics approach to investigate the effect of infection-induced cross-immunity on reducing such a pandemic risk. Here the model was extended by incorporating vaccination for seasonal influenza to assess its potential role on the pandemic emergence via reassortment and its effect in protecting humans if a pandemic does emerge. The vaccination is assumed to protect against the target strains but only partially against other strains. We find that a universal seasonal vaccine that provides full-spectrum cross-immunity substantially reduces the opportunity of pandemic emergence. However, our results show that such effectiveness depends on the strength of infection-induced cross-immunity against any novel reassortant strain. If it is weak, the vaccine that induces cross-immunity strongly against non-target resident strains but weakly against novel reassortant strains, can further depress the pandemic emergence; if it is very strong, the same kind of vaccine increases the probability of pandemic emergence.

CONCLUSIONS

Two types of vaccines are available: inactivated and live attenuated, only live attenuated vaccines can induce heterosubtypic immunity. Current vaccines are effective in controlling circulating strains; they cannot always help restrain pandemic emergence because of the uncertainty of the oncoming reassortant strains, however. This urges the development of universal vaccines for prevention of pandemic influenza.

Influenza-specific antibody-dependent cellular cytotoxicity: toward a universal influenza vaccine

There is an urgent need for universal influenza vaccines that can control emerging pandemic influenza virus threats without the need to generate new vaccines for each strain. Neutralizing Abs to the influenza virus hemagglutinin glycoprotein are effective at controlling influenza infection but generally target highly variable regions. Abs that can mediate other functions, such as killing influenza-infected cells and activating innate immune responses (termed "Ab-dependent cellular cytotoxicity [ADCC]-mediating Abs"), may assist in protective immunity to influenza. ADCC-mediating Abs can target more conserved regions of influenza virus proteins and recognize a broader array of influenza strains. We review recent research on influenza-specific ADCC Abs and their potential role in improved influenza-vaccination strategies.

Surveillance for emerging respiratory viruses

Several new viral respiratory tract infectious diseases with epidemic potential that threaten global health security have emerged in the past 15 years. In 2003, WHO issued a worldwide alert for an unknown emerging illness, later named severe acute respiratory syndrome (SARS). The disease caused by a novel coronavirus (SARS-CoV) rapidly spread worldwide, causing more than 8000 cases and 800 deaths in more than 30 countries with a substantial economic impact. Since then, we have witnessed the emergence of several other viral respiratory pathogens including influenza viruses (avian influenza H5N1, H7N9, and H10N8; variant influenza A H3N2 virus), human adenovirus-14, and Middle East respiratory syndrome coronavirus (MERS-CoV). In response, various surveillance systems have been developed to monitor the emergence of respiratory-tract infections. These include systems based on identification of syndromes, web-based systems, systems that gather health data from health facilities (such as emergency departments and family doctors), and systems that rely on self-reporting by patients. More effective national, regional, and international surveillance systems are required to enable rapid identification of emerging respiratory epidemics, diseases with epidemic potential, their specific microbial cause, origin, mode of acquisition, and transmission dynamics.

What can digital disease detection learn from (an external revision to) Google Flu Trends?

BACKGROUND

Google Flu Trends (GFT) claimed to generate real-time, valid predictions of population influenza-like illness (ILI) using search queries, heralding acclaim and replication across public health. However, recent studies have questioned the validity of GFT.

PURPOSE

To propose an alternative methodology that better realizes the potential of GFT, with collateral value for digital disease detection broadly.

METHODS

Our alternative method automatically selects specific queries to monitor and autonomously updates the model each week as new information about CDC-reported ILI becomes available, as developed in 2013. Root mean squared errors (RMSEs) and Pearson correlations comparing predicted ILI (proportion of patient visits indicative of ILI) with subsequently observed ILI were used to judge model performance.

RESULTS

During the height of the H1N1 pandemic (August 2 to December 22, 2009) and the 2012-2013 season (September 30, 2012, to April 12, 2013), GFT's predictions had RMSEs of 0.023 and 0.022 (i.e., hypothetically, if GFT predicted 0.061 ILI one week, it is expected to err by 0.023) and correlations of r=0.916 and 0.927. Our alternative method had RMSEs of 0.006 and 0.009, and correlations of r=0.961 and 0.919 for the same periods. Critically, during these important periods, the alternative method yielded more accurate ILI predictions every week, and was typically more accurate during other influenza seasons.

CONCLUSIONS

GFT may be inaccurate, but improved methodologic underpinnings can yield accurate predictions. Applying similar methods elsewhere can improve digital disease detection, with broader transparency, improved accuracy, and real-world public health impacts.

The ethics of sharing preliminary research findings during public health emergencies: a case study from the 2009 influenza pandemic

During the 2009 A(H1N1) influenza pandemic, a suite of studies conducted in Canada showed an unexpected finding, that patients with medically attended laboratory-confirmed pandemic influenza were more likely to have received seasonal influenza vaccination than test-negative control patients. Different bodies, including scientific journals and government scientific advisory committees, reviewed the evidence simultaneously to determine its scientific validity and implications. Decision-making was complicated when the findings made their way into the media. The normal trajectory of non-urgent research includes peer-review publication after which decision-makers can process the information taking into account other evidence and logistic considerations. In the situation that arose, however, the congruence of an unexpected finding and the simultaneous review of the evidence both within and outside the traditional peer-review sphere raised several interesting issues about how to deal with emerging evidence during a public health emergency. These events are used in this article to aid discussion of the complex interrelationship between researchers, public health decision-makers and scientific journals, the trade-offs between sharing information early and maintaining the peer-review quality assurance process, and to emphasise the need for critical reflection on the practical and ethical norms that govern the way in which research is evaluated, published and communicated in public health emergencies.

Performance of eHealth data sources in local influenza surveillance: a 5-year open cohort study

BACKGROUND

There is abundant global interest in using syndromic data from population-wide health information systems--referred to as eHealth resources--to improve infectious disease surveillance. Recently, the necessity for these systems to achieve two potentially conflicting requirements has been emphasized. First, they must be evidence-based; second, they must be adjusted for the diversity of populations, lifestyles, and environments.

OBJECTIVE

The primary objective was to examine correlations between data from Google Flu Trends (GFT), computer-supported telenursing centers, health service websites, and influenza case rates during seasonal and pandemic influenza outbreaks. The secondary objective was to investigate associations between eHealth data, media coverage, and the interaction between circulating influenza strain(s) and the age-related population immunity.

METHODS

An open cohort design was used for a five-year study in a Swedish county (population 427,000). Syndromic eHealth data were collected from GFT, telenursing call centers, and local health service website visits at page level. Data on mass media coverage of influenza was collected from the major regional newspaper. The performance of eHealth data in surveillance was measured by correlation effect size and time lag to clinically diagnosed influenza cases.

RESULTS

Local media coverage data and influenza case rates showed correlations with large effect sizes only for the influenza A (A) pH1N1 outbreak in 2009 (r=.74, 95% CI .42-.90; P<.001) and the severe seasonal A H3N2 outbreak in 2011-2012 (r=.79, 95% CI .42-.93; P=.001), with media coverage preceding case rates with one week. Correlations between GFT and influenza case data showed large effect sizes for all outbreaks, the largest being the seasonal A H3N2 outbreak in 2008-2009 (r=.96, 95% CI .88-.99; P<.001). The preceding time lag decreased from two weeks during the first outbreaks to one week from the 2009 A pH1N1 pandemic. Telenursing data and influenza case data showed correlations with large effect sizes for all outbreaks after the seasonal B and A H1 outbreak in 2007-2008, with a time lag decreasing from two weeks for the seasonal A H3N2 outbreak in 2008-2009 (r=.95, 95% CI .82-.98; P<.001) to none for the A p H1N1 outbreak in 2009 (r=.84, 95% CI .62-.94; P<.001). Large effect sizes were also observed between website visits and influenza case data.

CONCLUSIONS

Correlations between the eHealth data and influenza case rates in a Swedish county showed large effect sizes throughout a five-year period, while the time lag between signals in eHealth data and influenza rates changed. Further research is needed on analytic methods for adjusting eHealth surveillance systems to shifts in media coverage and to variations in age-group related immunity between virus strains. The results can be used to inform the development of alert-generating eHealth surveillance systems that can be subject for prospective evaluations in routine public health practice.

Influenza epidemiology and vaccine effectiveness among patients with influenza-like illness, viral watch sentinel sites, South Africa, 2005-2009

Background

There is limited data on the epidemiology of influenza and few published estimates of influenza vaccine effectiveness (VE) from Africa. In April 2009, a new influenza virus strain infecting humans was identified and rapidly spread globally. We compared the characteristics of patients ill with influenza A(H1N1)pdm09 virus to those ill with seasonal influenza and estimated influenza vaccine effectiveness during five influenza seasons (2005–2009) in South Africa.

Methods

Epidemiological data and throat and/or nasal swabs were collected from patients with influenza-like illness (ILI) at sentinel sites. Samples were tested for seasonal influenza viruses using culture, haemagglutination inhibition tests and/or polymerase chain reaction (PCR) and for influenza A(H1N1)pdm09 by real-time PCR. For the vaccine effectiveness (VE) analysis we considered patients testing positive for influenza A and/or B as cases and those testing negative for influenza as controls. Age-adjusted VE was calculated as 1-odds ratio for influenza in vaccinated and non-vaccinated individuals.

Results

From 2005 through 2009 we identified 3,717 influenza case-patients. The median age was significantly lower among patients infected with influenza A(H1N1)pdm09 virus than those with seasonal influenza, 17 and 27 years respectively (p<0.001). The vaccine coverage during the influenza season ranged from 3.4% in 2009 to 5.1% in 2006 and was higher in the ≥50 years (range 6.9% in 2008 to 13.2% in 2006) than in the <50 years age group (range 2.2% in 2007 to 3.7% in 2006). The age-adjusted VE estimates for seasonal influenza were 48.6% (4.9%, 73.2%); −14.2% (−9.7%, 34.8%); 12.0% (−70.4%, 55.4%); 67.4% (12.4%, 90.3%) and 29.6% (−21.5%, 60.1%) from 2005 to 2009 respectively. For the A(H1N1)pdm09 season, the efficacy of seasonal vaccine was −6.4% (−93.5%, 43.3%).

Conclusion

Influenza vaccine demonstrated a significant protective effect in two of the five years evaluated. Low vaccine coverage may have reduced power to estimate vaccine effectiveness.

Pandemic influenza A(H1N1)pdm09: risk of infection in primary healthcare workers

BACKGROUND

Healthcare workers in primary care are at risk of infection during an influenza pandemic. The 2009 influenza pandemic provided an opportunity to assess this risk.

AIM

To measure the prevalence of seropositivity to influenza A(H1N1)pdm09 among primary healthcare workers in Canterbury, New Zealand, following the 2009 influenza pandemic, and to examine associations between seropositivity and participants' sociodemographic characteristics, professional roles, work patterns, and seasonal influenza vaccination status.

DESIGN AND SETTING

An observational study involving a questionnaire and testing for influenza A(H1N1)pdm09 seropositivity in all primary healthcare workers in Canterbury, New Zealand between December 2009 and February 2010. Method Participants completed a questionnaire that recorded sociodemographic and professional data, symptoms of influenza-like illness, history of seasonal influenza vaccination, and work patterns. Serum samples were collected and haemagglutination inhibition antibody titres to influenza A(H1N1)pdm09 measured.

RESULTS

Questionnaires and serum samples were received from 1027 participants, from a workforce of 1476 (response rate 70%). Seropositivity was detected in 224 participants (22%). Receipt of seasonal influenza vaccine (odds ratio [OR] = 2.0, 95% confidence interval [CI] = 1.2 to 3.3), recall of influenza (OR = 1.9, 95% CI = 1.3 to 2.8), and age ≤45 years (OR = 1.4, 95% CI = 1.0 to 1.9) were associated with seropositivity.

CONCLUSION

A total of 22% of primary care healthcare workers were seropositive. Younger participants, those who recalled having influenza, and those who had been vaccinated against seasonal influenza were more likely to be seropositive. Working in a dedicated influenza centre was not associated with an increased risk of seropositivity.

Internet-based surveillance systems for monitoring emerging infectious diseases

Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases.

The significance of increased influenza notifications during spring and summer of 2010-11 in Australia

BACKGROUND & OBJECTIVE

During the temperate out-of-season months in Australia in late 2010 and early 2011, an unprecedented high number of influenza notifications were recorded. We aimed to assess the significance of these notifications.

METHODS

For Australia, we used laboratory-confirmed cases notified to the WHO FluNet surveillance tool; the percentage of these that were positive; notifications by state and influenza type and subtype; and surveillance data from Google FluTrends. For the state of Victoria, we used laboratory-confirmed notified cases and influenza-like illness (ILI) proportions. We compared virus characterisation using haemagglutination-inhibition assays and phylogenetic analysis of the haemagglutinin gene for seasonal and out-of-season notifications.

RESULTS

The increase in notifications was most marked in tropical and subtropical Australia, but the number of out-of-season notifications in temperate Victoria was more than five times higher than the average of the previous three seasons. However, ILI proportions in spring-summer were not different to previous years. All out-of-season viruses tested were antigenically and genetically similar to those tested during either the 2010 or 2011 influenza seasons. An increase in the number of laboratories testing for influenza has led to an increase in the number of tests performed and cases notified.

CONCLUSION

An increase in influenza infections in spring-summer of 2010-11 in tropical and temperate Australia was not associated with any differences in virus characterisation compared with viruses that circulated in the preceding and following winters. This increase probably reflected a natural variation in out-of-season virus circulation, which was amplified by increased laboratory testing.

Late season interim estimates of influenza vaccine effectiveness reliably predict end of season estimates in Victoria, Australia, 2007 to 2012

Twice each year the World Health Organization makes a recommendation for the composition of the influenza vaccine, based on circulating strains of influenza A(H3N2), A(H1N1) and B. Strain selection has always been based on immunogenicity studies with limited human data. Immunogenicity can be considered as a proxy for vaccine effectiveness (VE). However, only interim VE estimates for the target hemisphere can be considered in time for the strain selection meeting.Using surveillance data from Victoria, Australia, we retrospectively estimated and compared interim and final VE estimates for 2007 to 2012. In general, interim estimates were within five percentage points of final estimates. However, estimates made too early or in years of low influenza activity may be unreliable.

A Simulation Optimization Approach to Epidemic Forecasting

Reliable forecasts of influenza can aid in the control of both seasonal and pandemic outbreaks. We introduce a simulation optimization (SIMOP) approach for forecasting the influenza epidemic curve. This study represents the final step of a project aimed at using a combination of simulation, classification, statistical and optimization techniques to forecast the epidemic curve and infer underlying model parameters during an influenza outbreak. The SIMOP procedure combines an individual-based model and the Nelder-Mead simplex optimization method. The method is used to forecast epidemics simulated over synthetic social networks representing Montgomery County in Virginia, Miami, Seattle and surrounding metropolitan regions. The results are presented for the first four weeks. Depending on the synthetic network, the peak time could be predicted within a 95% CI as early as seven weeks before the actual peak. The peak infected and total infected were also accurately forecasted for Montgomery County in Virginia within the forecasting period. Forecasting of the epidemic curve for both seasonal and pandemic influenza outbreaks is a complex problem, however this is a preliminary step and the results suggest that more can be achieved in this area.

Using Google Trends for influenza surveillance in South China

BACKGROUND

Google Flu Trends was developed to estimate influenza activity in many countries; however there is currently no Google Flu Trends or other Internet search data used for influenza surveillance in China.

METHODS AND FINDINGS

Influenza surveillance data from 2008 through 2011 were obtained from provincial CDC influenza-like illness and virological surveillance systems of Guangdong, a province in south China. Internet search data were downloaded from the website of Google Trends. Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data and internet search trends. The correlation between CDC ILI surveillance and CDC virus surveillance was 0.56 (95% CI: 0.43, 0.66). The strongest correlation was between the Google Trends term of Fever and ILI surveillance with a correlation coefficient of 0.73 (95% CI: 0.66, 0.79). When compared with influenza virological surveillance, the Google Trends term of Influenza A had the strongest correlation with a correlation coefficient of 0.64 (95% CI: 0.43, 0.79) in the 2009 H1N1 influenza pandemic period.

CONCLUSIONS

This study shows that Google Trends in Chinese can be used as a complementary source of data for influenza surveillance in south China. More research in the future should develop new models using search trends in Chinese language to estimate local disease activity and detect early signals of outbreaks.

Profiling of humoral response to influenza A(H1N1)pdm09 infection and vaccination measured by a protein microarray in persons with and without history of seasonal vaccination

BACKGROUND

The influence of prior seasonal influenza vaccination on the antibody response produced by natural infection or vaccination is not well understood.

METHODS

We compared the profiles of antibody responses of 32 naturally infected subjects and 98 subjects vaccinated with a 2009 influenza A(H1N1) monovalent MF59-adjuvanted vaccine (Focetria, Novartis), with and without a history of seasonal influenza vaccination. Antibodies were measured by hemagglutination inhibition (HI) assay for influenza A(H1N1)pdm09 and by protein microarray (PA) using the HA1 subunit for seven recent and historic H1, H2 and H3 influenza viruses, and three avian influenza viruses. Serum samples for the infection group were taken at the moment of collection of the diagnostic sample, 10 days and 30 days after onset of influenza symptoms. For the vaccination group, samples were drawn at baseline, 3 weeks after the first vaccination and 5 weeks after the second vaccination.

RESULTS

We showed that subjects with a history of seasonal vaccination generally exhibited higher baseline titers for the various HA1 antigens than subjects without a seasonal vaccination history. Infection and pandemic influenza vaccination responses in persons with a history of seasonal vaccination were skewed towards historic antigens.

CONCLUSIONS

Seasonal vaccination is of significant influence on the antibody response to subsequent infection and vaccination, and further research is needed to understand the effect of annual vaccination on protective immunity.

Occurrence of AH1N1 viral infection and clinical features in symptomatic patients who received medical care during the 2009 influenza pandemic in Central Mexico

Background

In 2009 a new influenza serotype (AH1N1) was identified in Mexico that spread rapidly generating worldwide alarm. San Luis Potosi (SLP) was the third state with more cases reported in that year. The clinical identification of this flu posed a challenge to medical staff. This study aimed at estimating the AH1N1 infection, hospitalization and mortality rates, and at identifying related clinical features in persons who received medical care during the influenza pandemic.

Methods

Retrospective study with persons with flu-like illness who received public or private medical care in SLP from 15.03.09 to 30.10.09. Physicians purposely recorded many clinical variables. Samples from pharyngeal exudate or bronchoalveolar lavage were taken to diagnose AH1N1 using real-time PCR. Clinical predictors were identified using multivariate logistic regression with infection as a dependent variable. Odds ratios (OR) with 95% confidence intervals (CI) were computed. Analyses were stratified by age group based on the distribution of positive cases.

Results

From the 6922 persons with flu symptoms 6158 had available laboratory results from which 44.9% turned out to be positive for AH1N1. From those, 5.8% were hospitalized and 0.7% died. Most positive cases were aged 5–14 years and, in this subgroup, older age was positively associated with A H1N1 infection (95% CI 1.05-1.1); conversely, in patients aged 15 years or more, older age was negatively associated with the infection (95% CI 0.97-0.98). Fever was related in those aged 15 years or more (95% CI 1.4-3.5), and headache (95% CI 1.2-2.2) only in the 0–14 years group. Clear rhinorrhea and cough were positively related in both groups (p < 0.05). Arthralgia, dyspnea and vaccination history were related to lesser risk in persons aged 15 years or more, just as dyspnea, purulent rhinorrhea and leukocytosis were in the 0–14 years group.

Conclusion

This study identified various signs and symptoms for the clinical diagnosis of AH1N1 influenza and revealed that some of them can be age-specific.

Immunogenicity and safety of a 2009 pandemic influenza A (H1N1) monovalent vaccine in Chinese infants aged 6-35 months: a randomized, double-blind, controlled phase I clinical trial

Please cite this paper as: Li et al. (2012) Immunogenicity and safety of a 2009 pandemic influenza A (H1N1) monovalent vaccine in Chinese infants aged 6–35 months: a randomized, double‐blind, controlled phase I clinical trial. Influenza and Other Respiratory Viruses DOI: 10.1111/irv.12028.

Objectives  The goal of this double‐blind, randomized, controlled clinical trial was to assess the safety and immunogenicity of two different doses of a monovalent split‐virion 2009 pandemic influenza A/H1N1 vaccine without adjuvant in Chinese infants aged 6‐35 months.

Design and setting  Subjects were randomly assigned to receive either a 2009 pandemic (H1N1) vaccine containing 7.5 or 15 μg haemagglutinin (HA) or a seasonal influenza vaccine. 2 doses of the H1N1 vaccines or the seasonal influenza vaccine were given 21 days apart in younger infants aged 6‐23 months or older infants aged 24‐35 months.

Sample  Serum samples were collected immediately before the first injection and before and 21 days after the second injection.

Main outcome measures  Primary outcomes were haemagglutinin inhibition (HI) antibody responses 21 days following each vaccination. Safety was monitoring throughout the study.

Results  The first vaccination of 7.5 μg and 15 μg H1N1 vaccine induced seroprotective antibody titers (HI titers ≥ 1: 40) in 42.9‐57.4% of younger infants and 49.1‐61.0% older infants. Immune responses after completion of the two dose schedule were comparable in both age groups with seroprotective rates of 91‐98% in each vaccine and age group and GMTs of 173‐263. The H1N1 vaccine elicited similar rates of local and systemic adverse reactions as the seasonal influenza vaccine.

Conclusions  The 2009 pandemic influenza A /H1N1 vaccine were highly immunogenic in infants aged 6‐35 months, and displayed a safety and reactogenicity profile similar to the seasonal influenza vaccine.

Trial registration  ClinicalTrial.gov identifier: NCT01047202

Moderate influenza vaccine effectiveness with variable effectiveness by match between circulating and vaccine strains in Australian adults aged 20-64 years, 2007-2011

Please cite this paper as: Kelly et al. Moderate influenza vaccine effectiveness with variable effectiveness by match between circulating and vaccine strains in Australian adults aged 20–64 years, 2007–2011. Influenza and Other Respiratory Viruses DOI:10.1111/irv.12018.

Background  Influenza vaccines are licensed annually based on immunogenicity studies. We used five sequential years of data to estimate influenza vaccine effectiveness (VE), the critical outcome in the field.

Methods  Between 2007 and 2011, we performed annual prospective test‐negative design case–control studies among adults aged 20–64 years recruited from sentinel general practices in the Australian state of Victoria. We used PCR‐confirmed influenza as the endpoint to estimate influenza VE for all years. We compared annual VE estimates with the match between circulating and vaccine strains, determined by haemagglutination inhibition assays.

Results  The adjusted VE estimate for all years (excluding 2009) was 62% (95% CI 43, 75). By type and subtype, the point estimates of VE by year ranged between 31% for seasonal influenza A(H1N1) and 88% for influenza A(H1N1)pdm09. In 2007, when circulating strains were assessed as incompletely matched, the point estimate of the adjusted VE against all influenza was 58%. The point estimate was 59% in 2011 when all strains were assessed as well matched.

Conclusion  Trivalent inactivated vaccines provided moderate protection against laboratory‐confirmed influenza in adults of working age, although VE estimates were sensitive to the model used. VE estimates correlated poorly with circulating strain match, as assessed by haemagglutination inhibition assays, suggesting a need for VE studies that incorporate antigenic characterization data.

The impact of influenza A(H1N1)pdm09 compared with seasonal influenza on intensive care admissions in New South Wales, Australia, 2007 to 2010: a time series analysis

Background

In Australia, the 2009 epidemic of influenza A(H1N1)pdm09 resulted in increased admissions to intensive care. The annual contribution of influenza to use of intensive care is difficult to estimate, as many people with influenza present without a classic influenza syndrome and laboratory testing may not be performed. We used a population-based approach to estimate and compare the impact of recent epidemics of seasonal and pandemic influenza.

Methods

For 2007 to 2010, time series describing health outcomes in various population groups were prepared from a database of all intensive care unit (ICU) admissions in the state of New South Wales, Australia. The Serfling approach, a time series method, was used to estimate seasonal patterns in health outcomes in the absence of influenza epidemics. The contribution of influenza was estimated by subtracting expected seasonal use from observed use during each epidemic period.

Results

The estimated excess rate of influenza-associated respiratory ICU admissions per 100,000 inhabitants was more than three times higher in 2007 (2.6/100,000, 95% CI 2.0 to 3.1) than the pandemic year, 2009 (0.76/100,000, 95% CI 0.04 to 1.48). In 2009, the highest excess respiratory ICU admission rate was in 17 to 64 year olds (2.9/100,000, 95% CI 2.2 to 3.6), while in 2007, the highest excess rate was in those aged 65 years or older (9.5/100,000, 95% CI 6.2 to 12.8). In 2009, the excess rate was 17/100,000 (95% CI 14 to 20) in Aboriginal people and 14/100,000 (95% CI 13 to 16) in pregnant women.

Conclusion

While influenza was diagnosed more frequently and peak use of intensive care was higher during the epidemic of pandemic influenza in 2009, overall excess admissions to intensive care for respiratory illness was much greater during the influenza season in 2007. Thus, the impact of seasonal influenza on intensive care use may have previously been under-recognised. In 2009, high ICU use among young to middle aged adults was offset by relatively low use among older adults, and Aboriginal people and pregnant women were substantially over-represented in ICUs. Greater emphasis on prevention of serious illness in Aboriginal people and pregnant women should be a priority in pandemic planning.

Characterization of immune responses induced by immunization with the HA DNA vaccines of two antigenically distinctive H5N1 HPAIV isolates

The evolution of the H5N1 highly pathogenic avian influenza virus (HPAIV) has resulted in high sequence variations and diverse antigenic properties in circulating viral isolates. We investigated immune responses induced by HA DNA vaccines of two contemporary H5N1 HPAIV isolates, A/bar-headed goose/Qinghai/3/2005 (QH) and A/chicken/Shanxi/2/2006 (SX) respectively, against the homologous as well as the heterologous virus isolate for comparison. Characterization of antibody responses induced by immunization with QH-HA and SX-HA DNA vaccines showed that the two isolates are antigenically distinctive. Interestingly, after immunization with the QH-HA DNA vaccine, subsequent boosting with the SX-HA DNA vaccine significantly augmented antibody responses against the QH isolate but only induced low levels of antibody responses against the SX isolate. Conversely, after immunization with the SX-HA DNA vaccine, subsequent boosting with the QH-HA DNA vaccine significantly augmented antibody responses against the SX isolate but only induced low levels of antibody responses against the QH isolate. In contrast to the antibody responses, cross-reactive T cell responses are readily detected between these two isolates at similar levels. These results indicate the existence of original antigenic sin (OAS) between concurrently circulating H5N1 HPAIV strains, which may need to be taken into consideration in vaccine development against the potential H5N1 HPAIV pandemic.

Epidemiological characteristics and underlying risk factors for mortality during the autumn 2009 pandemic wave in Mexico

Background

Elucidating the role of the underlying risk factors for severe outcomes of the 2009 A/H1N1 influenza pandemic could be crucial to define priority risk groups in resource-limited settings in future pandemics.

Methods

We use individual-level clinical data on a large series of ARI (acute respiratory infection) hospitalizations from a prospective surveillance system of the Mexican Social Security medical system to analyze clinical features at presentation, admission delays, selected comorbidities and receipt of seasonal vaccine on the risk of A/H1N1-related death. We considered ARI hospitalizations and inpatient-deaths, and recorded demographic, geographic, and medical information on individual patients during August-December, 2009.

Results

Seasonal influenza vaccination was associated with a reduced risk of death among A/H1N1 inpatients (OR = 0.43 (95% CI: 0.25, 0.74)) after adjustment for age, gender, geography, antiviral treatment, admission delays, comorbidities and medical conditions. However, this result should be interpreted with caution as it could have been affected by factors not directly measured in our study. Moreover, the effect of antiviral treatment against A/H1N1 inpatient death did not reach statistical significance (OR = 0.56 (95% CI: 0.29, 1.10)) probably because only 8.9% of A/H1N1 inpatients received antiviral treatment. Moreover, diabetes (OR = 1.6) and immune suppression (OR = 2.3) were statistically significant risk factors for death whereas asthmatic persons (OR = 0.3) or pregnant women (OR = 0.4) experienced a reduced fatality rate among A/H1N1 inpatients. We also observed an increased risk of death among A/H1N1 inpatients with admission delays >2 days after symptom onset (OR = 2.7). Similar associations were also observed for A/H1N1-negative inpatients.

Conclusions

Geographical variation in identified medical risk factors including prevalence of diabetes and immune suppression may in part explain between-country differences in pandemic mortality burden. Furthermore, access to care including hospitalization without delay and antiviral treatment and are also important factors, as well as vaccination coverage with the 2008–09 trivalent inactivated influenza vaccine.

Sociodemographic factors and clinical conditions associated to hospitalization in influenza A (H1N1) 2009 virus infected patients in Spain, 2009-2010

The emergence and pandemic spread of a new strain of influenza A (H1N1) virus in 2009 resulted in a serious alarm in clinical and public health services all over the world. One distinguishing feature of this new influenza pandemic was the different profile of hospitalized patients compared to those from traditional seasonal influenza infections. Our goal was to analyze sociodemographic and clinical factors associated to hospitalization following infection by influenza A(H1N1) virus. We report the results of a Spanish nationwide study with laboratory confirmed infection by the new pandemic virus in a case-control design based on hospitalized patients. The main risk factors for hospitalization of influenza A (H1N1) 2009 were determined to be obesity (BMI≥40, with an odds-ratio [OR] 14.27), hematological neoplasia (OR 10.71), chronic heart disease, COPD (OR 5.16) and neurological disease, among the clinical conditions, whereas low education level and some ethnic backgrounds (Gypsies and Amerinds) were the sociodemographic variables found associated to hospitalization. The presence of any clinical condition of moderate risk almost triples the risk of hospitalization (OR 2.88) and high risk conditions raise this value markedly (OR 6.43). The risk of hospitalization increased proportionally when for two (OR 2.08) or for three or more (OR 4.86) risk factors were simultaneously present in the same patient. These findings should be considered when a new influenza virus appears in the human population.

Impacts on influenza A(H1N1)pdm09 infection from cross-protection of seasonal trivalent influenza vaccines and A(H1N1)pdm09 vaccines: systematic review and meta-analyses

Cross-protection by seasonal trivalent influenza vaccines (TIVs) against pandemic influenza A H1N1 2009 (now known as A[H1N1]pdm09) infection is controversial; and the vaccine effectiveness (VE) of A(H1N1)pdm09 vaccines has important health-policy implications. Systematic reviews and meta-analyses are needed to assess the impacts of both seasonal TIVs and A(H1N1)pdm09 vaccines against A(H1N1)pdm09.We did a systematic literature search to identify observational and/or interventional studies reporting cross-protection of TIV and A(H1N1)pdm09 VE from when the pandemic started (2009) until July 2011. The studies fulfilling inclusion criteria were meta-analysed. For cross-protection and VE, respectively, we stratified by vaccine type, study design and endpoint. Seventeen studies (104,781 subjects) and 10 studies (2,906,860 subjects), respectively, reported cross-protection of seasonal TIV and VE of A(H1N1)pdm09 vaccines; six studies (17,229 subjects) reported on both. Thirteen studies (95,903 subjects) of cross-protection, eight studies (859,461 subjects) of VE, and five studies (9,643 subjects) of both were meta-analysed and revealed: (1) cross-protection for confirmed illness was 19% (95% confident interval=13-42%) based on 13 case-control studies with notable heterogeneity. A higher cross-protection of 34% (9-52%) was found in sensitivity analysis (excluding five studies with moderate/high risk of bias). Further exclusion of studies that recruited early in the pandemic (when non-recipients of TIV were more likely to have had non-pandemic influenza infection that may have been cross-protective) dramatically reduced heterogeneity. One RCT reported cross-protection of 38% (19-53%) for confirmed illness. One case-control study reported cross-protection of 50% (40-59%) against hospitalisation. (2) VE of A(H1N1)pdm09 for confirmed illness was 86% (73-93%) based on 11 case-control studies and 79% (22-94%) based on two cohort studies; VE against medically-attended ILI was 32% (8-50%) in one cohort study. TIVs provided moderate cross-protection against both laboratory-confirmed A(H1N1)pdm09 illness (based on eight case-control studies with low risk of bias and one RCT) and also hospitalisation. A finding of increased risk from seasonal vaccine was limited to cases recruited early in the pandemic. A(H1N1)pdm09 vaccines were highly effective against confirmed A(H1N1)pdm09 illness. Although cross-protection was less than the direct effect of strain-specific vaccination against A(H1N1)pdm09, TIV was generally beneficial before A(H1N1)pdm09 vaccine was available.

Seroepidemiologic study of pandemic (H1N1) 2009 during outbreak in boarding school, England

TOC Summary: Prophylactic antiviral agents lower the odds of acute respiratory infection but not serologic infection.

Keywords: pandemic, influenza, A/H1N1, pandemic (H1N1) 2009, seroepidemiology, outbreak, serology, asymptomatic, prophylaxis, antiviral agents, vaccine, viruses, research

We conducted a seroepidemiologic study during an outbreak of pandemic (H1N1) 2009 in a boarding school in England. Overall, 353 (17%) of students and staff completed a questionnaire and provided a serum sample. The attack rate was 40.5% and 34.1% for self-reported acute respiratory infection (ARI). Staff were less likely to be seropositive than students 13–15 years of age (staff 20–49 years, adjusted odds ratio [AOR] 0.30; >50 years AOR 0.20). Teachers were more likely to be seropositive than other staff (AOR 7.47, 95% confidence interval [CI] 2.31–24.2). Of seropositive persons, 44.6% (95% CI 36.2%–53.3%) did not report ARI. Conversely, of 141 with ARI and 63 with influenza-like illness, 45.8% (95% CI 37.0%–54.0%) and 30.2% (95% CI 19.2%–43.0%) had negative test results, respectively. A weak association was found between seropositivity and a prophylactic dose of antiviral agents (AOR 0.55, 95% CI 0.30–0.99); prophylactic antiviral agents lowered the odds of ARI by 50%.

Intrahousehold transmission of pandemic (H1N1) 2009 virus, Victoria, Australia

To examine intrahousehold secondary transmission of pandemic (H1N1) 2009 virus in households in Victoria, Australia, we conducted a retrospective cross-sectional study in late 2009. We randomly selected case-patients reported during May-June 2009 and their household contacts. Information collected included household characteristics, use of prevention and control measures, and signs and symptoms. Secondary cases were defined as influenza-like illness in household contacts within the specified period. Secondary transmission was identified for 18 of 122 susceptible household contacts. To identify independent predictors of secondary transmission, we developed a model. Risk factors were concurrent quarantine with the household index case-patient, and a protective factor was antiviral prophylaxis. These findings show that timely provision of antiviral prophylaxis to household contacts, particularly when household members are concurrently quarantined during implementation of pandemic management strategies, delays or contains community transmission of pandemic (H1N1) 2009 virus.

Effectiveness of seasonal influenza vaccine against pandemic (H1N1) 2009 virus, Australia, 2010

To estimate effectiveness of seasonal trivalent and monovalent influenza vaccines against pandemic influenza A (H1N1) 2009 virus, we conducted a test-negative case–control study in Victoria, Australia, in 2010. Patients seen for influenza-like illness by general practitioners in a sentinel surveillance network during 2010 were tested for influenza; vaccination status was recorded. Case-patients had positive PCRs for pandemic (H1N1) 2009 virus, and controls had negative influenza test results. Of 319 eligible patients, test results for 139 (44%) were pandemic (H1N1) 2009 virus positive. Adjusted effectiveness of seasonal vaccine against pandemic (H1N1) 2009 virus was 79% (95% confidence interval 33%–93%); effectiveness of monovalent vaccine was 47% and not statistically significant. Vaccine effectiveness was higher among adults. Despite some limitations, this study indicates that the first seasonal trivalent influenza vaccine to include the pandemic (H1N1) 2009 virus strain provided significant protection against laboratory-confirmed pandemic (H1N1) 2009 infection.

Dynamic patterns of circulating seasonal and pandemic A(H1N1)pdm09 influenza viruses from 2007-2010 in and around Delhi, India

Influenza surveillance was carried out in a subset of patients with influenza-like illness (ILI) presenting at an Employee Health Clinic (EHS) at All India Institute of Medical Sciences (AIIMS), New Delhi (urban) and pediatric out patients department of civil hospital at Ballabhgarh (peri-urban), under the Comprehensive Rural Health Services Project (CRHSP) of AIIMS, in Delhi region from January 2007 to December 2010. Of the 3264 samples tested, 541 (17%) were positive for influenza viruses, of which 221 (41%) were pandemic Influenza A(H1N1)pdm09, 168 (31%) were seasonal influenza A, and 152 (28%) were influenza B. While the Influenza viruses were detected year-round, their types/subtypes varied remarkably. While there was an equal distribution of seasonal A(H1N1) and influenza B in 2007, predominance of influenza B was observed in 2008. At the beginning of 2009, circulation of influenza A(H3N2) viruses was observed, followed later by emergence of Influenza A(H1N1)pdm09 with co-circulation of influenza B viruses. Influenza B was dominant subtype in early 2010, with second wave of Influenza A(H1N1)pdm09 in August-September, 2010. With the exception of pandemic H1N1 emergence in 2009, the peaks of influenza activity coincided primarily with monsoon season, followed by minor peak in winter at both urban and rural sites. Age group analysis of influenza positivity revealed that the percent positivity of Influenza A(H1N1)pdm09 influenza virus was highest in >5-18 years age groups (OR 2.5; CI = 1.2-5.0; p = 0.009) when compared to seasonal influenza. Phylogenetic analysis of Influenza A(H1N1)pdm09 from urban and rural sites did not reveal any major divergence from other Indian strains or viruses circulating worldwide. Continued surveillance globally will help define regional differences in influenza seasonality, as well as, to determine optimal periods to implement influenza vaccination programs among priority populations.

Intradermal vaccination to protect against yellow fever and influenza

The viral infections yellow fever and influenza can lead to large epidemics, which may deplete limited vaccine supplies. The intradermal vaccination route of yellow fever and influenza vaccines has received renewed attention, because it allows dose reduction without loss of efficacy. In this chapter, we review these two vaccines, the history of vaccine development, correlates of protection, immune response to vaccination and current knowledge concerning intradermal vaccination, including the immunological background, both in healthy subjects and immunocompromized individuals.

"Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba

OBJECTIVES

We assessed the performance of syndromic indicators based on Google Flu Trends (GFT) and emergency department (ED) data for the early detection and monitoring of the 2009 H1N1 pandemic waves in Manitoba.

METHODS

Time-series curves for the weekly counts of laboratory-confirmed H1N1 cases in Manitoba during the 2009 pandemic were plotted against the three syndromic indicators: 1) GFT data, based on flu-related Internet search queries, 2) weekly count of all ED visits triaged as influenza-like illness (ED ILI volume), and 3) percentage of all ED visits that were triaged as an ILI (ED ILI percent). A linear regression model was fitted separately for each indicator and correlations with weekly virologic data were calculated for different lag periods for each pandemic wave.

RESULTS

All three indicators peaked 1-2 weeks earlier than the epidemic curve of laboratory-confirmed cases. For GFT data, the best-fitting model had about a 2-week lag period in relation to the epidemic curve. Similarly, the best-fitting models for both ED indicators were observed for a time lag of 1-2 weeks. All three indicators performed better as predictors of the virologic time trends during the second wave as compared to the first. There was strong congruence between the time series of the GFT and both the ED ILI volume and the ED ILI percent indicators.

CONCLUSION

During an influenza season characterized by high levels of disease activity, GFT and ED indicators provided a good indication of weekly counts of laboratory-confirmed influenza cases in Manitoba 1-2 weeks in advance.

Transmission characteristics of the 2009 H1N1 influenza pandemic: comparison of 8 Southern hemisphere countries

While in Northern hemisphere countries, the pandemic H1N1 virus (H1N1pdm) was introduced outside of the typical influenza season, Southern hemisphere countries experienced a single wave of transmission during their 2009 winter season. This provides a unique opportunity to compare the spread of a single virus in different countries and study the factors influencing its transmission. Here, we estimate and compare transmission characteristics of H1N1pdm for eight Southern hemisphere countries/states: Argentina, Australia, Bolivia, Brazil, Chile, New Zealand, South Africa and Victoria (Australia). Weekly incidence of cases and age-distribution of cumulative cases were extracted from public reports of countries' surveillance systems. Estimates of the reproduction numbers, R₀, empirically derived from the country-epidemics' early exponential phase, were positively associated with the proportion of children in the populations (p = 0.004). To explore the role of demography in explaining differences in transmission intensity, we then fitted a dynamic age-structured model of influenza transmission to available incidence data for each country independently, and for all the countries simultaneously. Posterior median estimates of R₀ ranged 1.2–1.8 for the country-specific fits, and 1.29–1.47 for the global fits. Corresponding estimates for overall attack-rate were in the range 20–50%. All model fits indicated a significant decrease in susceptibility to infection with age. These results confirm the transmissibility of the 2009 H1N1 pandemic virus was relatively low compared with past pandemics. The pattern of age-dependent susceptibility found confirms that older populations had substantial – though partial - pre-existing immunity, presumably due to exposure to heterologous influenza strains. Our analysis indicates that between-country-differences in transmission were at least partly due to differences in population demography.

Although relatively mild, the 2009 H1N1 pandemic reminded us once again of the on-going threat posed by novel respiratory viruses and the need for understanding better how such pathogens emerge and spread. From April to September 2009, countries in temperate regions of the Southern hemisphere experienced large epidemics of H1N1pdm during their winter season, with the new virus quickly becoming the predominant circulating influenza strain. We use mathematical modelling to analyse H1N1pdm epidemiological data from 8 southern hemisphere countries. We aim at understanding better the factors which may have influenced virus transmission in these countries. We find that transmissibility of the virus was relatively low compared with previous influenza pandemics, largely because of strong pre-existing age-dependent susceptibility to the virus (older people being less susceptible to infection, perhaps due to pre-existing immunity). We suggest that population demography had a strong impact on the virus spread and that higher transmission rates occurred in countries having a younger population. Our results highlight the requirement to use age-structured models for the analysis of influenza epidemics and support the need for country-specific analyses to inform the design of control policies for pandemic mitigation.