Pandemic potential of a strain of influenza A (H1N1): early findings

Modelling and analysis of influenza A (H1N1) on networks

Background

In April 2009, a new strain of H1N1 influenza virus, referred to as pandemic influenza A (H1N1) was first detected in humans in the United States, followed by an outbreak in the state of Veracruz, Mexico. Soon afterwards, this new virus kept spreading worldwide resulting in a global outbreak. In China, the second Circular of the Ministry of Health pointed out that as of December 31, 2009, the country’s 31 provinces had reported 120,000 confirmed cases of H1N1.

Methods

We formulate an epidemic model of influenza A based on networks. We calculate the basic reproduction number and study the effects of various immunization schemes. The final size relation is derived for the network epidemic model. The model parameters are estimated via least-squares fitting of the model solution to the observed data in China.

Results

For the network model, we prove that the disease-free equilibrium is globally asymptotically stable when the basic reproduction is less than one. The final size will depend on the vaccination starting time, T, the number of infective cases at time T and immunization schemes to follow. Our theoretical results are confirmed by numerical simulations. Using the parameter estimates based on the observation data of the cumulative number of hospital notifications, we estimate the basic reproduction number R₀ to be 1.6809 in China.

Conclusions

Network modelling supplies a useful tool for studying the transmission of H1N1 in China, capturing the main features of the spread of H1N1. While a uniform, mass-immunization strategy helps control the prevalence, a targeted immunization strategy focusing on specific groups with given connectivity may better control the endemic.

Reactive strategies for containing developing outbreaks of pandemic influenza

BACKGROUND

In 2009 and the early part of 2010, the northern hemisphere had to cope with the first waves of the new influenza A (H1N1) pandemic. Despite high-profile vaccination campaigns in many countries, delays in administration of vaccination programs were common, and high vaccination coverage levels were not achieved. This experience suggests the need to explore the epidemiological and economic effectiveness of additional, reactive strategies for combating pandemic influenza.

METHODS

We use a stochastic model of pandemic influenza to investigate realistic strategies that can be used in reaction to developing outbreaks. The model is calibrated to documented illness attack rates and basic reproductive number (R0) estimates, and constructed to represent a typical mid-sized North American city.

RESULTS

Our model predicts an average illness attack rate of 34.1% in the absence of intervention, with total costs associated with morbidity and mortality of US$81 million for such a city. Attack rates and economic costs can be reduced to 5.4% and US$37 million, respectively, when low-coverage reactive vaccination and limited antiviral use are combined with practical, minimally disruptive social distancing strategies, including short-term, as-needed closure of individual schools, even when vaccine supply-chain-related delays occur. Results improve with increasing vaccination coverage and higher vaccine efficacy.

CONCLUSIONS

Such combination strategies can be substantially more effective than vaccination alone from epidemiological and economic standpoints, and warrant strong consideration by public health authorities when reacting to future outbreaks of pandemic influenza.

Clinical manifestations of influenza caused by A/H1N1v virus among children and teenagers consulted in general practice

BACKGROUND

Children and young adults are more susceptible to pandemic A/H1N1v infection than older people. There are some publications concerning the course of the pandemic influenza among pediatric population but mostly from hospital or from emergency units. There are very few observations of the course of pandemic influenza from primary care settings.

OBJECTIVE

The aim of the study was to describe clinical manifestations of influenza caused by a pandemic strain A/H1N1v among children and teenagers younger than 14 years who were observed, diagnosed, and treated in general practice.

MATERIAL AND METHODS

The observations were conducted among patients with symptoms of an acute respiratory tract infection in an urban area of Warsaw, Poland in November 2009. The inclusion criteria for performing a rapid influenza diagnostic test (RIDT) were established using the CDC definition of 'influenza-like illness' (ILI): fever >38.7°C plus cough and/or sore throat in the absence of another known cause of illness. In patients who met ILI criteria, nasopharyngeal swabs were taken for RIDT and RT-PCR. -

RESULTS

433 patients were consulted by a general practitioner and reported symptoms of an acute respiratory tract infection, 128 (30%) of them met inclusion criteria for ILI and were tested with RIDT: 31 children younger than 14 years and 97 adults. All 31 children suspected of ILI also were tested by RT-PCR. 20 children had a positive result of the rapid influenza test. For all children tested negative, RT-PCR was also negative, and out of 20 children with the presumptive diagnosis of influenza established after rapid influenza test, the diagnosis was confirmed by RT-PCR in 18; their median age was 6.6 years and ranged from13 months to 14 years. The most common symptoms of influenza A/H1N1v were: high fever (>39°C) - 96% of patients, dry cough - 86% of patients, malaise - 78% of patients, headache - 66% of patients, and diarrhea or vomiting - 28% of patients. Two children received treatment with oseltamivir (one boy with congenital heart defect and Down's syndrome and another with severe bronchial asthma). The duration of symptoms ranged from 1 to 13 days (mean of 6.6 days). No patients required hospitalization either due to primary influenza infection or secondary complications.

CONCLUSIONS

The course of influenza caused by virus A/H1N1v in children younger than 14 years observed in a primary care setting was mild and self-limited without the necessity of antiviral treatment in most cases. A rapid influenza diagnostic test is helpful in diagnosing pandemic influenza.

Flash infrared radiation disinfection of fibrous filters contaminated with bioaerosols

AIMS

  To investigate the effectiveness of infrared (IR) radiation heating in disinfecting air filters loaded with bioaerosols.

METHODS AND RESULTS

  An irradiation device was constructed considering the unique characteristics of IR and the physical dimensions and radiative properties of air filters. Filters loaded with test bioaerosols were irradiated with the device and flash heated to an ultra-high temperature (UHT). A maximum of 3·77-, 4·38- and 5·32-log inactivation of B. subtilis spores, E. coli, and MS2 virus respectively was achieved within 5 s of irradiation. Inactivation efficiency could be increased by using a higher IR power. Microscopic analysis showed no visible damage from the heat treatment that would affect filtration efficiency.

CONCLUSIONS

  Because the disinfection was a dry heat process, a temperature greater than 200°C was found necessary to successfully inactivate the test micro-organisms. The results demonstrate that IR is able to quickly disinfect filters given sufficient incident power. Compared to existing filter disinfection technologies, it offers a faster and more effective solution.

SIGNIFICANCE AND IMPACT OF THE STUDY

  It has been shown that IR heating is a feasible option for filter disinfection; possibly reducing fomite transmission of collected micro-organisms and preventing bioaerosol reaerosolization.

Optimal H1N1 vaccination strategies based on self-interest versus group interest

Background

Influenza vaccination is vital for reducing H1N1 infection-mediated morbidity and mortality. To reduce transmission and achieve herd immunity during the initial 2009-2010 pandemic season, the US Centers for Disease Control and Prevention (CDC) recommended that initial priority for H1N1 vaccines be given to individuals under age 25, as these individuals are more likely to spread influenza than older adults. However, due to significant delay in vaccine delivery for the H1N1 influenza pandemic, a large fraction of population was exposed to the H1N1 virus and thereby obtained immunity prior to the wide availability of vaccines. This exposure affects the spread of the disease and needs to be considered when prioritizing vaccine distribution.

Methods

To determine optimal H1N1 vaccine distributions based on individual self-interest versus population interest, we constructed a game theoretical age-structured model of influenza transmission and considered the impact of delayed vaccination.

Results

Our results indicate that if individuals decide to vaccinate according to self-interest, the resulting optimal vaccination strategy would prioritize adults of age 25 to 49 followed by either preschool-age children before the pandemic peak or older adults (age 50-64) at the pandemic peak. In contrast, the vaccine allocation strategy that is optimal for the population as a whole would prioritize individuals of ages 5 to 64 to curb a growing pandemic regardless of the timing of the vaccination program.

Conclusions

Our results indicate that for a delayed vaccine distribution, the priorities that are optimal at a population level do not align with those that are optimal according to individual self-interest. Moreover, the discordance between the optimal vaccine distributions based on individual self-interest and those based on population interest is even more pronounced when vaccine availability is delayed. To determine optimal vaccine allocation for pandemic influenza, public health agencies need to consider both the changes in infection risks among age groups and expected patterns of adherence.

Seroprevalence of pandemic 2009 (H1N1) influenza A virus among schoolchildren and their parents in Tokyo, Japan

Since its emergence, the 2009 pandemic H1N1 virus has spread rapidly throughout the world. Previously, we reported that most individuals born after 1920 do not have cross-reactive virus-neutralizing antibodies against pandemic (H1N1) 2009 virus, indicating that they were immunologically naïve to the pandemic virus prior to its emergence. This finding provided us with an excellent opportunity for a seroepidemiological investigation of the transmission mode of the pandemic virus in the community. To gain insight into its transmission within communities, we performed a serosurvey for pandemic virus infection with schoolchildren at an elementary school in Tokyo, Japan, and their parents. We observed a high prevalence of neutralizing antibodies to the pandemic virus in the children at this school, although the percentage of children positive for the neutralizing antibodies varied among classrooms. While a much lower prevalence was observed among parents, seropositivity of the parents correlated with that of their schoolchildren. Moreover, many adults appeared to have experienced asymptomatic infection with the pandemic virus. These data suggest that the pandemic virus was readily transmitted among schoolchildren in elementary schools and that it was also transmitted from schoolchildren to their parents.

Geography may explain adult mortality from the 1918-20 influenza pandemic

Seasonal influenza takes its most pronounced toll on children and the elderly, giving the crude age-specific mortality rates a U-shape. In contrast, A(H1N1) 1918-20 pandemic mortality was W-shaped. When adjusting for the seasonal baseline, young adults had higher but the elderly lower than expected mortality. The lower than expected mortality for the elderly is one reason why total mortality in urban societies were relatively low in 1918-20 (<1%). Why mortality peaked at age 30 but declined into old age is still not clear. It has been suggested that cohorts >30 years was protected because they were exposed to H1-like viruses prior to 1889. This hypothesis assumes that people lived within the reach of the urban disease pools. Here I analyze mortality after age 30 in aboriginal populations assumed to be infrequently exposed to influenza due to their geographic isolation. Results show that Arctic and Pacific peoples also experienced a decline in relative mortality after age 30. However, the remotely living elderly did not have lower than expected mortality, suggesting that they had less prior exposure to influenza than their urban counterpart. Crude total mortality and mortality for all adults >30 years was nevertheless extremely high in the remote populations. Parish records quantitatively confirmed the anecdotes that children 5-14 years were the only survivors in some Arctic communities. Low exposure to H1-like viruses in adults could not alone explain the high total mortality in remote populations (up to 90%). A high concurrent disease load, crowding, low genetic variability, a lack of basic care, and infrequent exposure to other forms of influenza virus 1890-1917 may have played a role as well. This form of immunological cross-protection from previous exposure to A-type influenza viruses other than H1N1 can only be explained as a consequence of cellular immunity against internal proteins that show less inter-strain variation than the surface proteins.

Mitigation strategies for pandemic influenza A: balancing conflicting policy objectives

Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R₀ and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.

In the event of an influenza pandemic which has high mortality and the potential to spread rapidly, such as the 1918–19 pandemic, there are a number of non-pharmaceutical public health control options available to reduce transmission in the community and mitigate the effects of the pandemic. These include reducing social contacts by closing schools or postponing public events, and encouraging hand washing and the use of masks. These interventions will not only have a non-intuitive impact on the epidemic dynamics, but they will also have direct and indirect social and economic costs, which mean that governments will only want to use them for a limited amount of time. We use simulations to show that limited-time interventions that achieve one aim, e.g., contain the total number of cases below some maximum number of treatments available, are not the same as those that achieve another, e.g., minimize peak demand for health care services. If multiple aims are defined simultaneously, we often see that the optimal intervention need not commence immediately but can begin a few weeks into the epidemic. Our research demonstrates the importance of tailoring pandemic plans to defined policy targets with some flexibility to allow for uncertainty in the characteristics of the pandemic.

An insertion mutation that distorts antibody binding site architecture enhances function of a human antibody

The structural and functional significance of somatic insertions and deletions in antibody chains is unclear. Here, we demonstrate that a naturally occurring three-amino-acid insertion within the influenza virus-specific human monoclonal antibody 2D1 heavy-chain variable region reconfigures the antibody-combining site and contributes to its high potency against the 1918 and 2009 pandemic H1N1 influenza viruses. The insertion arose through a series of events, including a somatic point mutation in a predicted hot-spot motif, introduction of a new hot-spot motif, a molecular duplication due to polymerase slippage, a deletion due to misalignment, and additional somatic point mutations. Atomic resolution structures of the wild-type antibody and a variant in which the insertion was removed revealed that the three-amino-acid insertion near the base of heavy-chain complementarity-determining region (CDR) H2 resulted in a bulge in that loop. This enlarged CDR H2 loop impinges on adjacent regions, causing distortion of the CDR H1 architecture and its displacement away from the antigen-combining site. Removal of the insertion restores the canonical structure of CDR H1 and CDR H2, but binding, neutralization activity, and in vivo activity were reduced markedly because of steric conflict of CDR H1 with the hemagglutinin antigen.

Antibody diversification through VDJ gene recombination, junctional variation, and somatic hypermutation has clear importance for the generation of mature, high-affinity antibodies. Between 1.3 and 6.5% of antibody variable gene sequences have been reported to contain insertions or deletions, but their structural and functional significance remains less well defined. The pandemic influenza virus hemagglutinin antibody 2D1 data suggest that somatic insertions and deletions in antibody genes contribute important structural and functional features. We predict that such features can be critical for affinity and functional maturation of the human antibody repertoire.

The effect of risk perception on the 2009 H1N1 pandemic influenza dynamics

Background

The 2009 H1N1 pandemic influenza dynamics in Italy was characterized by a notable pattern: as it emerged from the analysis of influenza-like illness data, after an initial period (September–mid-October 2009) characterized by a slow exponential increase in the weekly incidence, a sudden and sharp increase of the growth rate was observed by mid-October. The aim here is to understand whether spontaneous behavioral changes in the population could be responsible for such a pattern of epidemic spread.

Methodology/Principal Findings

In order to face this issue, a mathematical model of influenza transmission, accounting for spontaneous behavioral changes driven by cost/benefit considerations on the perceived risk of infection, is proposed and validated against empirical epidemiological data. The performed investigation revealed that an initial overestimation of the risk of infection in the general population, possibly induced by the high concern for the emergence of a new influenza pandemic, results in a pattern of spread compliant with the observed one. This finding is also supported by the analysis of antiviral drugs purchase over the epidemic period. Moreover, by assuming a generation time of 2.5 days, the initially diffuse misperception of the risk of infection led to a relatively low value of the reproductive number , which increased to in the subsequent phase of the pandemic.

Conclusions/Significance

This study highlights that spontaneous behavioral changes in the population, not accounted by the large majority of influenza transmission models, can not be neglected to correctly inform public health decisions. In fact, individual choices can drastically affect the epidemic spread, by altering timing, dynamics and overall number of cases.

Strategies for antiviral stockpiling for future influenza pandemics: a global epidemic-economic perspective

Influenza pandemics present a global threat owing to their potential mortality and substantial economic impacts. Stockpiling antiviral drugs to manage a pandemic is an effective strategy to offset their negative impacts; however, little is known about the long-term optimal size of the stockpile under uncertainty and the characteristics of different countries. Using an epidemic-economic model we studied the effect on total mortality and costs of antiviral stockpile sizes for Brazil, China, Guatemala, India, Indonesia, New Zealand, Singapore, the UK, the USA and Zimbabwe. In the model, antivirals stockpiling considerably reduced mortality. There was greater potential avoidance of expected costs in the higher resourced countries (e.g. from $55 billion to $27 billion over a 30 year time horizon for the USA) and large avoidance of fatalities in those less resourced (e.g. from 11.4 to 2.3 million in Indonesia). Under perfect allocation, higher resourced countries should aim to store antiviral stockpiles able to cover at least 15 per cent of their population, rising to 25 per cent with 30 per cent misallocation, to minimize fatalities and economic costs. Stockpiling is estimated not to be cost-effective for two-thirds of the world's population under current antivirals pricing. Lower prices and international cooperation are necessary to make the life-saving potential of antivirals cost-effective in resource-limited countries.

Travel patterns in China

The spread of infectious disease epidemics is mediated by human travel. Yet human mobility patterns vary substantially between countries and regions. Quantifying the frequency of travel and length of journeys in well-defined population is therefore critical for predicting the likely speed and pattern of spread of emerging infectious diseases, such as a new influenza pandemic. Here we present the results of a large population survey undertaken in 2007 in two areas of China: Shenzhen city in Guangdong province, and Huangshan city in Anhui province. In each area, 10,000 randomly selected individuals were interviewed, and data on regular and occasional journeys collected. Travel behaviour was examined as a function of age, sex, economic status and home location. Women and children were generally found to travel shorter distances than men. Travel patterns in the economically developed Shenzhen region are shown to resemble those in developed and economically advanced middle income countries with a significant fraction of the population commuting over distances in excess of 50 km. Conversely, in the less developed rural region of Anhui, travel was much more local, with very few journeys over 30 km. Travel patterns in both populations were well-fitted by a gravity model with a lognormal kernel function. The results provide the first quantitative information on human travel patterns in modern China, and suggest that a pandemic emerging in a less developed area of rural China might spread geographically sufficiently slowly for containment to be feasible, while spatial spread in the more economically developed areas might be expected to be much more rapid, making containment more difficult.

The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale

BACKGROUND

Computational models play an increasingly important role in the assessment and control of public health crises, as demonstrated during the 2009 H1N1 influenza pandemic. Much research has been done in recent years in the development of sophisticated data-driven models for realistic computer-based simulations of infectious disease spreading. However, only a few computational tools are presently available for assessing scenarios, predicting epidemic evolutions, and managing health emergencies that can benefit a broad audience of users including policy makers and health institutions.

RESULTS

We present "GLEaMviz", a publicly available software system that simulates the spread of emerging human-to-human infectious diseases across the world. The GLEaMviz tool comprises three components: the client application, the proxy middleware, and the simulation engine. The latter two components constitute the GLEaMviz server. The simulation engine leverages on the Global Epidemic and Mobility (GLEaM) framework, a stochastic computational scheme that integrates worldwide high-resolution demographic and mobility data to simulate disease spread on the global scale. The GLEaMviz design aims at maximizing flexibility in defining the disease compartmental model and configuring the simulation scenario; it allows the user to set a variety of parameters including: compartment-specific features, transition values, and environmental effects. The output is a dynamic map and a corresponding set of charts that quantitatively describe the geo-temporal evolution of the disease. The software is designed as a client-server system. The multi-platform client, which can be installed on the user's local machine, is used to set up simulations that will be executed on the server, thus avoiding specific requirements for large computational capabilities on the user side.

CONCLUSIONS

The user-friendly graphical interface of the GLEaMviz tool, along with its high level of detail and the realism of its embedded modeling approach, opens up the platform to simulate realistic epidemic scenarios. These features make the GLEaMviz computational tool a convenient teaching/training tool as well as a first step toward the development of a computational tool aimed at facilitating the use and exploitation of computational models for the policy making and scenario analysis of infectious disease outbreaks.

Reconstructing disease outbreaks from genetic data: a graph approach

Epidemiology and public health planning will increasingly rely on the analysis of genetic sequence data. In particular, genetic data coupled with dates and locations of sampled isolates can be used to reconstruct the spatiotemporal dynamics of pathogens during outbreaks. Thus far, phylogenetic methods have been used to tackle this issue. Although these approaches have proved useful for informing on the spread of pathogens, they do not aim at directly reconstructing the underlying transmission tree. Instead, phylogenetic models infer most recent common ancestors between pairs of isolates, which can be inadequate for densely sampled recent outbreaks, where the sample includes ancestral and descendent isolates. In this paper, we introduce a novel method based on a graph approach to reconstruct transmission trees directly from genetic data. Using simulated data, we show that our approach can efficiently reconstruct genealogies of isolates in situations where classical phylogenetic approaches fail to do so. We then illustrate our method by analyzing data from the early stages of the swine-origin A/H1N1 influenza pandemic. Using 433 isolates sequenced at both the hemagglutinin and neuraminidase genes, we reconstruct the likely history of the worldwide spread of this new influenza strain. The presented methodology opens new perspectives for the analysis of genetic data in the context of disease outbreaks.

A simple stochastic lattice gas model for H1N1 pandemic. Application to the Italian epidemiological data

We construct a very simple epidemic model for influenza spreading in an age-class-distributed population, by coupling a lattice gas model for the population dynamics with a SIR stochastic model for susceptible, infected and removed/immune individuals. We use as a test case the age-distributed Italian epidemiological data for the novel influenza A(H1N1). The most valuable features of this model are its country-independent and virus-independent structure (few demographic, social and virological data are used to fix some parameters), its large statistic due to a very short run-time machine, and its easy generalizability to include mitigation strategies. In spite of its simplicity, the model presented reproduces the epidemiological Italian data, with sensible predictions for the reproduction number and theoretically interesting results for the generation time distribution.

Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic

After the emergence of the H1N1 influenza in 2009, some countries responded with travel-related controls during the early stage of the outbreak in an attempt to contain or slow down its international spread. These controls along with self-imposed travel limitations contributed to a decline of about 40% in international air traffic to/from Mexico following the international alert. However, no containment was achieved by such restrictions and the virus was able to reach pandemic proportions in a short time. When gauging the value and efficacy of mobility and travel restrictions it is crucial to rely on epidemic models that integrate the wide range of features characterizing human mobility and the many options available to public health organizations for responding to a pandemic. Here we present a comprehensive computational and theoretical study of the role of travel restrictions in halting and delaying pandemics by using a model that explicitly integrates air travel and short-range mobility data with high-resolution demographic data across the world and that is validated by the accumulation of data from the 2009 H1N1 pandemic. We explore alternative scenarios for the 2009 H1N1 pandemic by assessing the potential impact of mobility restrictions that vary with respect to their magnitude and their position in the pandemic timeline. We provide a quantitative discussion of the delay obtained by different mobility restrictions and the likelihood of containing outbreaks of infectious diseases at their source, confirming the limited value and feasibility of international travel restrictions. These results are rationalized in the theoretical framework characterizing the invasion dynamics of the epidemics at the metapopulation level.

A cluster randomized clinical trial comparing fit-tested and non-fit-tested N95 respirators to medical masks to prevent respiratory virus infection in health care workers

Please cite this paper as: MacIntyre et al. (2011) A cluster randomized clinical trial comparing fit‐tested and non‐fit‐tested N95 respirators to medical masks to prevent respiratory virus infection in health care workers. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750‐2659.2010.00198.x.

Background  We compared the efficacy of medical masks, N95 respirators (fit tested and non fit tested), in health care workers (HCWs).

Methods  A cluster randomized clinical trial (RCT) of 1441 HCWs in 15 Beijing hospitals was performed during the 2008/2009 winter. Participants wore masks or respirators during the entire work shift for 4 weeks. Outcomes included clinical respiratory illness (CRI), influenza‐like illness (ILI), laboratory‐confirmed respiratory virus infection and influenza. A convenience no‐mask/respirator group of 481 health workers from nine hospitals was compared.

Findings  The rates of CRI (3·9% versus 6·7%), ILI (0·3% versus 0·6%), laboratory‐confirmed respiratory virus (1·4% versus 2·6%) and influenza (0·3% versus 1%) infection were consistently lower for the N95 group compared to medical masks. By intention‐to‐treat analysis, when P values were adjusted for clustering, non‐fit‐tested N95 respirators were significantly more protective than medical masks against CRI, but no other outcomes were significant. The rates of all outcomes were higher in the convenience no‐mask group compared to the intervention arms. There was no significant difference in outcomes between the N95 arms with and without fit testing. Rates of fit test failure were low. In a post hoc analysis adjusted for potential confounders, N95 masks and hospital level were significant, but medical masks, vaccination, handwashing and high‐risk procedures were not.

Interpretation  Rates of infection in the medical mask group were double that in the N95 group. A benefit of respirators is suggested but would need to be confirmed by a larger trial, as this study may have been underpowered. The finding on fit testing is specific to the type of respirator used in the study and cannot be generalized to other respirators.

Trial registration  Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN: ACTRN12609000257268 (http://www.anzctr.org.au).

Overview/reflections on the 2009 H1N1 pandemic

The Influenza A H1N1 2009 pandemic was a test of the global public health response. Strategies that worked included mass vaccine production and antivirals while quarantine and isolation proved futile. Among the lessons learned was the importance of severity in the definition of a pandemic.

Theoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak

Background

While many pandemic preparedness plans have promoted disease control effort to lower and delay an epidemic peak, analytical methods for determining the required control effort and making statistical inferences have yet to be sought. As a first step to address this issue, we present a theoretical basis on which to assess the impact of an early intervention on the epidemic peak, employing a simple epidemic model.

Methods

We focus on estimating the impact of an early control effort (e.g. unsuccessful containment), assuming that the transmission rate abruptly increases when control is discontinued. We provide analytical expressions for magnitude and time of the epidemic peak, employing approximate logistic and logarithmic-form solutions for the latter. Empirical influenza data (H1N1-2009) in Japan are analyzed to estimate the effect of the summer holiday period in lowering and delaying the peak in 2009.

Results

Our model estimates that the epidemic peak of the 2009 pandemic was delayed for 21 days due to summer holiday. Decline in peak appears to be a nonlinear function of control-associated reduction in the reproduction number. Peak delay is shown to critically depend on the fraction of initially immune individuals.

Conclusions

The proposed modeling approaches offer methodological avenues to assess empirical data and to objectively estimate required control effort to lower and delay an epidemic peak. Analytical findings support a critical need to conduct population-wide serological survey as a prior requirement for estimating the time of peak.

Serological response to the 2009 pandemic influenza A (H1N1) virus for disease diagnosis and estimating the infection rate in Thai population

Background

Individuals infected with the 2009 pandemic virus A(H1N1) developed serological response which can be measured by hemagglutination-inhibition (HI) and microneutralization (microNT) assays.

Methodology/Principal Findings

MicroNT and HI assays for specific antibody to the 2009 pandemic virus were conducted in serum samples collected at the end of the first epidemic wave from various groups of Thai people: laboratory confirmed cases, blood donors and health care workers (HCW) in Bangkok and neighboring province, general population in the North and the South, as well as archival sera collected at pre- and post-vaccination from vaccinees who received influenza vaccine of the 2006 season. This study demonstrated that goose erythrocytes yielded comparable HI antibody titer as compared to turkey erythrocytes. In contrast to the standard protocol, our investigation found out the necessity to eliminate nonspecific inhibitor present in the test sera by receptor destroying enzyme (RDE) prior to performing microNT assay. The investigation in pre-pandemic serum samples showed that HI antibody was more specific to the 2009 pandemic virus than NT antibody. Based on data from pre-pandemic sera together with those from the laboratory confirmed cases, HI antibody titers ≥40 for adults and ≥20 for children could be used as the cut-off level to differentiate between the individuals with or without past infection by the 2009 pandemic virus.

Conclusions/Significance

Based on the cut-off criteria, the infection rates of 7 and 12.8% were estimated in blood donors and HCW, respectively after the first wave of the 2009 influenza pandemic. Among general population, the infection rate of 58.6% was found in children versus 3.1% in adults.

Risk factors for pandemic (H1N1) 2009 virus seroconversion among hospital staff, Singapore

TOC Summary: Infection was associated with occupational and nonoccupational risk factors.

We describe incidence and risk factors for pandemic (H1N1) 2009 virus infection in healthcare personnel during the June–September 2009 epidemic in Singapore. Personnel contributed 3 serologic samples during June–October 2009, with seroconversion defined as a >4-fold increase in hemagglutination inhibition titers to pandemic (H1N1) 2009. Of 531 participants, 35 showed evidence of seroconversion. Seroconversion rates were highest in nurses (28/290) and lowest in allied health staff (2/116). Significant risk factors on multivariate analysis were being a nurse (adjusted odds ratio [aOR] 4.5, 95% confidence interval [CI] 1.0–19.6) and working in pandemic (H1N1) 2009 isolation wards (aOR 4.5, 95% CI 1.3–15.6). Contact with pandemic (H1N1) 2009–infected colleagues (aOR 2.5, 95% CI 0.9–6.6) and larger household size (aOR 1.2, 95% CI 1.0–1.4) were of borderline significance. Our study suggests that seroconversion was associated with occupational and nonoccupational risk factors.

Optimizing tactics for use of the U.S. antiviral strategic national stockpile for pandemic influenza

In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.

Serological evidence of subclinical transmission of the 2009 pandemic H1N1 influenza virus outside of Mexico

Background

Relying on surveillance of clinical cases limits the ability to understand the full impact and severity of an epidemic, especially when subclinical cases are more likely to be present in the early stages. Little is known of the infection and transmissibility of the 2009 H1N1 pandemic influenza (pH1N1) virus outside of Mexico prior to clinical cases being reported, and of the knowledge pertaining to immunity and incidence of infection during April–June, which is essential for understanding the nature of viral transmissibility as well as for planning surveillance and intervention of future pandemics.

Methodology/Principal Findings

Starting in the fall of 2008, 306 persons from households with schoolchildren in central Taiwan were followed sequentially and serum samples were taken in three sampling periods for haemagglutination inhibition (HI) assay. Age-specific incidence rates were calculated based on seroconversion of antibodies to the pH1N1 virus with an HI titre of 1∶40 or more during two periods: April–June and September–October in 2009. The earliest time period with HI titer greater than 40, as well as a four-fold increase of the neutralization titer, was during April 26–May 3. The incidence rates during the pre-epidemic phase (April–June) and the first wave (July–October) of the pandemic were 14.1% and 29.7%, respectively. The transmissibility of the pH1N1 virus during the early phase of the epidemic, as measured by the effective reproductive number R₀, was 1.16 (95% confidence interval (CI): 0.98–1.34).

Conclusions

Approximately one in every ten persons was infected with the 2009 pH1N1 virus during the pre-epidemic phase in April–June. The lack of age-pattern in seropositivity is unexpected, perhaps highlighting the importance of children as asymptomatic transmitters of influenza in households. Although without virological confirmation, our data raise the question of whether there was substantial pH1N1 transmission in Taiwan before June, when clinical cases were first detected by the surveillance network.

Pandemic H1N1 vaccine requires the use of an adjuvant to protect against challenge in naïve ferrets

In the context of an A/H1N1 influenza pandemic situation, this study demonstrates that heterologous vaccination with an AS03-adjuvanted 2008/2009 seasonal trivalent and pandemic H5N1 monovalent split vaccine conferred partial protection in influenza-naïve ferrets after challenge with the influenza pandemic H1N1 A/The Netherlands/602/09 virus. Further, unlike saline control and non-adjuvanted vaccine, it was shown that immunization of naïve ferrets with an AS03-adjuvanted pandemic H1N1 A/California/7/09 influenza split vaccine induced increased antibody response and enhanced protection against the challenge strain, including significant reduction in viral shedding in the upper respiratory tract and reduced lung pathology post-challenge. These results show the need for vaccination with the adjuvanted vaccine to fully protect against viral replication and influenza disease in unprimed ferrets.

An epidemiological analysis of severe cases of the influenza A (H1N1) 2009 virus infection in Japan

BACKGROUND

The age distribution of confirmed cases with influenza A (H1N1) 2009 has shifted toward children and young adults, in contrast to interpandemic influenza, because of the age specificities in immunological reactions and transmission characteristics.

OBJECTIVES

Descriptive epidemiological analysis of severe cases in Japan was carried out to characterize the pandemic's impact and clinical features.

METHODS

First, demographic characteristics of hospitalized cases (n = 12,923), severe cases (n = 894) and fatal cases (n = 116) were examined. Second, individual records of the first 120 severe cases, including 23 deaths, were analyzed to examine potential associations of influenza death with demographic variables, medical treatment and underlying conditions. Among severe cases, we compared proportions of specific characteristics of survivors with those of fatal cases to identify predictors of death.

RESULTS

Age distribution of hospitalized cases shifted toward those aged <20 years; this was also the case for deaths without underlying medical conditions. Deaths in adults were mainly seen among those with underlying medical conditions, resulting in an increased risk of death as a function of age. According to individual records, the time from onset to death in Japan appeared rather short compared with that in other countries.

CONCLUSION

The age specificity of severe cases and their underlying medical conditions were consistent with other countries. To identify predictors of death in influenza A (H1N1) 2009 patients, more detailed clinical characteristics need to be examined according to different age groups and types of manifestations, which should ideally include mild cases as subjects.

Pandemic influenza A (H1N1) during winter influenza season in the southern hemisphere

Please cite this paper as: Hsieh Ying‐Hen. (2010) Pandemic influenza A (H1N1) during winter influenza season in the southern hemisphere. Influenza and Other Respiratory Viruses 4(4), 187–197.

Background  Countries in the southern hemisphere experienced sizable epidemics of pandemic influenza H1N1 in their winter season during May–August, 2009.

Methods  We make use of the Richards model to fit the publicly available epidemic data (confirmed cases, hospitalizations, and deaths) of six southern hemisphere countries (Argentina, Brazil, Chile, Australia, New Zealand, and South Africa) to draw useful conclusions, in terms of its reproduction numbers and outbreak turning points, regarding the new pH1N1 virus in a typical winter influenza season.

Results  The estimates for the reproduction numbers of these six countries range from a high of 1·53 (95% CI: 1·22, 1·84) for confirmed case data of Brazil to a low of 1·16 (1·09, 1·22) for pH1N1 hospitalizations in Australia. For each country, model fits using confirmed cases, hospitalizations, or deaths data always yield similar estimates for the reproduction number. Moreover, the turning points for these closely related outbreak indicators always follow the correct chronological order, i.e., case–hospitalization–death, whenever two or more of these three indicators are available.

Conclusions  The results suggest that the winter pH1N1 outbreaks in the southern hemisphere were similar to the earlier spring and later winter outbreaks in North America in its severity and transmissibility, as indicated by the reproduction numbers. Therefore, the current strain has not become more severe or transmissible while circulating around the globe in 2009 as some experts had cautioned. The results will be useful for global preparedness planning of possible tertiary waves of pH1N1 infections in the fall/winter of 2010.

Critical care management of major disasters: a practical guide to disaster preparation in the intensive care unit

Recent events and regulatory mandates have underlined the importance of medical planning and preparedness for catastrophic events. The purpose of this review is to provide a brief summary of current commonly identified threats, an overview of mass critical care management, and a discussion of resource allocation to provide the intensive care unit (ICU) director with a practical guide to help prepare and coordinate the activities of the multidisciplinary critical care team in the event of a disaster.

The nonadaptive nature of the H1N1 2009 Swine Flu pandemic contrasts with the adaptive facilitation of transmission to a new host

BACKGROUND

The emergence of the 2009 H1N1 Influenza pandemic followed a multiple reassortment event from viruses originally circulating in swines and humans, but the adaptive nature of this emergence is poorly understood.

RESULTS

Here we base our analysis on 1180 complete genomes of H1N1 viruses sampled in North America between 2000 and 2010 in swine and human hosts. We show that while transmission to a human host might require an adaptive phase in the HA and NA antigens, the emergence of the 2009 pandemic was essentially nonadaptive. A more detailed analysis of the NA protein shows that the 2009 pandemic sequence is characterized by novel epitopes and by a particular substitution in loop 150, which is responsible for a nonadaptive structural change tightly associated with the emergence of the pandemic.

CONCLUSIONS

Because this substitution was not present in the 1918 H1N1 pandemic virus, we posit that the emergence of pandemics is due to epistatic interactions between sites distributed over different segments. Altogether, our results are consistent with population dynamics models that highlight the epistatic and nonadaptive rise of novel epitopes in viral populations, followed by their demise when the resulting virus is too virulent.

Virulence determinants of pandemic influenza viruses

Influenza A viruses cause recurrent, seasonal epidemics and occasional global pandemics with devastating levels of morbidity and mortality. The ability of influenza A viruses to adapt to various hosts and undergo reassortment events ensures constant generation of new strains with unpredictable degrees of pathogenicity, transmissibility, and pandemic potential. Currently, the combination of factors that drives the emergence of pandemic influenza is unclear, making it impossible to foresee the details of a future outbreak. Identification and characterization of influenza A virus virulence determinants may provide insight into genotypic signatures of pathogenicity as well as a more thorough understanding of the factors that give rise to pandemics.

Perceived risk, anxiety, and behavioural responses of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands: results of three consecutive online surveys

Background

Research into risk perception and behavioural responses in case of emerging infectious diseases is still relatively new. The aim of this study was to examine perceptions and behaviours of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands.

Methods

Two cross-sectional and one follow-up online survey (survey 1, 30 April-4 May; survey 2, 15-19 June; survey 3, 11-20 August 2009). Adults aged 18 years and above participating in a representative Internet panel were invited (survey 1, n = 456; survey 2, n = 478; follow-up survey 3, n = 934). Main outcome measures were 1) time trends in risk perception, feelings of anxiety, and behavioural responses (survey 1-3) and 2) factors associated with taking preventive measures and strong intention to comply with government-advised preventive measures in the future (survey 3).

Results

Between May and August 2009, the level of knowledge regarding Influenza A (H1N1) increased, while perceived severity of the new flu, perceived self-efficacy, and intention to comply with preventive measures decreased. The perceived reliability of information from the government decreased from May to August (62% versus 45%). Feelings of anxiety decreased from May to June, and remained stable afterwards. From June to August 2009, perceived vulnerability increased and more respondents took preventive measures (14% versus 38%). Taking preventive measures was associated with no children in the household, high anxiety, high self-efficacy, more agreement with statements on avoidance, and paying much attention to media information regarding Influenza A (H1N1). Having a strong intention to comply with government-advised preventive measures in the future was associated with higher age, high perceived severity, high anxiety, high perceived efficacy of measures, high self-efficacy, and finding governmental information to be reliable.

Conclusions

Decreasing trends over time in perceived severity and anxiety are consistent with the reality: the clinical picture of influenza turned out to be mild in course of time. Although (inter)national health authorities initially overestimated the case fatality rate, the public stayed calm and remained to have a relatively high intention to comply with preventive measures.

Pandemic influenza: Modelling and public health perspectives

We describe the application of mathematical models in the study of disease epidemics with particular focus on pandemic influenza. We outline the general mathematical approach and the complications arising from attempts to apply it for disease outbreak management in a real public health context.

Joint quantification of transmission dynamics and diagnostic accuracy applied to influenza

The influenza A (H1N1) pandemic 2009 posed an epidemiological challenge in ascertaining all cases. Although the counting of all influenza cases in real time is often not feasible, empirical observations always involve diagnostic test procedures. This offers an opportunity to jointly quantify transmission dynamics and diagnostic accuracy. We have developed a joint estimation procedure that exploits parsimonious models to describe the epidemic dynamics and that parameterizes the number of test positives and test negatives as a function of time. Our analyses of simulated data and data from the empirical observation of interpandemic influenza A (H1N1) from 2007-08 in Japan indicate that the proposed approach permits a more precise quantification of the transmission dynamics compared to methods that rely on test positive cases alone. The analysis of entry screening data for the H1N1 pandemic 2009 at Tokyo-Narita airport helped us quantify the very limited specificity of influenza-like illness in detecting actual influenza cases in the passengers. The joint quantification does not require us to condition diagnostic accuracy on any pre-defined study population. Our study suggests that by consistently reporting both test positive and test negative cases, the usefulness of extractable information from routine surveillance record of infectious diseases would be maximized.

Prioritization of delayed vaccination for pandemic influenza

Limited production capacity and delays in vaccine development are major obstacles to vaccination programs that are designed to mitigate a pandemic influenza. In order to evaluate and compare the impact of various vaccination strategies during a pandemic influenza, we developed an age/risk-structured model of influenza transmission, and parameterized it with epidemiological data from the 2009 H1N1 influenza A pandemic. Our model predicts that the impact of vaccination would be considerably diminished by delays in vaccination and staggered vaccine supply. Nonetheless, prioritizing limited H1N1 vaccine to individuals with a high risk of complications, followed by school-age children, and then preschool-age children, would minimize an overall attack rate as well as hospitalizations and deaths. This vaccination scheme would maximize the benefits of vaccination by protecting the high-risk people directly, and generating indirect protection by vaccinating children who are most likely to transmit the disease.

Novel swine--origin influenza A: the 2009 H1N1 influenza virus

During April-May 2009, a novel H1N1 influenza virus was determined to be the cause of influenza outbreaks in North America. By June 2009, widespread infections were recorded all over the world and an ongoing pandemic was declared. The clinical manifestations ranged from a self limited illness to fatal disease. Current clinical data suggest that the highest infection rates and complications occur in children and young adults. In contrast to seasonal influenza, the rates of hospitalization and death in adults 65 years or older were low. Risk factors for severe disease are similar to those of seasonal influenza and include diverse medical conditions. However, pregnant women and children with neurodevelopmental disorders or chronic pulmonary conditions are at highest risk of developing severe disease. Rapid antigen detection tests have variable and suboptimal sensitivity for diagnosis of novel H1N1 influenza. Diagnosis is confirmed by real-time reverse transcriptase polymerase chain reaction or by virus isolation in cell culture. Treatment is recommended with oral oseltamivir or inhaled zanamavir for patients who are at risk of complications as well as those who are worsening clinically or have evidence of lower respiratory tract infection. Treatment with intravenous peramivir can be used in special situations when oral or inhaled antiviral therapy is not tolerated or considered inadequate. Inactivated and live attenuated vaccines are available. Current vaccination recommendations and infection control measures are discussed.

Disease Mongering and the Fear of Pandemic Influenza

The catastrophic H1N1 pandemic of 1918, which killed tens of millions, is now legendary, and influenza policy has centered on preventing another such disaster. There is reason for concern about influenza A. It can rapidly alter its genetic makeup to increase virulence and can jump from other species to humans. Nonetheless, ignorance about influenza in 1918, the lack of effective vaccines or antibacterial and antiviral drugs, and the social disruption caused by World War I also contributed heavily to the lethality, and it is unlikely that influenza of similar destructiveness will recur. The stupefying publicity over the threat of influenza has been generated partly by those, such as the pharmaceutical industry and influenza researchers, who benefit from the increased expenditures the publicity provokes. It is, in effect, disease mongering, the promotion of disease or dread of disease for one's own gain. Huge expenditures on influenza preparedness have produced little demonstrable benefit and some harm, independent of the wasted resources. Disease mongering, including spreading fear of influenza, is widespread and unhealthy and should be vigorously opposed.

Evaluation of vaccination strategies during pandemic outbreaks

During pandemic influenza, several factors could significantly impact the outcome of vaccination campaigns, including the delay in pandemic vaccine availability, inadequate protective efficacy, and insufficient number of vaccines to cover the entire population. Here, we incorporate these factors into a vaccination model to investigate and compare the effectiveness of the single-dose and two-dose vaccine strategies. The results show that, if vaccination starts early enough after the onset of the outbreak, a two-dose strategy can lead to a greater reduction in the total number of infections. This, however, requires the second dose of vaccine to confer a substantially higher protection compared to that induced by the first dose. For a sufficiently long delay in start of vaccination, the single-dose strategy outperforms the two-dose vaccination program regardless of its protection efficacy. The findings suggest that the population-wide benefits of a single-dose strategy could in general be greater than the two-dose vaccination program, in particular when the second dose offers marginal increase in the protection induced by the first dose.

Harnessing DNA Synthesis to Develop Rapid Responses to Emerging and Pandemic Pathogens

Given the interconnected nature of our world today, emerging pathogens and pandemic outbreaks are an ever-growing threat to the health and economic stability of the global community. This is evident by the recent 2009 Influenza A (H1N1) pandemic, the SARS outbreak, as well as the ever-present threat of global bioterrorism. Fortunately, the biomedical community has been able to rapidly generate sequence data so these pathogens can be readily identified. To date, however, the utilization of this sequence data to rapidly produce relevant experimental results or actionable treatments is lagging in spite of obtained sequence data. Thus, a pathogenic threat that has emerged and/or developed into a pandemic can be rapidly identified; however, translating this identification into a targeted therapeutic or treatment that is rapidly available has not yet materialized. This commentary suggests that the growing technology of DNA synthesis should be fully implemented as a means to rapidly generatein vivodata and possibly actionable therapeutics soon after sequence data becomes available.

A comparison of the epidemiology and clinical presentation of seasonal influenza A and 2009 pandemic influenza A (H1N1) in Guatemala

BACKGROUND

A new influenza A (H1N1) virus was first found in April 2009 and proceeded to cause a global pandemic. We compare the epidemiology and clinical presentation of seasonal influenza A (H1N1 and H3N2) and 2009 pandemic influenza A (H1N1) (pH1N1) using a prospective surveillance system for acute respiratory disease in Guatemala.

METHODOLOGY/FINDINGS

Patients admitted to two public hospitals in Guatemala in 2008-2009 who met a pneumonia case definition, and ambulatory patients with influenza-like illness (ILI) at 10 ambulatory clinics were invited to participate. Data were collected through patient interview, chart abstraction and standardized physical and radiological exams. Nasopharyngeal swabs were taken from all enrolled patients for laboratory diagnosis of influenza A virus infection with real-time reverse transcription polymerase chain reaction. We identified 1,744 eligible, hospitalized pneumonia patients, enrolled 1,666 (96%) and tested samples from 1,601 (96%); 138 (9%) had influenza A virus infection. Surveillance for ILI found 899 eligible patients, enrolled 801 (89%) and tested samples from 793 (99%); influenza A virus infection was identified in 246 (31%). The age distribution of hospitalized pneumonia patients was similar between seasonal H1N1 and pH1N1 (P = 0.21); the proportion of pneumonia patients <1 year old with seasonal H1N1 (39%) and pH1N1 (37%) were similar (P = 0.42). The clinical presentation of pH1N1 and seasonal influenza A was similar for both hospitalized pneumonia and ILI patients. Although signs of severity (admission to an intensive care unit, mechanical ventilation and death) were higher among cases of pH1N1 than seasonal H1N1, none of the differences was statistically significant.

CONCLUSIONS/SIGNIFICANCE

Small sample sizes may limit the power of this study to find significant differences between seasonal influenza A and pH1N1. In Guatemala, influenza, whether seasonal or pH1N1, appears to cause severe disease mainly in infants; targeted vaccination of children should be considered.

Safety review: squalene and thimerosal in vaccines

Few studies show the reluctance of the people to get vaccinated against A (H1N1) influenza for fear of side effects of squalene (MF59, AS03, AF03) and thimerosal. The aim of this paper is to assess the safety in using these adjuvants and preservative reviewing data of clinical trials relative to which formulation includes these compounds. In the current state of knowledge, these vaccines have proved to be effective even though they more frequently give local adverse events than non-adjuvanted influenza vaccines. Systemic side effects are generally not serious. In the studies, adjuvanted vaccines do not increase neither the risk of Guillain Barre syndrome nor auto-immune diseases. There is no convincing evidence that exposure to thimerosal in vaccines had any deletorious effect on physiological outcome.

Assortativity and the Probability of Epidemic Extinction: A Case Study of Pandemic Influenza A (H1N1-2009)

Unlike local transmission of pandemic influenza A (H1N1-2009), which was frequently driven by school children, most cases identified in long-distance intranational and international travelers have been adults. The present study examines the relationship between the probability of temporary extinction and the age-dependent next-generation matrix, focusing on the impact of assortativity. Preferred mixing captures as a good approximation the assortativity of a heterogeneously mixing population. We show that the contribution of a nonmaintenance host (i.e., a host type which cannot sustain transmission on its own) to the risk of a major epidemic is greatly diminished as mixing patterns become more assortative, and in such a scenario, a higher proportion of non-maintenance hosts among index cases elevates the probability of extinction. Despite the presence of various other epidemiological factors that undoubtedly influenced the delay between first importations and the subsequent epidemic, these results suggest that the dominance of adults among imported cases represents one of the possible factors explaining the delays in geographic spread observed during the recent pandemic.

Influenza pandemic waves under various mitigation strategies with 2009 H1N1 as a case study

A significant feature of influenza pandemics is multiple waves of morbidity and mortality over a few months or years. The size of these successive waves depends on intervention strategies including antivirals and vaccination, as well as the effects of immunity gained from previous infection. However, the global vaccine manufacturing capacity is limited. Also, antiviral stockpiles are costly and thus, are limited to very few countries. The combined effect of antivirals and vaccination in successive waves of a pandemic has not been quantified. The effect of acquired immunity from vaccination and previous infection has also not been characterized. In times of a pandemic threat countries must consider the effects of a limited vaccine, limited antiviral use and the effects of prior immunity so as to adopt a pandemic strategy that will best aid the population. We developed a mathematical model describing the first and second waves of an influenza pandemic including drug therapy, vaccination and acquired immunity. The first wave model includes the use of antiviral drugs under different treatment profiles. In the second wave model the effects of antivirals, vaccination and immunity gained from the first wave are considered. The models are used to characterize the severity of infection in a population under different drug therapy and vaccination strategies, as well as school closure, so that public health policies regarding future influenza pandemics are better informed.

Pandemic H1N1 2009 influenza virus with the H275Y oseltamivir resistance neuraminidase mutation shows a small compromise in enzyme activity and viral fitness

BACKGROUND

Resistance to the neuraminidase inhibitor oseltamivir can be conferred by a well-characterized mutation in the neuraminidase gene, H275Y. In human H1N1 viruses that circulated in the first years of the 21st century, this mutation carried a fitness cost and resistant viruses were rare. During the 2007-08 influenza season, oseltamivir-resistant viruses of H1N1 phenotype emerged and predominated. March 2009 saw the emergence of a novel H1N1 influenza pandemic. We examined whether the H275Y mutation affected neuraminidase enzyme activity or replication of the pandemic influenza virus.

METHODS

Using reverse genetics we engineered the H275Y mutation into the neuraminidase of a 2009 pandemic H1N1 virus and assessed the ability of this enzyme to desialylate mono- and multivalent substrates. The growth kinetics of wild-type and mutant viruses were assessed in Madin-Darby canine kidney (MDCK) and fully differentiated human airway epithelial (HAE) cells.

RESULTS

The presence of H275Y was associated with a 1.3-fold decrease in the affinity of the neuraminidase for a monovalent substrate and a 4-fold compromise in desialylation of multivalent substrate. This was associated with a fitness cost to viral replication in vitro, which only became apparent during competitive replication in the mucus-rich HAE culture system.

CONCLUSIONS

The neuraminidase protein of pandemic influenza isolates tolerates the H275Y mutation and this mutation confers resistance to oseltamivir. However, unlike seasonal H1N1 viruses isolated since 2007, the mutation is not associated with any fitness advantage and thus is unlikely to predominate without further antigenic drift, compensating mutations or intense selection pressure.

Reporting errors in infectious disease outbreaks, with an application to Pandemic Influenza A/H1N1

BACKGROUND

Effectively responding to infectious disease outbreaks requires a well-informed response. Quantitative methods for analyzing outbreak data and estimating key parameters to characterize the spread of the outbreak, including the reproductive number and the serial interval, often assume that the data collected is complete. In reality reporting delays, undetected cases or lack of sensitive and specific tests to diagnose disease lead to reporting errors in the case counts. Here we provide insight on the impact that such reporting errors might have on the estimation of these key parameters.

RESULTS

We show that when the proportion of cases reported is changing through the study period, the estimates of key epidemiological parameters are biased. Using data from the Influenza A/H1N1 outbreak in La Gloria, Mexico, we provide estimates of these parameters, accounting for possible reporting errors, and show that they can be biased by as much as 33%, if reporting issues are not accounted for.

CONCLUSIONS

Failure to account for missing data can lead to misleading and inaccurate estimates of epidemic parameters.