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

Novel insights into proteolytic cleavage of influenza virus hemagglutinin

The influenza virus hemagglutinin (HA) mediates the first essential step in the viral life cycle, virus entry into target cells. Influenza virus HA is synthesised as a precursor protein in infected cells and requires cleavage by host cell proteases to transit into an active form. Cleavage is essential for influenza virus infectivity and the HA‐processing proteases are attractive targets for therapeutic intervention. It is well established that cleavage by ubiquitously expressed subtilisin‐like proteases is a hallmark of highly pathogenic avian influenza viruses (HPAIV). In contrast, the nature of the proteases responsible for cleavage of HA of human influenza viruses and low pathogenic avian influenza viruses (LPAIV) is not well understood. Recent studies suggest that cleavage of HA of human influenza viruses might be a cell‐associated event and might be facilitated by the type II transmembrane serine proteases (TTSPs) TMPRSS2, TMPRSS4 and human airway trypsin‐like protease (HAT). Here, we will introduce the different concepts established for proteolytic activation of influenza virus HA, with a particular focus on the role of TTSPs, and we will discuss their implications for viral tropism, pathogenicity and antiviral intervention. Copyright © 2010 John Wiley & Sons, Ltd.

Novel influenza A (H1N1): clinical features of pediatric hospitalizations in two successive waves

OBJECTIVE

To describe and compare the characteristics of children hospitalized with novel influenza A (H1N1) during two successive waves.

METHODS

This was a medical chart review of all children hospitalized in a French Canadian pediatric hospital in Montreal in the spring and fall of 2009 with a positive real-time polymerase chain reaction for novel influenza A (H1N1) and flu-like symptoms.

RESULTS

We included 202 children with a median age of 4.9 (range 0.1-18) years. Demographic and clinical features of the children in the two waves were similar. One or more underlying medical conditions were found in 59% of the children. Clinical findings at admission were: fever (98%), cough (88%), congestion/rhinorrhea (58%), gastrointestinal symptoms (47%), oxygen saturation below 95% (33%), sore throat (20%), and neurological symptoms (9%). Admission to the intensive care unit was required for 22 (11%) children, and 14 patients needed respiratory support. During the second wave, the median duration of stay was shorter (3 vs. 4 days, p=0.003) and oseltamivir was used more often (84% vs. 40%, p<0.001).

CONCLUSIONS

Children hospitalized during the two successive waves of H1N1 were mainly school-aged and suffered from moderate disease. Although clinical features and severity of disease were similar, oseltamivir was prescribed more frequently and the length of hospital stay was shorter in the second wave.

[How the new generations of microbiologists view the specialty]

Despite their pivotal role in the Spanish healthcare system, clinical microbiology laboratories are experiencing difficult times and tough challenges. The following changes are required to adapt to the new situation: a) the use of molecular diagnostics to provide rapid diagnosis; b) the development of diagnostic capabilities to identify emerging or imported infectious diseases; c) the ability to advise on the interpretation of microbiological results; d) encouragement of the implantation of point-of-care testing and assessment of its performance and development; e) the implantation of quality control systems in the laboratory; f) the implementation of laboratory information systems to support real-time communication between hospital and community clinicians, public health laboratories and managers; g) the design of networking systems with professionals from other disciplines, and h) the promotion of training and teaching programs. Only if they are well prepared will clinical microbiology laboratories be able to implant the new technologies, be recognized as a cornerstone of the healthcare system, and achieve better recognition by society at large, hospital administrators and healthcare authorities.

Little Italy: an agent-based approach to the estimation of contact patterns- fitting predicted matrices to serological data

Knowledge of social contact patterns still represents the most critical step for understanding the spread of directly transmitted infections. Data on social contact patterns are, however, expensive to obtain. A major issue is then whether the simulation of synthetic societies might be helpful to reliably reconstruct such data. In this paper, we compute a variety of synthetic age-specific contact matrices through simulation of a simple individual-based model (IBM). The model is informed by Italian Time Use data and routine socio-demographic data (e.g., school and workplace attendance, household structure, etc.). The model is named “Little Italy” because each artificial agent is a clone of a real person. In other words, each agent's daily diary is the one observed in a corresponding real individual sampled in the Italian Time Use Survey. We also generated contact matrices from the socio-demographic model underlying the Italian IBM for pandemic prediction. These synthetic matrices are then validated against recently collected Italian serological data for Varicella (VZV) and ParvoVirus (B19). Their performance in fitting sero-profiles are compared with other matrices available for Italy, such as the Polymod matrix. Synthetic matrices show the same qualitative features of the ones estimated from sample surveys: for example, strong assortativeness and the presence of super- and sub-diagonal stripes related to contacts between parents and children. Once validated against serological data, Little Italy matrices fit worse than the Polymod one for VZV, but better than concurrent matrices for B19. This is the first occasion where synthetic contact matrices are systematically compared with real ones, and validated against epidemiological data. The results suggest that simple, carefully designed, synthetic matrices can provide a fruitful complementary approach to questionnaire-based matrices. The paper also supports the idea that, depending on the transmissibility level of the infection, either the number of different contacts, or repeated exposure, may be the key factor for transmission.

Data on social contact patterns are fundamental to design adequate control policies for directly transmissible infectious diseases, ranging from a flu pandemic to tuberculosis, to recurrent epidemics of childhood diseases. Most countries in the world do not dispose of such data. We propose an approach to generate synthetic contact data by simulating an artificial society that integrates routinely available socio-demographic data, such as data on household composition or on school participation, with Time Use data, which are increasingly available. We then validate the ensuing simulated contact data against real epidemiological data for varicella and parvo-virus. The results suggest that the approach is potentially a very fruitful one, and provide some insights on the biology of transmission of close-contact infectious diseases.

Contact heterogeneity and phylodynamics: how contact networks shape parasite evolutionary trees

The inference of population dynamics from molecular sequence data is becoming an important new method for the surveillance of infectious diseases. Here, we examine how heterogeneity in contact shapes the genealogies of parasitic agents. Using extensive simulations, we find that contact heterogeneity can have a strong effect on how the structure of genealogies reflects epidemiologically relevant quantities such as the proportion of a population that is infected. Comparing the simulations to BEAST reconstructions, we also find that contact heterogeneity can increase the number of sequence isolates required to estimate these quantities over the course of an epidemic. Our results suggest that data about contact-network structure will be required in addition to sequence data for accurate estimation of a parasitic agent's genealogy. We conclude that network models will be important for progress in this area.

Low-dimensional clustering detects incipient dominant influenza strain clusters

Influenza has been circulating in the human population and has caused three pandemics in the last century (1918 H1N1, 1957 H2N2 and 1968 H3N2). The 2009 A(H1N1) was classified by World Health Organization as the fourth pandemic. Influenza has a high evolution rate, which makes vaccine design challenging. We here consider an approach for early detection of new dominant strains. By clustering the 2009 A(H1N1) sequence data, we found two main clusters. We then define a metric to detect the emergence of dominant strains. We show on historical H3N2 data that this method is able to identify a cluster around an incipient dominant strain before it becomes dominant. For example, for H3N2 as of 30 March 2009, the method detects the cluster for the new A/British Columbia/RV1222/2009 strain. This strain detection tool would appear to be useful for annual influenza vaccine selection.

Hospitalised patients with Influenza A (H1N1) in the Royal Hospital, Oman: Experience of a tertiary care hospital, July-December 2009

OBJECTIVES

The aim of this study was to describe the clinical characteristics, risk factors, laboratory investigations and outcome of hospitalised patients with positive Influenza A (H1N1) at the Royal Hospital in Oman.

METHODS

We extracted data from the retrospective medical charts, radiological and laboratory findings of 131 patients who were confirmed as positive for Influenza A (H1N1) by real-time reverse-transcriptase-polymerase- chain-reaction from 21 July to 23 December 2009.

RESULTS

The median age was 24 years with 34.4% in the paediatric age group. Most (63%) of hospitalised patients were female. Symptoms at presentation included mainly fever (93.9%) and respiratory symptoms (89.3%). 83% of the patients had at least one risk factor and pregnancy was the most common associated condition (22.9%). Most of the patients had reduced lymphocytic count (57.3%) and high levels of serum C-reactive protein, aspartate transaminase and lactate dehydrogenase (75.7%, 75% and 70.8% respectively). The majority of the patients (64.5%) had evidence of pneumonia and radiological findings constituted mainly bi-lateral infiltrates (60.6%). Antiviral therapy was administered to 95.4% of the patients who mostly received it 48 hours after disease onset. Death occurred in 6.9% of patients. Out of these, 88.9% required Intensive Care Unit (ICU) care and mechanical ventilation.

CONCLUSION

Influenza A (H1N1) infection mainly affected those of younger age and females. Associated medical conditions were common, with pregnancy being interestingly the commonest risk factor. The infection caused severe illness that required ICU admission and led to death in 6.9% of patients.

Serological analysis of human pandemic influenza (H1N1) in Thailand

The study was aimed at determining the prevalence of pandemic influenza (H1N1) 2009 among patients with respiratory tract diseases during July-December 2009 using real-time reverse transcription polymerase chain reaction. Haemagglutination inhibition (HI) assay was performed to detect antibody titres against pandemic influenza in 255 medical personnel, 307 members of the general population during the second week of December 2009 in Khon Kaen province, Thailand, and in 100 stored sera collected from people of different age-groups during 2008. The results showed that the pandemic (H1N1) 2009 had occurred during July-December 2009. The results of the HI test after the wave of this outbreak showed that 123 (48%) of the 255 sera collected from the medical personnel, 109 (36%) of the 307 sera obtained from the general population, and only two of the 100 stored sera from 2008 contained antibodies (HI titres > or = 40) against pandemic influenza. Antibody against the pandemic (H1N1) 2009 was found in at least one-third of the population. In conclusion, the prevalence of virus and serological data obtained from the study can be used as the serological background level of the Thai population after the July-December pandemic. Finally, the serological data might be useful for outbreak-prevention and control strategies and for the management of vaccination for the pandemic (H1N1) 2009 in Thailand.

Estimating pathogen-specific asymptomatic ratios

The asymptomatic ratio (the proportion of asymptomatic infected cases among the total infected cases) is an important indicator in public health. However, symptoms manifested by a case infected with a pathogen may result from infections other than the specific pathogen of interest. When a case is infected with multiple pathogens, it can be difficult to distinguish which pathogen is causing the symptoms. These conditions complicate the estimation of asymptomatic ratios. We used influenza serologic data from Taiwan to test a novel log-linear binomial regression model that estimates pathogen-specific asymptomatic ratios for influenza subtypes. We find that 75% of the H1N1 subtype and 65% of the H3N2 subtype were asymptomatic. Asymptomatic ratios help to quantify the magnitude of asymptomatic persons who may be capable of spreading pathogens to others.

H1N1pdm influenza infection in hospitalized cancer patients: clinical evolution and viral analysis

Background

The novel influenza A pandemic virus (H1N1pdm) caused considerable morbidity and mortality worldwide in 2009. The aim of the present study was to evaluate the clinical course, duration of viral shedding, H1N1pdm evolution and emergence of antiviral resistance in hospitalized cancer patients with severe H1N1pdm infections during the winter of 2009 in Brazil.

Methods

We performed a prospective single-center cohort study in a cancer center in Rio de Janeiro, Brazil. Hospitalized patients with cancer and a confirmed diagnosis of influenza A H1N1pdm were evaluated. The main outcome measures in this study were in-hospital mortality, duration of viral shedding, viral persistence and both functional and molecular analyses of H1N1pdm susceptibility to oseltamivir.

Results

A total of 44 hospitalized patients with suspected influenza-like illness were screened. A total of 24 had diagnosed H1N1pdm infections. The overall hospital mortality in our cohort was 21%. Thirteen (54%) patients required intensive care. The median age of the studied cohort was 14.5 years (3–69 years). Eighteen (75%) patients had received chemotherapy in the previous month, and 14 were neutropenic at the onset of influenza. A total of 10 patients were evaluated for their duration of viral shedding, and 5 (50%) displayed prolonged viral shedding (median 23, range = 11–63 days); however, this was not associated with the emergence of a resistant H1N1pdm virus. Viral evolution was observed in sequentially collected samples.

Conclusions

Prolonged influenza A H1N1pdm shedding was observed in cancer patients. However, oseltamivir resistance was not detected. Taken together, our data suggest that severely ill cancer patients may constitute a pandemic virus reservoir with major implications for viral propagation.

Influenza in the tropics

PURPOSE OF REVIEW

Data on influenza in tropical countries remain scarce compared with that in temperate countries. However, the emergence of avian influenza virus (H5N1) and the 2009 pandemic represented a major stimulus for advances in knowledge about influenza in many of these countries. This review summarizes recent data on viral and epidemiologic aspects of the condition in tropical countries.

RECENT FINDINGS

Avian influenza and the influenza pandemic of 2009 have contributed to pioneer production of data on influenza in the tropical settings. Preliminary data on epidemiology, genetic diversity, and antiviral resistance of influenza viruses (seasonal and pandemic) in tropical countries have been published recently.

SUMMARY

The seasonality of influenza is very diverse in tropical countries. Recent studies on the subject confirm the year-round activity of these viruses in many countries and the regular occurrence of epidemic outbreaks in others. The use of molecular diagnostic methods has led to prevalence rates comparable to those seen in temperate countries. Phylogenetic analysis of hemagglutinin of influenza isolates allows understanding of the evolution and divergence of avian (H5N1) and human influenza viruses (A/H1N1, A/H3N2, and B) in tropical settings. Influenza viruses resistant to oseltamivir and zanamivir have been detected in tropical countries despite the rare use of these drugs in the treatment of influenza in people living in these areas.

Hantaviruses in the americas and their role as emerging pathogens

The continued emergence and re-emergence of pathogens represent an ongoing, sometimes major, threat to populations. Hantaviruses (family Bunyaviridae) and their associated human diseases were considered to be confined to Eurasia, but the occurrence of an outbreak in 1993–94 in the southwestern United States led to a great increase in their study among virologists worldwide. Well over 40 hantaviral genotypes have been described, the large majority since 1993, and nearly half of them pathogenic for humans. Hantaviruses cause persistent infections in their reservoir hosts, and in the Americas, human disease is manifest as a cardiopulmonary compromise, hantavirus cardiopulmonary syndrome (HCPS), with case-fatality ratios, for the most common viral serotypes, between 30% and 40%. Habitat disturbance and larger-scale ecological disturbances, perhaps including climate change, are among the factors that may have increased the human caseload of HCPS between 1993 and the present. We consider here the features that influence the structure of host population dynamics that may lead to viral outbreaks, as well as the macromolecular determinants of hantaviruses that have been regarded as having potential contribution to pathogenicity.

Rapid detection of pandemic influenza in the presence of seasonal influenza

BACKGROUND

Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland.

METHODS

We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data.

RESULTS

We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland.

CONCLUSIONS

While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical.

Real time reverse transcription (RRT)-polymerase chain reaction (PCR) methods for detection of pandemic (H1N1) 2009 influenza virus and European swine influenza A virus infections in pigs

BACKGROUND

There is a requirement to detect and differentiate pandemic (H1N1) 2009 (H1N1v) and established swine influenza A viruses (SIVs) by real time reverse transcription (RRT) PCR methods.

OBJECTIVES

First, modify an existing matrix (M) gene RRT PCR for sensitive generic detection of H1N1v and other European SIVs. Second, design an H1 RRT PCR to specifically detect H1N1v infections.

METHODS

RRT PCR assays were used to test laboratory isolates of SIV (n = 51; 37 European and 14 North American), H1N1v (n = 5) and avian influenza virus (AIV; n = 43). Diagnostic sensitivity and specificity were calculated for swabs (n = 133) and tissues (n = 116) collected from field cases and pigs infected experimentally with SIVs and H1N1v.

RESULTS

The "perfect match" M gene RRT PCR was the most sensitive variant of this test for detection of established European SIVs and H1N1v. H1 RRT PCR specifically detected H1N1v but not European SIVs. Validation with clinical specimens included comparison with virus isolation (VI) as a "gold standard", while field infection with H1N1v in swine was independently confirmed by sequencing H1N1v amplified by conventional RT PCR. "Perfect match" M gene RRT PCR had 100% sensitivity and 95.2% specificity for swabs, 93.6% and 98.6% for tissues. H1 RRT PCR demonstrated sensitivity and specificity of 100% and 99.1%, respectively, for the swabs, and 100% and 100% for the tissues.

CONCLUSIONS

Two RRT PCRs for the purposes of (i) generic detection of SIV and H1N1v infection in European pigs, and for (ii) specific detection of H1N1v (pandemic influenza) infection were validated.

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics

The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling--and manipulation--of epidemics and is especially powerful if complemented with adequate empirical data for parameterization.

Pandemic swine-origin H1N1 influenza A virus isolates show heterogeneous virulence in macaques

The first influenza pandemic of the new millennium was caused by a newly emerged swine-origin influenza virus (SOIV) (H1N1). This new virus is characterized by a previously unknown constellation of gene segments derived from North American and Eurasian swine lineages and the absence of common markers predictive of human adaptation. Overall, human infections appeared to be mild, but an alarming number of young individuals presented with symptoms atypical for seasonal influenza. The new SOIV also showed a sustained human-to-human transmissibility and higher reproduction ratio than common seasonal viruses, altogether indicating a higher pathogenic potential for this newly emerged virus. To study the virulence of the SOIV, we used a recently established cynomolgus macaque model and compared parameters of clinical disease, virology, host responses, and pathology/histopathology with a current seasonal H1N1 virus. We here show that infection of macaques with two genetically similar but clinically distinct SOIV isolates from the early stage of the pandemic (A/Mexico/4108/2009 and A/Mexico/InDRE4487/2009) resulted in upper and lower respiratory tract infections and clinical disease ranging from mild to severe pneumonia that was clearly advanced over the mild infection caused by A/Kawasaki/UTK-4/2009, a current seasonal strain. Unexpectedly, we observed heterogeneity among the two SOIV isolates in virus replication, host transcriptional and cytokine responses, and disease progression, demonstrating a higher pathogenic potential for A/Mexico/InDRE4487/2009. Differences in virulence may explain more severe disease, as was seen with certain individuals infected with the emerged pandemic influenza virus. Thus, the nonhuman primate model closely mimics influenza in humans.

Parameterizing state-space models for infectious disease dynamics by generalized profiling: measles in Ontario

Parameter estimation for infectious disease models is important for basic understanding (e.g. to identify major transmission pathways), for forecasting emerging epidemics, and for designing control measures. Differential equation models are often used, but statistical inference for differential equations suffers from numerical challenges and poor agreement between observational data and deterministic models. Accounting for these departures via stochastic model terms requires full specification of the probabilistic dynamics, and computationally demanding estimation methods. Here, we demonstrate the utility of an alternative approach, generalized profiling, which provides robustness to violations of a deterministic model without needing to specify a complete probabilistic model. We introduce novel means for estimating the robustness parameters and for statistical inference in this framework. The methods are applied to a model for pre-vaccination measles incidence in Ontario, and we demonstrate the statistical validity of our inference through extensive simulation. The results confirm that school term versus summer drives seasonality of transmission, but we find no effects of short school breaks and the estimated basic reproductive ratio (0) greatly exceeds previous estimates. The approach applies naturally to any system for which candidate differential equations are available, and avoids many challenges that have limited Monte Carlo inference for state-space models.

Effectiveness and cost-effectiveness of vaccination against pandemic influenza (H1N1) 2009

BACKGROUND

Decisions on the timing and extent of vaccination against pandemic (H1N1) 2009 virus are complex.

OBJECTIVE

To estimate the effectiveness and cost-effectiveness of pandemic influenza (H1N1) vaccination under different scenarios in October or November 2009.

DESIGN

Compartmental epidemic model in conjunction with a Markov model of disease progression.

DATA SOURCES

Literature and expert opinion.

TARGET POPULATION

Residents of a major U.S. metropolitan city with a population of 8.3 million.

TIME HORIZON

Lifetime.

PERSPECTIVE

Societal.

INTERVENTIONS

Vaccination in mid-October or mid-November 2009.

OUTCOME MEASURES

Infections and deaths averted, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness.

RESULTS OF BASE-CASE ANALYSIS

Assuming each primary infection causes 1.5 secondary infections, vaccinating 40% of the population in October or November would be cost-saving. Vaccination in October would avert 2051 deaths, gain 69 679 QALYs, and save $469 million compared with no vaccination; vaccination in November would avert 1468 deaths, gain 49 422 QALYs, and save $302 million.

RESULTS OF SENSITIVITY ANALYSIS

Vaccination is even more cost-saving if longer incubation periods, lower rates of infectiousness, or increased implementation of nonpharmaceutical interventions delay time to the peak of the pandemic. Vaccination saves fewer lives and is less cost-effective if the epidemic peaks earlier than mid-October.

LIMITATIONS

The model assumed homogenous mixing of case-patients and contacts; heterogeneous mixing would result in faster initial spread, followed by slower spread. Additional costs and savings not included in the model would make vaccination more cost-saving.

CONCLUSION

Earlier vaccination against pandemic (H1N1) 2009 prevents more deaths and is more cost-saving. Complete population coverage is not necessary to reduce the viral reproductive rate sufficiently to help shorten the pandemic.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality and National Institute on Drug Abuse.

The infection attack rate and severity of 2009 pandemic H1N1 influenza in Hong Kong

BACKGROUND

Serial cross-sectional data on antibody levels to the 2009 pandemic H1N1 influenza A virus from a population can be used to estimate the infection attack rates and immunity against future infection in the community.

METHODS

From April through December 2009, we obtained 12,217 serum specimens from blood donors (aged 16-59 years), 2520 specimens from hospital outpatients (aged 5-59 years), and 917 specimens from subjects involved in a community pediatric cohort study (aged 5-14 years). We estimated infection attack rates by comparing the proportions of specimens with antibody titers ≥ 1:40 by viral microneutralization before and after the first wave of the pandemic. Estimates were validated using paired serum samples from 324 individuals that spanned the first wave. Combining these estimates with epidemiologic surveillance data, we calculated the proportion of infections that led to hospitalization, admission to the intensive care unit (ICU), and death.

RESULTS

We found that 3.3% and 14% of persons aged 5-59 years had antibody titers ≥ 1:40 before and after the first wave, respectively. The overall attack rate was 10.7%, with age stratification as follows: 43.4% in persons aged 5-14 years, 15.8% in persons aged 15-19 years, 11.8% in persons aged 20-29 years, and 4%-4.6% in persons aged 30-59 years. Case-hospitalization rates were 0.47%-0.87% among persons aged 5-59 years. Case-ICU rates were 7.9 cases per 100,000 infections in persons aged 5-14 years and 75 cases per 100,000 infections in persons aged 50-59 years, respectively. Case-fatality rates were 0.4 cases per 100,000 infections in persons aged 5-14 years and 26.5 cases per 100,000 infections in persons aged 50-59 years, respectively.

CONCLUSIONS

Almost half of all school-aged children in Hong Kong were infected during the first wave. Compared with school children aged 5-14 years, older adults aged 50-59 years had 9.5 and 66 times higher risks of ICU admission and death if infected, respectively.

A neighborhood susceptibility index for planning of local physical interventions in response to pandemic influenza outbreaks

The global spread of a novel A (H1N1) influenza virus in 2009 has highlighted the possibility of a devastating pandemic similar to the 'Spanish flu' of 1917-1918. Responding to such pandemics requires careful planning for the early phases where there is no availability of pandemic vaccine. We set out to compute a Neighborhood Influenza Susceptibility Index (NISI) describing the vulnerability of local communities of different geo-socio-physical structure to a pandemic influenza outbreak. We used a spatially explicit geo-physical model of Linköping municipality (pop. 136,240) in Sweden, and employed an ontology-modeling tool to define simulation models and transmission settings. We found considerable differences in NISI between neighborhoods corresponding to primary care areas with regard to early progress of the outbreak, as well as in terms of the total accumulated share of infected residents counted after the outbreak. The NISI can be used in local preparations of physical response measures during pandemics.

Optimizing vaccine allocation at different points in time during an epidemic

Background

Pandemic influenza A(H1N1) 2009 began spreading around the globe in April of 2009 and vaccination started in October of 2009. In most countries, by the time vaccination started, the second wave of pandemic H1N1 2009 was already under way. With limited supplies of vaccine, we are left to question whether it may be a good strategy to vaccinate the high-transmission groups earlier in the epidemic, but it might be a better use of resources to protect instead the high-risk groups later in the epidemic. To answer this question, we develop a deterministic epidemic model with two age-groups (children and adults) and further subdivide each age group in low and high risk.

Methods and Findings

We compare optimal vaccination strategies started at various points in time in two different settings: a population in a developed country where children account for 24% of the population, and a population in a less developed country where children make up the majority of the population, 55%. For each of these populations, we minimize mortality or hospitalizations and we find an optimal vaccination strategy that gives the best vaccine allocation given a starting vaccination time and vaccine coverage level. We find that population structure is an important factor in determining the optimal vaccine distribution. Moreover, the optimal policy is dynamic as there is a switch in the optimal vaccination strategy at some time point just before the peak of the epidemic. For instance, with 25% vaccine coverage, it is better to protect the high-transmission groups before this point, but it is optimal to protect the most vulnerable groups afterward.

Conclusions

Choosing the optimal strategy before or early in the epidemic makes an important difference in minimizing the number of influenza infections, and consequently the number of influenza deaths or hospitalizations, but the optimal strategy makes little difference after the peak.

Report of the international forum on pandemic influenza 2010 Qingdao, China, 24-25 July 2010

The 2009 H1N1 influenza pandemic is the first pandemic to hit the world in the 21st century. According to World Health Organization (WHO) reports, as of 18 July 2010, more than 214 countries and overseas territories or communities have reported laboratory confirmed cases of pandemic influenza H1N1 2009, and over 18,336 people have died as a result of the disease [1]. In an effort to facilitate the exchange of strategic and operational experience in the fight against the pandemic, the Chinese Center for Disease Control and Prevention (China CDC), supported by the China Ministry of Health, in collaboration with WHO, the World Bank, the U.S. CDC, and co-organised with the Elsevier Publishing Group, hosted the International Forum on Pandemic Influenza 2010 in July. The two-day meeting, attended by over 600 international delegates, saw human health and animal health professionals discuss the current situation of the pandemic, the global response and vaccination strategies, pandemic surveillance and preparedness, and the animal-human interface in influenza and other emerging infectious diseases. A summary of the discussions is presented here.

Higher level of replication efficiency of 2009 (H1N1) pandemic influenza virus than those of seasonal and avian strains: kinetics from epithelial cell culture and computational modeling

The pathogenicity and transmission of influenza A viruses are likely determined in part by replication efficiency in human cells, which is the net effect of complex virus-host interactions. H5N1 avian, H1N1 seasonal, and H1N1 2009 pandemic influenza virus strains were compared by infecting human differentiated bronchial epithelial cells in air-liquid interface cultures at relatively low virus particle/cell ratios. Differential equation and computational models were used to characterize the in vitro kinetic behaviors of the three strains. The models were calibrated by fitting experimental data in order to estimate difficult-to-measure parameters. Both models found marked differences in the relative values of p, the virion production rate per cell, and R(0), an index of the spread of infection through the monolayer, with the values for the strains in the following rank order (from greatest to least): pandemic strain, followed by seasonal strain, followed by avian strain, as expected. In the differential equation model, which treats virus and cell populations as well mixed, R(0) and p varied proportionately for all 3 strains, consistent with a primary role for productivity. In the spatially explicit computational model, R(0) and p also varied proportionately except that R(0) derived for the pandemic strain was reduced, consistent with constrained viral spread imposed by multiple host defenses, including mucus and paracrine antiviral effects. This synergistic experimental-computational strategy provides relevant parameters for identifying and phenotyping potential pandemic strains.

On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada

Background

Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1) poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epidemiology, stochastic variation in the course of epidemics, and changing case definitions and surveillance practices.

Findings

The Richards model and its variants are used to fit the cumulative epidemic curve for laboratory-confirmed pandemic H1N1 (pH1N1) infections in Canada, made available by the Public Health Agency of Canada (PHAC). The model is used to obtain estimates for turning points in the initial outbreak, the basic reproductive number (R₀), and for expected final outbreak size in the absence of interventions. Confirmed case data were used to construct a best-fit 2-phase model with three turning points. R₀ was estimated to be 1.30 (95% CI 1.12-1.47) for the first phase (April 1 to May 4) and 1.35 (95% CI 1.16-1.54) for the second phase (May 4 to June 19). Hospitalization data were also used to fit a 1-phase model with R₀ = 1.35 (1.20-1.49) and a single turning point of June 11.

Conclusions

Application of the Richards model to Canadian pH1N1 data shows that detection of turning points is affected by the quality of data available at the time of data usage. Using a Richards model, robust estimates of R₀ were obtained approximately one month after the initial outbreak in the case of 2009 A (H1N1) in Canada.

Efficient simulation of the spatial transmission dynamics of influenza

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual-based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs.

Cellular immune responses to recurring influenza strains have limited boosting ability and limited cross-reactivity to other strains

Influenza vaccine provides protection against infection with matched strains, and this protection correlates with serum antibody titres. In addition to antibodies, influenza-specific CD8+ T-lymphocyte responses are important in decreasing disease severity and facilitating viral clearance. Because this response is directed at internal, relatively conserved antigens, it affords some cross-protection within a given subtype of influenza virus. With the possibility of a broader A(H1N1) Mexico outbreak in the fall of 2009, it appeared worthwhile studying the degree of cellular immune response-mediated cross-reactivity among influenza virus isolates. The composition of the 2006-2007 influenza vaccine included the A/New Caledonia/20/1999 strain (comprising a virus that has been circulating, and was included in vaccine preparations, for 6-7 years) and two strains not previously included (Wisconsin and Malaysia). This combination afforded us the opportunity to determine the degree of cross-reactive cellular immunity after exposure to new viral strains. We analysed the antibody responses and the phenotype and function of the T cell response to vaccine components. The results obtained show that antibody responses to A/New-Caledonia were already high and vaccination did not increase antibody or cytotoxic T lymphocyte responses. These data suggest that repeated exposure to the same influenza stain results in limited boosting of humoral and cellular immune responses.

Mortality attributable to pandemic influenza A (H1N1) 2009 in San Luis Potosí, Mexico

BACKGROUND

Acute respiratory infections are a leading cause of morbidity and mortality worldwide. Starting in 2009, pandemic influenza A(H1N1) 2009 virus has become one of the leading respiratory pathogens worldwide. However, the overall impact of this virus as a cause of mortality has not been clearly defined.

OBJECTIVES

To determine the impact of pandemic influenza A(H1N1) 2009 on mortality in a Mexican population.

METHODS

We assessed the impact of pandemic influenza virus on mortality during the first and second outbreaks in San Luis Potosí, Mexico, and compared it to mortality associated with seasonal influenza and respiratory syncytial virus (RSV) during the previous winter seasons.

RESULTS

We estimated that, on average, 8·1% of all deaths that occurred during the 2003-2009 seasons were attributable to influenza and RSV. During the first pandemic influenza A(H1N1) 2009 outbreak, there was an increase in mortality in persons 5-59 years of age, but not during the second outbreak (Fall of 2009). Overall, pandemic influenza A (H1N1) 2009 outbreaks had similar effects on mortality to those associated with seasonal influenza virus epidemics.

CONCLUSIONS

The impact of influenza A(H1N1) 2009 virus on mortality during the first year of the pandemic was similar to that observed for seasonal influenza. The establishment of real-time surveillance systems capable of integrating virological, morbidity, and mortality data may result in the timely identification of outbreaks so as to allow for the institution of appropriate control measures to reduce the impact of emerging pathogens on the population.

Genetic and phylogenetic analyses of influenza A H1N1pdm virus in Buenos Aires, Argentina

An influenza pandemic caused by swine-origin influenza virus A/H1N1 (H1N1pdm) spread worldwide in 2009, with 12,080 confirmed cases and 626 deaths occurring in Argentina. A total of 330 H1N1pdm viruses were detected from May to August 2009, and phylogenetic and genetic analyses of 21 complete genome sequences from both mild and fatal cases were achieved with reference to concatenated whole genomes. In addition, the analysis of another 16 hemagglutinin (HA), neuraminidase (NA), and matrix (M) gene sequences of Argentinean isolates was performed. The microevolution timeline was assessed and resistance monitoring of an NA fragment from 228 samples throughout the 2009 pandemic peak was performed by sequencing and pyrosequencing. We also assessed the viral growth kinetics for samples with replacements at the genomic level or special clinical features. In this study, we found by Bayesian inference that the Argentinean complete genome sequences clustered with globally distributed clade 7 sequences. The HA sequences were related to samples from the northern hemisphere autumn-winter from September to December 2009. The NA of Argentinean sequences belonged to the New York group. The N-4 fragment as well as the hierarchical clustering of samples showed that a consensus sequence prevailed in time but also that different variants, including five H275Y oseltamivir-resistant strains, arose from May to August 2009. Fatal and oseltamivir-resistant isolates had impaired growth and a small plaque phenotype compared to oseltamivir-sensitive and consensus strains. Although these strains might not be fit enough to spread in the entire population, molecular surveillance proved to be essential to monitor resistance and viral dynamics in our country.

Modification of nonstructural protein 1 of influenza A virus by SUMO1

Nonstructural protein 1 (NS1) is one of the major factors resulting in the efficient infection rate and high level of virulence of influenza A virus. Although consisting of only approximately 230 amino acids, NS1 has the ability to interfere with several systems of the host viral defense. In the present study, we demonstrate that NS1 of the highly pathogenic avian influenza A/Duck/Hubei/L-1/2004 (H5N1) virus interacts with human Ubc9, which is the E2 conjugating enzyme for sumoylation, and we show that SUMO1 is conjugated to H5N1 NS1 in both transfected and infected cells. Furthermore, two lysine residues in the C terminus of NS1 were identified as SUMO1 acceptor sites. When the SUMO1 acceptor sites were removed by mutation, NS1 underwent rapid degradation. Studies of different influenza A virus strains of human and avian origin showed that the majority of viruses possess an NS1 protein that is modified by SUMO1, except for the recently emerged swine-origin influenza A virus (S-OIV) (H1N1). Interestingly, growth of a sumoylation-deficient WSN virus mutant was retarded compared to that of wild-type virus. Together, these results indicate that sumoylation enhances NS1 stability and thus promotes rapid growth of influenza A virus.

The impact of case diagnosis coverage and diagnosis delays on the effectiveness of antiviral strategies in mitigating pandemic influenza A/H1N1 2009

BACKGROUND

Neuraminidase inhibitors were used to reduce the transmission of pandemic influenza A/H1N1 2009 at the early stages of the 2009/2010 pandemic. Policies for diagnosis of influenza for the purposes of antiviral intervention differed markedly between and within countries, leading to differences in the timing and scale of antiviral usage.

METHODOLOGY/PRINCIPAL FINDINGS

The impact of the percentage of symptomatic infected individuals who were diagnosed, and of delays to diagnosis, for three antiviral intervention strategies (each with and without school closure) were determined using a simulation model of an Australian community. Epidemic characteristics were based on actual data from the A/H1N1 2009 pandemic including reproduction number, serial interval and age-specific infection rate profile. In the absence of intervention an illness attack rate (AR) of 24.5% was determined from an estimated R(0) of 1.5; this was reduced to 21%, 16.5% or 13% by treatment-only, treatment plus household prophylaxis, or treatment plus household plus extended prophylaxis antiviral interventions respectively, assuming that diagnosis occurred 24 hours after symptoms arose and that 50% of symptomatic cases were diagnosed. If diagnosis occurred without delay, ARs decreased to 17%, 12.2% or 8.8% respectively. If 90% of symptomatic cases were diagnosed (with a 24 hour delay), ARs decreased to 17.8%, 11.1% and 7.6%, respectively.

CONCLUSION

The ability to rapidly diagnose symptomatic cases and to diagnose a high proportion of cases was shown to improve the effectiveness of all three antiviral strategies. For epidemics with R(0)< = 1.5 our results suggest that when the case diagnosis coverage exceeds ∼70% the size of the antiviral stockpile required to implement the extended prophylactic strategy decreases. The addition of at least four weeks of school closure was found to further reduce cumulative and peak attack rates and the size of the required antiviral stockpile.

Perception, attitudes and knowledge regarding the 2009 swine-origin influenza A (H1N1) virus pandemic among health-care workers in Australia

AIM

To determine the perceptions, attitudes and knowledge of Australian health-care workers (HCWs) regarding the novel, swine-origin influenza A (H1N1) virus (S-OIV) outbreak that reached the country in early May 2009.

METHODS

Self-administered, anonymous Web-based survey conducted during the early stages of the S-OIV pandemic. Participants comprised hospital- and community-based medical and nursing staff, medical students, allied health professionals, laboratory staff and administrative personnel.

RESULTS

Of the 947 participants surveyed, 59.4% were not convinced that Australia was sufficiently prepared for an influenza pandemic. Only 17.6% of the participants stated they were prepared to work unconditionally during a pandemic; 36.5% stated they would work if they had access to antiviral treatment; 27.9% would if provided with antiviral prophylaxis; and 7.5% would refuse to work. In addition, 37.5% of the participants responded they would refuse or avoid being involved in screening suspected cases. A total of 47.7% admitted to possessing a personal supply of antivirals or having considered this option. Only 48.0% provided a realistic estimate of the mortality associated with an influenza pandemic at a population level. HCWs overestimating the mortality risk and HCWs believing the efficacy of antiviral prophylaxis to be low were significantly less likely to be prepared to work (P= 0.04 and P= 0.0004, respectively).

CONCLUSIONS

To ensure adequate staffing during an influenza pandemic, preparedness plans should anticipate significant levels of absenteeism by choice. Interventions aimed at increasing staff retention during a pandemic require further evaluation.

Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention

In the spring of 2009, a novel strain of H1N1 swine-origin influenza A virus (S-OIV) emerged in Mexico and the United States, and soon after was declared a pandemic by the World Health Organization. This work examined the ability of real-time reports of influenza-like illness (ILI) symptoms and rapid influenza diagnostic tests (RIDTs) to approximate the spatiotemporal distribution of PCR-confirmed S-OIV cases for the purposes of focusing local intervention efforts. Cluster and age adjusted relative risk patterns of ILI, RIDT, and S-OIV were assessed at a fine spatial scale at different time and space extents within Cameron County, Texas on the US-Mexico border. Space-time patterns of ILI and RIDT were found to effectively characterize the areas with highest geographical risk of S-OIV within the first two weeks of the outbreak. Based on these results, ILI and/or RIDT may prove to be acceptable indicators of the location of S-OIV hotspots. Given that S-OIV data is often difficult to obtain real-time during an outbreak; these findings may be of use to public health officials targeting prevention and response efforts during future flu outbreaks.

Diagnostic Application of H3N8-Specific Equine Influenza Real-Time Reverse Transcription Polymerase Chain Reaction Assays for the Detection of Canine Influenza Virus in Clinical Specimens

The objective of the current study was to determine the capability of 3 recently described one-step TaqMan real-time reverse transcription polymerase chain reaction (real-time RT-PCR) assays targeting the nucleoprotein (NP), matrix (M), and hemagglutinin (HA) genes of H3N8 Equine influenza virus (EIV NP, EIV M, and EIV HA3 assays, respectively) to detect Canine influenza virus (CIV). The assays were initially evaluated with nucleic acid extracted from tissue culture fluid (TCF) containing the A/canine/FL/43/04 strain of Influenza A virus associated with the 2004 canine influenza outbreak in Florida. The EIV NP, EIV M, and EIV HA3 assays could detect CIV nucleic acid at threshold cycle (Ct) values of 16.31, 23.71, and 15.28, respectively. Three assays using TCF or allantoic fluid (AF) samples containing CIV ( n = 13) and archived canine nasal swab samples ( n = 20) originally submitted for laboratory diagnosis of CIV were further evaluated. All TCF and AF samples, together with 10 nasal swab samples that previously tested positive for virus by attempted isolation in embryonated hens' eggs or Madin–Darby canine kidney cells, were positive in all 3 real-time RT-PCR assays. None of the 3 assays detected the H1N1 Swine influenza virus strain in current circulation. These findings demonstrate that previously described real-time RT-PCR assays targeting NP, M, and H3 HA gene segments of H3N8 EIV are also valuable for the diagnosis of CIV infection in dogs. The assays could expedite the detection and identification of CIV.

Planning for the next influenza H1N1 season: a modelling study

Background

The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge.

Methods

This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination.

Results

During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly.

The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit.

Conclusions

These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection.

A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America

Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.

Preventive behaviors, beliefs, and anxieties in relation to the swine flu outbreak among college students aged 18-24 years

Aim

The objective of this study was to assess beliefs, misconception, and anxiety in relation to swine flu outbreak and whether perception of the outbreak predicted changes in behavior.

Subject and methods

In November 2009, we conducted an Internet-based cross-sectional survey of college students aged 18–24 years in a Midwestern State in the USA. We collected information on swine flu knowledge, perception on immunization safety, perceived efficacy of recommended behavior, changed behavior, and anxiety.

Results

Of the 236 respondents, 83.1% had some anxiety about swine flu, 64.8% believed avoiding crowded places was preventive, 33.5% believed the 2009 swine flu vaccine was safe, and 36.9% showed interest in receiving the vaccine. Misconceptions about swine flu contagion via eating cooked pork, water sources, and insect bites were common. Respondents were unaware of transmissions via contaminated objects and droplets. Only 42.6% were satisfied with governmental efforts. Women were more likely to wash hands frequently than men (odds ratio 2.80, p < 0.001).

Conclusion

There is a gap in swine flu knowledge, minimal risk reduction, increased amount of anxiety, and skepticism about swine flu vaccine safety. These gaps warrant serious attention to inform the public about specific actions regarding swine flu.

A novel algorithm to define infection tendencies in H1N1 cases in Mainland China

Incidences of H1N1 viral infections in Mainland China are collected by the Ministry of Health, the People's Republic of China. The number of confirmed cases and the timing of these outbreaks from May 13 to July 22, 2009 were obtained and subjected to a novel mathematical model to simulate the infection profile (time vs number). The model was predicated upon the grey prediction theory which allows assignment of future trends using limited numbers of data points. During the period of our analysis, the number of confirmed H1N1 cases in Mainland China increased from 1 to 1772. The efficiency of our model to simulate these data points was evaluated using Sum of squares of error (SSE), Relative standard error (RSE), Mean absolute deviation (MAD) and Average relative error (ARE). Results from these analyses were compared to similar calculations based upon the grey prediction algorithm. Using our equation, defined herein as equation D–R, results showed that SSE = 6742.00, RSE = 10.69, MAD = 7.07, ARE = 2.47% were all consistent with the D–R algorithm performing well in the estimation of future trends of H1N1 cases in Mainland China. Calculations using the grey theory had no predictive value [ARE for GM(1,1) = −104.63%]. To validate this algorithm, we performed a second analysis using new data obtained from cases reported to the WHO and CDC in the US between April 26 and June 8, 2009. In like manner, the model was equally predictive. The success of the D–R mathematical model suggests that it may have broader application to other viral infections among the human population in China and may be modified for application to other regions of the world.

Healthcare workers as parents: attitudes toward vaccinating their children against pandemic influenza A/H1N1

Background

Both the health care workers (HCWs) and children are target groups for pandemic influenza vaccination. The coverage of the target populations is an important determinant for impact of mass vaccination. The objective of this study is to determine the attitudes of HCWs as parents, toward vaccinating their children with pandemic influenza A/H1N1 vaccine.

Methods

A cross-sectional questionnaire survey was conducted with health care workers (HCWs) in a public hospital during December 2009 in Istanbul. All persons employed in the hospital with or without a health-care occupation are accepted as HCW. The HCWs who are parents of children 6 months to 18 years of age were included in the study. Pearson's chi-square test and logistic regression analysis was applied for the statistical analyses.

Results

A total of 389 HCWs who were parents of children aged 6 months-18 years participated study. Among all participants 27.0% (n = 105) reported that themselves had been vaccinated against pandemic influenza A/H1N1. Two third (66.1%) of the parents answered that they will not vaccinate their children, 21.1% already vaccinated and 12.9% were still undecided. Concern about side effect was most reported reason among who had been not vaccinated their children and among undecided parents. The second reason for refusing the pandemic vaccine was concerns efficacy of the vaccine. Media was the only source of information about pandemic influenza in nearly one third of HCWs. Agreement with vaccine safety, self receipt of pandemic influenza A/H1N1 vaccine, and trust in Ministry of Health were found to be associated with the positive attitude toward vaccinating their children against pandemic influenza A/H1N1.

Conclusions

Persuading parents to accept a new vaccine seems not be easy even if they are HCWs. In order to overcome the barriers among HCWs related to pandemic vaccines, determination of their misinformation, attitudes and behaviors regarding the pandemic influenza vaccination is necessary. Efforts for orienting the HCWs to use evidence based scientific sources, rather than the media for information should be considered by the authorities.

Inside the outbreak of the 2009 influenza A (H1N1)v virus in Mexico

BACKGROUND

Influenza viruses pose a threat to human health because of their potential to cause global disease. Between mid March and mid April a pandemic influenza A virus emerged in Mexico. This report details 202 cases of infection of humans with the 2009 influenza A virus (H1N1)v which occurred in Mexico City as well as the spread of the virus throughout the entire country.

METHODOLOGY AND FINDINGS

From May 1st to May 5th nasopharyngeal swabs, derived from 751 patients, were collected at 220 outpatient clinics and 28 hospitals distributed throughout Mexico City. Analysis of samples using real time RT-PCR revealed that 202 patients out of the 751 subjects (26.9%) were confirmed to be infected with the new virus. All confirmed cases of human infection with the strain influenza (H1N1)v suffered respiratory symptoms. The greatest number of confirmed cases during the outbreak of the 2009 influenza A (H1N1)v were seen in neighbourhoods on the northeast side of Mexico City including Iztapalapa, Gustavo A. Madero, Iztacalco, and Tlahuac which are the most populated areas in Mexico City. Using these data, together with data reported by the Mexican Secretariat of Health (MSH) to date, we plot the course of influenza (H1N1)v activity throughout Mexico.

CONCLUSIONS

Our data, which is backed up by MSH data, show that the greatest numbers of the 2009 influenza A (H1N1) cases were seen in the most populated areas. We speculate on conditions in Mexico which may have sparked this flu pandemic, the first in 41 years. We accept the hypothesis that high population density and a mass gathering which took in Iztapalapa contributed to the rapid spread of the disease which developed in three peaks of activity throughout the Country.

Metagenomic analysis of the viromes of three North American bat species: viral diversity among different bat species that share a common habitat

Effective prediction of future viral zoonoses requires an in-depth understanding of the heterologous viral population in key animal species that will likely serve as reservoir hosts or intermediates during the next viral epidemic. The importance of bats as natural hosts for several important viral zoonoses, including Ebola, Marburg, Nipah, Hendra, and rabies viruses and severe acute respiratory syndrome-coronavirus (SARS-CoV), has been established; however, the large viral population diversity (virome) of bats has been partially determined for only a few of the ∼1,200 bat species. To assess the virome of North American bats, we collected fecal, oral, urine, and tissue samples from individual bats captured at an abandoned railroad tunnel in Maryland that is cohabitated by 7 to 10 different bat species. Here, we present preliminary characterization of the virome of three common North American bat species, including big brown bats (Eptesicus fuscus), tricolored bats (Perimyotis subflavus), and little brown myotis (Myotis lucifugus). In samples derived from these bats, we identified viral sequences that were similar to at least three novel group 1 CoVs, large numbers of insect and plant virus sequences, and nearly full-length genomic sequences of two novel bacteriophages. These observations suggest that bats encounter and disseminate a large assortment of viruses capable of infecting many different animals, insects, and plants in nature.

Reflections on pandemic (H1N1) 2009 and the international response

Gabriel Leung and Angus Nicoll provide their reflections on the international response to the 2009 H1N1 influenza pandemic, including what went well and what changes need to be made in anticipation of future flu pandemics.

Evidence for avian and human host cell factors that affect the activity of influenza virus polymerase

Typical avian influenza A viruses do not replicate efficiently in humans. The molecular basis of host range restriction and adaptation of avian influenza A viruses to a new host species is still not completely understood. Genetic determinants of host range adaptation have been found on the polymerase complex (PB1, PB2, and PA) as well as on the nucleoprotein (NP). These four viral proteins constitute the minimal set for transcription and replication of influenza viral RNA. It is widely documented that in human cells, avian-derived influenza A viral polymerase is poorly active, but despite extensive study, the reason for this blockade is not known. We monitored the activity of influenza A viral polymerases in heterokaryons formed between avian (DF1) and human (293T) cells. We have discovered that a positive factor present in avian cells enhances the activity of the avian influenza virus polymerase. We found no evidence for the existence of an inhibitory factor for avian virus polymerase in human cells, and we suggest, instead, that the restriction of avian influenza virus polymerases in human cells is the consequence of the absence or the low expression of a compatible positive cofactor. Finally, our results strongly suggest that the well-known adaptative mutation E627K on viral protein PB2 facilitates the ability of a human positive factor to enhance replication of influenza virus in human cells.

Genetic analysis of influenza A/H1N1 of swine origin virus (SOIV) circulating in Central and South America

Since the first detection of swine origin virus (SOIV) on March 28, 2009, the virus has spread worldwide and oseltamivir-resistant strains have already been identified in the past months. Here, we show the phylogenetic analysis of 63 SOIV isolates from eight countries in Central and South America, and their sensitivity to oseltamivir.

Effectiveness of seasonal 2008-2009, 2009-2010 and pandemic vaccines, to prevent influenza hospitalizations during the autumn 2009 influenza pandemic wave in Castellón, Spain. A test-negative, hospital-based, case-control study

We estimate the impact of the two previous influenza seasonal vaccines and the pandemic vaccine on risk of A (H1N1) 2009 laboratory confirmed hospitalizations during the autumn 2009 pandemic wave in Castellón, Spain. We conducted a test-negative, hospital-based, case-control study. Influenza A (H1N1) 2009 infection was detected in 147 (44%) of 334 patients hospitalized for a presumptive influenza related illness. No effect was observed for the 2008-2009 and 2009-2010 seasonal influenza vaccines. However, the pandemic vaccine was associated with an adjusted vaccine effectiveness of 90% (95% CI, 48-100%). Pandemic vaccines were effective in preventing pandemic influenza associated hospitalizations.

The novel H1N1 Influenza A global airline transmission and early warning without travel containments

A novel influenza A (H1N1) has been spreading worldwide. Early studies implied that international air travels might be key cause of a severe potential pandemic without appropriate containments. In this study, early outbreaks in Mexico and some cities of United States were used to estimate the preliminary epidemic parameters by applying adjusted SEIR epidemiological model, indicating transmissibility infectivity of the virus. According to the findings, a new spatial allocation model totally based on the real-time airline data was established to assess the potential spreading of H1N1 from Mexico to the world. Our estimates find the basic reproductive number R0 of H1N1 is around 3.4, and the effective reproductive number fall sharply by effective containment strategies. The finding also implies Spain, Canada, France, Panama, Peru are the most possible country to be involved in severe endemic H1N1 spreading.

Evolutionary entropy determines invasion success in emergent epidemics

BACKGROUND

Standard epidemiological theory claims that in structured populations competition between multiple pathogen strains is a deterministic process which is mediated by the basic reproduction number (R0) of the individual strains. A new theory based on analysis, simulation and empirical study challenges this predictor of success.

PRINCIPAL FINDINGS

We show that the quantity R0 is a valid predictor in structured populations only when size is infinite. In this article we show that when population size is finite the dynamics of infection by multi-strain pathogens is a stochastic process whose outcome can be predicted by evolutionary entropy, S, an information theoretic measure which describes the uncertainty in the infectious age of an infected parent of a randomly chosen new infective. Evolutionary entropy characterises the demographic stability or robustness of the population of infectives. This statistical parameter determines the duration of infection and thus provides a quantitative index of the pathogenicity of a strain. Standard epidemiological theory based on R0 as a measure of selective advantage is the limit as the population size tends to infinity of the entropic selection theory. The standard model is an approximation to the entropic selection theory whose validity increases with population size.

CONCLUSION

An epidemiological analysis based on entropy is shown to explain empirical observations regarding the emergence of less pathogenic strains of human influenza during the antigenic drift phase. Furthermore, we exploit the entropy perspective to discuss certain epidemiological patterns of the current H1N1 swine flu outbreak.