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This study was conducted to assess the knowledge of H1N1 among medical students, their perceptions, and behavioral intentions in the wake of the H1N1 pandemic influenza. There were significant gaps in important self-isolation protocols and preventive measures. Increased contact with both patients and colleagues can lead to unintentional transmission and contraction of influenza. Universities should introduce and encourage infection control guidelines into routine curriculum.

We describe the epidemiology and virology of the official length of the 2009 pandemic (68 weeks from April 2009 to August 2010) in the 27 European Union Member States plus Norway and Iceland. The main trends are derived from published literature as well as the analysis and interpretation of data provided to the European Centre for Disease Prevention and Control (ECDC) through the European Influenza Surveillance Network (EISN) and data collected by the ECDC itself. The 2009 influenza A(H1N1) pandemic started in Europe around week 16 of 2009 (although the World Health Organization (WHO) declared only in week 18). It progressed into an initial spring/summer wave of transmission that occurred in most countries, but was striking only in a few, notably the United Kingdom. During the summer, transmission briefly subsided but then escalated again in early autumn, just after the re-opening of the schools. This wave affected all countries, and was brief but intense in most, lasting about 14 weeks. It was accompanied by a similar but slightly delayed wave of hospitalisations and deaths. By the time the WHO declared the pandemic officially over in August 2010 (week 32), Europe had experienced transmission at low level for about 34 weeks.

In the 2009 H1N1 pandemic, the Hospital Authority managing >90% of hospital beds and 74 outpatient clinics in Hong Kong implemented mandatory reporting for healthcare workers (HCWs) with confirmed pH1N1 and collected detailed data on infected HCWs.

Objectives: Workplace absences due to illness can disrupt usual operations and increase costs for businesses. This study of sickness absence due to influenza and influenza-related illness presents a unique opportunity to characterise and measure the impact of the 2009 (H1N1) pandemic, by comparing trends during the pandemic to those of previous years, and adding this information to that obtained by traditional epidemiological surveillance systems. Methods: We compared the numbers of cases of sickness absence due to illness caused by influenza and influenza-related illness in 2007-2009, and in the first 3 months of 2010 in Catalonia (n=811 940) using a time series approach. Trends were examined by economic activity, age and gender. The weekly endemic-epidemic index (EEI) was calculated and its 95% CI obtained with the delta method, with observed and expected cases considered as independent random variables. Results: Influenza activity peaked earlier in 2009 and yielded more cases than in previous years. Week 46 (in November 2009) had the highest number of new cases resulting in sickness absence (EEI 20.99; 95% CI 9.44 to 46.69). Women and the 'education, health and other social activities' sector were the most affected. Conclusions: Results indicate that the new H1N1 pandemic had a significant impact on business, with shifts in the timing of peak incidence, a doubling in the number of cases, and changes in the distribution of cases by economic activity sector and gender. Traditional epidemiological surveillance systems could benefit from the addition of information based on sickness absence data.

Objectives To follow up a UK national cohort of women admitted to hospital with confirmed 2009/H1N1 influenza in pregnancy in order to obtain a complete picture of pregnancy outcomes and estimate the risks of adverse fetal and infant outcomes. Design National cohort study. Setting 221 hospitals with obstetrician led maternity units in the UK. Participants 256 women admitted to hospital with confirmed 2009/H1N1 in pregnancy during the second wave of pandemic infection between September 2009 and January 2010; 1220 pregnant women for comparison. Main outcome measures Rates of stillbirth, perinatal mortality, and neonatal mortality; odds ratios for infected versus comparison women. Results Perinatal mortality was higher in infants born to infected women (10 deaths among 256 infants; rate 39 (95% confidence interval 19 to 71) per 1000 total births) than in infants of uninfected women (9 deaths among 1233 infants; rate 7 (3 to 13) per 1000 total births) (P

OBJECTIVES This study aimed to describe the design and implementation of an alternate site of care (ASC) for nonurgent pediatric patients with influenza-like illnesses during the 2009 H1N1 pandemic and to evaluate its performance. METHODS We describe the design and physical implementation of an ASC. Evaluation of the utilization, patient demographics, throughput, safety, family satisfaction, and cost are presented. RESULTS The process of project development, site selection, clinical algorithms, staffing supplies, and cost are detailed. The ASC was used for 7.5 days, and 137 patients were treated. The median age was 6.5 years. Forty-five percent were male, and English was the primary language. Median length of stay for patients evaluated was 65 minutes. Of patients, 5.8% were transferred from the ASC to the ED for further care. Also, 2.3% of patients returned to the ED within 72 hours; however, none required admission. There were no adverse events associated with the ASC and 92% of families rated overall care as very good or excellent. CONCLUSIONS Selected nonurgent patients with influenza-like illness during a pandemic can be treated in a safe and timely manner with high levels of family satisfaction in a novel setting.

Objectives Prepandemic projections anticipated huge excess attendances and mortality in an influenza pandemic. A number of tools had been suggested for triaging patients with influenza for inpatient and critical care admission, but none had been validated in these patients. The authors aimed to evaluate three potential triage toolsdCURB-65, PMEWS and the Department of Health community assessment tool (CAT)din patients in the first waves of the 2009 H1N1 pandemic. Setting Prospective cohort study in three urban emergency departments (one adult, one paediatric, one mixed) in two cities. Participants All patients presenting to the three emergency departments fulfilling the national definition of suspected pandemic influenza. Outcome measures 30-day follow-up identified patients who had died or had required advanced respiratory, cardiovascular or renal support. Results The pandemic was much less severe than expected. A total of 481 patients (347 children) were recruited, of which only five adults fulfilled the outcome criteria for severe illness. The c-statistics for CURB-65, PMEWS and CAT in adults in terms of discriminating between those admitted and discharged were 0.65 (95% CI 0.54 to 0.76), 0.76 (95% CI 0.66 to 0.86) and 0.62 (95% CI 0.51 to 0.72), respectively. In detecting adverse outcome, sensitivities were 20% (95% CI 4% to 62%), 80% (95% CI 38% to 96%) and 60% (95% CI 23% to 88%), and specificities were 94% (95% CI 88% to 97%), 40% (95% CI 32% to 49%) and 81% (95% CI 73% to 87%) for CURB-65, PMEWS and CAT, respectively. Conclusions Although limited by a paucity of cases, this research shows that current triage methods for suspectedpandemic influenza didnot reliably discriminate between patients with good and poor outcomes.

To learn more about racial and ethnic disparities in influenza vaccination during the 2009-H1N1 pandemic, we examined nationally representative survey data of US adults. We found disparities in 2009-H1N1 vaccine uptake between Blacks and Whites (13.8% vs 20.4%); Whites and Hispanics had similar 2009-H1N1 vaccination rates. Physician offices were the dominant location for 2009-H1N1 and seasonal influenza vaccinations, especially among minorities. Our results highlight the need for a better understanding of how communication methods and vaccine distribution strategies affect vaccine uptake within minority communities.

The sudden outbreak of swine H1N1 pandemic and its rapid disappearance are an important topic to study. This pandemic was believed due to a new influenza A virus formed by the reassortment among human, swine, and Eurasian avian strains. The difference between species and between subtypes would not be larger enough to prevent the cross-species infection and cross-subtype reassortment from occurring. In this study, we use model I ANOVA to analyze 1709 nucleoproteins influenza A virus available in database in order to see whether there is a difference between hosting species and between subtype, and then we use model II ANOVA to determine the inter- and intra subtype/species variations for these 1709 nucleoproteins. The results show that the difference between hosting species and between subtypes exists only in about half of cases, and the intra subtype/species variation is generally larger than inter subtype/species variation. Thus, this study provides the bioinformatic reason for cross-species infection and cross subtype mutation for nucleoproteins from influenza A virus.

SUMMARYThe Health Protection Agency/QSurveillance national surveillance system utilizes QSurveillance® a recently developed general practitioner database covering over 23 million people in the UK. We describe the spread of the first wave of the influenza A(H1N1) pandemic 2009 using data on consultations for influenza-like illness (ILI), respiratory illness and prescribing for influenza from 3400 contributing general practices. Daily data, provided from 27 April 2009 to 28 January 2010, were used to give a timely overview for those managing the pandemic nationally and locally. The first wave particularly affected London and the West Midlands with a peak in ILI in week 30. Children aged between 1 and 15 years had consistently high consultation rates for ILI. Daily ILI rates were used for modelling national weekly case estimates. The system enabled the ‘real-time’ monitoring of the pandemic to a small geographical area, linking morbidity and prescribing for influenza and other respiratory illnesses.

We discuss the efficacy 3 pandemic influenza, measures planned against an anticipated outbreak. First was an exclusive influenza outpatient clinic. Second was a medical call center for febrile illness subjects needing with fever clinic recommendation. The last was isolation. Before the outbreak, we had thought that all confirmed or suspected new influenza case should be quarantined. May 2009 brought the first A1/H1 pandemic influenza outbreak to Kobe, Japan. After the first infection announcement, call center and fever clinic consultations skyrocketed, filling all 55 designated Kobe hospital bed within 48 hours. Inquiries at call centers increased more rapidly than numbers of subjects rushing to fever clinics. Just after designated hospital beds were filled, medical service restrictions were rapidly relaxed. Our experiences suggest that compulsory hospitalization broke down quickest in the fever case overflow, so medical call centers may be crucial in preventing fever clinic overflows by subjects with fever of unknown origin not recommended to consult fever clinics. Those with severe influenza symptoms should be given priority in hospitalization and flexible policies are recommended.

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.

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.

The 2009 H1N1 influenza pandemic prompted the US Food and Drug Administration (FDA) to issue an emergency use authorization (EUA) for the intravenous antiviral peramivir, an unapproved neuraminidase inhibitor (NAI) currently under development. Peramivir use was limited to patients for whom other NAI therapy had failed or in whom oral or inhalational drug absorption was believed to be unreliable. This introduced a patient selection bias that precluded safety and efficacy assessment. Despite the challenges and risks, there was a compelling public health need for an intravenous agent during the 2009 H1N1 pandemic.

Measuring the burden of historic pandemics is not straightforward and often must be based on suboptimal mortality data. For example, the critical 1918 pandemic global burden estimate was based on excess in annual all-cause mortality--calculated as the difference between deaths during 1918-1920 and the surrounding 3-year periods. One intriguing result was a ∼ 40-fold between-country variation in pandemic mortality burden: ∼ 0.2% of Danes died, compared to ∼ 8% of populations in some Indian provinces (Murray et al., 2006 [16]). Using the same methodology and data source we explore the robustness of this methodology for different age-groups. For infants the country estimates varied 100-fold, from 15 to 1500 excess deaths/10,000 population, while for adults ≥ 45 years estimates ranged from -70 to 170/10,000 population. In contrast, estimates for children, 1-14 years, and adults aged 15-44 years, were far more stable. We next used detailed mortality data from Copenhagen to compare such estimates to the more precise estimates obtained from monthly mortality time series data and respiratory deaths. We found that the all-cause annual method substantially underestimated due to an unexplained depression in all-cause mortality in Denmark in 1918 and deaths caused by other epidemic diseases during the baseline periods. We conclude that country estimates for infants and older adults were highly variable by the Murray method due to substantial variability in annual all-cause mortality. A more precise 1918 pandemic burden estimate would be gotten from either focusing analysis on persons age 1-44 who suffered 95% of all pandemic deaths and had a substantial rise over their baseline mortality level, or if possible focus analysis on annual respiratory deaths. For less severe pandemics, including the ongoing 2009 H1N1 pandemic, the use of all-cause mortality data requires careful consideration of excess deaths in defined pandemic periods and a focus on age groups known to be at risk.

To enhance surveillance for influenza-like illness (ILI) in Denmark, a year-round electronic reporting system was established in collaboration with the Danish medical on-call service (DMOS). In order to achieve real-time surveillance of ILI, a checkbox for ILI was inserted in the electronic health record and a system for daily transfer of data to the national surveillance centre was implemented. The weekly number of all consultations in DMOS was around 60,000, and activity of ILI peaked in week 46 of 2009 when 9.5% of 73,723 consultations were classified as ILI. The incidence of ILI reached a maximum on 16 November 2009 for individuals between five and 24 years of age, followed by peaks in children under five years, adults aged between 25 and 64 years and on 27 November in senior citizens (65 years old or older). In addition to the established influenza surveillance system, this novel system was useful because it was timelier than the sentinel surveillance system and allowed for a detailed situational analysis including subgroup analysis on a daily basis.

The Early Aberration Reporting System (EARS) is used by some local health departments (LHDs) to monitor emergency room and clinic data for disease outbreaks. Using actual chief complaint data from local public health clinics, we evaluate how EARS—both the baseline system distributed by the CDC and two variants implemented by one LHD—perform at locally detecting the 2009 influenza A H1N1 pandemic. We also compare the EARS methods to a CUSUM-based method. We find that the baseline EARS system performed poorly in comparison to one of the LHD variants and the CUSUM-based method. These results suggest that changes in how syndromes are defined can substantially improve EARS performance. The results also show that incorporating algorithms that use more historical data will improve EARS performance for routine surveillance by local health departments.

Background Recent guidance from related regulatory agencies and medical societies supports mandatory vaccination of healthcare workers (HCW) against influenza. At St. Jude Children's Research Hospital, a pediatric oncology referral center, more than 90% of HCWs receive vaccine each year without a policy mandating immunization. Factors associated with HCW uptake of influenza vaccines have not previously been evaluated in a high compliance rate setting. Methods A structured, anonymous, electronic questionnaire was distributed in August 2010 to employees (HCW and non-HCW). Demographics, prior receipt of influenza vaccines, reasons for acceptance or refusal of seasonal and 2009 H1N1 pandemic vaccine, and attitudes on mandatory vaccination were assessed. Results 95.0% of 925 HCWs and 63.1% of all 3227 qualifying employees responded to the survey. 93.8% and 75.2% of HCW reported receiving seasonal and 2009 H1N1 influenza vaccines, respectively, in the 2009–2010 season. Benefits to self and/or patients were cited as the most frequent reasons for accepting seasonal (83.5% and 78.3%, respectively) and 2009 H1N1 (85.9% and 81.1%, respectively) vaccination. 36.6% of HCWs opposed mandating influenza vaccination; 88.2% and 59.9% of whom reported receiving the seasonal and 2009 H1N1 influenza vaccines, respectively. Violation of freedom of choice and personal autonomy were the most frequently reported reasons for opposition. Conclusion In this cohort of HCWs with a high influenza vaccination rate, realistic assessments of the potential benefits of vaccination appear to have driven the choice to accept immunization. Despite this, mandating vaccination was viewed unfavorably by a significant minority of vaccinated individuals. Employee concerns over autonomy should be addressed as institutions transition to mandatory vaccination policies.

While the 1918/1919 H1N1 influenza pandemic is widely recognized as a “worst-case scenario” for the emergence of a new influenza strain, relatively little is known about the origin of the responsible virus and its pattern of spread. Most studies of this virus in the United States rely on temporally and spatially aggregated data. Location-specific studies of the impact of the 1918 pandemic strain in the United States have been confined primarily to large cities on the East Coast or West Coast. In this study, data on pneumonia and influenza fatalities from 1910-1923 have been extracted from death certificates for Saint Joseph, Missouri, a typical mid-sized city in the central United States. An increase in pneumonia and influenza mortality was noted starting in the 1915/1916 influenza season. Initially, increased mortality was observed in infants and the elderly. In February 1918, an age-shift typical of pandemic strains of virus was seen, as the burden of mortality shifted to young adults, a characteristic of the 1918 pandemic virus. These results provide one of the first confirmations of the existence of a “herald wave” of influenza activity in the United States prior to the recognized start of the H1N1 pandemic in Spring 1918. This study is one of very few that measures the impact of 1918/1919 influenza in a particular location in the central United States.

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., This work has been partially funded by the National Institutes of Health R21-DA024259 award, the Lilly Endowment grant 2008 1639-000 and the DTRA-1-0910039 award to AV; the EC-ICT contract no. 231807 (EPIWORK) to AV and VC; the EC-FET contract no. 233847 (DYNANETS) to AV, VC, and JJR; the ERC Ideas contract n.ERC-2007-Stg204863 (EPIFOR) to VC, PB, CP, and MT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

During the recent H1N1 pandemic, children with Sickle Cell Disease (SCD) experienced more hospitalizations and more complications than the general pediatric population. We performed a retrospective multicenter survey at 9 Pediatric Haematology-Oncology Units across Italy. H1N1 admission rate was 5.2%, with all admissions occurring before vaccine availability. Length Of Stay (LOS) was 6.06 days (7.85 for Acute Chest Syndrome), longer than in other countries. Vaccination coverage was not homogeneous, ranging from 0 to 99%; several family-related and health-system related barriers in accessing vaccinations were identified that should be ameliorated to improve coverage in this high risk group of children.

Publisher Summary This chapter focuses on the biological features of influenza that have repeatedly allowed outbreaks to emerge undetected. It first briefly reviews influenza genetics and evolution and then reviews those aspects of human and swine influenza evolution during the past century required to frame the current knowledge of the origin of the 2009 H1N1 influenza pandemic. It also provides an overview of symptoms, diagnostics, surveillance, and techniques of molecular evolution and phylogenetics required to study the origin and spread of new strains and finishes by considering how current forensic techniques would suffice in the investigation of a criminal release. The influenza viruses comprise three genera in the family Orthomyxoviridae. The genera are, in practice, referred to as “types” A, B, and C. However, in terms of their potential to cause harm to humans, the influenza viruses can be divided into two categories. An influenza virus need not be unusually deadly to cause harm. The current 2009 H1N1 pandemic serves as an example of the social and economic disruption that can ensue from any outbreak of a novel influenza strain. The H1N1 2009 pandemic tested our capacity for influenza outbreak investigation at a time when a relative wealth of forensic technology was at our disposal. Nonetheless, the origin of the H1N1 2009 virus remains unknown, as are the exact origins of all past influenza pandemic strains.

The pig is one of the main hosts of influenza A viruses and plays important roles in shaping the current influenza ecology. The occurrence of the 2009 H1N1 pandemic influenza virus demonstrated that pigs could independently facilitate the genesis of a pandemic influenza strain. Genetic analyses revealed that this virus was derived by reassortment between at least two parent swine influenza viruses (SIV), from the northern American triple reassortant H1N2 (TR) and European avian-like H1N1 (EA) lineages. The movement of live pigs between different continents and subsequent virus establishment are preconditions for such a reassortment event to occur. Asia, especially China, has the largest human and pig populations in the world, and seems to be the only region frequently importing pigs from other continents. Virological surveillance revealed that not only classical swine H1N1 (CS), and human-origin H3N2 viruses circulated, but all of the EA, TR and their reassortant variants were introduced into and co-circulated in pigs in this region. Understanding the long-term evolution and history of SIV in Asia would provide insights into the emergence of influenza viruses with epidemic potential in swine and humans.

Influenza pandemics in the last century were characterized by successive waves and differences in impact and timing between different regions, for reasons not clearly understood. The 2009 H1N1 pandemic showed rapid global spread, but with substantial heterogeneity in timing within each hemisphere. Even within Europe substantial variation was observed, with the UK being unique in experiencing a major first wave of transmission in early summer and all other countries having a single major epidemic in the autumn/winter, with a West to East pattern of spread. Here we show that a microsimulation model, parameterised using data about H1N1pdm collected by the beginning of June 2009, explains the occurrence of two waves in UK and a single wave in the rest of Europe as a consequence of timing of H1N1pdm spread, fluxes of travels from US and Mexico, and timing of school vacations. The model provides a description of pandemic spread through Europe, depending on intra-European mobility patterns and socio-demographic structure of the European populations, which is in broad agreement with observed timing of the pandemic in different countries. Attack rates are predicted to depend on the socio-demographic structure, with age dependent attack rates broadly agreeing with available serological data. Results suggest that the observed heterogeneity can be partly explained by the between country differences in Europe: marked differences in school calendars, mobility patterns and sociodemographic structures. Moreover, higher susceptibility of children to infection played a key role in determining the epidemiology of the 2009 pandemic. Our work shows that it would have been possible to obtain a broad-brush prediction of timing of the European pandemic well before the autumn of 2009, much more difficult to achieve with simpler models or pre-pandemic parameterisation. This supports the use of models accounting for the structure of complex modern societies for giving insight to policy makers., Author Summary The 2009 H1N1pdm influenza pandemic spread rapidly but heterogeneously. A notable pattern occurred in Europe, with the UK exhibiting a first wave in early summer and a second wave in autumn, while all other European countries experienced a single wave in autumn/winter, resulting in a clear West to East pattern of spread. Our study asks which factors were most responsible for this variation, and to what extent the pattern of spread was predictable from data available in the first two months of the pandemic. Providing reliable answers to these questions would reduce uncertainty and improve situational awareness for policy-makers in the future, giving clearer expectations as to the likely impact and timing of a future pandemic and the potential effectiveness of mitigation measures. We found that that heterogeneity seen in 2009 can largely be explained by marked differences in school calendars, human mobility and demography across Europe. We also conclude that much of the variation in timing of the pandemic in Europe would have been predictable on the basis of data available in early June 2009. Our work supports the use of models accounting for the structure of complex modern societies for giving insight to policy makers in future pandemics.

INTRODUCTION: Several aspects of the epidemiology of 2009 (H1N1) pandemic influenza have not been accurately determined. We sought to study whether the age distribution of cases differs in comparison with seasonal influenza. METHODS: We searched for official, publicly available data through the internet from different countries worldwide on the age distribution of cases of influenza during the 2009 (H1N1) pandemic influenza period and most recent seasonal influenza periods. Data had to be recorded through the same surveillance system for both compared periods. RESULTS: For 2009 pandemic influenza versus recent influenza seasons, in USA, visits for influenza-like illness to sentinel providers were more likely to involve the age groups of 5-24, 25-64 and 0-4 years compared with the reference group of >64 years [odds ratio (OR) (95% confidence interval (CI)): 2.43 (2.39-2.47), 1.66 (1.64-1.69), and 1.51 (1.48-1.54), respectively]. Pediatric deaths were less likely in the age groups of 2-4 and 65 years [OR (95% CI): 7.19 (6.67-7.75), 5.33 (4.90-5.79), 5.04 (4.70-5.41), 3.12 (2.89-3.36) and 1.89 (1.75-2.05), respectively]. In New Zealand, consultations for influenza-like illness by sentinel providers were more likely in the age groups of 65 years [OR (95% CI): 2.38 (1.74-3.26), 1.99 (1.62-2.45), 1.57 (1.30-1.89), 1.57 (1.30-1.88), 1.40 (1.17-1.69) and 1.39 (1.14-1.70), respectively]. CONCLUSIONS: The greatest increase in influenza cases during 2009 (H1N1) pandemic influenza period, in comparison with most recent seasonal influenza periods, was seen for school-aged children, adolescents, and younger adults.

With the development of Internet, widely kind of web data have been applied in influenza surveillance and epidemic early warning. However there were less works focusing on the estimation of geospatial distribution of influenza. In order to evaluate the potential power of news comments for geospatial distribution estimation, we choose the H1N1 pandemic in the mainland of China in 2009 as case. After collecting 75878 comments of H1N1 related news from www.sina.com(a famous news site in the mainland of China), we compared the geospatial distribution of comments against surveillance data. The result shows that the comments data share a similar geospatial distribution with the epidemic data(a correlation of 0.848 p

Summary We report four patients with novel observations during extracorporeal membrane oxygenation support (ECMO). ECMO was initiated because of severe ARDS due to the primary H1N1 pandemic influenza pneumonia. Two patients had excessive conjugated hyperbilirubinemia and two had unproportional depletion of the coagulation factor IX. Pathogenetic mechanisms and clinical relevance of the noticed phenomena are discussed.

Objective: This study describes the clinical course, treatment, and outcome of 13 critically ill children due to infection with new influenza A H1N1, admitted to 2 pediatric intensive care units (PICUs) in the northwestern part of the Netherlands. Methods: Retrospective case series, conducted in 2 PICUs in Amsterdam, the Netherlands. Results: A total of 13 children with a new influenza A H1N1 infection were admitted at 2 Dutch PICUs. The majority of these children were 12 to 16 years old and had an underlying disease. All children required mechanical ventilatory support. Shock was present in 7 of 13 (54%) children. Two children were transferred to a supraregional PICU with facilities for extracorporeal membrane oxygenation. Conclusions: In a Dutch cohort of 13 critically ill children due to infection with new influenza (H1N1), respiratory (100%) and circulatory (54%) failure characterized the course of this infection in most of these children. All children survived.

The effect of multiple pandemic waves on morbidity as quantified by the number of intensive care unit admissions is investigated. A seasonal morbidity function based on probability data from the H1N1 pandemic of 2009 is used and compared to the most common approach used in current literature. We find pandemic scenarios where due to vaccination, a second wave in winter, spring or summer can have a higher number of intensive care unit (ICU) admissions overall even though vaccination is successful in reducing the number of infections in total. This occurs because of additional susceptibility available in winter due to vaccination in the fall. We also find that predicted estimates of ICU cases differ significantly on how the data on severe outcomes from a pandemic is modeled - whether the probability of an ICU admission is held constant or modeled as a seasonally varying function.

In order to understand the evolution of the 2009 influenza A (H1N1) pandemic within local regions of Japan, we studied the significance of regional migration between these regions. For this purpose, we have employed an extended SEIR model to describe the immigration of infected people and the stochastic variation of the infectious efficiency. We then applied a data assimilation technique in order to study how the agreement of the simulation results with the observed data depends on the presence/absence of immigration and the degree of variation of the infectious efficiency. Reproducibility is evaluated by log-likelihood values. The log-likelihood does not indicate the significance of immigration. Although there are multiple waves in the time course of the number of reported infected individuals, these waves could be explained by the stochastic nature of infectious events.

The purpose of this study was to describe infection control practices for influenza in mother and newborn units in United States hospitals in the context of the 2009 H1N1 pandemic. We conducted surveys of neonatal intensive care unit directors in February and November 2010 and requested information on infection control practices during the 2009 and 2010 influenza seasons. We received 111 responses to the initial survey and 48 to the follow-up survey. In 2009, 58% of respondents restricted breastfeeding by mothers with influenza-like illness; 42% did not. Ninety percent of the respondents maintained physical separation between an ill mother and her newborn infant, although the approaches to this separation varied. Eighty percent of postpartum units and 89% of neonatal intensive care units restricted access by children. In 2010, fewer hospitals restricted mother-infant contact and children visitation compared with 2009. Infection control practices for influenza in mother and newborn units vary considerably in US hospitals, particularly regarding contact between an ill mother and her newborn infant. The identification of this variation may inform best practices in this area, as well as future investigations and future guideline development.

Purpose of review The 2009 H1N1 pandemic focused attention on the speed and accuracy of influenza diagnostic methods. This review provides an update on current tests and new developments. Recent findings Widely used rapid antigen tests and immunofluorescence tests were generally less sensitive for 2009 H1N1 influenza than for seasonal influenza. In addition, marked variability was reported for the same tests in different settings and patient groups. The advantages of molecular testing gained wide recognition, namely high sensitivity, speed compared with culture, ability to assess viral load and to identify subtype. Although adoption of influenza molecular testing can be expected to accelerate, immunoassays and rapid cultures performed on site retain advantages for many facilities. Falsely negative results were seen with all methods, especially for samples collected very early or late. Summary Influenza diagnostic test performance can be adversely affected by viral genetic and antigenic changes and should be re-assessed annually. Variability in sensitivity and specificity of the same test in different settings highlights the need for each laboratory to ensure optimal procedures and work with clinicians to improve sample quality. Manufacturers have been motivated to improve immunoassays and develop simpler and faster multiplex molecular tests, hopefully in advance of the next 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.

In 2009 a novel H1N1 influenza virus emerged and spread rapidly. Soon after vaccine lots were released, however, the shelf life was revised downward due to an unexpected decrease in HA potency. In this study, we found differences in both stability and antigenic content of two monovalent H1N1/2009 vaccine preparations. These appear to have arisen due to differences in the A/California/7/2009-like influenza strain used to prepare vaccine.

Background The publicity of the H1N1 pandemic increased the demand for flu vaccination including in the egg allergic. The MMR protocol is safe but cumbersome. A simpler but less tried protocol with vaccines having

Despite extensive planning for the next influenza pandemic in humans, nature has once again confounded the influenza experts. The emergence and development of an H1N1 pandemic strain while an H1N1 virus was still circulating in humans is an unprecedented event. Here, we examine the emergence of H1N1 influenza viruses in the USA, Europe, and Asia from the natural aquatic bird reservoir through intermediate hosts including pigs and turkeys to humans. There were some remarkable parallel evolutionary developments in the swine influenza viruses in the Americas and in Eurasia. Classical swine influenza virus in the USA emerged either before or immediately after the Spanish influenza virus emerged in humans in 1918. Over the next 50 plus years this swine influenza virus became increasingly attenuated in pigs but occasionally transmitted to humans causing mild clinical infection but did not consistently spread human to human. The remarkable parallel evolution was the introduction of avian influenza virus genes independently in swine influenza viruses in Europe and the USA, with almost simultaneous acquisition of genes from seasonal human influenza. Influenza in pigs in both Eurasia and America became more aggressive necessitating the production of vaccines, and the incidence of transmission of clinical influenza to humans increased. Eventually the different triple reassortants with gene segments from avian, swine, and human influenza viruses in pigs in Europe and America met and mated and developed into the 2009 pandemic H1N1 influenza that is highly transmissible in people, pigs, and turkeys. Whether this occurred in Mexico or in Asia is currently unknown. The failure of the experts was to not recognize the importance of pigs in the evolution and host range transmission of influenza viruses with pandemic potential.

Twitter is a free social networking and micro-blogging service that enables its millions of users to send and read each other's “tweets,” or short, 140-character messages. The service has more than 190 million registered users and processes about 55 million tweets per day. Useful information about news and geopolitical events lies embedded in the Twitter stream, which embodies, in the aggregate, Twitter users' perspectives and reactions to current events. By virtue of sheer volume, content embedded in the Twitter stream may be useful for tracking or even forecasting behavior if it can be extracted in an efficient manner. In this study, we examine the use of information embedded in the Twitter stream to (1) track rapidly-evolving public sentiment with respect to H1N1 or swine flu, and (2) track and measure actual disease activity. We also show that Twitter can be used as a measure of public interest or concern about health-related events. Our results show that estimates of influenza-like illness derived from Twitter chatter accurately track reported disease levels.

In late April 2009 the emergence of 2009 pandemic influenza A (H1N1pdm) virus was detected in humans. From its detection through July 18th, 2009, confirmed cases of H1N1pdm in the Americas were periodically reported to the Pan American Health Organization (PAHO) by member states. Because the Americas span much of the world's latitudes, this data provides an excellent opportunity to examine variation in H1N1pdm transmission by season.Using reports from PAHO member states from April 26th, 2009 through July 18th, 2009, we characterize the early spread of the H1N1 pandemic in the Americas. For a geographically representative sample of member states we estimate the reproductive number (R) of H1N1pdm over the reporting period. The association between these estimates and latitude, temperature, humidity and population age structure was estimated.Estimates of the peak reproductive number of H1N1pdm ranged from 1.3 (for Panama, Colombia) to 2.1 (for Chile). We found that reproductive number estimates were most associated with latitude in both univariate and multivariate analyses. To the extent that latitude is a proxy for seasonal changes in climate and behavior, this association suggests a strong seasonal component to H1N1pdm transmission. However, the reasons for this seasonality remain unclear. Keywords: Pandemic H1N1, Influenza, Seasonality, Reproductive number

Objective. To understand the pathophysiology of influenza A, how seasonal strains behave differently from pandemic strains of the virus, and to summarize published data on the global response to the virus focusing on illness in the critical care setting.

We should not be breathing a sigh of relief because the H1N1 pandemic appears to be abating. 1 Rather, we should be alarmed by the specter of future, potentially more disastrous, outbreaks of zoonotic diseases (diseases transmissible from animals to humans) that ‘swine flu’ portends. Such consternation is warranted given that (a) over 60% of all pathogens currently known to cause disease in humans have an animal origin, 2 (b) over 75% of emerging human pathogens are zoonotic, 2 and (c) zoonoses are twice as likely to be associated with emerging disease in humans compared to nonzoonotic pathogens. 2 Since emergence is precipitated by population growth, global trade and travel, urbanization, agriculture, and climate change, 3,4 the threat posed by zoonotic diseases is only going to increase. Our vulnerability to outbreaks of zoonotic diseases is aggravated by traditional anthropocentric clinical- and laboratory-based disease surveillance systems that are capable of detecting zoonotic threats only after a disease has already emerged (and potentially become established) in human populations. 4 This shortcoming is illustrated by the fact that H1N1 was only identified in people two months after the initial human outbreak, 5

Background Several studies have shown a relatively high mortality rate among young people infected by the 2009 pandemic influenza A (H1N1) virus. Here we compared the age distributions of morbidity and mortality during two seasonal influenza epidemics (H1N1 and H3N2) in France and the United States with those of the 2009 H1N1 pandemic waves in the same countries. Methods Age-standardized ratios were used to compare the age distribution of morbidity and mortality due to influenza between the two countries and across the different years. Non parametric analysis of variance was used to compare these ratios between epidemic and pandemic influenza. Results Age distribution of morbidity was similar between the 2009 pandemic and seasonal epidemics due to H1N1 (p = 0.72) and H3N2 viruses (p = 0.68). In contrast, the proportion of under-60s among influenza deaths was markedly higher during the 2009 pandemic (peak Conclusions Young age was a principal mortality risk factor due to the 2009 H1N1 pandemic.