Estimating the disease burden of 2009 pandemic influenza A(H1N1) from surveillance and household surveys in Greece

Background

The aim of this study was to assess the disease burden of the 2009 pandemic influenza A(H1N1) in Greece.

Methodology/Principal Findings

Data on influenza-like illness (ILI), collected through cross-sectional nationwide telephone surveys of 1,000 households in Greece repeated for 25 consecutive weeks, were combined with data from H1N1 virologic surveillance to estimate the incidence and the clinical attack rate (CAR) of influenza A(H1N1). Alternative definitions of ILI (cough or sore throat and fever>38°C [ILI-38] or fever 37.1–38°C [ILI-37]) were used to estimate the number of symptomatic infections. The infection attack rate (IAR) was approximated using estimates from published studies on the frequency of fever in infected individuals. Data on H1N1 morbidity and mortality were used to estimate ICU admission and case fatality (CFR) rates. The epidemic peaked on week 48/2009 with approximately 750–1,500 new cases/100,000 population per week, depending on ILI-38 or ILI-37 case definition, respectively. By week 6/2010, 7.1%–15.6% of the population in Greece was estimated to be symptomatically infected with H1N1. Children 5–19 years represented the most affected population group (CAR:27%–54%), whereas individuals older than 64 years were the least affected (CAR:0.6%–2.2%). The IAR (95% CI) of influenza A(H1N1) was estimated to be 19.7% (13.3%, 26.1%). Per 1,000 symptomatic cases, based on ILI-38 case definition, 416 attended health services, 108 visited hospital emergency departments and 15 were admitted to hospitals. ICU admission rate and CFR were 37 and 17.5 per 100,000 symptomatic cases or 13.4 and 6.3 per 100,000 infections, respectively.

Conclusions/Significance

Influenza A(H1N1) infected one fifth and caused symptomatic infection in up to 15% of the Greek population. Although individuals older than 65 years were the least affected age group in terms of attack rate, they had 55 and 185 times higher risk of ICU admission and CFR, respectively.     

Nationwide molecular surveillance of pandemic H1N1 influenza A virus genomes: Canada, 2009

Background

In April 2009, a novel triple-reassortant swine influenza A H1N1 virus (“A/H1N1pdm”; also known as SOIV) was detected and spread globally as the first influenza pandemic of the 21^st century. Sequencing has since been conducted at an unprecedented rate globally in order to monitor the diversification of this emergent virus and to track mutations that may affect virus behavior.

Methodology/Principal Findings

By Sanger sequencing, we determined consensus whole-genome sequences for A/H1N1pdm viruses sampled nationwide in Canada over 33 weeks during the 2009 first and second pandemic waves. A total of 235 virus genomes sampled from unique subjects were analyzed, providing insight into the temporal and spatial trajectory of A/H1N1pdm lineages within Canada. Three clades (2, 3, and 7) were identifiable within the first two weeks of A/H1N1pdm appearance, with clades 5 and 6 appearing thereafter; further diversification was not apparent. Only two viral sites displayed evidence of adaptive evolution, located in hemagglutinin (HA) corresponding to D222 in the HA receptor-binding site, and to E374 at HA2-subunit position 47. Among the Canadian sampled viruses, we observed notable genetic diversity (1.47×10⁻³ amino acid substitutions per site) in the gene encoding PB1, particularly within the viral genomic RNA (vRNA)-binding domain (residues 493–757). This genome data set supports the conclusion that A/H1N1pdm is evolving but not excessively relative to other H1N1 influenza A viruses. Entropy analysis was used to investigate whether any mutated A/H1N1pdm protein residues were associated with infection severity; however no virus genotypes were observed to trend with infection severity. One virus that harboured heterozygote coding mutations, including PB2 D567D/G, was attributed to a severe and potentially mixed infection; yet the functional significance of this PB2 mutation remains unknown.

Conclusions/Significance

These findings contribute to enhanced understanding of Influenza A/H1N1pdm viral dynamics.     

Nationwide surveillance of influenza during the pandemic (2009-10) and post-pandemic (2010-11) periods in Taiwan

Introduction

Although WHO declared the world moving into the post-pandemic period on August 10, 2010, influenza A(H1N1) 2009 virus continued to circulate globally. Its impact was expected to continue during the 2010–11 influenza season. This study describes the nationwide surveillance findings of the pandemic and post-pandemic influenza periods in Taiwan and assesses the impact of influenza A(H1N1) 2009 during the post-pandemic period.

Methods

The Influenza Laboratory Surveillance Network consisted of 12 contract laboratories for collecting and testing samples with acute respiratory tract infections. Surveillance of emergency room visits and outpatient department visits for influenza-like illness (ILI) were conducted using the Real-Time Outbreak and Disease Surveillance system and the National Health Insurance program data, respectively. Hospitalized cases with severe complications and deaths were reported to the National Notifiable Disease Surveillance System.

Results

During the 2009–10 influenza season, pandemic A(H1N1) 2009 was the predominant circulating strain and caused 44 deaths. However, the 2010–11 influenza season began with A(H3N2) being the predominant circulating strain, changing to A(H1N1) 2009 in December 2010. Emergency room and outpatient department ILI surveillance displayed similar trends. By March 31, 2011, there were 1,751 cases of influenza with severe complications; 50.1% reported underlying diseases. Of the reported cases, 128 deaths were associated with influenza. Among these, 93 (72.6%) were influenza A(H1N1) 2009 and 30 (23.4%) A(H3N2). Compared to the pandemic period, during the immediate post-pandemic period, increased number of hospitalizations and deaths were observed, and the patients were consistently older.

Conclusions

Reemergence of influenza A(H1N1) 2009 during the 2010–11 influenza season had an intense activity with age distribution shift. To further mitigate the impact of future influenza epidemics, Taiwan must continue its multifaceted influenza surveillance systems, remain flexible with antiviral use policies, and revise the vaccine policies to include the population most at risk.     

The influenza pandemic of 2009: lessons and implications

Influenza is a moving target, which evolves in unexpected directions and is recurrent annually. The 2009 influenza A/H1N1 pandemic virus was unlike the 2009 seasonal virus strains and originated in pigs prior to infecting humans. Three strains of viruses gave rise to the pandemic virus by antigenic shift, reassortment, and recombination, which occurred in pigs as 'mixing vessels'. The three strains of viruses had originally been derived from birds, pigs, and humans. The influenza hemagglutinin (HA) and neuraminidase (NA) external proteins are used to categorize and group influenza viruses. The internal proteins (PB1, PB1-F2, PB2, PA, NP, M, and NS) are involved in the pathogenesis of influenza infection. A major difference between the 1918 and 2009 pandemic viruses is the lack of the pathogenic protein PB1-F2 in the 2009 pandemic strains, which was present in the more virulent 1918 pandemic strains. We provide an overview of influenza infection since 1847 and the advent of influenza vaccination since 1944. Vaccines and chemotherapy help reduce the spread of influenza, reduce morbidity and mortality, and are utilized by the global rapid-response organizations associated with the WHO. Immediate identification of impending epidemic and pandemic strains, as well as sustained vigilance and collaboration, demonstrate continued success in combating influenza.     

Reassortment events among swine influenza A viruses in China: implications for the origin of the 2009 influenza pandemic

That pigs may play a pivotal role in the emergence of pandemic influenza was indicated by the recent H1N1/2009 human pandemic, likely caused by a reassortant between viruses of the American triple-reassortant (TR) and Eurasian avian-like (EA) swine influenza lineages. As China has the largest human and pig populations in the world and is the only place where both TR and EA viruses have been reported to cocirculate, it is potentially the source of the H1N1/2009 pandemic virus. To examine this, the genome sequences of 405 swine influenza viruses from China were analyzed. Thirty-six TR and EA reassortant viruses were identified before and after the occurrence of the pandemic. Several of these TR-EA reassortant viruses had genotypes with most segments having the same lineage origin as the segments of the H1N1/2009 pandemic virus. However, these viruses were generated from independent reassortment events throughout our survey period and were not associated with the current pandemic. One TR-EA reassortant, which is least similar to the pandemic virus, has persisted since 2007, while all the other variants appear to be transient. Despite frequent reassortment events between TR and EA lineage viruses in China, evidence for the genesis of the 2009 pandemic virus in pigs in this region is still absent.     

Mutation analysis of 2009 pandemic influenza A(H1N1) viruses collected in Japan during the peak phase of the pandemic

Background

Pandemic influenza A(H1N1) virus infection quickly circulated worldwide in 2009. In Japan, the first case was reported in May 2009, one month after its outbreak in Mexico. Thereafter, A(H1N1) infection spread widely throughout the country. It is of great importance to profile and understand the situation regarding viral mutations and their circulation in Japan to accumulate a knowledge base and to prepare clinical response platforms before a second pandemic (pdm) wave emerges.

Methodology

A total of 253 swab samples were collected from patients with influenza-like illness in the Osaka, Tokyo, and Chiba areas both in May 2009 and between October 2009 and January 2010. We analyzed partial sequences of the hemagglutinin (HA) and neuraminidase (NA) genes of the 2009 pdm influenza virus in the collected clinical samples. By phylogenetic analysis, we identified major variants of the 2009 pdm influenza virus and critical mutations associated with severe cases, including drug-resistance mutations.

Results and Conclusions

Our sequence analysis has revealed that both HA-S220T and NA-N248D are major non-synonymous mutations that clearly discriminate the 2009 pdm influenza viruses identified in the very early phase (May 2009) from those found in the peak phase (October 2009 to January 2010) in Japan. By phylogenetic analysis, we found 14 micro-clades within the viruses collected during the peak phase. Among them, 12 were new micro-clades, while two were previously reported. Oseltamivir resistance-related mutations, i.e., NA-H275Y and NA-N295S, were also detected in sporadic cases in Osaka and Tokyo.     

Estimated cumulative incidence of pandemic (H1N1) influenza among pregnant women during the first wave of the 2009 pandemic

Background

Hospitalization and lab confirmed cases of H1N1 have been reported during the first wave of the 2009 pandemic but these are not accurate measures of influenza incidence in the population. We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic.

Methods

Two panels of stored frozen serum specimens collected for routine prenatal screening were randomly selected for testing before (March 2009, n = 252) and after (August 2009, n = 296) the first wave of the pandemic. A standard hemagglutination inhibition assay was used to detect the presence of IgG antibodies against the pandemic (H1N1) 2009 virus. The cumulative incidence of pandemic (H1N1) influenza was calculated as the difference between the point prevalence rates in the first and second panels.

Results

Of the specimens collected in March, 7.1% were positive for the IgG antibodies (serum antibody titre ≥ 1:40). The corresponding prevalence was 15.7% among the specimens collected in August. The difference indicated a cumulative incidence of 8.6% (95% confidence interval [CI] 3.2%–13.7%). The rate differed geographically, the highest being in the northern regions (20.8%, 95% CI 7.9%–31.8%), as compared with 4.0% (95% CI 0.0%–11.9%) in Winnipeg and 8.9% (95% CI 0.0%–18.8%) in the rest of the province.

Interpretation

We estimated that the cumulative incidence of pandemic (H1N1) influenza among pregnant women in Manitoba during the first wave of the 2009 pandemic was 8.6%. It was 20.8% in the northern regions of the province.During the first wave of the pandemic (H1N1) 2009, the province of Manitoba was more severely affected than almost any other Canadian province.¹ Pregnant women in particular had higher rates of laboratory-confirmed infection and of severe illness.² However, the number of laboratory-confirmed cases is not an accurate measure of the incidence of influenza in the population. The number and geographic distribution of confirmed cases are influenced by differences in access to medical care, physicians’ practices and other factors.³We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic. We did this by measuring the point seroprevalence in random samples of pregnant women presenting for routine prenatal screening before and after the first wave.     

Field effectiveness of pandemic and 2009-2010 seasonal vaccines against 2009-2010 A(H1N1) influenza: estimations from surveillance data in France

Background

In this study, we assess how effective pandemic and trivalent 2009-2010 seasonal vaccines were in preventing influenza-like illness (ILI) during the 2009 A(H1N1) pandemic in France. We also compare vaccine effectiveness against ILI versus laboratory-confirmed pandemic A(H1N1) influenza, and assess the possible bias caused by using non-specific endpoints and observational data.

Methodology and Principal Findings

We estimated vaccine effectiveness by using the following formula: VE  =  (PPV-PCV)/(PPV(1-PCV)) × 100%, where PPV is the proportion vaccinated in the population and PCV the proportion of vaccinated influenza cases. People were considered vaccinated three weeks after receiving a dose of vaccine. ILI and pandemic A(H1N1) laboratory-confirmed cases were obtained from two surveillance networks of general practitioners. During the epidemic, 99.7% of influenza isolates were pandemic A(H1N1). Pandemic and seasonal vaccine uptakes in the population were obtained from the National Health Insurance database and by telephonic surveys, respectively. Effectiveness estimates were adjusted by age and week. The presence of residual biases was explored by calculating vaccine effectiveness after the influenza period. The effectiveness of pandemic vaccines in preventing ILI was 52% (95% confidence interval: 30–69) during the pandemic and 33% (4–55) after. It was 86% (56–98) against confirmed influenza. The effectiveness of seasonal vaccines against ILI was 61% (56–66) during the pandemic and 19% (−10–41) after. It was 60% (41–74) against confirmed influenza.

Conclusions

The effectiveness of pandemic vaccines in preventing confirmed pandemic A(H1N1) influenza on the field was high, consistently with published findings. It was significantly lower against ILI. This is unsurprising since not all ILI cases are caused by influenza. Trivalent 2009-2010 seasonal vaccines had a statistically significant effectiveness in preventing ILI and confirmed pandemic influenza, but were not better in preventing confirmed pandemic influenza than in preventing ILI. This lack of difference might be indicative of selection bias.     

Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data

Background

In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity.

Methods and Findings

We tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP) from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1–2 wk before, and 3 wk after epidemic peak for individuals aged 5–14 y, 15–29 y, and 30–59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5–14 y, 15–19 y, and 20–29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30–59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%–10%.

Conclusions

Serial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and severity in an emerging pandemic. Sero-surveillance for pandemics should be considered. Please see later in the article for the Editors'' Summary     

Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1

This article synthesizes and extends discussions held during an international meeting on "Surveillance for Decision Making: The Example of 2009 Pandemic Influenza A/H1N1," held at the Center for Communicable Disease Dynamics (CCDD), Harvard School of Public Health, on June 14 and 15, 2010. The meeting involved local, national, and global health authorities and academics representing 7 countries on 4 continents. We define the needs for surveillance in terms of the key decisions that must be made in response to a pandemic: how large a response to mount and which control measures to implement, for whom, and when. In doing so, we specify the quantitative evidence required to make informed decisions. We then describe the sources of surveillance and other population-based data that can presently--or in the future--form the basis for such evidence, and the interpretive tools needed to process raw surveillance data. We describe other inputs to decision making besides epidemiologic and surveillance data, and we conclude with key lessons of the 2009 pandemic for designing and planning surveillance in the future.     

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

Background

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

Methodology/Principal Findings

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

Conclusions/Significance

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

Molecular mechanisms of interspecies transmission and pathogenicity of influenza viruses: Lessons from the 2009 pandemic

The emergence of the 2009 H1N1 virus pandemic was unexpected, since it had been predicted that the next pandemic would be caused by subtype H5N1. We also had to learn that a pandemic does not necessarily require the introduction of a new virus subtype into the human population, but that it may result from antigenic shift within the same subtype. The new variant was derived from human and animal viruses by genetic reassortment in the pig, supporting the concept that this animal is the mixing vessel for the generation of new human influenza viruses. Although it is generally believed that the 2009 outbreak was mild, there have been severe cases particularly among the young and the middle-aged. Pathogenicity and host range are determined to a large extent by the polymerase, the haemagglutinin and the NS1 protein of influenza A viruses. There is evidence that mutations of these proteins may change the pathogenicity of the new virus.     

School absenteeism as an adjunct surveillance indicator: experience during the second wave of the 2009 H1N1 pandemic in Quebec, Canada

Background

A school absenteeism surveillance system was implemented in the province of Quebec, Canada during the second wave of the 2009 H1N1pandemic. This paper compares this surveillance approach with other available indicators.

Method

All (3432) elementary and high schools from Quebec were included. Each school was required to report through a web-based system any day where the proportion of students absent for influenza-like illness (ILI) exceeded 10% of current school enrolment.

Results

Between October 18 and December 12 2009, 35.6% of all schools met the 10% absenteeism threshold. This proportion was greater in elementary compared to high schools (40% vs 19%) and in smaller compared to larger schools (44% vs 22%). The maximum absenteeism rate was reached the first day of reporting or within the next two days in 55% and 31% of schools respectively. The first reports and subsequent peak in school absenteeism provincially preceded the peak in paediatric hospitalization by two and one weeks, respectively. Trends in school surveillance otherwise mirrored other indicators.

Conclusion

During a pandemic, school outbreak surveillance based on a 10% threshold appears insufficient to trigger timely intervention within a given affected school. However, school surveillance appears well-correlated and slightly anticipatory compared to other population indicators. As such, school absenteeism warrants further evaluation as an adjunct surveillance indicator whose overall utility will depend upon specified objectives, and other existing capacity for monitoring and response.     

Characterizing the epidemiology of the 2009 influenza A/H1N1 pandemic in Mexico

Background

Mexico''s local and national authorities initiated an intense public health response during the early stages of the 2009 A/H1N1 pandemic. In this study we analyzed the epidemiological patterns of the pandemic during April–December 2009 in Mexico and evaluated the impact of nonmedical interventions, school cycles, and demographic factors on influenza transmission.

Methods and Findings

We used influenza surveillance data compiled by the Mexican Institute for Social Security, representing 40% of the population, to study patterns in influenza-like illness (ILIs) hospitalizations, deaths, and case-fatality rate by pandemic wave and geographical region. We also estimated the reproduction number (R) on the basis of the growth rate of daily cases, and used a transmission model to evaluate the effectiveness of mitigation strategies initiated during the spring pandemic wave. A total of 117,626 ILI cases were identified during April–December 2009, of which 30.6% were tested for influenza, and 23.3% were positive for the influenza A/H1N1 pandemic virus. A three-wave pandemic profile was identified, with an initial wave in April–May (Mexico City area), a second wave in June–July (southeastern states), and a geographically widespread third wave in August–December. The median age of laboratory confirmed ILI cases was ∼18 years overall and increased to ∼31 years during autumn (p<0.0001). The case-fatality ratio among ILI cases was 1.2% overall, and highest (5.5%) among people over 60 years. The regional R estimates were 1.8–2.1, 1.6–1.9, and 1.2–1.3 for the spring, summer, and fall waves, respectively. We estimate that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a 29%–37% reduction in influenza transmission in spring 2009. In addition, an increase in R was observed in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific fall pandemic waves began 2–5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases.

Conclusions

We documented three spatially heterogeneous waves of the 2009 A/H1N1 pandemic virus in Mexico, which were characterized by a relatively young age distribution of cases. Our study highlights the importance of school cycles on the transmission dynamics of this pandemic influenza strain and suggests that school closure and other mitigation measures could be useful to mitigate future influenza pandemics. Please see later in the article for the Editors'' Summary     

新世纪流感大流行的思考

2009年从墨西哥开始暴发了一场席卷全世界的流感疫情．此次大流行的毒株,甲型H1N1病毒,包含了猪源、禽源和人源流感病毒的基因片段．研究该毒株的基因重配、进化历程及其生物学特性,将对防控此次流行具有重要意义．目前,该毒株的遗传进化关系已明确,通过遗传性状分析可获知该毒株可能的生物学性状,但流感大流行动向、毒株遗传变化、毒力及致病性变化仍在密切监控中．流感病毒生态系统具有复杂性,其基因组易突变、易重配、易在自然宿主保存,使得流感大流行存在一定的必然性．正视流感大流行的威胁,积极提高流感病毒在生态系统中的监控,加强流行病学调查,发展疫苗与药物,建立有效公共卫生保障体系,才能降低流感大流行的破坏性．     

Incidence of avian flu worldwide and in the Russian Federation. Improvement of surveillance and control of influenza during preparation for potential pandemic

Problem of influenza and acute respiratory virus infections (ARVI) remains one of the most urgent medical and socio-economic issues in despite of certain achievements in vaccine and chemoprophylaxis. In Russia influenza and ARVI account for up to 90% of the total annual incidence of infectious disease (up to 30 million of sick people; 45-60% of them are children). Economic damage, caused by influenza and ARVI, makes around 86% of total economic damage, caused by infectious diseases. WHO predicts that in the years coming a new antigenic influenza virus will appear, which can lead to development of large pandemia with 4-5 times increase in disease incidence and 5-10 times increase in death rate. During 2005 some changes in animal influenza epidemiology were registered. New cases of people infections are detected, the virus has spread to some new countries. Avian influenza is a high contagious virus infection that can affect all bird species. For birds influenza is enteral infection, it severely affects parenchymatous organs, especially spleen, and lungs. By now it is known that carriers of avian influenza virus H5N1 can be all known species of wild waterfowl and near-water birds. Poultry is highly susceptible to many stocks of influenza virus H5N1, death rate reaches 100%. At that hens, especially chickens, are most susceptible. From January 2004 to 24th November 2005 in the world there were detected 131 cases of influenza, caused by virus A/H5N1/, 68 of them (51%) ended in lethal outcome (Vietnam--92 cases, Thailand--21 cases, Cambodia--4, Indonesia--11, China--3). Most of the described cases of avian influenza resulted from direct contact with infected birds (handling bird internal organs is especially dangerous). In frozen meat of infected birds the virus can remain for about one year. Heating kills virus (no cases of infection caused by use for food of poultry products were detected). In order to prevent wide ranging spread of infection over Russia it is necessary to organize medical monitoring of sea ships, aircraft and train crews, arriving from the countries where influenza H5N1 cases were detected, in case of need to arrange raids to outlets and markets to detect poultry and poultry products brought from these countries. In Russia it is necessary to prepare a reserve of vaccine strains of viruses--potential causative agent of pandemic, including H5N1 and H7N7, that can start to vaccine reproduction immediately in case of pandemic.     

Age distribution of cases of 2009 (H1N1) pandemic influenza in comparison with seasonal influenza

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 <2 years than the reference group of 5–17 years [OR (95% CI): 0.46 (0.25–0.85) and 0.49 (0.30–0.81), respectively]. In Australia, notifications for laboratory-confirmed influenza were more likely in the age groups of 10–19, 5–9, 20–44, 45–64 and 0–4 years than the reference group of >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 <1, 1–4, 35–49, 5–19, 20–34 and 50–64 years than the reference group 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.