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. Author manuscript; available in PMC: 2011 Nov 15.
Published in final edited form as: Clin Infect Dis. 2010 Nov 15;51(10):1184–1191. doi: 10.1086/656740

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

Joseph T Wu 1, Edward S K Ma 2, Cheuk Kwong Lee 3, Daniel K W Chu 2, Po-Lai Ho 2, Angela L Shen 1, Andrew Ho 1, Ivan FN Hung 4, Steven Riley 1, Lai Ming Ho 1, Che Kit Lin 3, Thomas Tsang 5, Su-Vui Lo 6,7, Yu-Lung Lau 8, Gabriel M Leung 1, Benjamin J Cowling 1,*, J S Malik Peiris 2,9,*
PMCID: PMC3034199  NIHMSID: NIHMS229816  PMID: 20964521

Abstract

Background

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

Methods

Between April and December 2009, we obtained 12,217 serum specimens from blood donors (16–59 yo), 2,520 from hospital outpatients (5–59yo), and 917 from subjects of a community pediatric cohort study (5–14yo). 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 sera 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, intensive care admission, and death.

Results

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

Conclusions

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

Keywords: Influenza, serology, attack rate, case-fatality rate, public health

INTRODUCTION

The 2009 pandemic influenza A/H1N1 (pdmH1N1) virus emerged in Mexico in early 2009 and rapidly spread around the world [1]. By January 2010, most countries had experienced at least one substantial epidemic wave. Vaccines against the novel H1N1 strain became available towards the end of 2009. Timely serologic data are important to facilitate identification of the target groups for whom pandemic vaccine would be most useful prior to subsequent waves, since some population groups may have substantial immunity following the first wave. We conducted a prospective sero-epidemiological study using serial cross-sectional as well as longitudinal cohort data to estimate age-specific pdmH1N1 infection attack rates (IARs) in the community during the first wave of the pandemic. We used our IAR estimates to infer the severity of the pandemic strain, including the age-specific proportion of infections that led to laboratory confirmation, hospitalization, intensive care unit (ICU) admission, and death[25].

METHODS

Subjects

Blood donors, 16–65 yo

Starting from 12 June 2009, blood donors from the four largest blood donation centers (Mongkok, Causeway Bay, Kwun Tong, and Tsuen Wan) of the Hong Kong Red Cross Blood Transfusion Service (BTS) were invited to participate in our serologic surveillance study. Eligible donors were healthy adults aged between 16 and 65 years old, weighing over 41 kg. Repeated participants were identified using their unique BTS identification numbers. A total of 12,217 serum samples collected between 12 June and 31 December 2009 were tested. Pre-(before 1 August 2009) and post-first pandemic wave (after 15 November 2009) paired serum specimens were collected from 324 blood donors. Blood donors do not receive any remuneration or compensation.

Hospital outpatients, 5 to 59 yo

Between 2 September and 31 December 2009, we invited patients visiting the Pediatric and Adolescent Medicine outpatient clinic and the Medicine outpatient clinic at Queen Mary Hospital to participate in our serologic surveillance study. Patients with acute respiratory infections or immunosuppression (including patients on chemotherapy for various malignancy, post-transplant or cirrhotic patients or any patients on systemic immunosuppressants) at recruitment were excluded from participation. A total of 2,520 serum samples collected between 2 September and 31 December 2009 were tested.

Subjects of a community study, 5 to 14yo

Between 1 November 2008 and 31 October 2009, we conducted a cohort study of pediatric seasonal influenza vaccination and household transmission of influenza. 151 children aged 5–14 were recruited and provided baseline sera in November and December 2008. Between September and December 2009 a further 766 children aged 5–14 were recruited and provided baseline sera for the second phase of the study. For the present study we tested the 151 sera collected before the first wave and the 766 sera collected after the first pandemic wave.

Informed consent

Written informed consent was obtained from all participants. Parental consent was obtained for participants aged 15 or younger, and children between the ages of 8 and 15 gave written assent. All study protocols were approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster.

Data on hospitalization, intensive care admission and death

Age-stratified data on virologically confirmed outpatient consultations, hospitalizations, ICU admissions, and deaths associated with pdmH1N1 from 29 April 2009 to 15 November 2009 were provided by the Hong Kong Hospital Authority (the e-flu database)[6]. Since May 2009, patients admitted with acute respiratory illnesses routinely underwent laboratory testing for pdmH1N1 virus by molecular methods. Population size data by age were obtained from the Hong Kong Government Census and Statistics Department.

Laboratory methods

Sera were tested for antibody responses to A/California/4/2009 by viral microneutralization (MN) [7]. Further details of our laboratory methods are provided in the Appendix.

Outcomes

Most individuals infected with influenza develop antibody titers ≥1:40 by viral microneutralization after recovery [8]. We defined the pdmH1N1 seroprevalence rate as the proportion of individuals who had antibody titers ≥1:40. While MN antibody titers of ≥40 are not by themselves conclusive evidence for pdmH1N1 infection in all age groups, we have assumed that the increase in cross-sectional seroprevalence between the pre-and post-first wave time periods are evidence of recent pdmHN1 infection. Seasonal influenza A infection or vaccination is not typically associated with an increase in antibody titers to pdmH1N1 [7, 9], while pdmH1N1 was the predominant circulating strain [10]. In analysis of paired sera, we defined the seroconversion rate as the proportion of individuals with antibody titers of ≤1:10 before the first wave and ≥1:40 after the first wave (i.e. at least a four-fold increase in antibody titer; titers of ≤1:10 were taken as 1:10 in our calculations).

The IAR was defined as the proportion of individuals infected by pdmH1N1 during the first wave. The case-confirmation rate (CCR), case-hospitalization rate (CHR), case-ICU-admission rate (CIR) and case-fatality rate (CFR) were defined as the proportion of pdmH1N1 infections that led to laboratory-confirmation, hospitalization, ICU admission, and death. Due to containment efforts until June 29, 2009 all laboratory-confirmed cases were required to be hospitalized for isolation regardless of disease severity, and therefore only surveillance data from June 30 onwards were used to estimate severity measures.

Statistical methods

We estimated the IAR as the difference between the pre-first-wave and post-first-wave seroprevalence rate. To validate this approach, we compared the IAR estimates with the seroconversion rates in paired-sera available from a subset of 324 blood donors aged 15–59. We used the estimated IAR as the denominator for calculating the CCR, CHR, CIR, and CFR from the e-flu surveillance data. We obtained the posterior distributions of age-specific IARs, CCRs, CHRs, CIRs and CFRs using Monte Carlo Markov Chain methods with non-informative priors for all parameters. Further details of the statistical methods are provided in the Appendix.

RESULTS

Virological surveillance data suggested that the first wave of pdmH1N1 in Hong Kong occurred from August to October and evidence of infection had largely declined by mid-November 2009 (Figure 1). Most of the laboratory-confirmed infections in this first wave occurred in individuals aged below 25 years old accounting for >72% of the lab-confirmed cases and hospitalizations, 32% of ICU admissions and 6% of deaths. Taking into account a delay of 2 to 3 weeks for antibody titers to appear during convalescence [8], we found that these virological surveillance data were consistent with our serial cross-sectional seroprevalence data which indicated a sharp rise in seroprevalence among the 5–25 yo from September to November and a plateau thereafter (Figure 2). This justified our decision to base the pre-and post-first wave seroprevalence estimates on sera collected in June and November-December respectively. Over 90% of pdmH1N1-associated hospitalizations between June 30 and November 15 occurred after August 1. This justified our use of August 1 as the pre-first-wave cutoff date for our paired-sera.

Figure 1.

Figure 1

Epidemiologic surveillance data for the first wave of pdmH1N1 in Hong Kong, 2009.

Figure 2. Age-specific proportions of individuals with antibody titers ≥1:40 by viral microneutralization between June 2009 and January 2010.

Figure 2

Each data point corresponds to an average over multiple days, and vertical bars indicate 95% confidence intervals estimated by the exact binomial method. Data points with sample size <10 are not shown. All subjects (151 aged 5–14) in the pediatric cohort study had antibody titers <1:40 by viral microneutralization in April 2009 (not shown).

Among individuals aged 5–14 years, the seroprevalence rates were similar across time between pediatric outpatient subjects and pediatric cohort study subjects (Figure 2). Similarly, for older age groups, the seroprevalence rates were largely similar between blood donor subjects and hospital outpatient subjects (except for the 20–29 yo in November-December). This provided some evidence that despite potential biases in our convenience sampling scheme, the resulting serologic data provided a reasonably representative description of seroprevalence in the community.

Prior to the first pandemic wave (June 2009), seroprevalence was uniformly low among the 5–59 yo but increased substantially in younger age groups during the first wave (Table 1 and Figure 2). Comparing the pre-and post-first-wave seroprevalence rate (i.e. the serial cross-sectional method), we estimated the IAR was 43.4% among 5–14 yo, 15.8% among 15–19 yo, 11.8% among 20–29 yo, 4.3% among 30–39 yo, 4.6% among 40–49 yo, and 4.0% among 50–59 yo (Table 1). These IAR estimates were broadly consistent with the IARs estimated from seroconversion rates in paired-serology of blood donor samples (see Appendix). Overall, we estimated a population-weighted IAR of 10.7% (9%–12%) among individuals aged 5–59 years through the first wave in Hong Kong.

Table 1.

Estimated proportion of the population with antibody titers ≥1:40 by viral microneutralization against pdmH1N1 before and after the first wave, and the estimated infection attack rate using the serial cross-sectional method.

Age Groups Before the first wave After the first wave Infection attack rate Posterior mode (95% credible interval)
No. positive/No. specimens % +ve (95% CI) Source No. positive/No. specimens % +ve (95% CI) Source

5–14 0/151 0.0% (0.0%–2.4%) [1] 183/422 43.4% (38.6%–48.2%) [3] 43.4% (37.9,%–47.6%)
15–19 3/97 3.1% (0.6%–8.8%) [2] 34/180 18.9% (13.5%–25.4%) [4] 15.8% (8.2%–22.1%)
20–29 12/336 3.6% (1.9%–6.2%) [2] 135/879 15.4% (13.0%–17.9%) [4] 11.8% (8.4%–14.7%)
30–39 17/302 5.6% (3.3%–8.9%) [2] 67/676 9.9% (7.8%–12.4%) [4] 4.3% (0.9%–7.5%)
40–49 10/238 4.2% (2.0%–7.6%) [2] 45/509 8.8% (6.5%–11.7%) [4] 4.6% (1.0%–7.9%)
50–59 6/352 1.7% (0.6%–3.7%) [2] 14/247 5.7% (3.1%–9.3%) [4] 4.0% (1.1%–7.5%)

Overall 5–59 3.3% (2.8%–4.7%) 14% (13.0%–15.4%) 10.7% (9.0%–12.0%)

Sources of specimens:

[1]

Pediatric cohort study (2–29 April 2009)

[2]

Hong Kong Red Cross Blood Transfusion Service (15–22 June 2009)

[3]

Pediatric cohort study (6 November to 19 December 2009)

[4]

Hong Kong Red Cross Blood Transfusion Service (1 November to 6 December 2009)

A total of 23,643 laboratory-confirmed H1N1 cases aged 5–59 were reported between 29 April and 15 November 2009. Before 30 June, 567 of the 849 laboratory-confirmed cases (67%) were isolated in hospitals as part of containment phase measures. These data were excluded from our analysis for severity estimates. From June 30 onwards, hospital admission was based on medical need, and 4,253 of the 22,794 lab-confirmed H1N1 cases (19%)aged 5–59 were admitted to hospitals between June 30 and November 15. There were 103 ICU admissions and 26 deaths among lab-confirmed pdmH1N1 cases aged 5–59. Based on our estimated IAR of 10.7% among the 5–59 yo (equivalent to 597,000 infections in Hong Kong), we estimated that around 3.9% (3.5%–6.2%)of infections were reported and lab-confirmed and around 0.73%(0.66%–1.22%)of infected individuals required hospitalization (Table 2). The rate of ICU admissions and deaths were around 17.6 (13.3–50.1) and 4.4 (3.2–17) per 100,000 infections (Table 2).

Table 2. Estimated age-specific proportions of individuals with pdmH1N1 infections that were laboratory-confirmed, were hospitalized, were admitted to ICU, and died.

Case-ICU and case-fatality rates are expressed as number of episodes per 100,000 infections.

Age group Case-confirmation (%) Case-hospitalization (%) Case-ICU (per 100,000 infections) Case-fatality (per 100,000 infections)
Counts (% of all) Posterior mode (95% cred. int.) Counts (% of all) Posterior mode (95% cred. int.) Counts (% of all) Posterior mode (95% cred. int.) Counts (% of all) Posterior mode (95% cred. int.)

5–14 10060 (44.1%) 4.0% (3.6%–4.6%) 2133 (50.2%) 0.84% (0.76%–0.97%) 20 (19.4%) 7.9 (5.2–12.6) 1 (3.8%) 0.4 (0.1–2.3)
15–19 3673 (16.1%) 5.4% (3.9%–10.5%) 522 (12.3%) 0.77% (0.53%–1.50%) 9 (8.7%) 13.3 (7.0–34.4) 2 (7.7%) 3 (0.9–13.2)
20–29 4314 (18.9%) 3.8% (3.0%–5.3%) 532 (12.5%) 0.47% (0.37%–0.66%) 7 (6.8%) 6.1 (3.0–13.9) 1 (3.8%) 0.9 (0.2–5.2)
30–39 1868 (8.2%) 4.0% (2.2%–18.2%) 378 (8.9%) 0.80% (0.45%–3.66%) 12 (11.7%) 25.4 (10.7–130.5) 4 (15.4%) 8.5 (3.2–53.1)
40–49 1615 (7.1%) 2.8% (1.6%–12.5%) 293 (6.9%) 0.51% (0.30%–2.26%) 21 (20.4%) 36.4 (18.8–171.5) 6 (23.1%) 10.4 (4.4–57.2)
50–59 1264 (5.5%) 2.8% (1.4%–10.1%) 395 (9.3%) 0.87% (0.45%–3.16%) 34 (33.0%) 75 (32.7–281.3) 12 (46.2%) 26.5 (10.4–108.9)

Overall 5–59 22794 (100.0%) 3.9% (3.5%–6.2%) 4253 (100.0%) 0.73% (0.66%–1.22%) 103 (100.0%) 17.6 (13.3–50.1) 26 (100.0%) 4.4 (3.2–17)

Case-hospitalization rates (CHR) were around 0.47%–0.87%among the 50–59 yo (Table 2 and Figure 3). Rates of pdmH1N1-associated ICU admission (CIR) increased from 7.9 (5.2–12.6) per 100,000 infections in 5–14 yo to 75 (32.7–281) per 100,000 infections in 50–59 yo. Rates of pdmH1N1-associated mortality(CFR) followed a similar trend with 0.4 (0.1–2.3) death per 100,000 infections in 5–14 yo to 26.5 (10.4–109) deaths per 100,000 infections in 50–59 yo. Compared to children aged 5–14, adults aged 50–59 were 9.5 and 66 times more likely to be admitted to ICU and die if infected.

Figure 3. Age-specific infection attack rates and severity measures of pdmH1N1 in Hong Kong.

Figure 3

A Pre-and post-first-wave seroprevalence rates and infection attack rates based on the serial cross-sectional approach. B The proportions of infections leading to laboratory-confirmation, hospitalization, ICU-admission, and fatality. The points and vertical bars indicate posterior modes and 95% credible intervals based on the fitted model.

DISCUSSION

We estimated that during the first wave in Hong Kong, 43.4% of school-age children and 10.7% of individuals aged 5–59 were infected by pdmH1N1. A serologic survey in England found similar IARs in London and the West Midlands [8]. Both studies highlight the importance of including serologic surveys as a component of pandemic surveillance. While our core results are based on data from serial cross-sectional samples, we found similar infection attack rates inferred from participants for whom paired sera were available. The geographically compact and homogeneously mixing population in the urban environment of Hong Kong permits some degree of confidence in the validity of our infection attack rate and severity estimates. The detailed pdmH1N1 reporting system, the wide coverage of the public healthcare system (which includes >90% of all local inpatient days [11]), and the resource investments since SARS have led to routine laboratory testing for all patients hospitalized with fever or pneumonia. This should allow identification of the majority of hospitalizations, ICU admissions and deaths directly associated with pdmH1N1 infection. Thus the completeness of the pdmH1N1 surveillance system, well-defined population denominator and our large-scale serologic survey provide accurate numerators and denominators for the severity measures.

We based severity estimates for pdmH1N1 on the infection attack rate as the denominator. Some previous studies of pdmH1N1 severity used clinical illness attack rate as the denominator which depends on the probability of symptoms as well as medical care seeking behavior of the population [3, 12]. Our estimated CIRs and CFRs are broadly consistent with Presanis et al’s “Approach 2” severity estimates but around 7–9 times lower than their “Approach 1” estimates [3]. Our estimates of CHR are 2–10 times higher than their Approach 2 estimates of symptomatic CHR. However, the hospitalization-death ratio was 4,253/27 = 164 as of November 15 in Hong Kong but 996/53 = 19 as of June 14 in New York [3], implying that the clinical threshold for admission in terms of disease severity at presentation may have been lower in Hong Kong.

We estimated that around 0.4 in 100,000 infections in school-age children led to mortality, while the risk of ICU admission and death per infection was 9.5 and 66 times higher in older adults aged 50–59 (Figure 3). These estimates for mortality rates in children are consistent with data from the UK, where one study estimated a mortality rate of 11 per 100,000 symptomatic cases in children aged 5–14 [12], while a serologic study suggested that the attack rates had been underestimated by a factor of 10 [8]. Our estimates are lower than early estimates of the case fatality rate but the denominators may not have been well estimated in those studies [1, 13, 14]. Previously a statistical model was used to estimate that the excess number of deaths due to seasonal influenza in Hong Kong was 11.8 (3.8–20.1) per 100,000 population for those aged 40–64 [15]. Assuming an annual infection attack rate of 20%, this estimate would translate into 44(14–81) per 100,000 infections which is similar to our pdmH1N1 CFR estimate of 18(9–74) per 100,000 infections for the 40–59 yo. This supports the prevailing view that pdmH1N1 is not more severe than seasonal influenza in terms of morbidity and mortality.

Simulation studies have suggested that administering pandemic vaccines to school-age children provides substantial benefits to the community [16, 17]. However since 43.4% of school-age children were infected in the first wave and likely immune to reinfection, and infections in school-age children are rarely severe (Table 2), there may be less justification to include this age group as a target group for vaccination after the first wave of the pandemic in Hong Kong. Furthermore, given the substantial attack rate in children in the first wave, we speculate that a large second wave may be unlikely to occur unless there is substantial antigenic drift. So far there has been no evidence for the emergence of antigenically-drifted pdmH1N1 viruses [18].

Our study has a number of limitations. First, we have used antibody titers of ≥1:40 by viral microneutralization as an indicator of recent infection, correcting for baseline (pre-existing) seroprevalence levels, but this may lead to underestimation of the IAR if not all infections led to antibody titers ≥1:40, or if some individuals with baseline titers ≥1:40 were infected. Another study found that around 5% of laboratory-confirmed H1N1 cases did not develop convalescent antibody titers above 1:40 by hemagglutinin inhibition tests [8]. Second, our estimates of the IAR would be biased upwards if infection with other circulating influenza viruses led to cross-reactive antibody responses resulting in antibody titers ≥1:40. However between August and October 2009, 83% of influenza A viruses detected in Hong Kong were pdmH1N1 and only 3% of isolated viruses were seasonal H1N1 viruses which are more likely to be associated with cross-serological cross reactions with pdmH1N1 (appendix) [10]. Third, a minority of severe illnesses associated with pdmH1N1 infection might not be identified by molecular detection methods, for example if admission occurred after cessation of viral shedding associated with the primary infection, and thus we may have underestimated the pandemic disease burden. We did not have sero-epidemiology data from those older than 60 years of age and consequently cannot comment on attack rates or complication rates in this important age group. Finally, our analyses are primarily based on seroprevalence among blood donors to the Hong Kong Red Cross, who may not be representative of the whole population. We do not have detailed data on donors to compare their risk of infection with the general population, but we did observe very similar seroprevalence rates across the three groups of subjects in our study, i.e. blood donors, hospital outpatients and participants in a community cohort (Figure 2 and Appendix Figure 2).

We chose to use microneutralization tests rather than hemagglutination inhibition tests following preliminary studies which showed that microneutralization was more sensitive than hemagglutination inhibition for detection of antibody responses in pdmH1N1 infection [7, 8]. There is only limited cross reactivity between pandemic and recent seasonal H1N1 viruses by the microneutralization test (used in this study) but there is some cross-reaction in individuals, increasing with age and particularly noticeable in those over 65 years of age[8, 9]. Thus in a given individual, current serological methods do not conclusively distinguish between antibody resulting from pdmH1N infection from cross-reactive antibody arising from prior infections with seasonal H1N1 influenza, especially in those over 60 years of age, which is one reason why we did not address the infection rates or disease severity in the elderly. Our study design is based on the difference in age-stratified seroprevalence in the pre vs post first-wave period, a time-period when there was minimal seasonal H1N1 virus circulation in Hong Kong. Thus, our conclusions for individuals <60 years of age are unlikely to be confounded by issues pertaining to serological cross-reactivity. While immune-senescence could potentially lead to an underestimation of attack rates in the elderly, especially those over >65 yo, this is unlikely to affect our study which investigates those younger than 60 years.

In conclusion, around 10.7% of the population aged 5–59 and half of all school-age children in Hong Kong were infected during the first wave of pandemic H1N1. Compared to school-children aged 5–14, older adults aged 50–59, though less likely to acquire infection, had 9.5 and 66 times higher risk of ICU-admission and death if infected. Thus the apparently low morbidity and mortality burden of 2009 pandemic influenza (H1N1), despite an infection attack rate in the first wave similar to a seasonal epidemic, appears to be due to low infection rates in older adults who faced a much greater risk of severe illness if infected. The reasons why older adults appear relatively resistant to pdmH1N1 infection even though they appear to lack neutralizing antibody remains unclear. If antigenic drift or other adaptation of the pdmH1N1 virus allows these older age groups to be infected more efficiently, the morbidity and mortality of subsequent waves of the pandemic could yet become substantial.

Supplementary Material

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Acknowledgments

We thank Edward Choi, Horace Choi, Vicky Fang, Roy Lau, William Lau, Winnie Lau, Anita Li, Joyce Mak, Loretta Mak, and Diane Ng for research support. We thank Chung-Hei Chan, Maying Tse, D Heenella Nawasinghage for laboratory support. We acknowledge the Hospital Authority Strategy & Planning Division, Quality & Safety Division, and Information Technology Division, and the Center for Health Protection for the collation of the e-flu database.

This project was supported by the Research Fund for the Control of Infectious Disease, Food and Health Bureau, Government of the Hong Kong SAR (grant nos. PHE-20 and PHE-2), the Area of Excellence Scheme of the Hong Kong University Grants Committee (grant no. AoE/M-12/06), the Harvard Center for Communicable Disease Dynamics from the US National Institutes of Health Models of Infectious Disease Agent Study program (grant number 1 U54 GM088558) EMPERIE (EU FP7 grant 223498) the National Institute of Allergy and Infectious Diseases, National Institutes of Health (Contract No. HHSN266200700005C; ADB No. N01-AI-70005). The funding bodies had no role in study design, data collection and analysis, preparation of the manuscript, or the decision to publish.

BJC reports receiving research funding from Med Immune Inc., a manufacturer of influenza vaccines.

Footnotes

Brief summary: Almost half of all school-age children in Hong Kong were infected during the first wave of 2009 pandemic (H1N1). Case-fatality rates increased from 0.4 per 100,000 infections in individuals aged 5–14 to 26.5 per 100,000 infections in individuals aged 50–59.

The authors report no other conflicts of interest.

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