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Version 2. PLoS Curr. 2009 Oct 1 [revised 2009 Oct 5];1:RRN1047.

The shifting demographic landscape of influenza.

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  • 1Center for Infectious Disease Dynamics, Penn State University; Division of Mathematical Modeling, British Columbia Centre for Disease Control; Weill Cornell Medical College (NYC) and Preparedness Modeling Unit, U.S. Centers for Disease Control and Prevention (CDC, Atlanta); Princeton University and The University of Texas at Austin.



As Pandemic (H1N1) 2009 influenza spreads around the globe, it strikes school-age children more often than adults. Although there is some evidence of pre-existing immunity among older adults, this alone may not explain the significant gap in age-specific infection rates.


Based on a retrospective analysis of pandemic strains of influenza from the last century, we show that school-age children typically experience the highest attack rates in primarily naive populations, with the burden shifting to adults during the subsequent season. Using a parsimonious network-based mathematical model which incorporates the changing distribution of contacts in the susceptible population, we demonstrate that new pandemic strains of influenza are expected to shift the epidemiological landscape in exactly this way.


Our results provide a simple demographic explanation for the age bias observed for H1N1/09 attack rates, and a prediction that this bias will shift in coming months. These results also have significant implications for the allocation of public health resources including vaccine distribution policies.

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Figure 3 Attack rates among adults and children during influenza pandemics and subsequent seasons: Multiple bars for a single strain represent data from different populations. Data are from a: [57], b: [56],c: [63], d: [64], e: [65], f: [66], g: [67], h: [68], i: [69], j: [70], k: [71], l: [32]. Numbers above bars represent odds ratios. While there are consistent qualitative patterns, the estimates are based on diverse data and methodologies and thus should not be compared quantitatively across studies. The 1968 Hong Kong H3N2 pandemic is the only one of the four strains that does not appear to have an initial bias towards children, which may be influenced by cross immunity from prior H2N2 infections as the two viruses shared nearly identical neuraminidase molecules [72]. Data for H1N1/09 is reported as number of confirmed cases as a proportion of age group size in the respective country.
Figure 4 Individual risk of influenza infection during two sequential outbreaks: (A) During the initial pandemic season, we notice a shift in the attack rate (the number of new cases during a week in an age group divided by the size of the age group). The attack rate among children is initially higher than the attack rate among adults, but this reverses after the epidemic peak. (B) During the initial pandemic, all individuals are susceptible, and risk of infection (defined in Methods) increases with number of contacts (dashed brown line, and right y-axis). During a subsequent outbreak the epidemiological risk landscape shifts towards moderately connected individuals, depending on the the level of immunity (green lines, and left y-axis) for  T1 = 0:09 (R0 = 1:6) and T2 = 0:15 (Re = 1:05; 1:16). (C) The degree distributions for school-age children (mean degree of 21.5) and adults (mean degree of 16.1) in our urban population network model. The bimodal adult degree distribution reflects heterogeneities in adult employment status.
Figure 5 Comparison of vaccination policies: (A) The impact of school-aged and adult vaccination priorities at 15% vaccine coverage in a naive (``Season 1”) and partially immune population (``Season 2”) population at alpha = 0.05 (B) The impact of these policies assuming pre-existing resistance among adults (9%) and elderly (33%) acquired through exposure to a strain of the same subtype prior to 1956. The first season pathogen has a reproductive ratio of R_0 = 1.6 and the second season pathogen has an effective reproductive ratio of R_e = 1.005
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