Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Feb 26;5(2):e9360.
doi: 10.1371/journal.pone.0009360.

The shifting demographic landscape of pandemic influenza

Affiliations

The shifting demographic landscape of pandemic influenza

Shweta Bansal et al. PLoS One. .

Abstract

Background: 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.

Methods and findings: 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.

Conclusions: Our analysis provides a simple demographic explanation for the age bias observed for H1N1/09 attack rates, and suggests that this bias may shift in coming months. These results have significant implications for the allocation of public health resources for H1N1/09 and future influenza pandemics.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Estimated age-specific contact rates in an urban population.
We compare six estimates for the mean degree by age of individuals (left panel) and the mean degree across the population (right panel). Meyers et al. and Eubank et al. are model-based estimates in which survey, census and other data were used to construct detailed computer simulations of contact patterns in Vancouver, BC and Portland, OR, respectively. The remaining four sets of estimates , , , are inferred from responses to survey questions about the frequencies of (a) two-way conversations lasting three or more words in the physical presence of another individual, and (b) a physical contacts which involve skin-to-skin contact. The Wallinga study includes only conversational contacts, while the Mossong, Read and Beutels studies include both contact types. The Read and Beutels studies only include adults. Our model (based on [9]) measures contacts during an average infectious period, while the remaining studies measure daily contacts.
Figure 2
Figure 2. Changing immunological structure of a population throughout an influenza pandemic.
Lines in these network diagrams indicate contacts through which influenza can spread. Prior to the introduction of a novel pandemic strain, most of the population is susceptible. The pandemic initially sweeps through the most connected portions of the populations, including groups of school-age children, leaving a wake of temporarily immunized individuals. The remaining susceptible population will consist of less connected portions of the population.
Figure 3
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: , b: , c: , d: , e: , f: , g: , h: , i: , j: , k: , l: . 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 neuriminidase molecules . Data for H1N1/09 is reported as number of confirmed cases as a proportion of age group size in the respective country.
Figure 4
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 formula image and formula image. (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
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 formula image (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 formula image and the second season pathogen has an effective reproductive ratio of formula image.

Update of

Similar articles

Cited by

References

    1. Chan M. Influenza A(H1N1): lessons learned and preparedness. 2009
    1. Centers for Disease Control and Prevention. 2009. CDC Estimates of 2009 H1N1 Influenza Cases, Hospitalizations and Deaths in the United States : Accessed Feb 5, 2010.
    1. Greenberg M, Lai M, Hartel G, Wichems C, Gittleson C. Response to a Monovalent 2009 Influenza A (H1N1) Vaccine. NEJM. 2009;361(25) - PubMed
    1. Garcia-Garcia L, Valdespino-Gomez J, Lazcano-Ponce E, Jimenez-Corona A, Higuera-Iglesias A. Partial protection of seasonal trivalent inactivated vaccine against novel pandemic influenza A/H1N1 2009: case-control study in Mexico City. BMJ. 2009;339:3928. - PMC - PubMed
    1. Centers for Disease Control and Prevention. Serum Cross-Reactive Antibody Response to a Novel Influenza A (H1N1) Virus After Vaccination with Seasonal Influenza Vaccine. Morb Mortal Wkly Rep. 2009;58:521–524. - PubMed

Publication types

MeSH terms

Substances