Searching for Sharp Drops in the Incidence of Pandemic
A/H1N1 Influenza by Single Year of Age
Jessica Hartman Jacobs1*, Brett Nicholas Archer2, Michael G. Baker3, Benjamin J. Cowling4,
Richard T. Heffernan5, Geoff Mercer6, Osvaldo Uez7, Wanna Hanshaoworakul8, Cécile Viboud9,
Joel Schwartz1,10, Eric Tchetgen Tchetgen1,11, Marc Lipsitch1,12
1 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, 2 National Institute for Communicable Diseases,
National Health Laboratory Service, Johannesburg, South Africa, 3 Department of Public Health, University of Otago, Wellington, New Zealand, 4 School of Public Health,
The University of Hong Kong, Hong Kong Special Administrative Region, China, 5 Division of Public Health, Wisconsin Department of Health Services, Madison, Wisconsin,
United States of America, 6 National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia, 7 National Institute of
Epidemiology, ANLIS, Ministry of Public Health, Buenos Aires, Argentina, 8 Department of Disease Control, Ministry of Public Health, Tiwanond, Nonthaburi, Thailand,
9 Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America,
10 Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, United States of America, 11 Department of Biostatistics, Harvard School
of Public Health, Boston, Massachusetts, United States of America, 12 Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston,
Massachusetts, United States of America
Abstract
Background: During the 2009 H1N1 pandemic (pH1N1), morbidity and mortality sparing was observed among the elderly
population; it was hypothesized that this age group benefited from immunity to pH1N1 due to cross-reactive antibodies
generated from prior infection with antigenically similar influenza viruses. Evidence from serologic studies and genetic
similarities between pH1N1 and historical influenza viruses suggest that the incidence of pH1N1 cases should drop
markedly in age cohorts born prior to the disappearance of H1N1 in 1957, namely those at least 52–53 years old in 2009,
but the precise range of ages affected has not been delineated.
Methods and Findings: To test for any age-associated discontinuities in pH1N1 incidence, we aggregated laboratoryconfirmed pH1N1 case data from 8 jurisdictions in 7 countries, stratified by single year of age, sex (when available), and
hospitalization status. Using single year of age population denominators, we generated smoothed curves of the weighted
risk ratio of pH1N1 incidence, and looked for sharp drops at varying age bandwidths, defined as a significantly negative
second derivative. Analyses stratified by hospitalization status and sex were used to test alternative explanations for
observed discontinuities. We found that the risk of laboratory-confirmed infection with pH1N1 declines with age, but that
there was a statistically significant leveling off or increase in risk from about 45 to 50 years of age, after which a sharp drop
in risk occurs until the late fifties. This trend was more pronounced in hospitalized cases and in women and was
independent of the choice in smoothing parameters. The age range at which the decline in risk accelerates corresponds to
the cohort born between 1951–1959 (hospitalized) and 1953–1960 (not hospitalized).
Conclusions: The reduced incidence of pH1N1 disease in older individuals shows a detailed age-specific pattern consistent
with protection conferred by exposure to influenza A/H1N1 viruses circulating before 1957.
Citation: Jacobs JH, Archer BN, Baker MG, Cowling BJ, Heffernan RT, et al. (2012) Searching for Sharp Drops in the Incidence of Pandemic A/H1N1 Influenza by
Single Year of Age. PLoS ONE 7(8): e42328. doi:10.1371/journal.pone.0042328
Editor: Patrick Tang, University of British Columbia, Canada
Received March 29, 2012; Accepted July 4, 2012; Published August 2, 2012
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for
any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: The project described was supported by the National Institute Of General Medical Sciences [Award Number U54GM088558], http://www.nigms.nih.
gov/. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute Of General Medical
Sciences or the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
manuscript.
Competing Interests: BJC has received research funding from MedImmune Inc. and consults for Crucell MV. ML declares consulting income/honoraria from
Pfizer, Novartis, Avian/Pandemic Flu Registry (Outcome Sciences, supported by Roche), and AIR Worldwide. The following co-authors are editors: Benjamin J
Cowling and Cecile Viboud. This does not alter the authors‘ adherence to all the PLoS ONE policies on sharing data and materials.
* E-mail: jhartman44@gmail.com
influenza epidemics [3,4,5,6]. During seasonal influenza epidemics, an estimated 90% of influenza-associated deaths occur among
people aged .65 years [7]. In contrast, the global experience
during the early months of the 2009 pandemic was a median age
of 37 years in confirmed fatal cases (n = 343 cases) with the
majority occurring in individuals aged 20–49 years [6]. Surveillance for hospitalized and laboratory confirmed pH1N1 cases also
Introduction
th
Consistent with earlier pandemics of the 20 century [1,2],
surveillance reports of hospitalized cases, laboratory confirmed
cases, and mortality due to the first wave of novel 2009 pandemic
influenza A/H1N1 (pH1N1) virus infection suggest a markedly
younger age distribution than typically observed during seasonal
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Pandemic A/H1N1 Influenza Incidence
isolates were considered probable pH1N1 infections. In New York
City, 67/996 (7%) of cases were designated as probable, defined as
confirmed influenza A and negative for seasonal subtypes but
lacking confirmatory pH1N1 testing [12]. Argentina, Hong Kong
and Wisconsin further reported cases by sex. The case data used in
this study from Argentina, Hong Kong, and Wisconsin are
included as an online supplement (Table S1). The hospitalization
status was unknown for South Africa and these data were not
included in the weighted incidence risk ratios but are reported
separately.
Collaborators in several locations additionally provided estimates of the 2009 population by single year of age. The
populations of South Africa [13] and Thailand were available in
5 year age groups, so we applied the Sprague Multiplier to
interpolate to population size for single year of age [14]. The 2010
census population of Argentina by single year of age and sex was
obtained from the National Institute of Statistics and Censuses
[15].
showed the inverse pattern of seasonal influenza, with the youngest
age groups dominating incidence estimates and case counts. Only
five percent of the first 272 patients hospitalized in the United
States from pH1N1 were aged .65 years [4]. In a comparison of
confirmed cases of pH1N1 from 10 countries on five continents
the age distribution was consistent between countries and the
largest source of variability was between continents [5]. About
75% of these cases occurred in persons aged ,30 years with a
small peak in ages 10–19 years; less than 3% of cases occurred in
the elderly ($65 years) [5].
The global surveillance data suggest that being an older adult is
protective against pH1N1 infection and hospitalization. The risk
of pH1N1-associated death among the elderly who were
hospitalized was slightly elevated compared to younger age groups
but the overall risk of death was much less so than in seasonal
influenza [8]. The reduced risk of pH1N1-associated disease in the
elderly population is likely the result of some level of immunity
provided by cross-reactive antibodies generated from prior
vaccination or infection with antigenically similar influenza A
viruses [9]. Combined with genetic and antigenic studies
demonstrating the similarities between pH1N1 and the descendants of the 1918 virus, the incidence of pH1N1 cases should drop
markedly in adults born prior to versus after the disappearance of
H1N1 in 1957, namely those at least 52–53 years old in 2009
[9,10,11].
To date, all published incidence data have used large age
categories due to the small numbers of confirmed cases in each
country or region. In order to evaluate whether sharp drops
associated with the protective effects of earlier exposure do indeed
exist, incidence should be compared across single-year age groups.
To test for any age associated discontinuities in the incidence of
laboratory-confirmed pH1N1 we analyzed data from 8 jurisdictions in 7 countries, stratified by single year of age, sex, and
hospitalization status. We quantified sharp drops in incidence by
looking for statistically significant negative second derivatives in
the incidence risk with respect to age.
Calculation of a Weighted Incidence Risk Ratio
We generated incidence risk ratios (RR) for each single year of
age, hospitalization status, and location, dividing the incidence risk
for each age group by the total for all age groups in that location
and hospitalization status to normalize for differences in reporting.
Thus the RR represents the risk of being a pH1N1 case for a
person of a specific age relative to the overall risk in all ages
combined. The variable sampling periods between locations and
difficulty in defining person time at risk for an infectious disease
where the true disease incidence is unknown required the use of
cumulative incidence instead of an incidence rate calculation. The
RR was defined as follows for each hospitalization status (H = h for
1 = hospitalized cases and 2 = not hospitalized), age (I = i from 0
to $100 years old) and location (L = l for the 7 locations exclusive
of South Africa). The risk (rh|i,l) for each h given age = i and
location = l was calculated using all confirmed cases (xi,h,l) of each
age in a location and hospitalization status divided by the
population for that age and location, as in equation (1). Similarly,
an all age risk (Rh|l) was calculated for each location and
hospitalization status by summing the cases over all ages and
dividing by the total population in that location. The RR for each
age, hospitalization status and location (RRi,h|l) was then calculated
by dividing (rh|i,l) by (Rh|l), as demonstrated in equation (1).
Methods
Data Sources
We obtained counts of laboratory confirmed cases of pH1N1
infection by single year of age and hospitalization status from
Argentina, Australia (Queensland), Hong Kong, New Zealand,
South Africa, Thailand, and the United States (Wisconsin and
New York City). All locations used a real time reverse transcription
polymerase chain reaction (RT-PCR) test to confirm cases of
pH1N1. The data were collected as part of routine surveillance for
pH1N1 conducted by the Ministries/Departments of Health in
each location, and were reported to us anonymously as aggregated
data covering many months (length of time varied by location).
Since the investigators of this study had no interaction with
patients and received no identifiable private information as part of
this study, we were not required to obtain ethics approval or
individual patient consent by the Harvard School of Public Health
institutional review board under the United States Department of
Health and Human Services’ regulations on human subjects.
These cases were reported in the first complete wave of the
pandemic for each location, under different testing protocols and
levels of surveillance, and subject to differing biases, yet were
analyzed together to have large cohorts within each age to identify
discontinuities. In Wisconsin, RT-PCR confirmed influenza A
cases that were not subtyped were included for the period June 1
to June 13, 2009, when testing confirmed that over 99.5% of
subtyped viruses were pH1N1; these unsubtyped influenza A
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xi,h,l
Prfcase, H~hDI~i,L~l g rhDi,l Populationi,l
~
~ xh,l
RRi,hDl ~
Prfcase, H~hDL~l g
RhDl
ð1Þ
Populationl
A weighted risk ratio (WRR) was then calculated for each age
and hospitalization status where location specific RRs were
weighted relative to their contribution to the total number of
hospitalized or not hospitalized cases. The weights were comparable to an inverse variance weighting, where locations contributing higher case counts were more heavily weighted than those
with smaller counts. The weights (wh,l) were calculated as follows in
equation (2), using the previously described nomenclature:
P
xi,h,l
xh,l
i
wh,l ~
~P
xi,h,l
xh
ð2Þ
The final product was the weighted risk ratio (WRRi,h) for each
age and hospitalization status, calculated as follows in equation (3):
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Pandemic A/H1N1 Influenza Incidence
WRRi,h ~
X
RRi,h,l |wh,l
highest among children aged 2 years and younger in all
locations but Thailand, where it peaked at age 5 (Table 2 and
Figure 1A). The magnitude of the age-specific relative risks
between locations is not solely due to differences in disease
burden but likely also reflects differences in surveillance (active
versus passive), criteria for hospitalization, and changing
protocols and recommendations as the pandemic wave progressed. Of greater interest than the absolute difference between
locations for a given age is the risk relative to other ages within
a place and whether the trend of RRs by age persists regardless
of geography.
The decline in risk from infancy towards adulthood plateaus
around the early thirties and the risk begins to increase from
45 years of age to the early fifties (Figures 1B and 1C). This
increase in the overall trend is consistent through all locations –
with an additional relative maximum in the early to mid
twenties occurring in several locations as well. The risk peaks
again at 53 years of age and then begins to decline rapidly, with
the rate of decline accelerating until 60 years of age (Figure 1D).
These features persist throughout varying bandwidths, whether
the effective sample size of neighbors included is 5.25 years
(b = 2.1, the lowest bandwidth where there is enough data to
create a smoothed curve) or 25 years (b = 10, the highest
bandwidth we explored on the SiZer plot). The WRR smoothed
with a bandwidth of 4 gave the visually optimal fit in terms of
capturing most data points while removing the less interesting
noise. The second derivative of the smoothed WRR suggests
that there is a statistically significant drop in the slope of the
WRR (in fact, switching from positive slope to negative slope) in
individuals between the ages of 50 to 58 years (born between
1951 and 1959).
ð3Þ
l
Since cases were stratified by sex in Argentina, Hong Kong, and
Wisconsin, we also created WRRi,h by sex for these locations.
Wisconsin had a small number of hospitalized cases and was only
included in the WRRi calculation for cases that were not
hospitalized. In addition, we compared the cumulative incidence
of being a male versus female among ,18, 18–64, and .64 year
olds cases that were and were not hospitalized. These subanalyses
allowed us to explore possible alternative mechanisms for any
significant changes in incidence by age, including gender related
exposure to pH1N1 or biological differences between the sexes in
immunologic response to pH1N1.
Graphical and Statistical Analysis of the Weighted Risk
Ratios
To detect sharp drops in incidence by age, we searched for
statistically significant, negative second derivatives in the smoothed
WRR, with respect to time, reasoning that these would correspond
to departures from underlying linear incidence trends with age.
Using the SiZer package version 0.1–4.0 [16] in the statistical
software R [17], we examined the first (1D) and second derivatives
(2D) of the smoothed WRR as a function of age. SiZer is a tool for
quantitatively identifying whether features of a data series rise
above the level of noise. It is different from traditional approaches
of smoothing and statistical inference because SiZer removes the
bias inherent in selecting a bandwidth and allows an inspection at
a wide range of smoothing bandwidths to see which features are
insensitive to bandwidth selection and likely to be true features
[18]. Small bandwidths can result in undersmoothing with large
variances but low bias, as only the local data points are used to
estimate the smoothed curve. In contrast, a large bandwidth
oversmooths the data points and results in low variance but large
bias, since many local data points are used which might not
represent the local phenomenon. A true feature in a data series will
persist across bandwidths.
The smoothing method employed in SiZer is a locally weighted
polynomial regression (LWPR) using a Gaussian kernel at
bandwidths (b) that vary per the user’s specifications. We allowed
b to vary from 1.5 to 10 years and chose a second degree
polynomial to be fit to the WRRi,h at each age. We specified that
the values of the LWPR smoothed WRRi,h be evaluated at each
integer of age (0–100 years). SiZer looks across a range of b and
classifies the 1D and 2D as significantly positive, possibly zero or
significantly negative. The choice of b determines how many
neighbors are used to generate the LWPR. In our range of
bandwidths, the effective sample size varies from 4 to 25 years. At
b = 4, the effective sample size is 10 and is similar to smoothing
over a decade of age. We also plotted the smoothed WRRi,h and
the 1D and 2D using a fixed b of 1, 2, and 4 with a polynomial of
degree 2.
Cases that were not Hospitalized
Six locations contributed to the count of confirmed pH1N1
cases that were not hospitalized for a total of 43,426. Hong
Kong and Queensland, Australia contributed almost 75% of
these infections (Table 1). The distribution of cases between the
three broad age groups (,18, 18–64, and 65 and older) looks
very similar between cases that were and were not hospitalized,
with 52.1% of the cases being in the youngest age group. Only
a very small percentage of the cases that did not require
hospitalization were older than 64 years (0.7%). In contrast to
the hospitalized cases, the peak in risk amongst the differing
locations is shifted to slightly older children and appears
between 6 and 19 years of age (Table 2 and Figure 2A). The
range in peak RRs among locations is narrower in cases that
were not hospitalized (2.0–4.2).
The WRR of cases who were not hospitalized peaks in 8 year
olds and then declines nearly continuously until the early
eighties (Figure 2B and 2C). The WRR flattens out briefly around
47–48 years of age but then declines again until 75 years of age
where the slope is zero until 82 years when the WRR declines
further. The rate of decline of the WRR slows dramatically
from 28 to 45 years of age but then this trend reverses between
49 and 56 years and the rate of decline in the WRR accelerates
(Figure 3D). From 61 to 75 years the rate of decline again slows
down and becomes stable after 75 years of age. The WRR
suggests that incidence begins to stabilize among adults in their
forties, but that around 49 years of age the incidence declined
rapidly.
In South Africa (N = 12,497), the age distribution of confirmed
cases (in which hospitalization status was not recorded) looks
similar to the distribution of cases that were not hospitalized,
suggesting that the majority of reports had not been hospitalized
Results
Hospitalized Cases
Seven locations contributed surveillance records of hospitalized cases for a total of 18,788 pH1N1 hospitalizations (Table 1).
Hong Kong, Thailand, and Argentina contributed 40, 24, and
22% of the hospitalized cases, respectively. The hospitalized
cases had a similar age distribution to the previously published
surveillance reports described above (Table 1). The RR was
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Table 1. Confirmed cases of 2009 pandemic A/H1N1 influenza by location and hospitalization status, the associated weights used
to calculate the weighted risk ratio (shown as %), and the cumulative incidence risk ratio (95% confidence intervals) of male versus
female cases by hospitalization status and age group for locations where sex was known.
Hospitalized
Not Hospitalized
(%)
(%)
M:F Risk Ratio
Hospitalized
1
M:F Risk Ratio
Not Hospitalized2
Location
Argentina
4,068 (21.7)
2,586 (6.0)
Australia, Queensland
726 (3.9)
10,820 (24.9)
Hong Kong
7,425 (39.5)
21,330 (49.1)
New Zealand
991 (5.3)
2,202 (5.1)
Thailand
4,421 (23.5)
2,169 (5.0)
United States, NYC
996 (5.3)
United States, Wisconsin
161 (0.9)
4,319 (9.9)
Age Group in years
,18
9,794 (52.1)
22,618 (52.1)
1.16 (1.10, 1.22)
1.24 (1.11, 1.38)
18–64
8,175 (43.5)
20.503 (47.2)
0.86 (0.81, 0.91)
0.85 (0.82, 0.88)
.64
819 (4.4)
305 (0.7)
1.72 (1.47, 2.03)
0.52 (0.37, 0.72)
18,788
43,426
Total
1
An unweighted cumulative incidence risk ratio determined using lab confirmed hospitalized cases from Argentina and Hong Kong.
An unweighted cumulative incidence risk ratio determined using lab confirmed cases that were not hospitalized from Argentina, Hong Kong, and Wisconsin.
doi:10.1371/journal.pone.0042328.t001
2
final decline in the WRR occurs from 61 to 67 years of age but the
WRR is then stable until 100 years of age. There is a narrow
acceleration in the rate of decline around 53 years of age, but it is
only statistically significant at larger bandwidths (Figure 3B).
Among hospitalized women, a similar rise in WRR occurs
between 46–52 years of age (Figure 3C), but then there is a rapid
acceleration in the rate of decline between 52 and 60 year olds
that is absent in men (Figure 3D).
This pattern of acceleration in the rate of decline among women
(which is less pronounced among men) beginning in the early fifties
and continuing until the early sixties occurs in cases that were not
hospitalized as well. Among men who where not hospitalized the
WRR increases initially and then declines from 11 to 45 years of
age when the WRR starts to stabilize and then declines again from
54 to 72 years of age (Figure 4A). Among adult men, there is little
statistical evidence of an acceleration in the rate of decline
(Figure 4B). The WRR among women who were not hospitalized is
(data not shown). The patterns observed in South Africa also
mirror those of cases that were not hospitalized (Figure S1). A peak
in risk occurs at 14 years of age (RR = 4.2) and then declines until
31 years, with the rate of decline significantly decreasing between
21 and 35 years of age (Figure S1). The RR plateaus between 32–
45 years of age but then a rapid acceleration in the rate of decline
occurs between 41–52 years of age at slightly higher bandwidths.
The RR declines steadily from 46–73 years of age and then it
plateaus again.
Role of Sex
To explore potential sex variation in age-specific incidence risk,
we further stratified the datasets from Argentina, Hong Kong, and
Wisconsin, for which sex information was available. Among men
hospitalized for pH1N1-related disease, the WRR declines from 4
to 28 years of age but then stabilizes and begins to rise again from
44 to 52 years of age before reaching a plateau again (Figure 3A). A
Table 2. Peak risk ratio by location, age and hospitalization status.1
Hospitalized Peak RR (Age)
Not Hospitalized Peak RR (Age)
Location
Argentina
3.3 (,1)
2.0 (6)
Australia, Queensland
4.6 (,1)
2.2 (7)
Hong Kong
11.1 (2)
4.2 (6)
New Zealand
7.1 (,1)
2.8 (19)
Thailand
4.4 (5)
3.3 (6)
United States, NYC
6.2 (,1)
United States, Wisconsin
3.9 (2)
3.8 (9)
Overall Weighted Risk Ratio
5.9 (1)
3.2 (7)
1
This is the actual risk ratio, not the peak in the locally weighted polynomial regression smoothed risk ratio.
doi:10.1371/journal.pone.0042328.t002
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Figure 1. Laboratory confirmed hospitalized cases. A The smoothed risk ratio of laboratory confirmed hospitalized cases in a single year age
group compared to the overall risk in all age groups. Smoothed curves for each location were created by a locally weighted polynomial regression
with fixed bandwidth of 4. B The smoothed weighted risk ratio (WRR) of laboratory confirmed hospitalized cases in a single year compared to the risk
in all age groups combined using a fixed bandwidth of 4. The single year of age WRR used to create the smoothed curve are plotted as open circles
and the 95% confidence bounds are shaded. The inset figure shows the truncated WRR from 0 to 29 years of age while the larger figure focuses on
the ages from 30–100. C SiZer plot of the first derivative of the WRR by age. The X axis represents age while the Y axis corresponds to the log of the
bandwidth (h). For example, log(0.6) corresponds to the fixed bandwidth of 4 used to create Figures A and B and a black horizontal line identifies this
bandwidth. The shading corresponds to the significance and direction of the slope (first derivative) of the WRR by age: red is significantly decreasing,
purple is possibly zero, blue is significantly increasing, and light grey represents areas where there is insufficient data to generate a smoothed curve.
The grid lines correspond to 1 year of age intervals. D SiZer plot of the second derivative of the WRR by age, where the shading corresponds to that
described for Figure 1C.
doi:10.1371/journal.pone.0042328.g001
similar to men who were not hospitalized (Figure 4C) with the
exception that the rate of decline accelerates in a statistically
significant way among women between the ages of 49–56
(Figure 4D).
Regardless of hospitalization status, male children had a
higher risk of laboratory confirmed pH1N1 than females; the
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cumulative incidence risk ratio (95% confidence interval) of
male versus females for hospitalized and not hospitalized cases
was 1.16 (1.10, 1.22) and 1.24 (1.11, 1.38), respectively (Table 1).
This pattern reversed in adults aged 18–64 years and women
had a higher incidence of pH1N1 disease than men; 0.86 (0.81,
0.91) and 0.85 (0.82, 0.88) for hospitalized and not hospitalized.
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Pandemic A/H1N1 Influenza Incidence
Figure 2. Laboratory confirmed cases that were not hospitalized. A The smoothed risk ratio of laboratory confirmed cases that were not
hospitalized in a single year age group compared to the overall risk in all age groups. Smoothed curves for each location were created by a locally
weighted polynomial regression with fixed bandwidth of 4. B The smoothed weighted risk ratio of cases that were not hospitalized in a single year
compared to the risk in all age groups combined using a fixed bandwidth of 4. The single year of age weighted risk ratios used to create the
smoothed curve are plotted as open circles and the 95% confidence bounds are shaded. The inset figure shows the truncated WRR from 0 to 29 years
of age while the larger figure focuses on the ages from 30–100. C SiZer plot of the first derivative of the weighted risk ratio by age. The X axis
represents age while the Y axis corresponds to the log of the bandwidth (h). For example, log(0.6) corresponds to the fixed bandwidth of 4 used to
create Figures A and B and a black horizontal line identifies this bandwidth. The shading corresponds to the significance and direction of the slope
(first derivative) of the weighted risk ratio by age: red is significantly decreasing, purple is possibly zero, blue is significantly increasing, and light grey
represents areas where there is insufficient data to generate a smoothed curve. The grid lines correspond to 1 year of age intervals. D SiZer plot of
the second derivative of the weighted risk ratio by age, where the symbols are as described for Figure 2C.
doi:10.1371/journal.pone.0042328.g002
Among the elderly, men had an increased risk of hospitalization
versus women while the opposite was true among cases that
were not hospitalized; 1.72 (1.47, 2.03) and 0.52 (0.37, 0.72),
respectively.
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Discussion
We have found evidence that the risk of laboratory confirmed
pH1N1 infection declines with age, but that there is a statistically
significant leveling off or increase in risk from about 45 to 50 years
of age, after which a sharp drop in risk occurs until the late fifties.
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Figure 3. Differences by sex in hospitalized cases. A Hospitalized Men. The smoothed risk ratio of laboratory confirmed hospitalized cases
among men in a single year age group compared to the overall risk in all male age groups. Smoothed curves were created by a locally weighted
polynomial regression with fixed bandwidth of 4. The single year of age weighted risk ratios used to create the smoothed curve are plotted as open
circles and the 95% confidence bounds are shaded. The inset figure shows the truncated WRR from 0 to 29 years of age while the larger figure
focuses on the ages from 30–100. B Hospitalized Men. SiZer plot of the second derivative of the weighted risk ratio by age among male
hospitalized cases. C Hospitalized Women. The smoothed risk ratio of laboratory confirmed hospitalized cases among women in a single year of
age compared to the overall risk in all female age groups. Smoothed curves were created by a locally weighted polynomial regression with fixed
bandwidth of 4. The single year of age weighted risk ratios used to create the smoothed curve are plotted as open circles and the 95% confidence
bounds are shaded. The inset figure shows the truncated WRR from 0 to 29 years of age while the larger figure focuses on the ages from 30–100. D
Hospitalized Women. SiZer plot of the second derivative of the weighted risk ratio by age among female hospitalized cases.
doi:10.1371/journal.pone.0042328.g003
and hospitalization by single year of age, our results are in broad
agreement with previous studies [5,19]. Several mechanisms,
which are not mutually exclusive, could account for the rapid
decline in influenza risk past 50 years of age: variation in prior
immunity from earlier life exposure (cellular immunity and cross-
This trend was more pronounced in hospitalized cases and
women, regardless of location. The age range at which the decline
in risk accelerates corresponds to the cohort born between 1951–
1959 (hospitalized) and 1953–1960 (not hospitalized). Although
this is the first study describing the age patterns of pH1N1 cases
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Figure 4. Differences by sex in cases that were not hospitalized. A Men not hospitalized. The smoothed risk ratio of cases among men
who were not hospitalized in a single year age group compared to the overall risk in all age groups. Smoothed curves were created by a locally
weighted polynomial regression with fixed bandwidth of 4. The single year of age weighted risk ratios used to create the smoothed curve are plotted
as open circles and the 95% confidence bounds are shaded. The inset figure shows the truncated WRR from 0 to 29 years of age while the larger
figure focuses on the ages from 30–100. B Men not hospitalized. SiZer plot of the second derivative of the weighted risk ratio by age among men
who were not hospitalized. C Women not hospitalized. The smoothed risk ratio of cases among women who were not hospitalized in a single
year of age compared to the overall risk in all female age groups. Smoothed curves were created by a locally weighted polynomial regression with
fixed bandwidth of 4. The inset figure shows the truncated WRR from 0 to 29 years of age while the larger figure focuses on the ages from 30–100.
The single year of age weighted risk ratios used to create the smoothed curve are plotted as open circles and the 95% confidence bounds are shaded.
D Women not hospitalized. SiZer plot of the second derivative of the weighted risk ratio by age among women who were not hospitalized.
doi:10.1371/journal.pone.0042328.g004
reactive antibodies to conserved epitopes), in exposure to pH1N1
during the pandemic, and immune function related to aging and
sex. We further discuss each in light of our findings.
The history of a person’s exposure to influenza A viruses
determines their response to a new infection. It is not currently
evident whether the clinical protection against pH1N1 observed
PLoS ONE | www.plosone.org
among the elderly comes from prior immunity associated with
their first encounter with an influenza virus (original antigenic sin)
or from an accumulation of exposures to conserved epitopes in
seasonal and older antigenically similar H1N1 that elicit a cellular
and humoral immune response [11]. Clinical protection could
result from both antibody-based protection from infection, which
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Pandemic A/H1N1 Influenza Incidence
is determined by exposure to antigenically similar hemagglutinin
(HA), and lessened disease severity, which is influenced by T cells
and antibodies primed by multiple epitopes in the H1N1 virus. We
do not have the capability to distinguish between these types of
immune protection among the older adults in our study.
The theory of original antigenic sin stipulates that the first
encounter with an influenza A virus in childhood sets the immune
response to all other influenza A viruses in the future, which could
explain the observed clinical protection against 2009 pH1N1 in
seniors [20,21]. Even when a person is exposed to an influenza
virus that is antigenically dissimilar to the first virus they
encountered, their immune system will mount a strong immune
response to that first virus. If the theory of original antigenic sin
holds, then anyone born prior to 1957 (especially those born
several years prior, having lived through several H1N1 influenza
seasons) would likely have had their first influenza A encounter
with an H1N1 influenza virus and thus have some cross-protection
to pH1N1. At a population level, this protection would increase
past age 52 as the probability of a first infection with an H1N1
virus increases. In contrast, when H1N1 reemerged in 1977, it cocirculated with H3N2 viruses, which would have resulted in fewer
individuals whose first exposure was to H1N1. This is consistent
with the results of our study, where we saw no sharp decline in risk
in the age cohort that was born after 1977 (those who were 32 in
2009) but a sharp decline in risk in those born prior to 1957.
If protection relied solely on exposure to a specific virus that has
antigenic similarities to pH1N1, then we would have expected a
sharp drop in risk in those that were born before 1943, or in adults
66 and older. The likely origin of the HA of the 2009 pH1N1 is a
classical swine virus that has been relatively antigenically stable
since it entered into swine around 1918 [22,23]. The human 1918
and 2009 pH1N1 HA have the same neutralizing epitopes on the
receptor-binding domain and both lack glycosylation sites in this
region [24]. As the 1918 strain drifted in humans, glycosylation
sites were added to the HA head and the current seasonal H1N1
strain has 2 glycosylation sites, so that there is no cross-reactivity
between modern seasonal H1N1 strains and pH1N1 [25]. In
contrast, the pH1N1 virus is antigenically most similar to human
H1N1 viruses that circulated from around 1918 to the early 1940 s
and classical swine H1N1 viruses [26]. Thus our study results
suggesting a sharp decline in risk beginning at age 52, not age 66,
suggests that immunologic protection is derived primarily from
first exposure to any H1N1 virus and depends less on the antigenic
similarity of the H1N1 strains.
Studies of pre-pandemic stored serum have provided fairly
consistent evidence that cross-protective immunity from antibodies
against pH1N1 increases with age, with the highest levels
occurring in adults .60 years old [27,28]. Comparability of
serology studies published to date is hampered by a multitude of
factors. These studies show a broad range in the age-specific
prevalence of immune protection from prior H1N1 infection
[9,27,29,30,31,32]. Cross-protective immunity is most commonly
defined as a hemagglutinin inhibition (HI) titer of .1:40 or a
microneutralization (MN) assay titer of .1:160, which translates
into a 50% reduction in influenza infection or disease in a
population [27]. In the locations included in our study where prepandemic serology studies have been conducted, most conclude
that around 20–30% of the population over 60 years old had preexisting antibodies. In New Zealand, 22.6% (95% CI: 15.3–30%)
of adults .60 years old (N = 124 samples) had pre-existing
protection (determined by HI assay) [29]. In North Queensland,
Australia, 19% (95% CI: 4–34%) of adults .65 years old (n = 27)
had pre-existing immunity (determined by HI assay) while a larger
study of 259 adults .60 years old in Australia found pre-existing
PLoS ONE | www.plosone.org
immunity in 37.5% (95% CI: 31.6–43.3%) [33,34]. In the United
States, 34% of adults born before 1950 (N = 115) had crossreactive antibodies to pH1N1 (determined by MN) [9] while in
Hong Kong 37% (n = 30) adults .65 years showed seroprotective
levels of antibodies to pH1N1 [35]. In Thailand, of 100 stored
serum samples from persons aged 11–86 years, only 2 (both from
adults aged .50 years), showed seroprotective HI assays, however
it is unclear from the study how many adults .50 years old were
sampled [36]. No serology studies have been published in
Argentina.
In studies grouped by 10-year increments of age, there was
evidence of cross-reactive antibodies in those born in the 1950 s,
suggesting some circulation of H1N1 viruses that were antigenically similar to pH1N1. However, a positive cross-protective
antibody serum test is only part of the immune response that has
spared the elderly in this pandemic. If 20–30% of the population
aged .50 years had HI assay titers .1:40 and this corresponds to
a 50% reduction in infection, we could expect a risk reduction for
only 10–15% of this population. This reduction of risk is much less
than that observed among the elderly during the pandemic and
less than the risk reduction observed in our study.
While the HI and MN assays are good indicators of the immune
response to an influenza virus, other antibody responses and the
avidity of the antibodies produced also contribute to viral
clearance from a host [37]. In one study, the elderly had memory
B cells from prior exposure to 1918-like H1N1 viruses that were
rapidly recruited, underwent selection, and affinity maturation
when presented with pH1N1 vaccine, resulting in a quantitatively
and qualitatively superior response than adults aged 18–65 years
[37]. Given restrictions on the number of samples included in that
study, the group of most interest for comparison with our study
was aggregated into 46–64 years of age, which precludes a direct
comparison with our study results.
Memory B cells isolated from survivors of the 1918 pandemic
are capable of producing neutralizing antibodies against 1918
H1N1 and 1930 influenza A/Swine/Iowa/15/30, and to a lesser
degree 1943 and 1977 H1N1 viruses, after surviving more than
90 years in the human body; this suggests that immunity to
antigenically similar influenza A viruses is life long [38].
In addition to benefiting from immunologic protection resulting
from prior H1N1 exposure, adults in their late fifties during the
2009 pandemic also likely benefitted from a lower exposure to
school aged children; the age group with the highest attack rates
[39]. We could not assess this possibility further as we did not have
data on the number of children in the household for individual
cases. However, despite different age and family structures, we did
not find meaningful differences in the WRR between countries.
This suggests that exposure to school aged children is not a
significant determinant in the age-associated decline in incidence.
An additional mechanism for the acceleration in WRR decline
that we observed could be changes in the sex specific hormones
that are dramatically altered in post-menopausal women. We
explored the differences in WRR decline between men and
women and found that regardless of hospitalization status, women
had a statistically significant acceleration in decline of the WRR
between 52–60 years (hospitalized) or 49–56 (not hospitalized),
which was more pronounced than in men. The paucity of data on
the response of post-menopausal women to influenza and in
particular the role of sex hormones in the modulation of disease
severity or susceptibility complicates our interpretation [40]. We
cannot rule out a possible role of menopause in causing the sharp
decline in risk that we observed in women more strongly than men
in their fifties. Whether this effect is a main effect of menopause, or
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Pandemic A/H1N1 Influenza Incidence
a modifying effect of menopause on the strength of acquired
immunity cannot be assessed in this study.
The primary limitation in our study is that we have no
information about the cases other than their age and incomplete
data on sex. We do not know what their prior exposure to
influenza A viruses (including wild- or vaccine-type exposures) has
been, nor do we have information about comorbidities, family,
and social structure. As such, we have no sense of the unique
immunological history of each individual case. The immune
response to influenza A viruses is complex and not well understood
and operates in the landscape of other systems in a human body –
i.e. two equally aged individuals with the exact same exposure
history to influenza could have different responses to pH1N1
exposure based on other risk factors. Another limitation of our
study is the lack of information on testing practices and healthcare
seeking behaviors, and it is possible that there were age biases in
propensities to test or in ability to detect influenza given infection,
as well as gender biases in referral. Ideally, the age distribution of
laboratory confirmed pH1N1 cases could be compared to that of
seasonal influenza to adjust for such biases, but unfortunately no
highly detailed age-specific dataset was available from earlier
influenza seasons. Despite this complexity and the stratification of
our study by only single year of age, the acceleration in the decline
of incidence in cohorts born prior to 1957, consistently found in 8
international locations, is striking.
Our study has demonstrated that the relative risk of being a
laboratory confirmed pH1N1 case levels off among adults aged 30
to late 40 and even increases among hospitalized cases, and then
declines rapidly among adults in their fifties. Our results do not
show an exact drop in those born before 1957 (i.e. 52 years of age
in 2009) for several reasons. First, birth year is only an indication
of exposure to H1N1 or prior infection with influenza H1N1
viruses; not everyone is exposed to influenza every year and the
effect of these mechanisms should be spread out. Second, the use
of a smoothing bandwidth of 4 could account for the smoothed
WRR for cohorts born the three years after 1957 being involved in
the observed rapid decline, as smoothing borrows information
from the neighboring ages before and after the age for which it is
estimating the WRR. Overall, our multinational dataset is most
consistent with immune protection in people older than 52 years
in 2009, resulting from priming with any A/H1N1 virus
circulating before 1957, consistent with the theory of original
antigenic sin. In addition, our data highlight gender variation in
influenza risk by age that could be linked with changes in immune
function due to menopause. Interestingly, these variations are not
expected to be unique to the 2009 pandemic and hence the
importance of menopause could be confirmed with data from
seasonal outbreaks. Further experimental and epidemiological
studies should shed light on the role of sex in the risk of influenza
morbidity and mortality – a relatively new field of research [40].
Supporting Information
Figure S1 Confirmed Cases in South Africa. A The
smoothed weighted risk ratio (WRR) of laboratory confirmed
cases in a single year compared to the risk in all age groups
combined using a fixed bandwidth of 4. The single year of age
WRR used to create the smoothed curve are plotted as open
circles and the 95% confidence bounds are shaded. The inset
figure shows the truncated WRR from 0 to 29 years of age while
the larger figure focuses on the ages from 30–80+, where 5 cases in
80–90 year olds were aggregated into one single year of age. B
SiZer plot of the first derivative of the WRR by age. The X axis
represents age while the Y axis corresponds to the log of the
bandwidth. For example, log(0.6) corresponds to the fixed
bandwidth of 4 used to create Figures A and a black horizontal
line identifies this bandwidth. The shading corresponds to the
significance and direction of the slope (first derivative) of the WRR
by age: red is significantly decreasing, purple is possibly zero, blue
is significantly increasing, and light grey represents areas where
there is insufficient data to generate a smoothed curve. The grid
lines correspond to 1 year of age intervals. C SiZer plot of the
second derivative of the WRR by age, where the shading
corresponds to that described for Figure 1B.
(DOC)
Table S1 This table includes the cumulative cases for each single
year of age (0–.99 years) by sex for three of the locations in this
study. Included are Wisconsin, Hong Kong, and Argentina. The
population is also included to allow the replication of these
analyses.
(XLSX)
Acknowledgments
We thank the many individuals and organizations that contributed toward
the data utilized in this project. We would like to thank the New York City
Department of Health and Mental Hygiene Bureau of Communicable
Diseases for providing data for New York City and Dr. Cheryl Cohen
(National Institute for Communicable Diseases, South Africa) for providing
comments on the project.
Author Contributions
Conceived and designed the experiments: JHJ ETT ML. Analyzed the
data: JHJ. Contributed reagents/materials/analysis tools: BNA MGB BJC
RTH GM OU WH. Wrote the paper: JHJ BNA MGB BJC RTH GM OU
WH CV JS ETT ML.
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