Serological Evidence of Subclinical Transmission of the
2009 Pandemic H1N1 Influenza Virus Outside of Mexico
Day-Yu Chao1., Kuang-Fu Cheng2., Tsai-Chung Li2,3, Trong-Neng Wu3,4, Chiu-Ying Chen4, Chen-An
Tsai2,3, Jin-Hwa Chen2,3, Hsien-Tsai Chiu2,4, Jang-Jih Lu5,6, Mei-Chi Su6, Yu-Hsin Liao1, Wei-Cheng Chan1,
Ying-Hen Hsieh3,4*
1 Graduate Institute of Microbiology and Public Health, College of Veterinary Medicine, National Chung-Hsing University, Taichung, Taiwan, 2 CMU Biostatistics Center,
China Medical University, Taichung, Taiwan, 3 Graduate Institute of Biostatistics, China Medical University, Taichung, Taiwan, 4 Department of Public Health, China Medical
University, Taichung, Taiwan, 5 Graduate Institute of Clinical Medical Science, China Medical University, Taichung, Taiwan, 6 Department of Laboratory Medicine, China
Medical University Hospital, Taichung, Taiwan
Abstract
Background: Relying on surveillance of clinical cases limits the ability to understand the full impact and severity of an
epidemic, especially when subclinical cases are more likely to be present in the early stages. Little is known of the infection
and transmissibility of the 2009 H1N1 pandemic influenza (pH1N1) virus outside of Mexico prior to clinical cases being
reported, and of the knowledge pertaining to immunity and incidence of infection during April–June, which is essential for
understanding the nature of viral transmissibility as well as for planning surveillance and intervention of future pandemics.
Methodology/Principal Findings: Starting in the fall of 2008, 306 persons from households with schoolchildren in central
Taiwan were followed sequentially and serum samples were taken in three sampling periods for haemagglutination
inhibition (HI) assay. Age-specific incidence rates were calculated based on seroconversion of antibodies to the pH1N1 virus
with an HI titre of 1:40 or more during two periods: April–June and September–October in 2009. The earliest time period
with HI titer greater than 40, as well as a four-fold increase of the neutralization titer, was during April 26–May 3. The
incidence rates during the pre-epidemic phase (April–June) and the first wave (July–October) of the pandemic were 14.1%
and 29.7%, respectively. The transmissibility of the pH1N1 virus during the early phase of the epidemic, as measured by the
effective reproductive number R0, was 1.16 (95% confidence interval (CI): 0.98–1.34).
Conclusions: Approximately one in every ten persons was infected with the 2009 pH1N1 virus during the pre-epidemic
phase in April–June. The lack of age-pattern in seropositivity is unexpected, perhaps highlighting the importance of children
as asymptomatic transmitters of influenza in households. Although without virological confirmation, our data raise the
question of whether there was substantial pH1N1 transmission in Taiwan before June, when clinical cases were first
detected by the surveillance network.
Citation: Chao D-Y, Cheng K-F, Li T-C, Wu T-N, Chen C-Y, et al. (2011) Serological Evidence of Subclinical Transmission of the 2009 Pandemic H1N1 Influenza Virus
Outside of Mexico. PLoS ONE 6(1): e14555. doi:10.1371/journal.pone.0014555
Editor: Cesar V. Munayco, Direccion General de Epidemiologia, Peru
Received July 2, 2010; Accepted December 14, 2010; Published January 18, 2011
Copyright: ß 2011 Chao et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by National Science Council of Taiwan (NSC 97-2118-M-039-004) and China Medical University, Taiwan (CMU 97 323). The
funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: hsieh@mail.cmu.edu.tw
. These authors contributed equally to this work.
on probable H1N1 cases, airport fever screening, quarantine, and
antiviral therapy on probably cases [5]. However, the effectiveness
of these interventions remains questionable as the S-OIV human
cases were identified in U.S. as early as the last week of March
after the first S-OIV case was confirmed in Mexico in March 11
[6,7]. Relying on surveillance limits the ability to understand the
full impact and severity of the epidemic, especially when
asymptomatic to mild-symptoms cases are more likely to be
present in the early phase before the epidemic occurred [8,9].
According to US Centers for Disease Control and Prevention
(CDC) estimates, more than 1 million people were infected with SOIV between April 15 and July 24, 2009, leading to 5,011
hospitalizations and 301 deaths in the US [10]. However, reliance
on data from routine surveillance to estimate age-specific attack
Introduction
Since the swine-origin H1N1 influenza virus (S-OIV) was first
identified in humans in April, 2009, the virus has caused a
widespread illness in many countries worldwide that meets the
World Health Organization (WHO) criteria for a pandemic [1,2].
As this virus contains a unique combination of gene segments from
both North American and Eurasian swine lineages, and is
antigenically distinct from seasonal human influenza A, a
deficiency in protective immunity in persons born after 1957 has
been observed, presumably because of their lack of exposure to
H1N1 influenza strains that no longer circulated after that time
[3,4]. Prompt action to mitigate the clinical and societal effects of
the pandemic was taken by many countries, including surveillance
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Early Transmission of pH1N1
rates during an emerging pandemic is hampered by changes in the
sensitivity and specificity of clinical surveillance schemes and the
proportion of subclinical infections [10,11]. Although several
serological surveys had been recently conducted, which provided
an estimate of the number of people infected with 2009 pandemic
H1N1 over time [12], the actual transmission of the virus during
different phase of the epidemic can only be estimated by a
longitudinal follow-up study.
Although reports of the epidemic in Mexico, the US and
Canada has provided important information about the transmissibility of the 2009 pandemic H1N1 virus [7,13,14], little is known
of the way viruses were transmitted in the community in the early
phase before the epidemic. In this report, we provide first
serological evidence of early infection by the 2009 pandemic
H1N1 viruses outside of Mexico before the imported pandemic
H1N1 cases being reported. Compared with surveillance data
based on clinical cases and virological investigation, our direct
measurement of incidence in different phases (during April–June
and July–October) of the epidemic highlights the importance of
serology data for providing a novel insight into the epidemiology of
2009 pandemic H1N1 influenza.
56uC and after which an equal volume of 1.6% trisodium citrate
was added for enzyme inactivation. The different strains of
influenza viruses used in this study were first prepared from the
culture supernatants of infected Madin-Darby canine kidney
(MDCK) cells. 25 microliters (ul) (4 hemagglutination units, HA)
of influenza virus was incubated at room temperature for one hour
with an equal volume of RDE-treated serum in a V-shape 96-well
microtiter plate. After incubation, 25 ul of 1% (vol/vol) chicken
red blood cells was added to each well. Hemagglutination
inhibition was read after 30 minutes. The virus strain used was
originally isolated from the patient infected by S-OIV H1N1,
which is antigenically and genetically closely related to A/
California/07/2009. To evaluate the cross-reactivity, a vaccine
strain of H1N1 (A/Brisbane/59/2007) and the wild-type strain
which represented more than 80% of circulating H1N1 during the
2008/2009 influenza season (A/Taiwan/606/2008) were also
used. For the HI assay, serum samples were tested with an initial
dilution of 1:10 and a final dilution of 1:1024, and the titers were
expressed as the reciprocal of the highest dilution of serum where
hemagglutination was prevented. Samples that were negative by
HI were assigned a titre of 1:5 for the computational purpose of
obtaining a geometric mean titre (GMT). We defined seroconversion as a four-fold increase in antibody titers, which was used to
calculate the three-month incidence rate later in the statistical
analysis.
A set of samples collected during April–June, 2009 with HI
titer$40 was further confirmed by micro-neutralization assay in
accordance with WHO standard protocol [15,16]. In brief, human
serum was heat inactivated for 30 minutes at 56uC and two-fold
serial dilution were performed in a 50-ul volume of virus growth
medium (VGM) starting from 1:10 in immunoassay plates. The
diluted serum was mixed with an equal volume of 100 TCID50 per
50 ul of VGM at 37uC for 2 hours. The virus-antibody mixture
was added to the 96-well microtiter plate with confluent MDCK
cells and incubated for 48 hours at 37uC. At least quadruplicate
repeats of each serum samples were performed. Neutralization
titer was expressed as the reciprocal serum dilution giving a 50%
reduction of the cytotoxic effect.
Methods
Ethics Statement
All subjects in this study gave informed consent and the study
was approved by the Medical Ethics Committee of China Medical
University with written consent.
Enrollment of subjects and serological specimens
Since 2007, all schoolchildren in grades 1–4 in Taiwan received
a free annual influenza vaccination from the government. In order
to evaluate vaccine efficacy, students from elementary schools
located in urban (Taichung city) and rural (Nantou county) areas
in central Taiwan were recruited for evaluation in a three-year
study starting in the fall of 2008, with additional volunteers
recruited each successive year. Family members of the students
were also recruited to join the study to further the understanding
of household transmissions and vaccine effectiveness pertaining to
seasonal influenza viruses. The study protocol based on clinical
and laboratory data was established including at least two blood
samples drawn from the study subjects before and after influenza
seasons. Two questionnaire interviews were also conducted by
trained interviewers regarding basic demographic and social
contact information, in addition to upper respiratory-related
symptoms recorded by bi-weekly telephone interview during the
influenza season. All subjects gave informed consent and the study
was approved by the Medical Ethics Committee of China Medical
University.
To evaluate the antibody response against the 2009 pandemic
H1N1 virus, only 306 study subjects with three sequential blood
samples, taken in the fall of 2008, April–June in 2009 (after the
2008/2009 influenza season), and September–October in 2009
(before the vaccination of both 2009/2010 seasonal and 2009
pandemic influenza strains) were selected. Only information
regarding age, sex, geographical area, vaccination status, and
collection dates of blood sample were used in this study.
Clinical and virological surveillance data sources
Due to the initial novel H1N1 influenza epidemic in Mexico
and the increasing number of affected persons in other countries
because of traveling, the Taiwanese government set up an
influenza pandemic clinical surveillance system that includes
airport fever screening followed by laboratory confirmation
starting April 28, 2009. The system required that hospitals and
clinics report the probable cases determined by the occurrence of
at least one of the following conditions: (1) clinically present fever
(.38uC), flu-like symptoms, or other flu-related severe diseases
such as pneumonia; (2) epidemiologically related, including having
direct contact with confirmed or probable cases or having a travel
history to countries with confirmed 2009 pandemic H1N1 cases.
The system also monitored travelers with fever using ultra-red scan
in the airports, and throat swabs were collected from travelers with
fever for laboratory confirmation. The government initiated the
pandemic H1N1 clinical surveillance system that started April 29
and an increasing number of probable cases was reported,
especially after May 15, which correlated with the first imported
laboratory-confirmed pH1N1 case on May 19 [17]. The level of
the global influenza alert system was raised from phase 5,
announced on April 29, to phase 6 on June 11 by the WHO as
the number of probable or laboratory-confirmed cases in Taiwan
also increased. Due to the fact that all pH1N1-confirmed cases
before the end of June were travel-related, we refer to the duration
Laboratory methods
Antibody titres were measured by use of a haemagglutination
inhibition (HI) assay following the standard protocol by the WHO
[15,16]. In brief, serum samples were pre-treated with receptor
destroying enzyme (RDE, Deka Seriken Co Ltd, Tokyo, Japan) in
1:4 ratio at 37uC for 16 hours, followed by another 30 minutes at
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Table 1. Cross-reactive antibody response against seasonal influenza vaccine and wild-type strains and pandemic influenza A
(H1N1) virus among different age groups.
Age group
5–18
19–60
.60
Sample size (N = )
143
147
16
Mean
9.3562.23
39.3466.66
67.5664.88
Range
5–16
25–60
61–75
Male
72(50.3%)
57(38.8%)
4(25%)
Female
71(49.7%)
90(61.2%)
12(75%)
Urban
49(34.3%)
48(32.7%)
12(75%)
Sub-urban
94(65.7%)
99(67.3%)
4(25%)
88(61.5%)
10(6.8%)
8(50%)
Age(years)
Gender
Region
Recipients of 08/09 seasonal influenza vaccine
Increase in antibody titer from the second samples by a factor of $4-fold
Vaccine strain
16(11.2%)
1(0.7%)
0(0%)
Wild-type seasonal strain
13(9.1%)
23(15.6%)
3(18.8%)
Pandemic strain
26(18.2%)
35(23.8%)
5(31.3%)
Vaccine and pandemic strains
4(2.8%)
0(0%)
0(0%)
Seasonal and pandemic strains
5(3.5%)
8(5.4%)
1(6.3%)
doi:10.1371/journal.pone.0014555.t001
between April-June as the pre-epidemic period. The surveillance
system in Taiwan was discontinued after June 18 and replaced by
the routine influenza surveillance system, which included the
severe cases reporting system and virological surveillance as
reported in other publications [18,19]. The period between July–
October was referred to as the epidemic period in our study.
package version 9.2 (SAS Institute Inc., Cary, NC) to account for
correlated data within household. At each selected day, a person is
defined as an incidence case if his/her HI has four-fold increase
before that day. The reproductive numbers (R0) for these two
periods with 95% Confidence intervals were also estimated, based
on the final size equation of epidemic [20].
Statistical analysis
Results
As a haemagglutination inhibition titre above 1:40 is correlated
with protection The three-month incidence rates in two different
time periods were calculated based on the new infections among
the susceptible population by excluding the persons with antibody
titre higher than 1:40 from the previous blood sampling. The point
estimates and 95% point-wise confidence intervals (CIs) of
cumulative incidence rates at selected time points between April
and June of 2009 were calculated using generalized estimating
equation (GEE) with GENMOD procedure in the SAS statistical
Among the 306 study subjects, 143 were from schoolchildren
and their siblings between 5–18 years of age with mean6standard
deviation (s.d.) 9.3562.23 years; 147 were from family adults
between 19–60 years of age with mean6s.d. 39.3466.66 years;
and 16 people were older than 60 with mean6s.d. 67.5664.88
years. The gender distribution was about 1:1 in the 5–18 age
group but about twice and three times as many females as males in
the 19–60 and older than 60 age groups, respectively. In all three
Table 2. Proportion of sequential serum samples obtained in different sampling time from the 306-subjects cohort with
haemagglutination inhibition titre above the cutoff.
Incidence rate
(April–June)
3rd sampling time
Incidence rate
(July–October)
. = 10
. = 10
. = 10
HI
1st sampling time*
2nd sampling time
Age (years)
. = 10
. = 10
5–18
0(0%)
0(0%)
33(23.1%)
19(13.3%)
23.1%
13.3%
104(72.7%)
44(30.8%)
66.9%
29.8%
19–60
1(0.7%)
0(0%)
42(28.6%)
21(14.3%)
28.6%
14.3%
121(82.3%)
49(33.3%)
66.7%
29.4%
. = 40
. = 40{
. = 40
. = 40
. = 40
.60
2(12.5%)
0(0%)
7(43.8%)
3(18.8%)
43.8%
18.8%
16(100%)
4(25%)
76.9%
30.8%
Total
3(0.98%)
0(0%)
82(26.8%)
43(14.1%)
26.8%
14.1%
241(78.8%)
97(31.7%)
71.1%
29.7%
*1st sampling time refer to samples collected in 2008 (after 08–09 seasonal influenza vaccination), 2nd sampling time refer to samples collected during April to June in
2009 (after the 08–09 influenza season) and 3rd sampling time refer to samples collected during September to October in 2009.
{
Among those samples with HI titer$40, 14 (9.8%), 12 (8.2%), and 3 (18.8%) showed neutralization antibody titer.10 in the 5–18, 19–60, and .60 age groups,
respectively.
doi:10.1371/journal.pone.0014555.t002
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to be caused by influenza A were further identified as positive for
2009 pandemic H1N1. It is consistent with our serological finding
of intense transmission of the pandemic influenza virus from July
to October with an average of 71.1% having an HI titre of greater
than or equal to 10 and also an average of 29.7% having an HI
titre greater than or equal to 40 (Table 2).
Based on seroconversion (titre turns into 1:10) or a four-fold
increase of the serum titre of the susceptible population in different
periods, we conclude that the average incidence rate during the
age groups, there were twice as many study subjects from rural
area as those from the urban city. Because of the free vaccination
policy for schoolchildren and people over 65 years old, 61.5% and
50% of study subjects voluntarily received 2008/2009 seasonal
influenza vaccine in the 5–18 and .60 age groups, respectively.
However, only 6.8% of subjects from the 19–60 age groups had
been vaccinated (Table 1).
In this study, we detected little or no preexisting cross-reactive
antibodies against the 2009 H1N1 virus in the 306 samples from
all three age groups. Although the GMT of antibodies against the
H1N1 vaccine or seasonal strain were significantly high in the sera
collected before 2009 among all three age groups, only three had
the titre at or above 1:10, including 2 (12.5%) from the .60 age
group and 1 (0.7%) 56 years old grouped with the 19–60 years old
(Tables 1 and 2). In the follow-up sera collected from April to
June, the overall decrease of the GMT of the antibodies against
the H1N1 vaccine or seasonal strain was observed (Table 1).
However, 3.5%, 5.4%, and 6.3% of the people from the schoolage, adult, and .60 age groups, respectively, were observed
having a four-fold increase of HI antibodies against seasonal and
2009 pandemic H1N1 simultaneously. Likewise, 2.8%, 0%, and
0% of these three groups had a four-fold increase of the HI
antibodies that simultaneously acts against the vaccine strain and
2009 pandemic H1N1 in the school-aged, adult, and .60 age
groups, respectively.
Table 2 shows the proportion of samples in each age group with
antibody titre at or above the minimum detection limit (1:10) or
with a titre at least four times the minimum detection limit of the
HI assay (1:40). one of the sera collected during the 1st sampling
period presented HI titres greater than 40. Among the sera from
the same group collected during the second sampling period
(April–June), there were 23.1%, 28.6%, and 43.8% in the
respective school-aged, adult, and .60 age groups with HI titres
at or above 1:10. Similar attack rates by 2009 pandemic H1N1
among three age groups (13.3%, 14.3%, and 18.8% from the
young, adult, and old age groups, respectively) were observed if
HI$40 was used as the cutoff. Interestingly, significant proportions of blood samples (72.7%, 82.3%, and 100% in the respective
young, adult, and older age groups) showed HI titers at or above
1:10 in the sera collected during the third sampling period
(September–October). Again, by using HI$40 as the cutoff, there
was an average of 31.7% having an antibody titer against 2009
pandemic H1N1 among three age groups (30.8%, 33.3%, and
25% from the young, adult and old age groups, respectively). Agespecific reverse cumulative distribution curves of the HI titre from
the blood samples collected at different times among the three age
groups is given in Figure 1.
The time course of the early phase infection from April to June
before the first wave of the 2009 pandemic H1N1 influenza virus is
shown in Figure 2.The time distribution of blood samples collected
during the first week of April to the last week of June is shown in
Figure 2. Surprisingly the earliest time period from nine blood
samples with the HI titre against 2009 pandemic H1N1 greater
than 40 was between April 5 and 11, which is much earlier than
what our clinical H1N1 surveillance system suggested and the first
official imported case. Particularly, 4 out of 9 samples were from
the children and the rest were from the family contacts.
The first wave of 2009 pandemic H1N1 began around July 1
and lasted until the end of September, and was soon followed by
the second wave of the fall/winter epidemic with a rapid
insurgence of clinically severe influenza cases between October
and November that significantly dropped after December, perhaps
due to the mass vaccination (Figure 3). The laboratory surveillance
data also supported that 90% of the clinical severe cases confirmed
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Figure 1. Reverse cumulative distribution curves of antibody
titre measured by haemagglutination inhibition assay during
April to June and July to October, 2009 among (a) 5–18 age
group (b) 19–60 age group (c) .60 age group.
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Figure 2. Time course of the early phase before the first wave of 2009 pandemic H1N1. Rectangular bar represented the numbers of sera
collected in each week and the antibody titre less than 10 by haemagglutination inhibition assay in white, but in black if equal to or greater than 10.
Dash line represented the probably pandemic H1N1 cases fulfilled with the case definition according to the clinical surveillance system. Solid line
represented the confirmed H1N1 cases by laboratory confirmation.
doi:10.1371/journal.pone.0014555.g002
further traced back to the infection period at least before the late of
March based on the duration of sero-conversion after infection.
Countries in Asia, though far away from the American continent,
could be affected as early as the epidemic occurred in Mexico in
March as the seroepidemiological studies conducted in Singapore
also implied similar findings [21]. Moreover, a recent modeling
study in Australia suggests that community transmission of pH1N1
was well established in the state of Victoria in April when the virus
was first identified in North America [22]. Therefore, it is plausible
the 2009 pandemic influenza virus had spread globally much
earlier than any imported cases being detected by the surveillance.
Knowledge of virus-specific immunity in the population and the
manner in which it changed as the pandemic progressed is essential
for understanding disease transmission. With a direct serological
measurement from the sequential specimens of the cohort population, the virus transmission pattern can be estimated from the
immunity profile instead of from the clinical attack rate, especially
when there may be one-third of asymptomatic or mild infections as
reported from the previous volunteer challenge studies [23].
Moreover, most of the studies provide clinical or infection attack
rates during the epidemic phase, while our study for the first time in
our knowledge gives the immunity profile during the early phase and
the first wave of the epidemic. This gave us a better understanding
regarding virus transmissibility in different phases of the epidemic as
well as its association with clinical surveillance and the effect of
control measures including quarantine and surveillance system such
as airport fever screening implemented worldwide since May.
Another unique strength of our study is the longitudinal followup of the same household cohort which provides the immunity
level in different stages of the epidemic. Most studies used the
early phase (April–June) of the first wave of the pandemic was
26.8%, ranging from 23.1% in the 5–18 age group to 43.8% in the
.60 age group. Meanwhile, the incidence rate during the first
wave (July–October) of the pandemic averaged 71.1%. If the HI
titre$40 was determined as seroconversion, the incidence rate
during April–June and July–October would be 14.1% and 29.7%
on the average, respectively (Table 2).
Since the sample size in the .60 age group was too small, the
GEE estimate and 95% point-wise CI of the cumulative incidence
rate were stratified by the school-age and adult (.18 years old) age
groups by combining the adult (19–60) and elderly (.60) age
group as shown in Figure 4. The transmission pattern increased
smoothly with an incidence rate of 8.3% by April 5, followed by an
incidence rate of 14% by April 14, and a gradual increase to
18.2% by the end of June in the school-aged group. However, in
the adult age group there was a nearly four-time increase in the
cumulative incidence rate from 6.2% by April 5 to 23.3% by April
12 and then remained nearly unchanged with a cumulative
incidence rate of 24.5% by the end of June. The transmissibility of
2009 H1N1 pandemic influenza virus during the early phase of the
epidemic, as measured by the effective reproductive number R0,
was 1.16 (95% CI: 0.98–1.34). However, the transmissibility of the
virus intensified during the second phase, between July and
September, when R0 = 1.87 (95% CI: 1.68–2.06).
Discussion
Our study identified that the earliest blood sampling time period
with the HI titer against 2009 pandemic H1N1 greater than 40
was in the three weeks between April 5 and 11, which could be
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Figure 3. Numbers of hospitalized H1N1 influenza cases and positive H1N1 isolates based on influenza surveillance system in
Taiwan. (Source: CDC-Taiwan Novel Influenza A/H1N1 website).
doi:10.1371/journal.pone.0014555.g003
equal to 40 without accounting for a pre-immunity status
[12,24,25]. It is surprising to find a high seroconversion rate
during the second and third sampling periods of the epidemic after
cross-sectional serum samples collected either before or after the
epidemic, and the calculation of seroprevalence data would have
to be based on a certain cut-off such as an HI titre greater than or
Figure 4. The GEE estimates and 95% point-wise confidence intervals of the cumulative incidence rate during April to June, 2009
for different age groups.
doi:10.1371/journal.pone.0014555.g004
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accounting for the pre-immunity status of the cohort. Our data
suggests that the attack rate could be much higher than what we
expected if pre-immunity is taken into consideration.
Although the 2009 pandemic H1N1 is antigenically and
genetically distinct from haemagglutinins of contemporary human
seasonal influenza H1N1 viruses, some degree of cross-reactivity
with H1N1 seasonal influenza viruses exists, especially in the older
age population as suggested by our data and previous publications
[3,12]. However, the cross-reactive antibody is unlikely to be
derived from previous immunization with seasonal influenza
vaccine, since such vaccination has been shown to induce little or
no cross-reactive antibody to the 2009 pandemic H1N1 virus in
any age group [3]. There was a possibility that the sero-positivity
of the second blood samples collected during April–June came
from cross-reactivity of seasonal H1N1 influenza virus, which
circulated in early 2009 in Taiwan as has been documented
before. A set of samples collected during April–June, 2009 with HI
titer$40 was further confirmed by the micro-neutralization assay
and the result suggested that 9.8%, 8.2%, and 18.8% of the young,
adult, and old age groups, respectively, had neutralization titer
equal to or greater than 10 against pH1N1, as compared to,
respectively, of 13.3%, 14.3%, and 18.8% of the HI titers from the
young, adult, and old age groups (Table 2). Although it is still
possible that the cross-reactive antibodies present in the serum
could still neutralize the virus, our incidence rate during the early
phase (April to June) of the epidemic was still quite significant.
Our seropositivity rates by April–June were flat with respect to
age (Table 2), while the observation across the world was that for
pandemic H1N1 school-age children were most affected with high
infection rates whereas few elderly were infected. However, since
our cohort was based on a household study design, it may not
reflect the infection pattern in the general population. On the
other hand, it highlights the important role of children in
household transmission of influenza [26], since these adults in
our study all live with children and perhaps hence are more likely
to be infected at home than adults in general. The lack of
virological confirmation also poses a limitation to our study. Also,
the gender distribution was about 1:1 in the 5–18 age group but
about twice and three times as many females as males in the 19–60
and older than 60 age groups, respectively (Table 1), perhaps
because more females were at home during the blood sampling.
Our estimate of the incidence rate during July–October was
29.7% on the average, which was very similar to the previous
publications with 21% in the US and 32% in England [12,24].
Furthermore, the blood samples collected from the populations
living in urban and rural areas also suggest a significant difference
in seropositivity as suggested previously by Miller et al [12].
Regional variations in seropositivity might be caused by higher
transmissions or the higher likelihood of cases being imported to
more densely populated regions. Further serum samples during
follow-up studies will be tested to document the cumulative
incidences of infection by region after the second fall/winter wave
of the epidemic, and to investigate whether R0 does vary between
regions, which might be associated with factors such as population
density, household structure, or social contact patterns.
Based on our serological data, the estimate of R0 during the
early phase before the first wave of the epidemic (Apr–Jun) is 1.16,
which increased to 1.87 during the first wave of the epidemic
(July–September). The estimate for first wave of the epidemic is
very close to the previous publications based on US school
outbreaks and Mexico [7,13,27]. Whether different generation
time, social contacts, or secondary attack rate would apply to the
pre-epidemic phase due to virus transmissibility pattern or viral
load is a topic for future research [28–30].
In summary, our serological results, in combination with the
longitudinal study design, show a unique pattern of 2009
pandemic H1N1 infections in different phases of the first wave
of the pandemic in Taiwan. This finding should be applicable to
other countries that have experienced a similar first wave.
Together with the surveillance data, virological surveillance, and
serological finding, our study provides valuable insights into the
epidemiology of the disease and how this relates to pre-immunity
status. This data has been further validated by using Taiwan-CDC
pH1N1 hospitalization surveillance data to construct a simple
mathematical model to investigate the impact of mass immunization in Taiwan (Hsieh et al. manuscript in preparation). This
study, together with the serological data, indicates that the number
of infections started to become saturated by mid-November, which
suggests that by the time the mass immunization took place in
November, the potential for mitigating the overall effect of the
second wave by vaccination was relatively limited, perhaps due to
population-level immunity acquired from previous infection and
intervention such as a class closing policy that had already been in
place. Our study will continue to provide the age-specific baseline
antibody prevalence and infection rates for specific subtypes (H1,
H3 and B) to enhance our understanding of the epidemiology of
influenza and its association with the role of transmission played
by schoolchildren within households and community, as well as
the potential benefits of vaccine protection within household and
to the whole population.
Acknowledgments
We would like to thank Lydia Wang for English editing. The authors are
grateful to the referees for constructive comments which significantly
improved this paper.
Author Contributions
Conceived and designed the experiments: KFC TCL TNW CAT JHC
YHH. Performed the experiments: DYC CYC HTC JJL MCS YHL
WCC. Analyzed the data: DYC KFC TCL TNW CYC CAT JHC HTC
YHH. Contributed reagents/materials/analysis tools: JJL. Wrote the
paper: DYC KFC YHH.
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