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C O R R E S P O N D E N C E Open Access
Comparison of five influenza surveillance systems
during the 2009 pandemic and their association
with media attention
Marit MA de Lange
1*
, Adam Meijer
1
, Ingrid HM Friesema
1
, Gé A Donker
2
, Carl E Koppeschaar
3
, Mariëtte Hooiveld
2
,
Nel Ruigrok
4
and Wim van der Hoek
1
Abstract
Background: During the 2009 influenza pandemic period, routine surveillance of influenza-like-illness (ILI) was
conducted in The Netherlands by a network of sentinel general practitioners (GPs). In addition during the pandemic
period, four other ILI/influenza surveillance systems existed. For pandemic preparedness, we evaluated the
performance of the sentinel system and the others to assess which of the four could be useful additions in the
future. We also assessed whether performance of the five systems was influenced by media reports during the
pandemic period.
Methods: The trends in ILI consultation rates reported by sentinel GPs from 20 April 2009 through 3 January 2010
were compared with trends in data from the other systems: ILI cases self-reported through the web-based Great
Influenza Survey (GIS); influenza-related web searches through Google Flu Trends (GFT); patients admitted to
hospital with laboratory-confirmed pandemic influenza, and detections of influenza virus by laboratories. In
addition, correlations were determined between ILI consultation rates of the sentinel GPs and data from the four
other systems. We also compared the trends of the five surveillance systems with trends in pandemic-related
newspaper and television coverage and determined correlation coefficients with and without time lags.
Results: The four other systems showed similar trends and had strong correlations with the ILI consultation rates
reported by sentinel GPs. The number of influenza virus detections was the only system to register a summer peak.
Increases in the number of newspaper articles and television broadcasts did not precede increases in activity
among the five surveillance systems.
Conclusions: The sentinel general practice network should remain the basis of influenza surveillance, as it
integrates epidemiological and virological information and was able to maintain stability and continuity under
pandemic pressure. Hospital and virological data are important during a pandemic, tracking the severity,
molecular and phenotypic characterization of the viruses and confirming whether ILI incidence is truly related to
influenza virus infections. GIS showed that web-based, self-reported ILI can be a useful addition, especially if
virological self-sampling is added and an epidemic threshold could be determined. GFT showed negligible
added value.
Keywords: Influenza virus, Pandemic, Surveillance, Influenza-like illness, Media attention
* Correspondence: marit.de.lange@rivm.nl
1
National Institute for Public Health and the Environment (RIVM), Centre for
Infectious Disease Control Netherlands, P.O. Box 1, 3720 BA Bilthoven,
The Netherlands
Full list of author information is available at the end of the article
© 2013 de Lange et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
de Lange et al. BMC Public Health 2013, 13:881
http://www.biomedcentral.com/1471-2458/13/881
Background
In April 2009, the first cases of influenza A(H1N1)pdm09
virus infection were confirmed in Mexico and the United
States [1]. On 11 June 2009, the World Health Org-
anization declared the first influenza pandemic of the 21st
century [2]. In The Netherlands, the first case was con-
firmed on 30 April 2009 [3], and influenza activity was
increased from 5 October through 13 December 2009 [4].
The Dutch Continuous Morbidity Registration sentinel
general practice network was established in 1970 for sur-
veillance of influenza-like illness (ILI). Following the
1992/1993 influenza season, virological investigation was
added to the network [4]. Most European countries have
comparable integrated epidemiological-virological senti-
nel surveillance systems [5]. However, even before the
2009 pandemic, the ability of these systems to cope with
pressure during a pandemic was a matter of concern.
There was discussion as to whether or not ancillary sur-
veillance systems were needed in preparation for and dur-
ing a pandemic [6]. During the 2009 pandemic in The
Netherlands, four other surveillance systems were used.
These included an internet-based monitor of self-reported
ILI symptoms in the Dutch and Belgian general popula-
tion: the Great Influenza Survey (GIS) [7,8]. Another was
Google Flu Trends (GFT), that estimates ILI incidence
based on influenza-related queries to online search en-
gines [9]. A third system was the number of influenza
virus detections reported by virology laboratories. Finally,
during the pandemic period, all hospitals were required to
report patients admitted due to laboratory-confirmed
influenza A(H1N1)pdm09 virus infection [10,11].
Throughout the pandemic period in Europe, strong media
coverage took place. In Wales, the first wave of ILI consult-
ation rates reported by sentinel general practitioners (GPs)
in 2009 was possibly influenced by the intensive media ac-
tivity[12].Themediaareknowntobeabletoinfluencethe
behavior of the public as well as health professionals [13].
IntheUK,mediacoveragemayhavebiasedestimatesofILI
and influenza virus infections, as it created significant anx-
iety in the population [14]. In The Netherlands, coverage
may have influenced information-seeking behavior on the
internet, participation in web-based surveillance systems,
healthcare-seeking behavior, and laboratory testing practices.
In preparation for a future influenza pandemic, it is im-
portant to evaluate how the Dutch sentinel general practice
network and the four other surveillance systems performed
during the pandemic period in 2009. Therefore, our aim
was to assess the performance of the routine influenza sur-
veillance system (ILI consultation rates reported by sentinel
GPs) and whether the other available surveillance systems
would be useful additions to the sentinel system. We also
studied whether increased media coverage influenced the
data trends of the five surveillance systems during the pan-
demic period.
Methods
Data sources
GP data
The sentinel general practice network covers a patient
population which represents the national population in
gender, age, regional distribution, and population density
[4]. In 2009, the network included 42 sentinel practices
that had a total of 129,065 enrolled patients in the average
year. In June 2009, an additional 12 general practices ac-
cepted to join the network from the Netherlands Information
Network of GPs care (LINH) and participated in surveil-
lance for the duration of the pandemic [15]. The network
defined ILI as sudden onset, fever (≥38.0°C) accompanied
by cough, sore throat, running nose, frontal headache,
retrosternal chest pain or muscle pain [4]. Incidence was
defined as the weekly number of people who consulted
their GP with ILI divided by the total number of patients
enrolled in the sentinel practices. Increased influenza ac-
tivity was defined as an ILI consultation rate higher than
5.1 per 10,000 persons for two consecutive weeks, accom-
panied by detection of influenza virus in respiratory speci-
mens. Each general practice took a nose and throat swab
from two ILI patients per week. Practices who saw no
such patients in a given week were requested to swab two
patients with another acute respiratory infection (ARI)
[16]. To evaluate how well the sentinel general practice
network functioned during the pandemic, we compared
2009 with the five preceding years (2004 through 2008) as
to the percentage of days for which a sentinel group
reported no ILI/influenza cases.
To estimate the workload of the GPs during the pan-
demic period, we accessed the electronic medical files of all
68 LINH GPs to obtain data on all their patient contacts
by diagnosis and type of consultation: i.e. clinic visits, home
visits, and telephone consultations [15]. All consultations
for influenza, as defined by the International Classification
of Primary Care code R80, were included and the weekly
number was expressed per 10,000 enrolled patients.
Informed consent was not needed, as the Dutch Cen-
tral Committee on Research Involving Human Subjects
considers it not obligatory for routine surveillance stud-
ies using anonymous data. The privacy regulation of the
LINH network was approved by the Dutch Data Protec-
tion Authority.
Great Influenza Survey (GIS)
This data was used with permission from the company
Science in Action, which started GIS in the 2003/2004
influenza season. Since that season, yearly press releases
have encouraged people from the Dutch and Belgian gen-
eral population to fill in a web-based baseline questionnaire
asking for demographical, medical and lifestyle data. Partic-
ipants receive a weekly e-mail with a link to a short ques-
tionnaire asking about ILI symptoms experienced since
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their previous visit to the website. When symptoms are
reported, additional questions are asked about GP consul-
tations and whether or not daily activities were adjusted
due to the symptoms. The GIS case definition of ILI is sud-
den onset of fever accompanied by muscle pain and cough
and/or sore throat and/or chest pain. Measurement of
body temperature is not required [8]. The incidence of ILI
was defined as the weekly number of GIS participants
reporting ILI symptoms divided by the total number of
participants that week.
In our study, we excluded Belgian participants and se-
lected the Dutch incidence data with certain restrictions.
Cases of ILI were used only if reported within 2 weeks after
day of onset. Cases were considered recurrent only when
at least one week without symptoms fell between episodes.
A person who participated in GIS more than once in a
given week was counted only once for that week. Finally,
to maximize data reliability, we sought the most active and
experienced participants by 1) eliminating the first instance
of GIS participation for each individual and 2) excluding
any individual with fewer than three instances of participa-
tion. For the pandemic season of 2009, about 20,000 GIS
participants fit these criteria and were used in our study.
Google Flu Trends (GFT)
GFT is a free internet-based surveillance tool which uses
an automated method of selecting ILI/influenza-related
search queries to estimate the ILI incidence. A search
query is a complete, exact sequence of terms issued by a
Google search user. Its weekly estimates reflect findings
from Sunday through Saturday, whereas the other four sur-
veillance systems and media coverage reflect findings from
Monday through Sunday [9]. At http://www.google.org/
flutrends (data openly available), we downloaded the esti-
matedILIincidenceforTheNetherlandsfortheperiod20
April 2009 through 3 January 2010 [17]. No information
was available on participants’background, age or gender.
Hospital admissions
On 29 April 2009, influenza A(H1N1)pdm09 virus infec-
tion was designated a “category A notifiable disease”in
The Netherlands. From that date, doctors and laboratories
had to report the name of the patient to the Municipal
Health Service (GGD) when the infection was suspected
or identified. Each notification was then entered into a na-
tional anonymous and password-protected web-based
database including information on the patient’stravelhis-
tory, vaccination status, clinical symptoms, co-morbidity,
treatments, hospitalisations and contact with symptomatic
cases. On 15 August 2009, the notification criteria changed.
From that date, reporting was mandated only for cases
who were admitted to a hospital or died because of a
laboratory-confirmed influenza A(H1N1)pdm09 virus in-
fection [10,11]. The incidence per week was defined as the
number of hospital admissions divided by the total popula-
tion of The Netherlands in 2009.
As the National Institute for Public Health and the Envir-
onment (RIVM) is legally permitted to use these anonym-
ous data, permission from a research ethics committee was
not needed for our study.
Laboratory detections of influenza virus
Data on influenza virus detections was obtained from
three sources.
From 20 April through 9 August 2009 all suspected influ-
enza A(H1N1)pdm09 cases underwent virological testing at
the National Influenza Center, located at the Erasmus Med-
ical Center in Rotterdam, and at RIVM in Bilthoven. After
29 June through 9 August 2009, this effort was joined by
nine regional outbreak assistance laboratories [18,19].
After 9 August 2009, not all suspected cases were viro-
logically tested anymore. After this date, we therefore used
data of The Dutch Working Group for Clinical Virology.
This group issued its usual voluntary Weekly Virology Re-
port, listing detections of influenza A and B virus at med-
ical microbiological laboratories. These 21 laboratories
around the country included the nine mentioned above.
Also for the total period (20 April 2009 through 3
January 2010), the sentinel GPs continued their normal
routine by collecting nose and throat swabs for virus de-
tection, as described above. The specimens were tested at
the RIVM for the presence of influenza virus types A and
B, and the influenza A viruses were further sub-typed [4].
The reporting week of the positive specimens of the first
period (through 9 August) and those from the sentinel
general practice network was defined as the week in which
specimens were collected. The reporting week of positive
specimens noted in the Weekly Virology Reports was the
week of laboratory diagnosis. Because of the urgency for
laboratory diagnosis during the pandemic period, those
weeks are generally comparable.
All virological data described above are regularly pro-
vided by laboratories to RIVM as part of routine surveil-
lance of influenza. Aggregated data are freely available
at the RIVM website (in Dutch): http://www.rivm.nl/
Onderwerpen/Onderwerpen/V/Virologische_weekstaten/
Rapportages/Open_rapportages_virologische_weekstaten
and http://www.rivm.nl/griep.
Media attention
The Netherlands News Monitor (NNM), an independ-
ent scientific institute researching journalism in The
Netherlands, provided data on media attention. Its re-
searchers screened newspaper articles and television
broadcasts related to the influenza pandemic [20]. They
included national newspapers that are distributed free
of charge five times a week (‘Metro’,‘Spits’,‘de Pers’)and
subscription-based national newspapers distributed six
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times a week (‘NRC Handelsblad’,‘Algemeen Dagblad’,
‘de Volkskrant’,‘Trouw’,‘De Telegraaf ’). These eight
newspapers had a total of 2,964,364 daily copies [21].
For comparison, there were 7 million households in The
Netherlands on 1 January 2009 [22]. For our study, we
selected all articles about the influenza that appeared
from 20 April 2009 through 3 January 2010.
In addition, NNM screened daily news broadcasts on na-
tional television that discussed pandemic influenza. These
included the ‘NOS Journaal’(aired at 8 pm), ‘RTL Nieuws’
(7.30 pm) and ‘Hart van Nederland’(7 pm) [20]. The first
two programs had most viewers, averaging 3.4 and 1.4 mil-
lion. The third program averaged about 1 million but was
included because its audience was considered to be different
from the audience of the other two [23]. The Dutch popula-
tion consisted of 16 million people on 1 January 2009 [22].
Our study focused on all influenza-related broadcasts that
aired from 20 April through 3 January 2010.
For each newspaper or television report, NNM deter-
mined the source from the content of a sample of all
newspapers articles and television broadcasts. The source
was defined as the person or authority that was cited in
the media report [20].
Statistical analysis
Weekly ILI consultation rates reported by the sentinel
GPs and ILI/influenza data from the four other surveil-
lance systems were compared, and Spearman rank cor-
relation coefficients were determined for the period 20
April 2009 through 3 January 2010.
To assess whether the media reports influenced the ILI/
influenza data reported by the five surveillance systems,
the data are graphically displayed and compared for the
period 20 April 2009 through 3 January 2010. In addition,
Spearman rank correlation coefficients were determined
between the weekly ILI/influenza rates and the weekly
number of newspaper articles and television broadcasts
for the same period. Furthermore, Spearman rank correl-
ation coefficients were determined for the periods in
which media attention was observed to coincide with the
trends of the ILI/influenza surveillance systems. Time lags
and 95% confidence intervals of the correlation coeffi-
cients were calculated to investigate if the media attention
preceded rises in ILI/influenza rates.
Statistical significance was set at p < 0.05. All data were
analysed using SAS version 9.2 (SAS Institute Inc., USA).
Results
Trends in ILI/influenza
The ILI consultation rates reported by the sentinel GPs
(Figure 1A) and the incidence of hospital admissions due
to influenza A(H1N1)pdm09 (Figure 1B) both peaked in
the week of 9 November 2009. In the year 2009, the per-
centage of non-reporting days was not higher (9.0%)
compared to the average percentage during the 5 years be-
fore the pandemic (13.2%) [4]. The consultation rates of
the sentinel GPs, indicated increased influenza activity from
5 October through 13 December 2009. Likewise, an average
of 36.8% of sentinel-submitted samples tested positive for
influenza virus, which was higher than seen before or after
this period. The incidence of hospital admissions also
showed a continuous increase from 5 October 2009 on-
wards. The GIS ILI incidence increased from 5 October
2009 onwards (Figure 1C) and peaked in the weeks of 26
October and 9 November 2009. The incidence according to
GFT started to rise one week later, on 12 October 2009,
and peaked in the week of 2 November 2009 (Figure 1D).
The number of influenza virus detections (Figure 1E) had
two peaks: a small summer peak in the weeks of 27 July
and 3 August and a second increase from the week of 19
October onwards with a peak in the week of 9 November
2009. Both peaks coincide with peaks of the number of
newspapers and television broadcasts.
From 20 April 2009 through 3 January 2010, only 26 cases
of influenza virus type B were noted in the Weekly Virology
Report of hospital laboratories in The Netherlands. There-
fore, almost all their influenza virus detections were type
A (n = 6,802). Because almost all sub-typed influenza A
viruses (99.7%) obtained from sentinel GPs were
A(H1N1)pdm09, we assume that the clinical observa-
tions at both sentinel practices and hospitals represented
A(H1N1)pdm09 influenza virus activity.
Distribution of GP visitors and GIS participants
The ILI consultation rates of the sentinel general prac-
tice network were highest for children 0–4 years old,
followed by those 5–14 years old. The lowest ILI con-
sultation rate was seen for people 65 years of age or
older (data not shown).
Most of the GIS participants were 15 to 64 years old
(91.5%), and the majority were female (66.1%).
Type of GP consultations
Figure 2 displays the type of ILI/influenza consultations
with sentinel GPs that occurred from 1 January 2009
through 31 December 2009. The number of clinic and
home visits showed only a slight increase compared to
the 2008/2009 influenza season, but the number of tele-
phone consultations was much higher during the pan-
demic period, comprising half the total. For comparison,
during the peak of the 2008/2009 influenza season, 23%
of all contacts were telephone consultations.
Trends in media attention
In the period from 20 April 2009 through 3 January 2010,
2,194 newspaper articles and 294 television broadcasts
were counted with pandemic flu as a topic. Figure 1F dis-
plays the weekly number of articles and broadcasts about
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influenza virus A(H1N1)pdm09. The number of news-
paper articles peaked several times: in the week of 27
April, 15 June, 20 July, 3 August and 9 November 2009.
Television broadcasts peaked in roughly the same weeks:
27 April, 15 June, 3 August, and 9 November 2009.
The most frequently quoted sources in media reports
about pandemic influenza were from the general society
(e.g. business representatives and ordinary citizens),
the government, and experts such as RIVM and NIVEL
(National Institute for Health Services Research) [20].
Correlations
All four other surveillance systems (GIS, GFT, hospital
admissions, and laboratory detections of influenza) had
a strong correlation with the ILI consultation rates of
the sentinel GPs (Table 1). The highest correlation coef-
ficient was seen for the incidence of hospital admissions,
followed by the ILI incidence estimated by GFT and
reported by GIS, respectively.
The correlation between trends in ILI/influenza rates
and trends in media attention was low to moderate in the
period of 20 April 2009 through 3 January 2010 (Table 2).
The highest correlation coefficient was seen for the num-
ber of influenza virus detections compared to both the
number of newspaper articles (rho = 0.52) and the number
of television broadcasts (rho = 0.36). These correlations
were both statistically significant (p < 0.05). The lowest cor-
relation was seen for the ILI incidence of GIS with both
0
5
10
15
20 ILI consultation rate Epidemic threshold
0
0,1
0,2
0,3
0
25
50
75
100
0
10
20
30
0
500
1000
1500
0
5
10
15
20
25
30
0
50
100
150
200
20-Apr
4-May
18-May
1-Jun
15-Jun
29-Jun
13-Jul
27-Jul
10-Aug
24-Aug
7-Sep
21-Sep
5-Oct
19-Oct
2-Nov
16-Nov
30-Nov
14-Dec
28-Dec
Monday of reported week
Newspaper articles Television broadcasts
A
B
C
D
E
F
Figure 1 Trends in media attention and ILI/influenza rates in 2009. A. ILI/influenza consultation rates reported by the sentinel general practices
per 10,000 enrolled patients. B. Number of hospitalisations for influenza type A(H1N1)pdm09 infection per 10,000 inhabitants. C. ILI incidence, Great
Influenza Survey, per 10,000 participants. D. Estimated ILI incidence, Google Flu Trends, per 10,000 inhabitants. E. Total number of influenza virus
detections. F. Number of newspaper articles (left axis) and number of television broadcasts (right axis) related to pandemic influenza. The vertical red
lines indicate peaks of media attention which coincided with the peaks of ILI/influenza data reported by surveillance systems.
de Lange et al. BMC Public Health 2013, 13:881 Page 5 of 10
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media types. The correlations between media attention
and the five surveillance methods in the peak period (31
August 2009 through 3 January 2010) were stronger com-
pared to the whole period (Table 3). The 95% confidence
intervals of the correlation coefficients with one-week
time lag overlapped those of the same week (data not
shown). This result was seen for the peak in media atten-
tion in the period of 29 June 2009 through 23 August
2009 and for the peak in the period 31 August 2009
through 3 January 2010.
Discussion
Key findings and interpretation
The sentinel general practice network maintained its sta-
bility and continuity during the pandemic in 2009, as GPs
continued to report their weekly ILI consultation numbers
and provide valid information for action. However, even in
this relatively mild pandemic, their workload was higher
than in the 2008–2009 influenza season, mainly due to an
increased number of telephone consultations and extra in-
fluenza vaccinations.
All five ILI/influenza surveillance systems showed the
same trends, with a strong correlation between the rou-
tinely used sentinel general practice network and the
four other systems. However, the number of influenza
virus detections was the only surveillance data that reg-
istered a summer peak in the week of 3 August 2009.
This was the result of a policy of intensive case-finding
and the return of infected travellers during that period.
Probably because effective transmission had not been
established at the time, the other systems did not detect
this summer peak.
From this study, it is hard to conclude which other sys-
tem gave an earlier signal of increased influenza activity in
the pandemic peak period than the ILI consultation rates
reported by the sentinel GPs, because the trends were very
similar, and a mathematically derived epidemic threshold
was available only for the sentinel general practice net-
work. No surveillance system gave an earlier increase in
the pandemic period compared to the increased influenza
activity determined by the sentinel GPs. Although, in the
seasons 2003/2004 through 2007/2008 the trend in GIS-
ILI incidence was one week ahead compared to the ILI
consultation rates reported by the sentinel GPs [8].
Since all five ILI/influenza surveillance systems showed
the same trends during the 2009 pandemic period, which
of the other systems would be a useful addition to the sen-
tinel general practice network during a future pandemic?
Information about hospital admissions is a very important
addition, providing information about the severe cases.
Virological data is likewise valuable, being needed to
0
5
10
15
20
25
30
35
40
45
29-Dec
12-Jan
26-Jan
9-Feb
23-Feb
9-Mar
23-Mar
6-Apr
20-Apr
4-May
18-May
1-Jun
15-Jun
29-Jun
13-Jul
27-Jul
10-Aug
24-Aug
7-Sept
21-Sept
5-Oct
19-Oct
2-Nov
16-Nov
30-Nov
14-Dec
Number of contacts / 10,000 enrolled
patients
Monday of reported week
Clinic visits Home visits Telephone consultations
Figure 2 General practitioner-patient contacts for influenza in The Netherlands Information Network of General Practice (LINH) during
the year 2009.
Table 1 Correlation between ILI consultation rates of the sentinel general practice network and four other
surveillance systems
*
Number of hospital
admissions/10,000 inhabitants
ILI incidence
GIS/10,000 participants
Estimated ILI incidence
GFT/10,000 inhabitants
Number of influenza
virus detections
ILI consultation rates, sentinel
GPs/10,000 enrolled patients
0.92 0.84 0.84 0.77
(p < 0.001) (p < 0.001) (p < 0.001) (p < 0.001)
ILI influenza-like illness, GIS Great Influenza Survey, GP general practitioner, GFT Google Flu Trends.
*Spearman rank correlation coefficients were determined for the complete study period (20-4-2009 through 3-1-2010).
de Lange et al. BMC Public Health 2013, 13:881 Page 6 of 10
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confirm whether the ILI incidence is truly related to
influenza virus infections, to monitor for virulence and
resistance markers, to monitor for possible changes in
immune-dominant regions, and to estimate the efficacy of
current vaccines. With regard to recommendations of
strains for future vaccines, antigenic characterization data
is important to understand the match of circulating vi-
ruses with the current vaccine strain. The GIS system
could be a useful addition, because it measures the ILI
incidence directly in the community. Additionally, it is a
cheap and flexible system and collects a lot of background
information about participants. Its value will increase if it
adds virological testing, thus combining epidemiological
and virological data. The GFT system, however, adds no
information compared to the other systems and reveals
nothing about its users or whether they truly had an influ-
enza infection.
According to the agenda-setting theory, newspapers and
broadcasts select certain topics and omit certain topics.
This selective coverage influences what subjects the audi-
ence knows about, thinks about, and has feelings about
[24,25]. The influenza pandemic turned out to be a big
topic in the news media at various points in the period
from 20 April 2009 through 3 January 2010, with an im-
portant potential impact on the public agenda and the sur-
veillance data. While causal inference cannot be inferred,
this study provides no indication that media attention pre-
ceded increasing trends in ILI incidence and influenza
virus detections as reported in five surveillance systems
during the pandemic period. We found that the number
of newspaper articles and television broadcasts peaked
more often compared to the surveillance data. Correla-
tions between the five surveillance systems and media at-
tention were low-moderate in the pandemic period
covering 20 April 2009 through 3 January 2010, albeit
stronger in the peak pandemic period from 31 August
2009 through 3 January 2010. Even in that peak period,
media coverage did not peak earlier than data from sur-
veillance systems. The 95% confidence intervals of the cor-
relation coefficients between the media attention and the
five surveillance systems with one-week time lag did over-
lap those of the same week. Finally, there was no indication
that media attention preceded the number of laboratory de-
tections of influenza at its summer peak (29 June 2009
through 23 August 2009).
In the intensive case finding period of the pandemic (till
9 august 2009), weekly reports of laboratory detections of
cases were presented on Fridays on the website of the
RIVM (http://www.rivm.nl). Therefore, the summer peak
in media attention probably reflects the weekly reports of
the case finding as reflected in the number of A(H1N1)
pdm09-positive specimens (Figure 1E).
Comparison to other studies
The comparability between traditional surveillance sys-
tems (ILI consultation rates reported by sentinel GPs) and
Table 2 Correlation between five influenza surveillance systems and media attention, 20-4-2009 –3-1-2010*
Surveillance system Number of newspaper articles Number of television broadcasts
Spearman rank
correlation coefficient
P-value Spearman rank
correlation coefficient
P-value
ILI consultation rates, sentinel GPs/10,000 enrolled patients 0.32 0.055 0.22 0.188
Number of hospital admissions/10,000 inhabitants 0.22 0.183 0.15 0.372
ILI incidence, GIS/10,000 participants 0.06 0.706 0.09 0.585
Estimated ILI incidence, GFT/10,000 inhabitants 0.34 0.039 0.23 0.162
Number of influenza virus detections 0.52 <0.001 0.36 0.030
ILI influenza-like illness, GIS Great Influenza Survey, GP general practitioner, GFT Google Flu Trends.
*Spearman rank correlation coefficients were determined for the complete study period (20-4-2009 through 3-1-2010).
Table 3 Correlation between five influenza surveillance systems and media attention, 31-8-2009 –3-1-2010*
Number of newspaper articles Number of television broadcasts
Spearman correlation
coefficient
P-value Spearman
correlation coefficient
P-value
ILI consultation rates, sentinel GPs/10,000 enrolled patients 0.74 <0.001 0.68 0.002
Number of hospital admissions/10,000 inhabitants 0.74 <0.001 0.80 <0.001
ILI incidence, GIS/10,000 participants 0.49 0.038 0.59 0.010
Estimated ILI incidence, GFT/10,000 inhabitants 0.62 0.006 0.61 0.007
Number of influenza virus detections 0.79 <0.001 0.79 <0.001
ILI influenza-like illness, GIS Great Influenza Survey, GP general practitioner, GFT Google Flu Trends.
*Spearman rank correlation coefficients were determined for the period in which media attention coincided with trends of the ILI/influenza surveillance systems
(31-8-2009 through 3-1-2010).
de Lange et al. BMC Public Health 2013, 13:881 Page 7 of 10
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newer surveillance systems (GIS and GFT) was established
in several countries in non-pandemic years [7-9,26,27].
Our research and other studies confirm that this compar-
ability also existed during the pandemic period [28-32].
The findings of our study are in line with those from
New Zealand where trends of media attention peaked more
often than trends of GFT-estimated ILI incidence and con-
sultation rates reported by the national sentinel general
practice network during the pandemic period [28]. In
Guam, similar to our study, a high correlation was found
between the temporal pattern in number of ‘swine flu’stor-
ies and the temporal pattern in clinical diagnoses of ARI in
the emergency department of a hospital and laboratory-
confirmed cases of influenza A(H1N1)pdm09. Unlike our
study, the number of ‘swine flu’stories peaked one week
earlier compared to the hospital emergency room ARI data,
suggesting media influence on consultation behavior. How-
ever, no correlation coefficients with time lag were deter-
mined in that study [33]. In the UK, newspaper coverage
about A(H1N1)pdm09 likewise increased one week before
increases in the number of laboratory-confirmed cases in
thebeginningofthepandemicperiod[34].
Limitations
Several limitations were inherent to the surveillance sys-
tems examined in this study. For example, the sentinel
general practice network mostly captured young children,
both during the pandemic and in the seasons before [35],
probably because young children are brought to the doc-
tor by concerned parents. During the pandemic, GIS-ILI
cases were not virological confirmed, although it began to
address this limitation in the 2011/2012 influenza season,
requiring the GPs in Belgium to swab patients and also
starting a pilot program in Sweden that includes self-
sampling. Moreover, in this study, GIS participants did not
represent the Dutch general population, with 91.1% of par-
ticipants being 15 to 64 years of age whereas 67.3% of the
Dutch population falls in this age group. In addition, more
women than men participated than are represented in the
general population (67.3% versus 50.5%) [36]. During the
years 2003 through 2008, children and the elderly were un-
derrepresented in GIS; its elderly population was healthier,
participants aged 15–24 years were less often employed,
and participants under 45 had a higher vaccination uptake
compared to the Dutch population [8]. Like GIS, GFT is
prone to selective participation and in addition lacks viro-
logical confirmation.
Besides the limitations inherent to the surveillance sys-
tems, other limitations were associated with our study. We
only counted the newspaper articles and television broad-
casts about influenza A(H1N1)pdm09 which had been col-
lected in context of another study [20]. Beyond articles and
broadcasts, people could have obtained information about
thepandemicfromothersources, such as social media
[37,38]. As an emerging source of information, social media
was hypothesized to have limited impact on our study dur-
ing the pandemic period, but it should be monitored in fu-
ture studies. An epidemic threshold was only determined
for the ILI consultation rates reported by the sentinel GPs
[39], and its determination fortheothersurveillancesys-
tems would possibly assess the period of increased influ-
enza activity in an earlier way. A final limitation of this
study is that there was no daily data available for most of
the surveillance systems. Therefore, we could not investi-
gate the influence of the media attention on a daily basis.
Conclusions
Results of different surveillance systems during the influ-
enza pandemic showed similar trends and were highly cor-
related with each other. There was no indication that
media attention influenced the trends in ILI/influenza
rates. The number of virus detections was the only system
which registered a summer peak, thus giving the earliest
signal. The ILI consultation rates reported by the sentinel
GPs remain the basis of surveillance in The Netherlands,
because the system integrates epidemiological and viro-
logical information and was able to sustain its operation
under pandemic pressure. Hospital data and virological
data will remain very important during a pandemic period,
providing information on the severity, molecular and
phenotypic characterization of the viruses, and whether
the ILI incidence is truly related to influenza virus infec-
tions. GIS can be a good addition during a pandemic
period, because it is a cheap and flexible method and pro-
vides a lot of background information about the partici-
pants. GIS will be even more useful when it includes
virological testing and when determination of an epidemic
threshold can help to detect an impending epidemic. GFT
showed negligible added value.
Abbreviations
ARI: Acute respiratory infection; GFT: Google flu trends; GGD: Municipal health
services; GIS: Great influenza survey; GP: General practitioner; ILI: Influenza-like
illness; LINH: Netherlands information network of GPs care; NIVEL: Netherlands
institute for health services research; NNM: Netherlands news monitor;
RIVM: National institute for public health and the environment; SAS: Statistical
analysis software.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
MMAdL contributed to the design of the study, performed the statistical
analysis, and drafted the manuscript. WvdH contributed to the design of the
study and helped to draft the manuscript. IHMF assisted with the statistical
analysis and reviewed the article critically. AM coordinated the virus
diagnostics, provided help with the data collection and revised the article.
GAD, MH, NR and CEK collected data and reviewed the article critically. All
authors read and approved the final manuscript.
Acknowledgements
We thank the participating general practices for their cooperation in the data
collection. Next, we thank the Municipal Health Services (GGD), hospitals,
and laboratories throughout The Netherlands for providing data; the
de Lange et al. BMC Public Health 2013, 13:881 Page 8 of 10
http://www.biomedcentral.com/1471-2458/13/881
technicians of the Laboratory for Infectious Diseases and Screening of the
National Institute for Public Health and the Environment (RIVM), and the
Department of Virology of the Erasmus Medical Centre Rotterdam for
performing the virological diagnostic tests. Part of this work was supported
by the Netherlands Organisation for Health Research and Development
ZonMW (grant number 125050003).
Author details
1
National Institute for Public Health and the Environment (RIVM), Centre for
Infectious Disease Control Netherlands, P.O. Box 1, 3720 BA Bilthoven,
The Netherlands.
2
NIVEL, Netherlands Institute for Health Services Research,
P.O. Box 1568, 3500 BN Utrecht, The Netherlands.
3
The Great Influenza
Survey / Science in Action, P.O. Box 1786, 1000 BT Amsterdam,
The Netherlands.
4
The Netherlands News Monitor, Buitenveldertselaan 3,
1082 VA Amsterdam, The Netherlands.
Received: 13 August 2012 Accepted: 16 September 2013
Published: 24 September 2013
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doi:10.1186/1471-2458-13-881
Cite this article as: de Lange et al.:Comparison of five influenza
surveillance systems during the 2009 pandemic and their association
with media attention. BMC Public Health 2013 13:881.
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