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R E S E A R C H A R T I C L E Open Access
Q fever in the Netherlands: public perceptions
and behavioral responses in three different
epidemiological regions: a follow-up study
Marloes Bults
1,2*
, Desirée Beaujean
3
, Clementine Wijkmans
4
, Jan Hendrik Richardus
1,2
and Hélène Voeten
1,2
Abstract
Background: Over the past years, Q fever has become a major public health problem in the Netherlands, with a
peak of 2,357 human cases in 2009. In the first instance, Q fever was mainly a local problem of one province with a
high density of large dairy goat farms, but in 2009 an alarming increase of Q fever cases was observed in adjacent
provinces. The aim of this study was to identify trends over time and regional differences in public perceptions and
behaviors, as well as predictors of preventive behavior regarding Q fever.
Methods: One cross-sectional survey (2009) and two follow-up surveys (2010, 2012) were performed. Adults,
aged ≥18 years, that participated in a representative internet panel were invited (survey 1, n = 1347; survey 2, n = 1249;
survey 3, n = 1030).
Results: Overall, public perceptions and behaviors regarding Q fever were consistent with the trends over time in the
numbers of new human Q fever cases in different epidemiological regions and the amount of media attention focused
on Q fever in the Netherlands. However, there were remarkably low levels of perceived vulnerability and perceived
anxiety, particularly in the region of highest incidence, where three-quarters of the total cases occurred in 2009. Predictors
of preventive behavior were being female, older aged, having Q fever themselves or someone in their household, more
knowledge, and higher levels of perceived severity, anxiety and (self-) efficacy.
Conclusions: During future outbreaks of (zoonotic) infectious diseases, it will be important to instil a realistic sense of
vulnerability by providing the public with accurate information on the risk of becoming infected. This should be given in
addition to information about the severity of the disease, the efficacy of measures, and instructions for minimising
infection risk with appropriate, feasible preventative measures. Furthermore, public information should be adapted to
regional circumstances.
Keywords: Zoonotic infections, Q fever, Risk perception, Behavioral responses, General public, risk communication
Background
Q fever is a zoonosis caused by the bacterium Coxiella
burnetii. The primary reservoirs of the bacterium are farm
animals, including goats, sheep, and cattle [1]. Acute Q
fever typically presents as an influenza-like illness, but se-
vere infections, like pneumonia and/or hepatitis, may also
occur [2,3]. Approximately, 1-5% of all Q fever cases may
progress to a chronic infection, which often leads to life-
threatening endocarditis. Although Q fever is associated
with substantial morbidity, mortality is uncommon (1-2%
of cases) [1,4].
In the Netherlands, the first community outbreak of Q
fever occurred in 2007, in the southern region of the
Netherlands [5,6]. By the end of that year, 168 human Q
fever cases were reported [7]. The second wave, in 2008,
resulted in exactly 1,000 cases; in 2009, the number of
cases reached a peak of 2,357 [7-9]. Research showed
that the primary source of infection for humans was the
wave of abortions on dairy goat farms, and that people
that lived near these farms (within 5 km) were primarily
* Correspondence: m.bults@rotterdam.nl
1
Municipal Public Health Service Rotterdam-Rijnmond, P.O. Box 70032,
3000 Rotterdam, LP, The Netherlands
2
Department of Public Health, Erasmus MC, University Medical Center
Rotterdam, P.O. Box 2040, 3000 Rotterdam, CA, The Netherlands
Full list of author information is available at the end of the article
© 2014 Bults 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 credited.
Bults et al. BMC Public Health 2014, 14:263
http://www.biomedcentral.com/1471-2458/14/263
affected [10]. As a result, the incidence of Q fever in the
Netherlands differed between regions (Figure 1). In the
first instance, Q fever was mainly a local problem of the
Noord-Brabant province, which had a high density of large
dairy goat farms. However, in 2009, an alarming increase
in Q fever incidence was observed in adjacent provinces,
including Utrecht and Limburg [8,11]. In 2009, the Dutch
government decided to tackle the source by imposing
various veterinary measures [8,12]. Furthermore, vete-
rinarians, physicians, and the public were informed
through targeted mailings, publications, and the news
media. When a dairy goat or dairy sheep farm tested posi-
tive for Coxiella burnetii, all inhabitants living within a
radius of 5 km of the farm received a letter to inform them
of the presence of a Q fever-positive farm in their proxim-
ity. In 2011, patients with specific cardiovascular condi-
tions and patients with aortic aneurysms or vascular
prostheses that lived in high-risk areas were offered Q
fever vaccinations [13]. These comprehensive measures
have led to a significant decrease in the incidence of hu-
man cases (504 in 2010; 81 in 2011; 66 in 2012) [7].
Surveillance of public perceptions and behavioral re-
sponses during infectious disease outbreaks can provide
useful information for designing health risk communica-
tions that achieve successful changes in public behavior
[14,15]. Studies on public perceptions and behavioral re-
sponses have been conducted during outbreaks of other
zoonotic infections, including severe acute respiratory
syndrome (SARS) and avian influenza [16-23]. However,
studies on public perceptions and behaviors during Q
fever outbreaks have been limited, and they were mainly
directed at specific risk groups [13,24,25]. The aim of
the present study was to identify trends over time (2009,
2010, and 2012) and regional differences in public per-
ceptions and behavioral responses, as well as predictors
of preventive behavior, with regard to Q-fever.
Methods
Timing of the three surveys
The first survey took place from 13 August to 1 September,
2009. This followed a sharp increase in the incidence of hu-
man cases in spring 2009, primarily in the province of
Noord-Brabant (as in 2007 and 2008), but it had also spread
geographically to adjacent provinces (Figure 1). In late 2009
and early 2010, media attention markedly increased, and
drastic veterinary measures were implemented. The
Deuning CM (RIVM). Notified Q fever patients, 2009. In: Volksgezondheid Toekomst Verkenning,
Nationale Atlas Volksgezondheid. Bilthoven: RIVM, <http://www.zorgatlas.nl>
Zorgatlas\Gezondheid en ziekte\Ziekten en aandoeningen\Infectieziekten, 18 december 2009.
Figure 1 Notified patients with Q fever in 2009 (N = 2,357).
Bults et al. BMC Public Health 2014, 14:263 Page 2 of 13
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second survey took place from 1 to 12 April 2010. This
followed the period from January to May 2010, when 208
human cases were identified; this was lower than the
number identified in the same period in 2009 [12]. The
third survey took place from 2 to 17 April 2012, when the
incidence had largely dropped off (66 cases in 2012) [7].
Participants
The survey was conducted through an internet panel
(the Flycatcher panel; www.flycatcher.eu), which retains
national list of volunteers with the distribution of demo-
graphic variables (gender, age, region, and level of educa-
tion) comparable to the general Dutch population. These
volunteers can be invited to participate in online surveys.
The Flycatcher panel meets high quality requirements and
is ISO-certified. Panel members of three regions with dif-
ferent incidences of Q fever were invited to participate in
this study. The regions included Noord-Brabant (with
around 2464 000 inhabitants), which had the highest inci-
dence of human Q fever, and Utrecht and Limburg (with
around 2360 000 inhabitants), where Q fever had been
more recently introduced. Two other provinces with low
incidences of human Q fever, Groningen and Friesland
(with around 1229 000 inhabitants), served as control re-
gions (Figure 1). At three different time points, the partici-
pants completed an online survey. In the first survey,
independent, random samples were selected for each geo-
graphical region; we invited a total of 2511 panel members
(aged ≥18 years; about 800 per region). All respondents to
the first survey were invited to participate in the second
and third surveys. Sampled panel members were sent an
email with an internet link. The surveys were available on-
line for 5 to 10 days; during that time, panel members
were required to respond. Upon completion of each sur-
vey, panel members received 1.50 Euro in credits, which
could be exchanged for gift vouchers through the Fly-
catcher website.
This general, internet-based survey conducted with
healthy volunteers from the general population did not
require formal, medical ethical approval, according to
Dutch law [26].
Online questionnaire
The questionnaires were based on questionnaires used
in similar studies on SARS, avian influenza, and Influenza
A (H1N1) [18,21,22,27], with some modifications. The
questions were based on an integrated model designed to
explain health behavior. Constructs were used from the
Protection Motivation Theory [28] and the Health Belief
Model [29]; they included contact with the disease, per-
ceived severity and vulnerability, feelings of anxiety, per-
ceived efficacy of preventive measures, a persons’ability
(self-efficacy), intention to take measures, and actual
preventive behavior. Participants were asked about eight
(hypothetical) preventive measures against Q fever. Know-
ledge was examined with 7 true/false statements. The
questionnaire concluded with items on the amount of in-
formation received on Q fever, attention paid to the infor-
mation, and the reliability and sufficiency of governmental
information. The questionnaires were similar across the
three survey rounds (Additional file 1).
Analysis
Data analysis was performed with SPSS for Windows,
release 19.0. For all constructs with 3 or more items,
Cronbach’s alpha was calculated (range 0.6 to 0.8).
Therefore, for each construct, a summary score was cal-
culated by summing the individual item scores and div-
iding by the number of items. For assessing knowledge,
a summary score was created based on the number of cor-
rect answers (range 0–7). We computed the unadjusted bi-
variate correlations between the study variables using
Cramérs V (for nominal vs. nominal/ordinal/interval vari-
ables) and Spearman’s Rho (for ordinal/interval vs. ordinal/
interval variables). Paired t-tests (for comparing means)
and McNemar tests (for comparing percentages) were used
to analyse time trends between the baseline and first
follow-up survey, and between the first and second follow-
up surveys. Overall significant trends over time for the
3 regions are shown in the tables. Univariate logistic
regressions were used to assess confounding factors.
Comparisons of regional public perceptions and behavioral
responses were analysed with ANOVAs and adjusted for
the confounders; a p-value <0.05 was considered statistically
significant. For each outcome variable, corrected regional
means were calculated based on the results from the
ANOVA model. Univariate and multivariate logistic re-
gression analyses were performed to identify factors sig-
nificantly associated with taking one or more preventive
measures regarding Q fever. Prospective/follow-up studies
are preferably used to identify a causal relationship be-
tween the predictors (measured at T1) and actual behavior
(measured at T2) [30]. Therefore, we used data from
the first survey in 2009 for the predictors in the regres-
sion analyses, whereas data from the follow-up survey
in 2010 were used for the outcome variable (i.e. pre-
ventive behavior). For the multivariate regression ana-
lyses, all factors with a p-value <0.1 in the univariate
analyses were entered in the multivariate model, and
removed one-by-one (starting with the most insignificant
one etc.) until only statistically significant predictors
(p < 0.05) remained.
Results
In August 2009, 2511 panel members were invited to par-
ticipate. Of these, 64% (n = 1609) responded (baseline
study). In the first follow-up survey, all 1609 respondents
from the baseline study were invited, and 79% (n = 1263)
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responded. For the second follow-up survey, 1343 mem-
bers of the 1609 respondents from the baseline study were
invited, and 77% (n = 1032) responded. A total of 1347 re-
spondents completed at least 1 follow-up survey and were
included in the analyses. Of these, 932 completed both
follow-up surveys. Significant differences were observed in
the sex, age, education, employment, and marital status of
participants in different regions; in the low incidence re-
gion a higher proportion of female, younger aged, higher
educated, employed and single respondents participated
compared to the high and intermediate incidence regions
(Table 1). Univariate logistic regression analyses showed
that sex, age, education, and employment status were sta-
tistically significant determinants (p < 0.05) in the majority
of outcome variables, but not marital status.
Correlations
Table 2 provides the unadjusted bivariate correlations
between the study variables. Regarding the socio-
demographic variables, for example, higher levels of per-
ceived susceptibility, chance, anxiety and intention were
observed among the lower educated (resp. p < 0.001; p <
0.001; p < 0.002; p < 0.001). However, low correlation
values (<0.1 or between 0.1-0.3) were observed between
the socio-demographic and cognitive variables. A couple
of variables had moderate correlation values (between
0.3 and 0.5). Respondents with higher levels of perceived
severity, susceptibility and chance also felt more anxious.
A moderate correlation was also found between per-
ceived susceptibility and chance, between perceived effi-
cacy and self-efficacy/intention, and between perceived
anxiety and preventive behaviour. A high correlation
(0.78; p < 0.001) was found between self-efficacy and
intention.
Trends over time (2009, 2010, 2012)
Public knowledge regarding Q fever increased significantly
between 2009 and 2010, but slightly decreased between
2010 and 2012 (Table 3). Perceived severity increased over
time from 2009 to 2010, and from 2010 to 2012. Perceived
severity of the disease was rather high; the majority of re-
spondents agreed that Q fever is a severe disease, that it is
very harmful for their health, and that the consequence
of getting Q fever in the coming year is (very) severe.
The perceived personal susceptibility to Q fever remained
stable over time, while the perceived chance of getting in-
fected in the coming year decreased between 2010 and
2012. Perceived vulnerability generally was rather low, with
less than 15% of respondents perceiving that they were
susceptible. Perceived anxiety increased from 2009 to
2010, but decreased between 2010 and 2012 to the level
of the first survey in 2009. Throughout this period, anx-
iety levels remained low (with less than 10% worrying
about Q-fever).
From 2009 to 2010 to 2012, an increase was observed
in the overall perceived efficacy of measures for preventing
Q fever. The measures with the highest perceived efficacies
were avoiding contact with goats and sheep and avoiding
Q fever-affected regions. Overall, perceived self-efficacy de-
creased between 2009 and 2010 and remained stable there-
after. Respondents felt most confident in practicing better
hygiene and avoiding contact with goats and sheep.
Intentions to take preventive measures decreased be-
tween 2009 and 2010 and remained stable thereafter. In-
tentions were highest for practicing better hygiene and
avoiding contact with goats and sheep. The percentage
of respondents that had actually taken one or more mea-
sures for preventing Q fever increased significantly be-
tween 2009 and 2010 (from 22% to 30%), but decreased
between 2010 and 2012 to the level of the first survey in
2009 (from 30% to 23%). The respondents most often re-
ported avoiding contact with goats and sheep and prac-
ticing better hygiene.
Between 2009 and 2010, increases were observed in the
amount of information respondents received on Q fever,
the amount of attention paid to this information, and the
perceived sufficiency of governmental information (data
not shown). Between 2010 and 2012, decreases were ob-
served in the amount of information respondents received
and the attention paid to information on Q fever. The per-
ceived reliability of governmental information on Q fever
was stable over time (with almost half of respondents per-
ceiving governmental information to be reliable).
Regional differences
In 2009, 2010, and 2012, public knowledge regarding Q
fever was highest in the high incidence region and lowest
in the low incidence region (Table 4). Over time, there
were no regional differences in the perceived severity of Q
fever. Generally, perceived vulnerability was highest in the
high incidence region and lowest in the low incidence re-
gion (although not always significant). In all three surveys,
perceived anxiety was highest in the high incidence region
and lowest in the low incidence region.
Regional differences were observed in perceived effi-
cacy of measures only in 2009, with highest scores in the
high incidence region and lowest in the medium incidence
region. No regional differences were observed in perceived
self-efficacy in 2009, but in 2010 and 2012 it was highest in
the low incidence region. Regarding intention to take mea-
sures, no regional differences were observed over the three
surveys. In all three surveys, respondents in the high inci-
dence region most often took measures to prevent Q fever.
Regional differences were also observed in the reported
amount of information received (all three surveys), in the
amount of attention paid to that information (all three sur-
veys), and in the perceived sufficiency of information pro-
vided by the government (2009). All amounts were highest
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among respondents in the high incidence region (data not
shown). There were no regional differences in the perceived
reliability of governmental information on Q fever.
Predictors of preventive behavior
Univariate and multivariate logistic regression analyses
were performed to identify predictors significantly asso-
ciated with taking one or more preventive measure re-
garding Q fever (Table 5). From the multivariate logistic
regression analysis, predictors of preventive behavior
were being female (OR 1.4; 95% CI 1.1-1.8), older aged
(>50 yrs: OR 2.0; 95% CI 1.3-3.1), having Q fever them-
selves/someone in their household (OR 5.4; 95% CI 1.0-
28.1); more knowledge (OR 1.6; 95% CI 1.2-2.1), and
higher levels of perceived severity (OR 1.6; 95% CI 1.2-
2.1), feelings of anxiety (OR 2.3; 95% CI 1.7-3.1), efficacy
(OR 1.7; 95% CI 1.3-2.2), and self-efficacy (OR 1.4; 95%
CI 1.1-1.9).
Discussion
Between 2009 and 2010, we found increases in the public
knowledge, perceived severity, anxiety, and perceived effi-
cacy of measures related to Q fever in the Netherlands. In
the same period, increases were also observed in actual
behavior, the amount of information received, the atten-
tion paid to the information, and the perceived sufficiency
of government-provided information. These increasing
trends coincided with marked increases in media attention
to the Q fever outbreak in the Netherlands and in the
drastic veterinary measures that were implemented in late
2009 and early 2010. Other studies also described an asso-
ciation between media coverage/the amount of informa-
tion people received and the levels of public knowledge/
Table 1 Demographic characteristics of respondents in each region (survey 1, August 2009)
Characteristics Region 1: high
incidence region
a
Region 2: medium
incidence region
b
Region 3: low
incidence region
c
Total p-Value
(n = 459) (n = 491) (n = 397) (n = 1347)
Sex
Male 52% 53% 35% 47%
Female 48% 47% 65% 53% <0.001
Age
18-30 years 14% 13% 26% 17%
30-50 years 38% 43% 44% 42%
Above 50 years 48% 44% 30% 41% <0.001
Ethnicity
d
Native Dutch 91% 91% 93% 92%
Immigrant 9% 9% 7% 9% ns
Education
e
Low 31% 34% 16% 28%
Intermediate 40% 35% 45% 40%
High 30% 31% 39% 33% <0.001
Employment status
Employed 61% 62% 69% 64%
Unemployed/Retired 39% 38% 31% 36% 0.04
Marital status
Single 17% 19% 25% 20%
Married/Cohabitating 80% 72% 69% 74%
Divorced/Widowed 4% 9% 5% 6% <0.001
Children < 18 years in household
Yes 34% 37% 40% 37%
No 66% 63% 60% 63% ns
a
Region 1= Noord-Brab ant –high incidence region;
b
Region 2= Utrecht & Limburg –intermediate incidence region;
c
Region 3= Gron ingen & Friesland –low
incidence region;
d
immigrant =born abroad or at least one parent born abroad;
e
low educational level (i.e. primary education, lower general/vocational education or less);
intermediate educational level (i.e. secondary general or vocational education); high educational level (i.e. higher professional education or university);
ns = not significant. Chi
2
test was used to test demographic differences between regions.
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risk perception [22,31]. Apparently, in April 2010 (when
the first follow-up survey took place), the public was not
well-informed on the reduced number of human cases
during the spring of 2010. Perhaps public risk perception
and preventive behavior had not yet decreased at that
time, due to the increase number of fatal cases reported
(7 in 2009; 11 in 2010) and the recent implementation
of veterinary measures. In 2011 and 2012, the number
of new human Q fever cases decreased further, largely
as a result of the implemented veterinary measures [12].
Furthermore, at that time, media attention had decreased
regarding the Q fever outbreak in the Netherlands. This
may have led to the decreases (between 2010 and 2012) in
public knowledge, perceived anxiety, preventive behavior,
amount of information received, and attention paid to the
information on Q fever.
Respondents in the high incidence region exhibited
the highest levels of public knowledge, perceived anxiety,
preventive behavior, amount of information received, and
attention paid to the information. This was most likely
due to the facts that this region had a high density of large
dairy goat farms, had the first community outbreak of Q
fever, and had the most human Q fever cases. Also, the
local media in that region focused more attention on the
Q fever outbreak.
Predictors of preventive behavior regarding Q fever
were being female, older aged, having Q fever them-
selves/someone in their household, higher levels of
knowledge, perceived severity, feelings of anxiety, and
(self-)efficacy. So, besides rational arguments (such as
perceived severity and efficacy of measures), emotional
aspectlikeanxietyplayaroleindecision-makingcon-
cerning preventive behavior.
We found a strong correlation between self-efficacy and
intention to take preventive measures against Q fever.
This is very much in agreement with other studies, that
describe that threatening information only leads to pre-
ventive behaviour if efficacy beliefs are also high [32,33].
The perceived vulnerability and perceived anxiety were
rather low, even in the high incidence region, during the
peak of the outbreak. Other studies describe this finding
as an “optimistic bias”, which could have an adverse ef-
fect on risk perception and public compliance [27,34,35].
It is important for the public to have an appropriate
level of perceived vulnerability, because those that per-
ceive themselves at risk are more likely to comply with
government-advised preventive measures [16,18,36].
If worn properly, face masks are an effective intervention
strategy in controlling an outbreak [37]. Studies conducted
in Asia during outbreaks of SARS and avian influenza
reported rather high levels of face mask use among the
general public [16,20]. However, we found low levels of
perceived (self-)efficacy and intention to wear face mask.
Possible explanations are the fact that wearing a face
mask has many practical barriers and appears to be associ-
ated with negative feelings, like disease victimization, and
stigmatization.
A clear strength of this study was that data collection
took place during an actual outbreak situation, in contrast
to other studies, which used scenarios based on hypothet-
ical situations. Another strength was that this study con-
sisted of three repeated survey rounds; this enabled the
analysis of trends over time. Moreover, we followed-up in-
dividuals; thus, the differences between survey rounds rep-
resented real trends over time and were not due to
differences between study populations [38]. Furthermore,
Table 2 Bivariate correlations
a
for demographic and cognitive variables (survey 2010, n = 1249)
1234567891011a11b1213141516
Variable
b
9 Knowledge .07 .09 .10 .16** .09 .09 .09 .11* 1
10 Perceived severity .10 .16** .08 .10 .17** .11 .11 .09 .12** 1
11a Perceived susceptibility .04 .06 .05 .12** .08 .07 .04 .14** .11** .23** 1
11b Perceived chance .09* .07 .05 .14** .07 .06 .07 .19** .02 .11** .42** 1
12 Perceived anxiety .10 .18** .07 .14** .17** .13** .06 .16** .22** .38** .37** .34** 1
13 Perceived efficacy .14 .16 .14 .18 .20* .14 .14 .15 .14** .14** .09** -.013 .19** 1
14 Perceived self-efficacy .19 .22** .18 .18 .18 .16 .18 .15 .08** .17** .06* -.007 .17** .40** 1
15 Intention .14 .25** .13 .20** .21** .17 .18 .19* .09** .26** .13** .06* .29** .43** .78** 1
16 Behaviour .09 .13** .07 .08 .11* .06 .06 .25** .13** .20** .21** .14** .38** .20** .20** .28** 1
a
Calculated using Cramérs V (for nominal vs. nominal/ordinal/interval variables) and Spearman’s Rho (for ordinal/interval vs. ordinal/interval variables);
b
1 = gender (1: male; 2: female); 2= age (1: 18–30 yrs; 2: 30–50 yrs; 3: >50 yrs); 3= ethnicity (1: native dutch; 2: immigrant); 4 = education (1: low; 2: intermediate;
3: high); 5 =employment status (1: unemployed/retired; 2: employed); 6 = marital status (1: single; 2: married/cohabiting; 3: divorced/widowed); 7 = children in
household (1: no children; 2: one or more children < 18 yrs); 8 = contact with disease (1: no; 2: had Q fever themselves/partner/child(ren); 9 = knowledge=0–7
items correct; number 10–15 on header row relate to the corresponding number and variable presented vertically (1–5 point likert scale); 16 = behaviour (0–5
number of preventive measures taken).
*Correlation is significant at the 0.05 level (2-tailed); ** Correlation is significant at the 0.01 level (2-tailed).
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Table 3 Trends over time in public perceptions and behaviors regarding Q fever in the Netherlands (2009, 2010, and 2012)
Survey 1 Survey 2 Survey 3 Trends over time
August 2009:
baseline (n = 1347)
April 2010: first
follow-up (n = 1249)
April 2012: second
follow-up (n = 1030)
a
Survey 1 versus 2 Survey 2 versus 3
High score (%)
b
Mean High score (%)
b
Mean High score (%)
b
Mean p-value
c
p-value
c
Knowlegde
Summary score –Chronbach’s alpha 0.6 33 2.73 59 3.80 49 3.42 <0.001 (+) <0.001 (−)
Perceived severity [scale 1–5]
1. “Q fever is a severe disease”57 3.53 73 3.79 78 3.89 <0.001 (+) 0.04 (+)
2. “Q fever is very harmful for my health”53 3.45 63 3.65 67 3.73 <0.001 (+) ns
3. Severity of getting Q fever coming year 57 3.67 70 3.94 77 4.08 <0.001 (+) <0.001 (+)
Summary score –Chronbach’s alpha 0.7 –3.55 –3.79 –3.90 <0.001 (+) <0.001 (+)
Perceived vulnerability [scale 1–5]
1. Perceived susceptibility for oneself 11 2.63 14 2.67 14 2.67 ns ns
2. Perceived chance of getting infected coming year 2 2.22 3 2.20 1 2.03 ns <0.001 (−)
Perceived anxiety [scale 1–5]
1. Worried about Q fever 5 2.17 8 2.36 6 2.16 <0.001 (+) <0.001 (−)
2. Fear for Q fever 3 2.11 5 2.23 4 2.12 <0.001 (+) <0.001 (−)
3. Thinking of Q fever 1 1.74 1 1.98 1 1.66 <0.001 (+) <0.001 (−)
Summary score –Chronbach’s alpha 0.8 –2.01 –2.19 –1.98 <0.001 (+) <0.001 (−)
Perceived efficacy [scale 1–5]
1. Practice better hygiene 60 3.57 50 3.31 51 3.34 <0.001 (−)ns
2. Avoid Q fever affected regions 64 3.64 75 3.92 80 4.10 <0.001 (+) <0.001 (+)
3. Avoid contact with goats and sheep 81 4.13 85 4.25 84 4.28 <0.001 (+) ns
4. Do not use raw dairy products 57 3.57 60 3.65 66 3.84 0.04 (+) <0.001 (+)
5. Wear face mask 24 2.65 30 2.85 45 3.29 <0.001 (+) <0.001 (+)
6. Move to place without Q fever 17 2.21 31 2.61 42 3.14 <0.001 (+) <0.001 (+)
7. Seek medical consultation with onset of symptoms 59 3.57 55 3.46 51 3.42 <0.001 (−)ns
8. Take antibiotics 34 3.01 32 2.93 36 3.11 0.047 (−) <0.001 (+)
Summary score –Chronbach’s alpha 0.7 –3.29 –3.37 –3.56 <0.001 (+) <0.001 (+)
Perceived self-efficacy
d
[scale 1–5]
1. Practice better hygiene 88 4.32 84 4.22 82 4.21 <0.001 (−)ns
2. Avoid Q fever affected regions 65 3.72 67 3.77 66 3.77 ns ns
3. Avoid contact with goats and sheep 83 4.26 85 4.26 83 4.22 ns ns
4. Do not use raw dairy products 71 3.94 71 3.95 70 3.92 ns ns
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Table 3 Trends over time in public perceptions and behaviors regarding Q fever in the Netherlands (2009, 2010, and 2012) (Continued)
5. Wear face mask 40 3.15 40 3.08 42 3.15 0.04 (−)ns
6. Move to place without Q fever 9 1.86 12 1.99 13 2.10 0.001 (+) 0.005 (+)
7. Seek medical consultation with onset of symptoms 81 4.20 76 4.05 75 4.03 <0.001 (−)ns
8. Take antibiotics 73 3.98 67 3.81 71 3.90 <0.001 (−)ns
Summary score –Chronbach’s alpha 0.8 –3.68 –3.64 –3.66 0.02 (−)ns
Intention
d
[scale 1–5]
1. Practice better hygiene 86 4.33 81 4.17 80 4.15 <0.001 (−)ns
2. Avoid Q fever affected regions 70 3.86 69 3.82 72 3.93 ns 0.01 (+)
3. Avoid contact with goats and sheep 84 4.29 83 4.24 82 4.22 0.03 (−)ns
4. Do not use raw dairy products 70 3.97 70 3.93 71 3.95 ns ns
5. Wear face mask 40 3.10 36 3.00 39 3.10 0.003 (−) 0.04 (+)
6. Move to place without Q fever 8 1.79 11 1.92 11 2.04 <0.001 (+) 0.003 (+)
7. Seek medical consultation with onset of symptoms 79 4.17 73 3.98 68 3.89 <0.001 (−) <0.001 (−)
8. Take antibiotics 68 3.90 63 3.71 61 3.71 <0.001 (−)ns
Summary score –Chronbach’s alpha 0.8 –3.68 –3.60 –3.62 <0.001 (−)ns
ns = not statistically significant;
a
932 respondents participated in both follow-up surveys (331 of region 1; 350 of region 2; 251 of region 3);
b
percentage of respondents who scored 4–5 (except for knowledge: percent-
age of respondents who answered 4 or more out of 7 items correctly);
c
time trends based on p-values obtained using paired t-tests;
d
respondents were asked to imagine that governmental health institutes would
recommend the preventive measure; ‘(+)’indicates a significant increase over time p < 0.05; ‘(−)‘indicates a significant decrease over time p < 0.05.
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Table 4 Regional differences in public perceptions and behaviors regarding Q fever in the Netherlands (high, medium, and low incidence regions)
Survey 1 (August 2009) - baseline Survey 2 (April 2010) - first follow-up Survey 3 (April 2012)-second follow-up -
Region 1:
high
incidence
(n = 459)
Region 2:
medium
incidence
(n = 491)
Region 3:
low incidence
(n = 397)
p-value
a
Region 1:
high
incidence
(n = 430)
Region 2:
medium
incidence
(n = 456)
Region 3:
low incidence
(n = 363)
p-value
a
Region 1:
high
incidence
(n = 354)
Region 2:
medium
incidence
(n = 375)
Region 3:
low incidence
(n = 277)
p-value
a
Mean
b
Mean
b
Mean
b
Mean
b
Mean
b
Mean
b
Mean
b
Mean
b
Mean
b
Knowlegde
Summary score –Chronbach’s alpha 0.6 2.99 2.73 2.45 <0.001 4.02 3.67 3.68 0.001 3.55 3.44 3.22 0.04
Perceived severity
1. “Q fever is a severe disease”3.50 3.58 3.49 ns 3.75 3.81 3.80 ns 3.90 3.90 3.86 ns
2. “Q fever is very harmful for my health”3.44 3.48 3.42 ns 3.64 3.65 3.66 ns 3.69 3.76 3.75 ns
3. Severity of getting Q fever coming year 3.68 3.68 3.65 ns 4.02 3.95 3.84 0.03 4.11 4.12 4.02 ns
Summary score –Chronbach’s alpha 0.7 3.54 3.58 3.52 ns 3.80 3.81 3.77 ns 3.90 3.93 3.88 ns
Perceived vulnerability
1. Perceived susceptibility for oneself 2.73 2.60 2.58 0.003 2.73 2.67 2.61 ns 2.72 2.72 2.54 0.003
2. Perceived chance of getting
infected coming year
2.73 2.67 2.60 ns 2.29 2.19 2.11 0.02 2.12 2.10 1.87 <0.001
Perceived anxiety [scale 1–5]
1. Worried about Q fever 2.25 2.18 2.10 0.02 2.47 2.31 2.30 0.004 2.25 2.18 2.06 0.02
2. Fear for Q fever 2.16 2.09 2.07 ns 2.29 2.22 2.18 ns 2.20 2.14 2.03 0.03
3. Thinking of Q fever 1.91 1.68 1.60 <0.001 2.12 1.94 1.86 <0.001 1.76 1.67 1.54 <0.001
Summary score –Chronbach’s alpha 0.8 2.11 1.98 1.92 <0.001 2.29 2.15 2.12 <0.001 2.07 2.00 1.88 0.001
Perceived efficacy [scale 1–5]
1. Practice better hygiene 3.63 3.50 3.58 ns 3.31 3.28 3.36 ns 3.27 3.35 3.41 ns
2. Avoid Q fever affected regions 3.63 3.63 3.66 ns 3.90 3.91 3.96 ns 4.04 4.11 4.15 ns
3. Avoid contact with goats and sheep 4.22 4.17 3.98 <0.001 4.32 4.25 4.18 ns 4.29 4.28 4.27 ns
4. Do not use raw dairy products 3.61 3.49 3.64 ns 3.61 3.65 3.70 ns 3.81 3.87 3.86 ns
5. Wear face mask 2.68 2.57 2.73 ns 2.83 2.79 2.95 ns 3.22 3.27 3.39 ns
6. Move to place without Q fever 2.26 2.03 2.37 <0.001 2.69 2.50 2.66 ns 3.19 3.01 3.24 0.04
7. Seek medical consultation with
onset of symptoms
3.62 3.58 3.50 ns 3.53 3.39 3.46 ns 3.46 3.42 3.37 ns
8. Take antibiotics 3.07 2.95 3.01 ns 2.97 2.87 2.96 ns 3.11 3.11 3.13 ns
Summary score –Chronbach’s alpha 0.7 3.34 3.24 3.31 0.03 3.39 3.34 3.40 ns 3.55 3.55 3.60 ns
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Table 4 Regional differences in public perceptions and behaviors regarding Q fever in the Netherlands (high, medium, and low incidence regions) (Continued)
Perceived self-efficacy
c
[scale 1–5]
1. Practice better hygiene 4.38 4.31 4.27 ns 4.18 4.26 4.19 ns 4.25 4.18 4.20 ns
2. Avoid Q fever affected regions 3.57 3.73 3.90 <0.001 3.55 3.78 4.02 <0.001 3.58 3.81 3.99 <0.001
3. Avoid contact with goats and sheep 4.35 4.22 4.21 0.04 4.28 4.25 4.25 ns 4.23 4.19 4.26 ns
4. Do not use raw dairy products 3.99 3.90 3.95 ns 3.94 3.90 4.03 ns 3.84 3.94 4.05 0.03
5. Wear face mask 3.13 3.07 3.27 ns 3.02 3.00 3.27 0.003 3.07 3.12 3.31 0.04
6. Move to place without Q fever 1.74 1.76 2.13 <0.001 1.90 1.88 2.23 <0.001 2.00 2.04 2.28 0.006
7. Seek medical consultation with
onset of symptoms
4.24 4.20 4.16 ns 4.06 4.01 4.07 ns 4.03 4.03 4.03 ns
8. Take antibiotics 4.04 3.96 3.95 ns 3.83 3.80 3.81 ns 3.91 3.87 3.92 ns
Summary score –Chronbach’s alpha 0.8 3.68 3.64 3.73 ns 3.60 3.61 3.73 0.008 3.62 3.65 3.76 0.04
Intention
c
[scale 1–5]
1. Practice better hygiene 4.39 4.32 4.25 0.046 4.20 4.22 4.06 0.048 4.18 4.17 4.09 ns
2. Avoid Q fever affected regions 3.77 3.87 3.97 0.04 3.69 3.85 3.95 0.006 3.82 4.02 4.00 0.02
3. Avoid contact with goats and sheep 4.39 4.30 4.19 0.01 4.29 4.23 4.20 ns 4.25 4.25 4.18 ns
4. Do not use raw dairy products 4.06 3.91 3.96 ns 3.95 3.87 3.99 ns 3.94 4.00 3.94 ns
5. Wear face mask 3.14 3.03 3.14 ns 2.92 2.94 3.17 0.01 3.06 3.12 3.17 ns
6. Move to place without Q fever 1.73 1.70 1.98 <0.001 1.80 1.87 2.12 <0.001 1.96 1.98 2.20 0.02
7. Seek medical consultation with
onset of symptoms
4.23 4.15 4.12 ns 4.01 3.99 3.95 ns 3.92 3.89 3.85 ns
8. Take antibiotics 3.95 3.88 3.87 ns 3.73 3.68 3.73 ns 3.82 3.68 3.67 ns
Summary score –Chronbach’s alpha 0.8 3.71 3.65 3.69 ns 3.57 3.58 3.64 ns 3.62 3.64 3.64 ns
ns = not statistically significant;
a
p-value obtained using ANOVA with sex, age, education, and employment status as confounders;
b
means are corrected for differences in sex, age, education, and employment status;
c
respondents were asked to imagine that governmental health institutes would recommend the preventive measure.
Bults et al. BMC Public Health 2014, 14:263 Page 10 of 13
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we used an online questionnaire, which created less of a
social desirability bias than personal telephone interviews.
This study also had some limitations. First, the surveys
took place in different months of the year (August in
2009 and April in 2010 and 2012). Although cases of Q
fever can occur at any time of the year, most cases re-
ported the onset of illness during the spring and early
summer months, with peaks in April and May [8,12].
Our first survey took place during the summer, when
the number of new human Q fever cases decreased. The
second and third surveys took place during the spring,
when the number of Q fever cases had increased. Thus,
survey timing may have had some influence on public
perceptions and behaviors. Second, the Internet panel
was representative for the Netherlands as a whole with
regard to gender, age and education. Our study popula-
tion comprised inhabitants of three regions. Therefore,
the results may not be generalisable to the whole
country. Furthermore, participants were not fully rep-
resentative for their region. Although gender, age and
education were included as confounders when analys-
ing regional differences in risk perception and pre-
ventive behavior, other results can be slightly biased
(for example the percentages in Table 3). Third, sam-
ples were drawn from an Internet panel which often
include ‘heavy internet users’who are more likely to
perform information seeking behavior. This might
have led to some bias in the perceived amount of
information received. Last, the fact that it was a
follow-up study may have influenced participating
respondents; after the first survey, they might have
become more aware of Q fever in the Netherlands,
and therefore, they might have paid more attention to
information on Q fever in the media.
Our study had several implications for health author-
ities. First, when levels of knowledge, public perceptions,
and/or behavioral responses are generally low, providing
the public with more information through the media
is expected to increase these factors. During future
outbreaks of (zoonotic) infectious diseases, it will be
important to provide the public with accurate and up-
to-date information on the risk of becoming infected to
instil a realistic sense of vulnerability. This should be given
in addition to information about the severity of the disease,
information on the efficacy of measures, and instructions
for minimising infection risk with appropriate, feasible
measures. Second, health communicators should take the
public’s perceptions into account when formulating mes-
sages about the prevention of zoonotic infections; these
messages should be adapted to regional circumstances.
Therefore, surveillance of public perceptions and behav-
ioral responses during outbreaks of infectious diseases is
important. Furthermore, involving the public in risk com-
munication or the decision-making process regarding the
implementation of public preventive measures could have
added value, because the public can provide important
information, particularly about the (practical) feasibility
of specific preventive measures. This is consistent with
a previous evaluation report of the Q fever outbreak in
Table 5 Predictors of preventive behavior regarding Q fever
% of respondents
that took one or
more preventive
measures
Oddsratio (95%-CI)
§
Univariate Multivariate
Sex
Male 26.7 1.0 1.0
Female 32.6 1.3 (1.0-1.7) 1.4 (1.1-1.8)
Age
18-30 yrs 17.9 1.0 1.0
30-50 yrs 27.4 1.7 (1.2-2.6) 1.6 (1.1-2.5)
> 50 yrs 37.0 2.7 (1.8-4.0) 2.0 (1.3-3.1)
Contact with disease
No 29.5 1.0 1.0
Yes
#
75.0 7.2 (1.4-35.7) 5.4 (1.0-28.1)
Level of knowledge
0-3 items corectly
answered
25.8 1.0 1.0
4-7 items correctly
answered
37.7 1.7 (1.4-2.2) 1.6 (1.2-2.1)
Perceived severity
Low perceived
severity
21.4 1.0 1.0
High perceived
severity
36.9 2.1 (1.7-2.8) 1.6 (1.2-2.1)
Level of anxiety
Low perceived
anxiety
17.1 1.0 1.0
High perceived
anxiety
39.1 3.1 (2.4-4.1) 2.3 (1.7-3.1)
Perceived efficacy of measures
Low perceived
efficacy
22.2 1.0 1.0
High perceived
efficacy
37.3 2.1 (1.6-2.7) 1.7 (1.3-2.2)
Perceived self-efficacy
Low perceived
self-efficacy
22.4 1.0 1.0
High perceived
self-efficacy
36.2 2.0 (1.5-2.5) 1.4 (1.1-1.9)
§
95%-CI 95% confidence interval;
#
had Q fever themselves or someone in
their household.
The following determinant are not included in this table, because they were
not significant in the multivariate model (although they were univariate a
significant predictor of preventive behaviour); education, ethnicity,
employment status, marital status, and intention.
The following determinants were univariate not a significant predictor of
taking preventive measures regarding Q fever: having children <18 years in
household and perceived vulnerability (2 items).
Bults et al. BMC Public Health 2014, 14:263 Page 11 of 13
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the Netherlands, which stated that “the public should be
more involved in the dilemmas of the government”[39].
Conclusions
Overall, the trends over time and the regional differences
in public perceptions and behaviors regarding Q fever ap-
peared to parallel the trends in the number of new human
Q fever cases in the different epidemiological regions in
2009, 2010, and 2012, and the amount of media attention
on Q fever in the Netherlands during those years. How-
ever, the low levels of perceived vulnerability and perceived
anxiety were remarkable, particularly in the high incidence
region, with three-quarters of the total cases in 2009. Dur-
ing future outbreaks of (zoonotic) infectious diseases, it is
therefore important to provide the public accurate infor-
mation on the risk of becoming infected to instil a realistic
sense of vulnerability. Furthermore, information should be
adapted to regional circumstances. New research could
focus on searching for the most effective methods (e.g.,
personalising risk) for providing this information during
future outbreaks of infectious diseases.
Data sharing
data are available on request from MB m.bults@rotter
dam.nl
Additional file
Additional file 1: Survey questions ‘Q fever in the Netherlands:
public perceptions and behavioural responses in three different
epidemiological regions: a follow-up study’.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
All authors contributed to the study design. MB, HV, DB, and CW played a
primary role in the data collection. Data analysis was performed by MB and
HV. MB and HV wrote the first draft of the manuscript; DB, CW, and JHR
critiqued the manuscript and contributed to further drafts. HV is the
guarantor. All authors read and approved the final manuscript.
Acknowledgements
This study was financed by the Netherlands Organization for Health Research
and Development (ZonMw), the National Institute of Public Health and the
Environment, and the Municipal Public Health Service ‘Hart voor Brabant’.
The authors thank Henriëtte Giesbers (National Institute of Public Health and
the Environment) for designing Figure 1, Pleun Aardening (Flycatcher Internet
Research) for help in the data collection process, and Caspar Looman (Erasmus
MC) for advice on data analyses. Last but not least, the authors would like to
thank all the panel members that participated in this study.
Author details
1
Municipal Public Health Service Rotterdam-Rijnmond, P.O. Box 70032, 3000
Rotterdam, LP, The Netherlands.
2
Department of Public Health, Erasmus MC,
University Medical Center Rotterdam, P.O. Box 2040, 3000 Rotterdam, CA, The
Netherlands.
3
National Institute of Public Health and the Environment, Centre
for Infectious Disease Control, P.O. Box 1, 3720 Bilthoven, BA, The
Netherlands.
4
Municipal Public Health Service “Hart voor Brabant”, P.O. Box
3166, 5203 DD ‘s-Hertogenbosch, The Netherlands.
Received: 2 July 2013 Accepted: 14 March 2014
Published: 20 March 2014
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Cite this article as: Bults et al.:Q fever in the Netherlands: public
perceptions and behavioral responses in three different epidemiological
regions: a follow-up study. BMC Public Health 2014 14:263.
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