Teresa Nazareth1, Carla Alexandra Sousa2, Graça Porto3, Luzia Gonçalves4, Gonçalo Seixas5, Luís Antunes6, Ana Clara Silva7, Rosa Teodósio8. 1. GABBA Doctoral Program, ICBAS, Abel Salazar Institute for the Biomedical Sciences, University of Porto, Porto, Portugal; Unidade Clínica Tropical, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal; Unidade de Parasitologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal. 2. Unidade de Parasitologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal; Unidade de Parasitologia e Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal. 3. GABBA Doctoral Program, ICBAS, Abel Salazar Institute for the Biomedical Sciences, University of Porto, Porto, Portugal; Basic & Clinical Research on Iron Biology, IBMC, Institute for Molecular and Cellular Biology, Porto, Portugal. 4. Unidade de Saúde Pública e Internacional e Bioestatística, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal; Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL), Lisboa, Portugal. 5. Unidade de Parasitologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal. 6. DROTA-Direção de Serviços de Informação Geográfica e Cadastro, Direção Regional de Ordenamento de Território e Ambiente, Funchal, Região Autónoma da Madeira, Portugal. 7. Departamento de Saúde, Planeamento e Administração Geral, Instituto de Administração da Saúde e Assuntos Sociais, Funchal, Região Autónoma da Madeira, Portugal. 8. Unidade Clínica Tropical, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal; Centro de Malária e Doenças Tropicais, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.
Abstract
The ability to effectively modify behaviours is increasingly relevant to attain and maintain a good health status. Current behaviour-change models and theories present two main approaches for (healthier) decision-making: one analytical/logical, and one experiential/emotional/intuitive. Therefore, to achieve an integral and dynamic understanding of the public perceptions both approaches should be considered: community surveys should measure cognitive understanding of health-risk contexts, and also explore how past experiences affect this understanding. In 2011, community perceptions regarding domestic source reduction were assessed in Madeira Island͘. After Madeira's first dengue outbreak (2012) a unique opportunity to compare perceptions before and after the outbreak-experience occurred. This was the aim of this study, which constituted the first report on the effect of an outbreak experience on community perceptions regarding a specific vector-borne disease. A cross-sectional survey was performed within female residents at the most aegypti-infested areas. Perceptions regarding domestic source reduction were assessed according to the Essential Perception (EP)-analysis tool. A matching process paired individuals from studies performed before and after the outbreak, ensuring homogeneity in six determinant variables. After the outbreak, there were more female residents who assimilated the concepts considered to be essential to understand the proposed behaviour. Nevertheless, no significant difference was observed in the number of female residents who achieved the defined 'minimal understanding''. Moreover, most of the population (95.5%) still believed at least in one of the identified myths. After the outbreak some myths disappeared and others appeared. The present study quantified and explored how the experience of an outbreak influenced the perception regarding a dengue-preventive behaviour. The outbreak experience surprisingly led to the appearance of new myths within the population, apart from the expected increase of relevant concepts' assimilation. Monitoring public perceptions is therefore crucial to make preventing dengue campaigns updated and worthy.
The ability to effectively modify behaviours is increasingly relevant to attain and maintain a good health status. Current behaviour-change models and theories present two main approaches for (healthier) decision-making: one analytical/logical, and one experiential/emotional/intuitive. Therefore, to achieve an integral and dynamic understanding of the public perceptions both approaches should be considered: community surveys should measure cognitive understanding of health-risk contexts, and also explore how past experiences affect this understanding. In 2011, community perceptions regarding domestic source reduction were assessed in Madeira Island͘. After Madeira's first dengue outbreak (2012) a unique opportunity to compare perceptions before and after the outbreak-experience occurred. This was the aim of this study, which constituted the first report on the effect of an outbreak experience on community perceptions regarding a specific vector-borne disease. A cross-sectional survey was performed within female residents at the most aegypti-infested areas. Perceptions regarding domestic source reduction were assessed according to the Essential Perception (EP)-analysis tool. A matching process paired individuals from studies performed before and after the outbreak, ensuring homogeneity in six determinant variables. After the outbreak, there were more female residents who assimilated the concepts considered to be essential to understand the proposed behaviour. Nevertheless, no significant difference was observed in the number of female residents who achieved the defined 'minimal understanding''. Moreover, most of the population (95.5%) still believed at least in one of the identified myths. After the outbreak some myths disappeared and others appeared. The present study quantified and explored how the experience of an outbreak influenced the perception regarding a dengue-preventive behaviour. The outbreak experience surprisingly led to the appearance of new myths within the population, apart from the expected increase of relevant concepts' assimilation. Monitoring public perceptions is therefore crucial to make preventing dengue campaigns updated and worthy.
Most of the 2011 worldwide major causes of death (MCD), rely on behaviour changes for
their prevention [1].
Increasing physical activity, fruits/vegetables intake, hand-washing, use of
condoms, and decreasing not only fat, salt and sugar intake but also smoking habits,
are crucial in the control of heart disease (1st MCD), stroke
(2nd MCD), chronic obstructive lung disease (4th MCD),
diarrhoea (5th MCD), HIV (6th MCD), or diabetes
(8th MCD). Behaviour changes are increasingly relevant to attain and
maintain a good health status, especially when facing health threats for which there
is no efficient or timely treatment. This is the case for dengue fever that such as
other mosquito-borne diseases, requires a good compliance to certain preventive,
protective or therapeutic actions. Moreover, since there is no vaccine or treatment
for dengue fever, neither 100% effective insecticides, community behaviour has a
huge impact on its prevention and control [2].It is still not widely understood how to effectively promote behaviour changes [3]. During several decades,
many behaviour impact campaigns were shown to be fruitless. In the past 50 years,
literature extensively presented theoretical models which tried to clarify cognitive
ways of (healthier) behaviour acquisition [4,5,6,7,8,9]. Recently, the concept of
‘past experiences’ was stated as being crucial in determining
(healthier) decision-making. Many authors claimed that, due to the type of emotions
and intuition that they produced, ‘past experiences’ could strongly
encourage or discourage a particular action [6,7,8,9,10].Altogether, these contributions seem to present two different approaches by which
humans perceive decision-making and then make decisions: one analytical and one
experiential [11]. In order
to improve the efficacy of the behaviour-promoting messages, the authors firmly
suggested that messages should be not only meaningful but also emotionally adequate
for the targeted community. This way, the assessment of community’s
cognitive and emotional perceptions, is hence useful in the guiding of effective
health-seeking messages. However, few studies explored emotional experience-driven
perceptions but rather frequently only focused on the assessment of the cognitive
ones [12].Some evidence suggested that experience can influence public perceptions and
reactions in two ways [13].
In one aspect, it can over-estimate the risk perception [10,13] (i.e. alert-feeling,
referred to as ‘availability bias’ [14]) and consequently promote protective/preventive
actions. It can also underestimate the risk perception [12,15] (i.e. habituation effect
also called ‘gambler’s fallacy’[14]) which can discourage protective/preventive actions.
Only few studies have explored this issue in real situations. Besides the scientific
interest of scrutinizing the complex process of (healthier) decision-making, the
monitoring of public perceptions and behaviours contributes to the continuous and
adequate update of the behaviour-promoting messages concerning their (rational and
emotional) content. This is the case of any chronic and endemic disease, where the
(health) risk is maintained during time such as dengue epidemic and endemic areas
[12].In 2005, a dengue vector species, Aedes aegypti was reported in
Madeira archipelago. In 2012, the first dengue outbreak was recorded in the
territory [16]. Community
perception regarding preventive behaviours (domestic source reduction) was assessed
and described in details by the current investigators, before the outbreak had been
declared [17]. At the end of
the outbreak, a unique opportunity to explore and compare community perception
before and after the outbreak appeared. The aim of this study was thus to re-assess
community perceptions regarding the same preventive behaviour (domestic source
reduction) just after the dengue outbreak in order to compare how it has altered
with the outbreak experience. This constitutes to our knowledge the first report of
this kind describing the effect of an outbreak experience on community perceptions
regarding a specific vector-borne disease.
Methods
As subsequently explained, methodology of the present survey (herein stated as
POST-outbreak study) followed as much as possible the methodology used in the
prior-to-the outbreak survey (herein mentioned as PRE-outbreak study) [17]. This ensured an accurate
comparison between public perceptions before and after the dengue outbreak in
Madeira Island.Therefore, the tool used in the assessment of the community perceptions was
maintained, i.e., the ‘Essential-Perception
analysis’ (see sub-section of the same name). However, since the outbreak was
not planed ahead nor predicted, in the POST-outbreak survey was not possible to
reproduce exactly the same methodology used before the outbreak. Due to ethic, time
and logistic constrains implicit in the preparation of this survey during the
outbreak and in its implementation just after it, adjustments in the size of the
studied sample and in the sampling methodology, were mandatory to make the
POST-outbreak survey possible. The introduced alterations were sample size reduction
(through rural and male residents’ exclusion) and intentional sample
selection instead of the previous random one. These alterations are explained in
detail in ‘Studied population’ sub-section. Finally a matching process
was developed in order to overcome those constrains and guarantee an unbiased
comparison between the two studies despite their differences in sampling
methodology. For that, populations surveyed in both PRE/POST-outbreak studies and
who had fully completed the questionnaires were scored according to the perceptions
demonstrated (for EP-Score calculation) and marked according to the six
socio-demographic characteristics (for the matching process). After this,
populations were matched according to critical socio-demographic variables, as
described in sub-section ‘Matching Process’ and EP-score was compared
within matched pairs. Individuals who presented missing questions were excluded from
the analysis.
Studied Population
Out of the several municipalities which were covered by the PRE-outbreak study
area, only some were selected to be included in this POST-outbreak study (Fig. 1). In order to decrease
the sample size, ‘Câmara de Lobos’ was excluded since it
was the sole rural municipality. Facing the impossibility of including both
urban and rural municipalities, the urban ones were preferred based on two main
reasons: (i) they presented a dengue incidence rate greater than 200 during the
outbreak (S1
Fig.); and (ii) they comprise the capital city of the archipelago,
Funchal, and thus an important point of aegypti-dispersion.
Part of the Funchal municipalities: ‘Sé’, ‘Santa
Maria Maior’ and ‘Imaculado Coração de
Maria’, were also included in the POST-outbreak study area besides those
considered in the PRE-outbreak study (‘São Pedro’ and
‘Santa Luzia’). These extra-included area were also
covered by the 2012’s most aegypti-infested area
(presenting a density level of 31% or over along the year), thus ensuring a
homogeneous level of natural exposure to the A. aegypti among
the studied residents [18]. The geographic area covered in the present study will be mentioned
as ‘Extended-AEGYPTI area’ and consists, thus, in part of five
Funchal’s municipalities from the 2012 most
aegypti-infested area.
Fig 1
Study areas from PRE-outbreak and POST-outbreak studies.
Fig. 1 (upper) shows
Aedes aegypti’s distribution (2011) resulted
from the Island-wide transversal entomological survey using ovitraps.
Study areas of both PRE-outbreak and POST-outbreak studies were also
described. Black administrative boundaries described are relative to
Island Counties (or Districts). Pink area corresponds to the area
included in both PRE-outbreak and POST-outbreak surveys (it also
corresponds to what is defined the ‘urban area’). Brown
area corresponds to the area included in PRE-outbreak survey but not in
the POST-outbreak one (corresponds to the ‘rural area’).
Blue area corresponds to the area included only in the POST-outbreak
survey. Fig. 1
(bottom) detail of the previous maps focusing on the
density levels based on the number of eggs founded and on the incidence
rates of the study areas. Administrative boundaries described are
relative to parishes (or ‘Municipalities’) Pink
area corresponds the area included in both PRE-outbreak and
POST-outbreak surveys. Brown area corresponds to the area included in
PRE-outbreak survey but not in the POST-outbreak one. Blue area
corresponds to the area included only in the POST-outbreak survey.
Numbers represent the part of each municipality covered in the study
areas: 1- São Pedro; 2- Santa Luzia;3-Câmara de Lobos; 4-
Sé; 5- Imaculado Coração e Maria; 6- Santa Maria
Maior.
Study areas from PRE-outbreak and POST-outbreak studies.
Fig. 1 (upper) shows
Aedes aegypti’s distribution (2011) resulted
from the Island-wide transversal entomological survey using ovitraps.
Study areas of both PRE-outbreak and POST-outbreak studies were also
described. Black administrative boundaries described are relative to
Island Counties (or Districts). Pink area corresponds to the area
included in both PRE-outbreak and POST-outbreak surveys (it also
corresponds to what is defined the ‘urban area’). Brown
area corresponds to the area included in PRE-outbreak survey but not in
the POST-outbreak one (corresponds to the ‘rural area’).
Blue area corresponds to the area included only in the POST-outbreak
survey. Fig. 1
(bottom) detail of the previous maps focusing on the
density levels based on the number of eggs founded and on the incidence
rates of the study areas. Administrative boundaries described are
relative to parishes (or ‘Municipalities’) Pink
area corresponds the area included in both PRE-outbreak and
POST-outbreak surveys. Brown area corresponds to the area included in
PRE-outbreak survey but not in the POST-outbreak one. Blue area
corresponds to the area included only in the POST-outbreak survey.
Numbers represent the part of each municipality covered in the study
areas: 1- São Pedro; 2- Santa Luzia;3-Câmara de Lobos; 4-
Sé; 5- Imaculado Coração e Maria; 6- Santa Maria
Maior.Due to the mentioned unfeasibility to include a representative sample of the
resident population of the study area, an intentional sample of exclusively
female subjects who lived in the study area—‘Extended-AEGYPTI
area’ aged 18 years old or over and who didn’t integrate the
previous PRE-outbreak survey was selected from customers of central hairdressers
and pharmacies, placed in the selected area. The women selection was based on
three main reasons: (i) before the outbreak women were significantly less aware
of domestic source reduction than men (S2 Fig. and S1 Table);
(ii) women are the majority within the studied population [19]; (iii) women above 15
years-old were the age/gender-group more affected by the disease during the
outbreak [20]; and (iv)
culturally, in Madeira Island, women are more related to the main
dengue-preventive behaviour proposed than men do (see details about the
behaviour proposed in ‘Essential-Perception’ subsection).
All women who entered in the establishment and who met the inclusion criteria
were invited to participate.The type of establishment were chosen in order to allow the study to cover the
most possible heterogeneous women sample, in what concerns their age groups,
education levels and socio-economic background. In order to stimulate
participation of women from all the included municipalities, two central
establishments of each service were chosen to participate in the study according
to their convenient geographical location, being one placed in the east and the
other in the west region of the studied area.The study area has a population density which can be as high as 1433.5 habitants
per square kilometers [21]. The sample size was calculated using Epitools’ sample size
calculators (2014, AusVet Animal Health Services) in order to perform a
comparison of two means using the t-test (2-tailed) where a 1 point is relevant
in Essential-Perception Score difference (variation between −10, 10)
[22]. The sample size
calculation considered a 95% confidence level, a power of 80% and a pooled
variance equal to 10 (S = √10 = 3.16). The obtained n was 157 (S2 Table).
Finally, this sample size was inflated in 30% to account for incomplete
interviews.
Questionnaire
A cross-sectional survey was performed to assess residents’ perceptions
through face-to-face interviews. Before data collection, establishments’
managers/participants gave their written/oral informed consent respectively.
Previous to the beginning of this survey, the questionnaire was pre-tested in a
non-selected establishment placed in the selected area. During the interview, a
questionnaire comprising 21 questions was applied, covering dengue-preventive
issues and personal-socio-demographic characteristics. In agreement with what
was inquired in the PRE-outbreak study, questionnaire covered five main topics:
‘Medical Importance’ (two questions), ‘Local
Context’ (two questions), ‘Domestic Attribute’ (three
questions), ‘Mosquito Breeding’ (three questions) and
‘Control Measures’ (three questions) [17]. Besides the variables
‘gender’, ‘education level’, ‘age
group’, and ‘geographical area’, two other variables were
assessed: ‘travels to dengue endemic countries (DEC)’ which
measures who had already been to any dengue endemic country and ‘admitted
mosquito exposure (AME)’ which measures who recognized to had been bitten
by mosquitoes. The survey was performed by trained personnel from the local
health authority from 22nd of March until 16th of April,
2013. In each establishment (pharmacies/hairdressers), interviews were performed
during a Monday-to-Saturday week, between 9am and 7pm (according to
establishments’ opening hours) The study was approved by
Instituto de Higiene e Medicina Tropical Ethics Committee, Instituto de Higiene
e Medicina Tropical, Universidade Nova de Lisboa, Lisbon (reference:
09-2013-TD).
Matching Process
Populations studied in both PRE/POST-outbreak surveys were matched into pairs,
ensuring homogeneity in six critical socio-demographic variables. Resulting
matching population comprised thus pairs of individuals composed of an
individual from the PRE-outbreak study and an individual from the POST-outbreak
study with equivalent personal-socio-demographic characteristics. Matching pairs
of individuals were equal in (or “blocked” on) gender, education
level, age group, geographical area, travels to DEC and AME variables, already
shown to be determinants to the individual perception [17]. This sampling
methodology can also be called as randomized block design, and the latter
variables as blocking factors [23].For comparative purposes, the criteria ‘geographic area’ was
applied in two different ways, generating two different matching approaches. In
one matching approach, herein called ‘adjusted matching’, the
‘geographic area’ criteria distinguished only residents living in
urban areas from residents living in rural areas. According to this criteria,
‘Câmara de Lobos’ (covered exclusively in PRE-outbreak
study area) was the sole rural municipality. In the other matching approach,
herein called ‘restricted matching’, the geographic criteria
besides the previous distinction between urban and rural areas also
differentiated urban municipalities covered in both PRE-outbreak and
POST-outbreak studies (‘Santa Luzia’ and ‘São
Pedro’) from the remaining urban ones which were exclusively included in
the POST-outbreak study (‘Sé’, ‘Santa Maria
Maior’ and ‘Imaculado Coração de Maria’). The
other criteria (gender, education level, age group, travels to DEC and AME) were
strictly applied in both matching approaches,
i.e. only individuals who were equal in
this variables were matched.Both matching procedures were built in Excel (Microsoft Office, Windows 8), and
guaranteed that individuals were randomly selected within those that were
personal-socio-demographically equivalent. Moreover, matching procedures were
optimized in order to re-include all the non-selected individuals in the
subsequent matching rounds.
The assessment of the community perception was performed using the
Essential-Perception analysis (EP-analysis), as described below.Essential-Perception analysis assesses community perception regarding a
particular behavioural proposal: the domestic aegypti’s
source reduction, considered the most critical dengue-preventive practice by the
World Health Organization [24]. This corresponds to the elimination (emptying, covering or
removing) of water-containers present inside or around residential buildings.
The EP-analysis’ considers ten essential concepts which assimilation by
individuals was revealed to be determinant to the performance of the proposed
behaviour (Table 1) [17]. Essential-Perception
analysis allows the characterization and estimation of the community’s
perceptions through four different approaches, all of them used here: (i) score
of Essential-Perception, (ii) concept assimilation, (iii) topic understanding
and (iv) myth identification and estimation. The first measures the number of
concepts that were assimilated (out of those defined to be
‘essential’) and thus how far-off is the studied population from
achieving the complete ‘Essential Perception’ (EP-Score = 10). The
second describes how much those ‘essential’ concepts were
assimilated or not-assimilated by the community. The third, organizes the
‘essential concepts’ in topics and describes how topics are/not
being understood. Residents who have acknowledged both topic-related
concepts are according to this tool considered to have ‘completely
understood the topic’, the acknowledgement of only one out of the two
topic-related concepts is considered as a ‘partial understanding of the
topic’, and residents who did not perceive any of the two topic-related
concepts are considered to have ‘not understood the topic’.
Finally the fourth, by analysing the concept assimilation, identifies erroneous
beliefs which may persist in the community (herein mentioned as
‘myths’) and estimates their putative frequency in the studied
population (see example in S3 Fig.).
Table 1
List of ten concepts defined as essential within Essential
Perception-analysis.
Essential Topic
Essential Concepts
Medical Importance (MI)
MI1-concept- Recognition of the transmission of
disease through mosquitoes (bite)
MI2-concept—Recognition of the one
example of mosquito-borne diseases
Local Context (LC)
LC1-concept—Recognition of the presence
of vector-mosquitoes in their own residential area
LC2-concept—Recognition of the high
possibility of a dengue outbreak in Madeira
Domestic Attribute (DA)
DA1-concept—Recognition of the
eventuality of indoor mosquito-breeding
DA2-concept—Recognition of the impact of
domestic vector control
Mosquito Breeding (MB)
MB1-concept—Recognition of the role of
water-containers as breeding contributors
MB2-concept—Recognition of the false
role of ‘pets’ or ‘food debris’
as breeding contributors
Control Measures (CM)
CM1-concept—Recognition of source
reduction as an effective domestic
aegypti-control measure
CM2-concept—Recognition of
‘insecticide application’ or ‘use of a
flyswatter’ as ineffective measures for the domestic
aegypti-control’
Statistical Analysis
All collected information was introduced and records were double-checked.
Statistical analysis was performed using Statistical Package for Social Sciences
19.0 (SPSS, Inc., Chicago, IL, USA). Answers obtained from the questionnaires
were re-coded to obtain other categorical variables implicit in the EP-analysis.
The personal-socio-demographic feature of the studied population presented in
Table 2 was described
in what concerns the gender, age group, education level, municipal division,
travels to dengue endemic countries (DEC) and AME. The age groups were
categorized in ten-year intervals and the education level was divided into five
categories starting from ‘never studied’ until ‘upper
graduation’. This categorization allow that groups were similar in number
of individuals.
Table 2
Personal-socio-demographic feature description of Total and Paired
samples in both PRE-outbreak and POST-outbreak studies (adjusted
matching).
Total Sample
Total Sample
Paired Sample•(No. of
pairs = 90)
PRE-out. Study (n = 1145) ⱡ
POST-out. study (n = 154)
Gender
Female
466 (40.7%)
154 (100%)
90 (100%)
Male
679 (59.3%)
-
-
Education level (years)
Never studied (0)
69 (6.0%)
44 (28.6%)
12 (13.3%)
Fourth Grade (4)
438 (38.3%)
31 (20.1%)
24 (26.7%)
Ninth Grade (9)
254 (22.2%)
30 (19.5%)
18 (20.02%)
High School (12)
204 (17.8%)
43 (27.9%)
31 (34.4%)
Upper Education (+12)
180 (15.7%)
6 (3.9%)
5 (5.6%)
Age groups (years)
25 or younger
152 (13.3%)
7 (4.5%)
4 (4.4%)
26–35
157 (13.7%)
19 (12.3%)
9 (10.0%)
36–45
186 (16.2%)
24 (15.6%)
17 (18.9%)
46–55
198 (17.3%)
40 (26.0%)
21 (23.3)
56–65
170 (14.8%)
36 (23.4%)
19 (21.1%)
66–75
160 (14.0%)
21 (13.6%)
14 (15.6%)
76 or older
122 (10.7%)
7 (4.5%)
6 (6.7%)
Municipal Division
Funchal
666 (58.2%)+
154 (100.0%)‘
90 (100.0%)‘
Câmara de Lobos
479 (41.8%)
-
-
Travelled to DEC1
yes
863 (75.4%)
89 (57.8%)
62 (68.9%)
no
282 (24.6%)
65 (42.2%)
28 (31.1%)
Admitted MQ exposure
(AME)2
yes
286 (25.0%)
46 (29.9%)
22 (24.4%)
No
859 (75.0%)
108 (70.1%)
68 (75.6%)
Since paired sample from both studies were equivalent in these six
variables their socio-demographic characteristics are equal
(presented as ‘Paired sample’).
1 Distinguish those that have/not travelled to dengue
endemic countries (at least once)
2 Reflects those who admitted/not to had been bitten by
mosquitoes
ⱡ Individuals that were scored regarding the 13
questions for perception assessment and that also have answered to
the personal-socio-demographic questions implicated in the matching
process
•Adjusted matching
* Differences resulted from the adjustment done in in this
matching process
+Including ‘Santa Luzia’ and
‘São Pedro’ municipalities
‘Including ‘Santa Luzia’, ‘São
Pedro’, ‘Sé’, ‘Imaculado
Coração de Maria’ and ‘Santa Maria
Maior’ municipalities
Since paired sample from both studies were equivalent in these six
variables their socio-demographic characteristics are equal
(presented as ‘Paired sample’).1 Distinguish those that have/not travelled to dengue
endemic countries (at least once)2 Reflects those who admitted/not to had been bitten by
mosquitoesⱡ Individuals that were scored regarding the 13
questions for perception assessment and that also have answered to
the personal-socio-demographic questions implicated in the matching
process•Adjusted matching* Differences resulted from the adjustment done in in this
matching process+Including ‘Santa Luzia’ and
‘São Pedro’ municipalities‘Including ‘Santa Luzia’, ‘São
Pedro’, ‘Sé’, ‘Imaculado
Coração de Maria’ and ‘Santa Maria
Maior’ municipalitiesComparison of the two urban municipalities covered in both PRE-outbreak and
POST-outbreak studies (‘Santa Luzia’ and ‘São
Pedro’) confirmed a priori the validity of the criteria
‘geographic area’ in the restricted matching. In this matching
those municipalities were considered equivalent. S3 Table shows that despite the
previous observed differences observed in their EP-score level, when
“blocking” the education level there are no significant
differences between the two municipalities.Analysis of the demographic data of the extra-included areas compared the new
added municipalities (‘Sé’, ‘Santa Maria
Maior’ and ‘Imaculado Coração de Maria’) and
the previously studied (‘Santa Luzia’ and ‘São
Pedro’). Comparison is presented in S4 Table showing that there were no
relevant differences between them in what concerns the two critical
socio-demographic determinants: age group and education level supporting thus a
priori the validity of the criteria ‘geographic
area’ in the adjusted matching.Comparisons of EP-score medians between populations from PRE/POST-outbreak
studies were made using the non-parametric Wilcoxon Test (Table 3), after rejecting
the normality of Essential-Perception score difference through Kolmogrov-Smirnov
test. Additionally, the number of individuals who achieved an EP-score equal to
or higher than seven (EP-score≥7) was calculated in both studies and
differences were compared, using the McNemar Test (Table 4). This cut-off was chosen due to lack of
subjects that achieved an EP-score equal to ten (EP-score = 10). In order to
evaluate the methodology used during the matching process, comparisons between
paired and non-paired samples were performed, according to their EP-score and
their socio-demographic characteristics. In order to ensure that restricted and
adjusted matching sample sizes (n = 47and n = 90) were satisfactory, the power
associated to Wilcoxon test (the non-parametric alternative to t-test) was
calculated a posteriori using free statistical power analysis
program, G*Power 3.0 [25].
Table 3
The EP-scores from Total and Paired samples of both PRE/POST-outbreak
surveys and associations between them.
n Total ⱡ (matching
compatible)
EP-Score medians
(P25-P75) +
n Paired
EP-Score medians
(P25-P75) +
p value
PRE-outbreak survey
1145•
5.0 (3.0–6.0)
90
5.0 (4.0–7.0)
0.952′
↕
POST-outbreak survey
154
7.0 (5.0–8.0)
90
7.0 (6.0–8.0)
0.073′
p value
<0.001*‘’
+ Weighted Average method
* Wilcoxon test
‘ Mann-Whitney test
‘’ t-test
ⱡ number of individuals compatible for matching
i.e. individuals who were
scored regarding the 13 questions for perception assessment and who
also have answered to the personal-socio-demographic questions
implicated in the matching process.
• Out of the 1182 individuals that were scored in the
PRE-outbreak study, 37 subjects were not included in the matching
process, since they lack critical socio-demographic data
Table 4
Evolution of the residents’ groups according to the cut-off:
EP-Score ≥ 7 (Before/After the outbreak).
POST-outbreak survey (paired
population)
p value
EP-Score < 7
EP-Score ≥7
PRE-outbreak survey (paired
population)
EP-Score < 7
27 (=)
38 (↑)
<0.001+
EP-Score ≥ 7
4 (↓)
21 (=)
nTOTAL = 90 pairs
(=) Number of individuals that did not change the EP-Score level
compared with its pair
(↓) Number of individuals that have increased the EP-Score
level compared with its pair
(↑) Number of individuals that have decreased the EP-Score
level compared with its pair
+ McNemar test
+ Weighted Average method* Wilcoxon test‘ Mann-Whitney test‘’ t-testⱡ number of individuals compatible for matching
i.e. individuals who were
scored regarding the 13 questions for perception assessment and who
also have answered to the personal-socio-demographic questions
implicated in the matching process.• Out of the 1182 individuals that were scored in the
PRE-outbreak study, 37 subjects were not included in the matching
process, since they lack critical socio-demographic datanTOTAL = 90 pairs(=) Number of individuals that did not change the EP-Score level
compared with its pair(↓) Number of individuals that have increased the EP-Score
level compared with its pair(↑) Number of individuals that have decreased the EP-Score
level compared with its pair+ McNemar test
Results
A total of 154 female Extended-AEGYPTI residents answered the complete questionnaire
in the present POST-outbreak survey. A total of 90 pairs resulted from the adjusted
matching between 154 female from the POST-outbreak survey and 1145 subjects who
participated in the PRE-outbreak study. Each pair composed of an individual from the
PRE-outbreak study and an individual from the POST-outbreak study with equivalent
personal-socio-demographic characteristics. Nine individuals out of those surveyed
had dengue and five were paired. The personal-socio-demographic feature of the
studied sample populations is described in Table 2. When not mentioning subsequent paragraphs as
well as the data presented in Figs. 2, 3, 4 and 5, and Tables 2, 3, 4 and 5 present
results from the adjusted matching.
Fig 2
The EP-Score distributions of the paired samples and of the total sample
in PRE-outbreak study.
Comparison of EP-score distribution from paired samples of both
PRE/POST-outbreak studies (upper) and comparison of EP-score distribution
from total and paired samples of the PRE-outbreak study (bottom) are
presented.
Fig 3
The EP-Score distributions of the paired samples and of the total sample
in POST-outbreak study.
Comparison of EP-score distribution from paired samples of both
PRE/POST-outbreak studies (upper) and comparison of EP-score distribution
from total and paired samples of the POST-outbreak study (bottom) are
presented.
Fig 4
Percentage of residents who have assimilated each Essential concepts in
both PRE-outbreak and POST-outbreak studies.
For Figure simplification, essential concepts were abbreviated to their name
initials: Medical Importance 1 and 2 (MI 1 and MI 2), Local Context 1 and 2
(LC 1 and LC 2), Domestic Attribute 1 and 2 (DA 1 and DA 2), Mosquito
Breeding 1 and 2 (MB 1 and MB 2), Control Measures 1 and 2 (CM 1 and
CM2).
Fig 5
Percentage of residents who have ‘understood’,
‘partially understood’ or ‘not understood’ each
studied topic.
For Figure simplification, topics were abbreviated to their name initials:
Medical Importance (MI), Local Context (LC), Domestic Attribute (DA),
Mosquito Breeding (MB), Control Measures (CM) ‘PRE’
and ‘POST’ represents PRE-outbreak study and POST-outbreak
study.
Table 5
Alleged myths in both PRE-outbreak and POST-outbreak studies and
respective frequencies The myths which were derived from PRE-outbreak study
were re-numbered.
PRE-outbreak study
POST-outbreak study
Difference
Essential Topics
Old / New No.
Alleged Myths
n (%)
n (%)
Medical Importance
Myth 1
‘Mosquitoes do not transmit
diseases’
10 (11.1)
5 (5.6)
↓
Myth 2
‘Mosquitoes only cause mild clinical
consequences such as allergies, fever, etc.’
46 (51.1)
20 (22.2)
↓↓↓
Local Context
Myths 3and
4
‘Dengue is not a mosquito-borne
disease’ and/or “Dengue only occur in
tropical/non-developed countries”
14 (15.6)
(disappeared)
Myth 3 and Myth
6a
‘Dengue will not occur again in Madeira, it
is very not likely‘
34 (37.8)
(new)
‘Dengue was, finally,
eradicated‘
Myths 5and
6
(i) ‘Since I do not feel the
byte, I am not at risk of being bitten/infected’; (ii)
“Mosquitoes are allocated in a specific area and are not
able to spread through my municipality’
14 (15.6)
9 (10.0)
↓
Myths 4 and 5
Myth 7
‘Madeira’s residents are not at
risk‘
41 (45.6)
(disappeared)
Myth 6b
‘Dengue/A.
aegypti was, finally,
eradicated‘
14 (15.6)
(new)
Domestic
Attribute
Myth 7(myth
8)
‘Local health authorities are the key
intervenient in the domestic control of mosquitoes‘
10 (11.1)
12 (13.3)
=
Myth 8*(myth
9)
‘Insecticides or other protective measures
can control mosquitoes‘
33 (36.7) *
17 (18.9) *
↓↓
Myth 9(myth
10)
‘I am (Community is) not an intervenient in
the aegypti-control‘
22 (24.4)
11 (12.2)
↓↓
Mosquito Breeding
Myths 10 and 11 (myths 11
and 12)
‘Clean houses or houses without animals do
not have mosquitoes’ and/or ‘Clean people have
nothing to do concerning the control of mosquitoes’
53 (58.9)
57 (63.3)
=
Control Measures
Myth 12*(myth
13)
‘By the usage of insecticides and/or
flyswatter, I am already contributing to the
aegypti-control‘
72 (80.0) *
56 (62.2) *
↓↓
*Myths 8 and 12 cover the same idea, there were a total of 67.0%
of the residents who believed in one or the other myth, i.e. who felt
that by the usage of protective measures, they are already contributing
to the aegypti-control.
(↓) Differences of 5–10 percentage points
(↓↓) Differences of 10–20 percentage points
(↓↓↓) Differences of more than 20 percentage
points
(=) Differences of less than 5 percentage points
The EP-Score distributions of the paired samples and of the total sample
in PRE-outbreak study.
Comparison of EP-score distribution from paired samples of both
PRE/POST-outbreak studies (upper) and comparison of EP-score distribution
from total and paired samples of the PRE-outbreak study (bottom) are
presented.
The EP-Score distributions of the paired samples and of the total sample
in POST-outbreak study.
Comparison of EP-score distribution from paired samples of both
PRE/POST-outbreak studies (upper) and comparison of EP-score distribution
from total and paired samples of the POST-outbreak study (bottom) are
presented.
Percentage of residents who have assimilated each Essential concepts in
both PRE-outbreak and POST-outbreak studies.
For Figure simplification, essential concepts were abbreviated to their name
initials: Medical Importance 1 and 2 (MI 1 and MI 2), Local Context 1 and 2
(LC 1 and LC 2), Domestic Attribute 1 and 2 (DA 1 and DA 2), Mosquito
Breeding 1 and 2 (MB 1 and MB 2), Control Measures 1 and 2 (CM 1 and
CM2).
Percentage of residents who have ‘understood’,
‘partially understood’ or ‘not understood’ each
studied topic.
For Figure simplification, topics were abbreviated to their name initials:
Medical Importance (MI), Local Context (LC), Domestic Attribute (DA),
Mosquito Breeding (MB), Control Measures (CM) ‘PRE’
and ‘POST’ represents PRE-outbreak study and POST-outbreak
study.*Myths 8 and 12 cover the same idea, there were a total of 67.0%
of the residents who believed in one or the other myth, i.e. who felt
that by the usage of protective measures, they are already contributing
to the aegypti-control.(↓) Differences of 5–10 percentage points(↓↓) Differences of 10–20 percentage points(↓↓↓) Differences of more than 20 percentage
points(=) Differences of less than 5 percentage points
Essential-Perception Analysis
Score of Essential Perception (EP-score)
Altogether Figs. 2 and
3 represent the
EP-score distribution of four samples: PRE-outbreak study’s total
subjects (n = 1145), PRE-outbreak study’s paired subjects (n = 90),
POST-outbreak study’s total subjects (n = 154) and POST-outbreak
study’s paired subjects (n = 90). In upper part of Figs. 2 and 3 is presented the
EP-score distribution from both paired subjects (from PRE-outbreak and
POST-outbreak surveys) revealing an increase in the EP-score level after the
outbreak. The graph at the bottom of the latter figures show the EP-score
distribution from total and paired populations in PRE-outbreak and
POST-outbreak studies (respectively) revealing a similar EP-score
distribution within the paired and the respective total population. Detailed
information is presented subsequently in the ‘statistical
analysis’ results sub-section.
Concept assimilation
When comparing the observed concept assimilation in both studies, the
POST-outbreak study had more individuals who assimilated each of the
essential concepts (Fig.
4). The percentage of female residents considering ‘the
existence of mosquito-borne diseases’ (MI2-concept), ‘the
presence of vector species in their residential area’ (LC1-concept)
and that ‘mosquitoes can breed inside houses’ (DA1-concept)
almost doubled, from 37.8% to 72.2%, from 38.9% to 74.4% and from 38.9% to
68.9%, respectively. Regarding the remaining essential concepts, they also
increased after the outbreak in terms of the percentage of individuals that
have acknowledged them, with the exception of the MB2-concept that slightly
decreased. Overall, following the experience of a dengue outbreak, almost
all the respondents (94.4%, 96.7% and 97.8%) believed that
‘mosquitoes can transmit diseases’ (MI1-concept), recognized
‘water as a mosquito breeding inducers’ (MB1-concept) and
referred to ‘the reduction of breeding sites as being a
(fairly/very/extremely) effective measure in the control of
mosquitoes’ (CM1-concept). In contrast to, there were some essential
concepts which remained unknown for the majority of the studied
individuals. These were the ‘Local Context 2’,
‘Mosquito Breeding 2’ and ‘Control Measures 2’
which are also the less acknowledged essential concepts. In fact, only 46.7%
believed that ‘there is a high possibility for dengue (re-)emergence
in Madeira’ (LC2-concept), merely 38.9% correctly admitted to the
‘false role of pets and food debris in the mosquito breeding’
(MB2-concept) and only 37.8% did not identify ‘the use of a
flyswatter or indoor insecticide spraying, as effective for
aegypti-control’ (CM2-concept).
Topic understanding
Topic understanding clearly improved after the outbreak (Fig. 5). In general, the
percentage of those who had totally understood each topic increased and the
percentage of those who did not completely understand each of topic
decreased. ‘Medical Importance’ and ‘Domestic
Attribute’ topics became completely understood by the majority of the
female Extended-AEGYPTI residents (72.2% and 55.6%). Even after the
noticeable increase of people that had totally understood the topics
‘Local Risk’, ‘Mosquito Breeding’ and
‘Control Measures’, the majority of the studied residents
still did not understand, or only partially understood them. Similar to the
PRE-outbreak study, the ‘Local Context’ topic in the
POST-outbreak study had the highest proportion of respondents who
disregarded both topic-related concepts.
Myth identification and estimation
Based on the thirteen myths that were identified in the PRE-outbreak study,
an updated list is suggested in Table 5 which includes new myths identified
after the outbreak. The frequency of each believed myth were (re-)calculated
in S5
Table and are also presented in Table 5. Out of the thirteen alleged myths
identified in the PRE-outbreak study, some had most likely disappeared after
the outbreak. This was what happened with the myths: «dengue is not a
mosquito-borne disease» or «dengue only occur in
tropical/non-developed countries» (Table 5). However, new beliefs emerged after the
end of the outbreak, such as the idea that ‘Madeira is protected from
a second dengue outbreak’ (alleged myths 3, 6a and 6b). Altogether
these myths are suggested to be believed by the majority of the female
community (53.3%). According to the myth analysis, after the outbreak each
female resident believed, on average, in three out of the twelve myths, less
than the four myths out of thirteen believed by the average of the residents
before the outbreak. Most of them believed at least in one myth either
before or after the outbreak (98.9% and 96.7%, respectively). After the
outbreak, the most disseminated alleged myth were «clean houses or
houses without animals do not have mosquitoes» and «by the
usage of insecticides and/or flyswatter, I am already contributing to the
aegypti-control». These myths were respectively
found in 62.3% and 61.2% of the paired sample.
Statistical Analysis (Test Statistics)
Statistical tests were performed in order to explore the differences between
medians of the EP-score from studied populations in both PRE/POST-outbreak
studies, confirming a significant increase in the EP-Score median after the
outbreak (p<0.001, Table
3). An increase in the number of individuals who achieved an EP-score
equal to or higher than seven (EP-score≥7) in the POST-study population
was also statistically confirmed (p<0.001, Table 4).
Confirming validity of the ‘Matching Process’
The validity of the matching processes was also statistically established. As
shown in Table 3 the
EP-score from the paired and non-paired samples (in both PRE/POST-outbreak
studies) did not change significantly (p>0.05 in both cases). In what
concerns the personal-socio-demographic feature, total and paired
populations also did not differ expressively (Figs. 6 and 7). Slight differences
were detected in proportions of age groups and in high education levels
between total populations from PRE-outbreak and POST-outbreak studies.
Fig 6
Comparison of personal-socio-demographic data between paired and
non-paired samples from PRE-outbreak study.
Data from paired sample (A) and data from non-paired sample of the
PRE-outbreak study (B) are presented. Age group, Education level,
Travels to DEC, and AME (bitten by mosquitoes) variables are
presented. Since Gender and geographic are blocked within matching
pairs (only female residents from Funchal municipalities were
matched) these variables are not presented in these figures.
Fig 7
Comparison of personal-socio-demographic data between paired and
non-paired samples from POST-outbreak study.
Data from paired sample (A) and data from non-paired sample of the
POST-outbreak study (C) are presented. Age group, Education level,
Travels to DEC, and AME (bitten by mosquitoes) variables are
presented. Since Gender and geographic are blocked within matching
pairs (only female residents from Funchal municipalities were
matched) these variables are not presented in these figures.
Comparison of personal-socio-demographic data between paired and
non-paired samples from PRE-outbreak study.
Data from paired sample (A) and data from non-paired sample of the
PRE-outbreak study (B) are presented. Age group, Education level,
Travels to DEC, and AME (bitten by mosquitoes) variables are
presented. Since Gender and geographic are blocked within matching
pairs (only female residents from Funchal municipalities were
matched) these variables are not presented in these figures.
Comparison of personal-socio-demographic data between paired and
non-paired samples from POST-outbreak study.
Data from paired sample (A) and data from non-paired sample of the
POST-outbreak study (C) are presented. Age group, Education level,
Travels to DEC, and AME (bitten by mosquitoes) variables are
presented. Since Gender and geographic are blocked within matching
pairs (only female residents from Funchal municipalities were
matched) these variables are not presented in these figures.
Comparison between restricted and adjusted matching models
The restricted matching resulted in 47 pairs of individuals with equivalent
personal-socio-demographic characteristics, being the pairs derived from
individuals of the PRE/POST-outbreaks studies performed. The assessed
differences in the perception of those surveyed before and after the
outbreak, were equivalent to the differences observed, obtained from the
comparison of perception of the pairs derived from the adjusted matching. As
previously described for the adjusted matching, the EP-score median of the
pairs derived from restricted matching has also significantly increased in
the POST-outbreak when compared to the PRE-outbreak one (p<0.001).
Moreover, the distribution of the EP-score, the concept assimilation and the
topic understanding observed for the 47 pairs selected by the restricted
matching, were approximately the same that the ones measured for the 90
pairs resulted from the adjusted matching. Additionally, a significant
increase of the number of individuals that achieved an EP-score equal to or
higher than seven (EP-score≥7) in the POST-study paired population,
was also observed when looking at pairs derived from the restricted matching
(p<0.001). Table
6 summarizes the data regarding both matching processes,
including the power values which were equal in both cases.
Table 6
Comparison between restricted and adjusted matching criteria and
respective results.
Restricted Matching
Adjusted Matching
Study area included
AEGYPTI area:
Extended-AEGYTI area:
Part of ‘Santa Luzia’ and
‘São Pedro’ municipalities,
corresponding to the 2011-aegypti-most
infested area
Part of ‘Santa Luzia’,
‘São Pedro’, ‘Imaculado
Coração de Maria’, ‘Santa
Maria Maior’ and ‘Sé’
municipalities, corresponding to the
2012-aegypti-most infested
area
No. of individuals in the POST Total
sample (matching compatible)**
93
154
No. of pairs PRE/POST (POST
Paired sample)
47
90
EP-score medians and
percentiles
PRE-outbreak
5.0 (3.0–6.0)
5.0 (4.0–7.0)
POST outbreak
8.0 (6.0–9.0)
7.0 (6.0–8.0)
Power of the Wilcoxon test
(used in the comparison between POST/ PRE EP- Score
median)
∼1.000
∼1.000
* No main differences observed (S2
Table)
** Individuals that were scored regarding the 13
questions for perception assessment and that also have answered
to all the personal-socio-demographic questions implicited in
the matching process
* No main differences observed (S2
Table)** Individuals that were scored regarding the 13
questions for perception assessment and that also have answered
to all the personal-socio-demographic questions implicited in
the matching process
Discussion
In general, the community perception regarding preventive domestic practices improved
within female residents of most aegypti-infested areas in Madeira
Island after they experienced a dengue outbreak. By analysing how and how much
assimilation of each 'Essential-concept’ has changed, crucial information can
be retrieved regarding people´s perceptions about this experience and their
future role in its prevention.For many Madeira residents, the experience of this dengue outbreak was probably the
first contact with a mosquito borne disease (it was the first in almost a hundred
years in Europe, [26]. This
can explain the observed increase in the assimilation of the idea that
‘mosquitoes can transmit diseases’ (MI1-concept). Moreover, before
experiencing the outbreak, the community's worst incident with mosquitoes were
allergic reactions, which could be considered as the sole health consequence of
mosquito bites. After the outbreak, it was not surprising that the percentage of
residents that were aware of ‘the kind of diseases that mosquitoes can
transmit (such as dengue, yellow fever and malaria)’ (MI2-concept) almost
doubled. Therefore, in the POST-outbreak study there were a higher percentage of
people who rightly appraised the impact of mosquitoes in health. Since no fatal
cases occurred during the dengue outbreak, some beliefs such as, ‘dengue
disease does not kill’ and ‘dengue in Madeira is less
aggressive’ may be present in the community. These questions should
be clarified within the community due to the possibility of a different virus
serotype reaches the Madeira territory, increasing the risk of dengue haemorrhagic
cases to occur.Even though assimilation of both ‘Local Context’ concepts increased
after the outbreak, the majority of residents still ignored that ‘there is a
high possibility for a (second) dengue outbreak in Madeira’ (LC2-concept).
The acknowledgement of this concept was expected to increase after the outbreak,
assuming that the previous identified myth which states that ‘Madeira were
not at risk of have dengue’ would be opposed with the experience of a dengue
outbreak. However, its assimilation merely increased 10%. Even though people
had probably realized that Madeira was at risk and that several dengue cases
occurred, two erroneous interpretations could explain this 10% result. Firstly, the
false belief that the ‘dengue outbreak have ended due to the eradication of
the disease or the mosquito’ (alleged myths 6a/6b, Table 5). Secondly,
gambler’s fallacy, the invalid belief that when something happens more
frequently than normal during a period of time, the probability of happening again
in the future decreases (alleged myth 3, Table 5) [14]. People who believe in these alleged myths
underestimate the probability of another dengue epidemics occur in Madeira
Island.Improvements in DA1-concept, DA2-concept, LC1-concept and MB1-concept can be
attributed to the “boom” of educational information transmitted during
the outbreak. This information was transmitted by the news, by official
reports, and most importantly by the exhaustive door-to-door campaign that was
rapidly implemented in the areas where most dengue cases were being reported during
the outbreak period. In the latter, trained personnel of the health-authorities
entered in residential buildings and supported the residents in performing correct
and extensive elimination of mosquito breeding sites inside and in the surroundings
of their houses (i.e. aegypti source reduction). This provided a
useful opportunity for residents to realize ‘the existence of larval
forms/mosquitoes in their own houses’ (DA 1-concept), to ‘recognize
containers that were serving as breeding sites’ (MB1-concept), to emphasize
the idea that ‘domestic control could be efficient in the A.
aegypti control’ (DA2-concept), and finally to comprehend that
their ‘residential area had (indeed) vector-mosquitoes’
(LC1-concept).In contrast to the improvement in the above stated concepts, the percentage of people
who believed in ‘false mosquito breeding inducers, such as, animals or food
debris’ augmented after the outbreak and thus, MB2-concept was the sole
concept of which assimilation had declined after the outbreak. Female residents may
have ‘erroneously indorsed A. aegypti’s proliferation
to dirty environments’ (with food debris or animals). This assumption could
be interpreted as an intuitive explanation for the appearance/establishment of the
A. aegypti and dengue disease in the Island. As stated in
psychology in the attribution theory, humans need to “attribute”
causes to events which are not understood [27]. Female residents, who agreed with latter belief, and
believe to live in clean households, will not feel responsible to perform domestic
source reduction.Finally, almost all the female residents agreed with the efficacy of domestic source
reduction in the control of mosquitoes (CM1-concept). However, the majority
still erroneously consider ‘insecticide application or flyswatter
usage’ as effective measures to control mosquito population (CM2-concept). In
fact, these practices are protective (i.e. can, in some manner, avoid the mosquito
bite) but are not preventive (i.e. are able to control the mosquito proliferation).
This mistake is determinant because people that believe in it tend to focus their
efforts on these easier but less efficient practices and to disfavour the truly
efficient ones, which are more difficult to implement (such as, domestic source
reduction). Moreover, previous studies had shown that the local A.
aegypti population, present in Madeira Island, was resistant to the
most common insecticides, which raised questions about the reasonability of its
application, even when used with protective objectives [28].Overall, there were only three Essential Concepts that were still not considered by
the majority of the studied population (LC2-concept, MB2-concept and CM2-concept).
Under the assumptions of the EP-analysis, the individual minimal understanding and
putative subsequent compliance to the proposed behaviour, requires the assimilation
of all the ten concepts defined as ‘essential'. Consequently, the weak
integration of one of these concepts by the community can compromise the usefulness
of the behaviour impact campaigns. It is worth pointing out that, even though
concept assimilation had generally improved after the outbreak, only 4.5% of the
studied population achieved the referred ‘minimal understanding’
(EP-Score equal to ten). Consequently, there were still very few residents that are
ready to engage in the proposed behaviour.Along with the observed improvement of essential concept assimilation, myths believed
by the community also changed. Even though the community is now closer to
the needed ‘minimal understanding’, the task of local authorities is
still difficult since after the outbreak they have to cope with new/different
beliefs, following ideas such as ‘Madeira is immune to suffer a
second outbreak’ (alleged myth 3 and 6).In reality, myths could subtly persist in the community, weakening the effect of
strategies aimed at behaviour changes. Therefore, an adequate monitoring of public
perceptions is undoubtedly crucial to (more quickly) detect them, allowing
preventive campaigns to be planned accordingly. Apart from the here observed public
erroneous interpretations (probably caused by their short contact with the vector
and the disease) community can provide other enriching contribution such as
technical hitches in implementing proposed behaviours, pointing out messages or
expressions difficult to understand, and suggesting housewives-friendly solutions
[29,30].The similarity found between paired and non-paired samples, regarding their EP-score
levels supported the validity of the criteria used in the adjusted matching
approach. Moreover, the observed equivalent results between the adjusted and the
restricted matching procedures corroborated the validity of the geographical
adjustments. Furthermore, the calculated power value supported the strength of the
results albeit the apparently small size of the sample. In fact, prior sample size
estimations indicated a minimal amount of 157 subjects required to fulfil the
objectives of this study (as mentioned in Methods section), assuming a minimal
difference (1 point) between the EP-score levels from PRE/POST-outbreak studies.
However, since a difference of 2 point was observed, only 40 pairs of subjects were
needed to detect it fulfilling the same objectives (S2 Table). The studied sample size was
thus higher than the required to the aimed analysis. Therefore, the power associated
to Wilcoxon test is also high as described in Table 6.It is worth noticing that considering the studied sample, only women from urban areas
were covered, and therefore results may not be equivalent in male subjects, rural
communities or in long-term dengue regions.In conclusion, after experiencing a dengue outbreak in Madeira Island, female
community perception towards the aimed preventive engagement improved in some
aspects (as intuitively expected) but also deviated in other aspects, particularly
by the emergence of new myths. The most frequent myths may be used in the future to
outline appropriate priority messages. Subsequent health-messages tailored according
to present findings could strengthen community engagement in dengue-preventive
behaviours.Monitoring public perceptions (before/after an intervention or an outbreak) revealed
a great value, not only for public health professionals but also for researchers who
may be interested in investigating the complex interplay between experiences,
perceptions and decision-making. Thus, lessons taken from this work can be useful
not only for local authorities but also for all professionals who are engaged in
dengue preparedness in endemic or epidemic countries, as well as, to those
interested in strengthening tools for other behaviour-based preventable
diseases.
STROBE check list.
(DOC)Click here for additional data file.
Dengue outbreak incidence (2012) and PRE-outbreak and POST-outbreak study
areas.
Figure shows the incidence rate of the 2012 dengue outbreak (probable dengue
cases per 10.000 residents). Administrative boundaries refer to
‘Municipalities’.(TIF)Click here for additional data file.
The EP-score median differences regarding gender from PRE-outbreak
study.
Figure shows the output scheme from Statistical Package for Social Sciences
19.0 (SPSS, Inc., Chicago, IL, USA) for EP-score representation by Gender in
PRE-outbreak study (n = 1145).(TIF)Click here for additional data file.
Example of a myth.
An example of how a myth can appear from partial/non-cumulative
acknowledgement (not covering all essential concepts defined by the
Essential Perception analysis).(TIF)Click here for additional data file.
The EP-score median differences regarding from PRE-outbreak
study.
Comparison of EP-score medians, percentiles according to Gender in
PRE-outbreak study total sample and respective p-value(DOCX)Click here for additional data file.
Sample size estimation of the PRE/POST pairs required for comparison of
their EP-score means.
Results from Epitools’ sample size calculators for a comparison of two
means using the t-test (2-tailed) [24].(DOCX)Click here for additional data file.
Analysis of the restricted matching process Municipality
adjustment.
Comparisons of EP-Score medians between ‘Municipalities’
according to their Education level(DOCX)Click here for additional data file.
Socio-demographic characterization of Funchal’s
municipalities.
Santa Luzia (SL), São Pedro (SP), Sé, Imaculado
Coração de Maria (ICM) and Santa Maria Maior (SMM).
Differences between proportions of those included in the PRE-study (SP and
SL, in green) and those that were added in the POST-study (Sé, ICM
and SMM in orange) are presented (in grey).(DOCX)Click here for additional data file.
Authors: Teresa Nazareth; Rosa Teodósio; Graça Porto; Luzia Gonçalves; Gonçalo Seixas; Ana Clara Silva; Carla Alexandra Sousa Journal: BMC Public Health Date: 2014-01-15 Impact factor: 3.295