Volume 17 (Issue 1) June 2024

I n te rn a ti o n a l Jo u rn a l on S ust ainabl e T r opic al D esign R esear c h and P r ac t ic e

A CONCEPTUAL FRAMEWORK FOR ASSESSING THE FIELD EFFICIENCY OF DRONES

IN IDENTIFYING POTENTIAL BREEDING SITES OF THE Aedes MOSQUITO
Zulfadli Mahfodz1,2*, Nazri Che Dom1, Hasber Salim3 and Nopadol Precha4
1
Faculty of Health Sciences, Universiti Teknologi MARA, Selangor Branch, Puncak Alam Campus, 42300 Selangor, Malaysia
2
Faculty of Applied Sciences, Universiti Teknologi MARA, Perak Branch, Tapah Campus, Tapah Road, 35400 Perak, Malaysia
3
School of Biological Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia
4
Department of Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat, Thailand

ARTICLE INFO ABSTRACT

Keywords: The identification of breeding sites is crucial for effective dengue prevention strategies. Com-
Aedes mosquito, munity readiness and surveillance of these sites are essential for controlling the Aedes mosquito
breeding site, population. Drones have emerged as a promising tool for surveillance activities. This paper aims
drones, to develop a conceptual framework and present comprehensive intervention methods for con-
machine learning, trolling dengue cases. The study explores community readiness, habitat profiling, and mapping.
surveillance Phase I focuses on community readiness, using a questionnaire to gather information about the
community’s knowledge, attitudes, and practices related to dengue control. Phase II involves
profiling and mapping potential breeding sites of Aedes mosquitoes in selected areas using in-
novative drone technologies. This phase aims to identify and characterize breeding sites based
on various parameters, such as size, water quality, and proximity to human dwellings. System-
atic aerial surveys with drones equipped with high-resolution cameras and sensors will capture
detailed images and environmental data. The results will be presented in interactive maps and
detailed reports, supporting targeted interventions and data-driven decision-making for effective
dengue prevention and control. This conceptual framework can assess the efficiency of drones
as an alternative tool for dengue surveillance, which can be applied in dengue-endemic regions.

1. INTRODUCTION

Aedes aegypti is the main vector of dengue, yellow fever, and awareness (Hasnan et al., 2017; Madzlan et al., 2017). The strategies
chikungunya (Passos et al., 2022). There are no vaccines or antiviral employed to control mosquitoes differ according to the individual,
treatments available to treat mosquito-borne diseases. Therefore, community, and regional environments (Joshi & Miller, 2021). The
the most appropriate method currently available for combating COVID-19 pandemic has affected dengue monitoring and control
these diseases is to remove any potential mosquito breeding field technicians dynamically as they confront a new occupational
sites (Rahman et al., 2021). In general, the breeding sites can be hazard (Valdez-Delgado et al., 2021). Currently, health inspectors
categorized as either artificial or natural containers (Amarasinghe are required to visit residences to identify and destroy mosquito
et al., 2017). Aedes mosquitoes reproduce in stagnant and clean breeding grounds. This practice is difficult for officials to carry
water (Mehra et al., 2016). Subsequently, all water-holding out and presents a number of disadvantages, including time limits,
containers have the potential to serve as breeding grounds. Mosquito safety hazards, and high expenses (Mehra et al., 2016; Passos et
control and monitoring efforts can become costly, time-wasting, al., 2022). Drones were originally envisioned as simple devices,
and ineffective without sufficient technical support (Passos et al., but their complexity has developed in tandem with the intricacy of
2022). Contributing to the failure of control programmes are human their designated duties. According to Hardy et al. (2022) and Mohd
social factors, improper garbage collection, and a lack of hygienic Daud et al. (2022), the type, size, power, and application conditions
of drones are the main factors that determine their operational
*Corresponding author: zulfa2015@uitm.edu.my capabilities.
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Drones are used in public health research for a wide range of to those with no technical background. As stated in Valdez-Delgado
purposes, including tracing survivors after natural disasters, shipping et al. (2021), the advancement of machine learning must be further
medical supplies to isolated areas, and providing initial treatment investigated, and further research is required to spread out the usage
in emergency locations (Carrillo-Larco et al., 2018; Fornace et al., of neural networks in mosquito surveillance. Improving the precision
2014; Hiebert et al., 2020; Passos et al., 2022). Drones are also put of technology requires a comprehensive commitment and data from
into operation in various other fields, including agriculture, forestry, many images representing a vast array of situations.
ecology, and environmental monitoring (Stanton et al., 2021). The
As preliminary data, we conducted a SWOT analysis (Figure 1) on
evidence on the efficiency of drones in finding mosquito breeding
the viability of using drones for surveillance based on information
sites is insufficient and limited (Valdez-Delgado et al., 2021).
from related articles. Each article described a new and better way to
Satellite imaging is considered unfeasible due to its long repeat times,
use drone images to find possible mosquito breeding grounds. The
cloud contamination, limited geographical and temporal resolutions,
ability of drones to fly in difficult-to-access areas is their greatest
and high costs (Fornace et al., 2014; Hardy et al., 2022). Rapid
advantage. According to Hardy et al. (2022), drones can not only
technological advancements, encouraged by commercial demand
capture images or videos with greater spatial or temporal resolution
and open market competition, have changed drones from mere
but also from a variety of angles and heights. In addition, deploying
hobbies into potentially useful tools that can shorten surveillance
programmable drones increases health inspectors’ safety by
activities and enrich mosquito control programmes (Faraji et al.,
decreasing their contact with potentially hazardous incidents or sets.
2021).
The initial cost of drone hardware is considerable, but it is feasible
In this study, aerial photography of water retention from drones used since a small team can cover a vast area from the air with minimal
to produce a map. It supplies data based on the shadow effect and operating costs (Chiroli et al., 2017). Drone implementation for
the tilt angle of the drone camera with adequate precision to detect mosquito breeding site surveillance may face numerous challenges.
water retention. This is related to the studies in Carrasco-Escobar For example, the laws and guidelines for flying drones in each region
et al. (2019) and Haas-Stapleton et al. (2019), which examine the are different. There is no standard set of guidelines for operating
properties of water bodies to identify potential mosquito breeding or regulating drones; there are restricted zones where drones cannot
places. In the study conducted by Dias et al. (2018), drones were be used; there are topographic and climate differences; there are
operated to attain many aerial image configurations for a database. privacy concerns; and community attitudes towards and acceptance
Using the collected photos and the annotated database, the proposed of drones vary across cultures (Annan et al., 2022; Mohd Daud et
system was tested and trained. This technology allows the detection al., 2022; Poljak & Šterbenc, 2020). The scalability of the proposed
of tiny objects that cannot be observed by existing remote sensing method may be limited due to limitations in the geographical area
methods (Bravo et al., 2021). In the study, Mukabana et al. (2022) that a single drone can cover (Bravo et al., 2021). However, Hardy
provided an example of architectural innovation by combining two et al. (2017) demonstrated that a low-cost drone can be used to map
established technologies and executing them in a new market and water bodies in various settings, including natural water bodies, rice
context. The results revealed that a combination of drone application paddies, and urban areas, with the goal of identifying and mapping
and insecticides can effectively reduce mosquito populations in an aquatic mosquito habitats. A well-organized database for identifying
irrigated rice agroecosystem. Most of the research emphasizes that and categorizing objects in aerial videos is also an essential element.
developments in computer and software engineering and computer Among the features highlighted by Passos et al. (2022), a database
science are the primary drivers of drone technological growth (Mohd should have a significant number of samples for each target group,
Daud et al., 2022). Numerous significant outcomes have been yielded an absence of image distortions, and precise object annotation.
by the application of technology to drones. Drone surveying attempts
Detecting water bodies in remote areas using drone-captured images
for man-made containers, for instance, are made more precise by
requires several technological and competence hurdles. Creating
pairing Global Positioning System (GPS) receivers with machine
orthomosaics from drone imagery is a time-consuming process that
learning techniques and image technologies like multispectral
calls for a powerful computer, a huge space for records of information,
imaging (Schenkel et al., 2020). In the following investigation was
and specialised software (Stanton et al., 2021; Wyngaard et al.,
reported in Ali et al. (2022), they merged the Internet of Medical
2018). In addition to hardware and software concerns, misconfigured
Things (IoMT) and Geographic Information System (GIS) maps.
drones can pose risks and vulnerabilities (Wyngaard et al., 2018).
The authors provide a way to mitigate and manage dengue virus
Flight experience was essential for calculating the ideal flight hours,
outbreaks through call data record analysis. Once the patient’s
as the drone could not be piloted in rainy weather and the influence of
specific location has been confirmed, a spray unit will be alerted
adverse weather on the equipment could cause it to overheat on hot
to send out drones to treat the affected area. In another scenario,
days. More engagements between stakeholders and specialists across
Hardy et al. (2022) analyse drone data using a hybrid of mapping
disciplines are required to provide more specific recommendations
methods: supervised image classification using machine learning
on how this technology can be used most efficiently (Stanton et al.,
and technology-assisted digitising mapping that is accessible even
2021).

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2022)global health security has been threatened by the geographical

expansion of vector-borne infectious diseases such as malaria,
dengue, yellow fever, Zika and chikungunya. For a range of these
vector-borne diseases, an increase in residual (exophagic.

2.1 Evaluation of the Conceptual Framework

This phase focuses on assessing community readiness for dengue

prevention strategies using a detailed questionnaire. The questionnaire
collects data on community demographics, knowledge of dengue
(such as awareness of transmission and symptoms), attitudes towards
dengue prevention (including concern and perceived responsibility),
and practices related to dengue control (such as source reduction
and use of protective measures). It also explores perceived
barriers and the community’s acceptance of drone technology for
mosquito surveillance. This data is coded and analyzed to identify
Figure 1: SWOT analysis on the viability of using drones for surveillance common themes and develop a theoretical framework that explains
activities community readiness and influencing factors. This approach
ensures that interventions are culturally sensitive and contextually
Therefore, from the literature search and SWOT analysis, the
appropriate, enhancing community participation and supporting
objective of this paper is to develop a conceptual framework and
effective dengue prevention implementation. The insights gained
discuss the intervention methods that are summarized in Figure
help tailor interventions to specific community needs and foster a
2. These phases revolve around three main interventions whereby
collaborative approach to dengue control (Charmaz, 2014; Creswell
community assessment, profiling potential habitat, and technology
& Poth, 2018).
integration are fully taken into consideration in developing
sustainable dengue preventive measures. It is essential to have 2.2 Feasibility of the Approach
a comprehensive understanding of the conceptual frameworks
To enhance the effectiveness and sustainability of dengue control
associated with different aspects in dengue management. This
measures, it is crucial to promote evidence-based strategies, utilize
includes understanding how communities are mobilized, their roles
local knowledge and scientific skills, and incorporate innovative
in vector control, efforts in health education, and the ability to
solutions in collaboration with communities. Implementing new
sustain new prevention measures over a long period of time.
technologies is most convenient when linked with participatory
2. PHASE I: COMMUNITY ASSESSMENT processes that strengthen household engagement, civil society, and
system accountability. Participatory action research framework
Many studies related to the prevention and control of the Aedes
can be used to reevaluate any challenges and rapidly test multiple
mosquito indicate that household intervention can aid in larval
strategies tailored to specific geographic locations (Duque et al.,
reduction programmes; however, empowering and sustaining
2019). To enable the effective implementation of health data systems,
such practises over time and outside of research projects can be
specialized techniques are specifically designed for healthcare
challenging (Rahman et al., 2021)we aimed to map the spatial
domains. Thus, enhance the performance and effectiveness of the
distribution of female adult Ae. aegypti and predict its abundance in
system, facilitate learning and user experience, minimize medical
northeastern Thailand based on socioeconomic, climate change, and
faults, design time, funding, and training costs (Zhang, 2005). This
dengue knowledge, attitude and practices (KAP. The integration of
approach will also emphasize the performance efficiency, security
household involvement into routine dengue programmes, including
and privacy, usability, and portability of the proposed project. This
the most effective strategies, types of educational materials
process will ensure that the technology products adopted for the
needed, programme regularity, and participation models, is still
project are prototyped, examined, and fine-tuned to improve their
the subject of ongoing research. As discussed by Kleinman (2010),
performance and acceptance by end-users.
interventions are dynamic, can result in unforeseen effects, and
are socially established. A review of dengue programmes in four 3. PHASE II: PROFILING POTENTIAL BREEDING
countries by Horstick et al. (2010)questionnaires indicated several SITES OF Aedes MOSQUITO
factors that contributed to the failure of the programmes. It includes
In several regions worldwide, Aedes mosquitoes primarily inhabit
a shortage of manpower, funds, and knowledge; an overdependence
artificial containers (Carrasco-Escobar et al., 2022; Madzlan et
on chemicals; a low level of household participation; and a nearly
al., 2017). The physical landscape characteristics and availability
non-existent comprehensive assessment system. Therefore, any
of containers that can retain water have been discovered to be
interventions must be tailored according to the local landscape
critical elements in the reproduction of mosquitoes in Malaysia and
and engage specific communities at risk (Carrasco-Escobar et al.,
other countries (Muñiz-sánchez et al., 2022). Knowing the habitat
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characteristics and other elements like vegetation indices, land use, placement, the traps will be returned to the laboratory. Concurrently,
canopy cover, and elevation can provide comprehensive knowledge larval surveys will be done at prospective breeding sites identified
about mosquito abundance and distribution (Carrasco-Escobar et al., by the drone survey. The larvae of mosquitoes will be identified to
2022). Health inspectors are currently conducting larval surveys and the species level using the criteria given by the Malaysian Ministry
destroying dengue breeding grounds in dengue hotspot areas as part of Health. Three larval indices, namely the Aedes Index, Container
of the Ministry of Health Malaysia’s preventative measures. Due to Index, and Breteau Index, will also be measured in accordance with
broad coverage areas and a limited number of health inspectors in World Health Organization (WHO) standards.
each district, this task is time-consuming and cannot be completed
3.3 Data Analysis and Image Classification
properly. Consequently, drone-based monitoring of breeding sites
will have a wider scope, be more prospective, and require less The images captured by the drone will be used for visual inspection
human work. to find any water bodies that may serve as potential breeding sites.
Subsequently, a comprehensive map of the mosquito breeding
3.1 Drone Surveillance grounds and the surrounding landscape can be generated (Carrasco-
Aerial surveillance permits the identification of potential breeding Escobar et al., 2022)global health security has been threatened by
sites in areas that are inaccessible to traditional ground surveillance. the geographical expansion of vector-borne infectious diseases such
Thus, it assists health inspectors in accurately identifying and as malaria, dengue, yellow fever, Zika and chikungunya. For a range
mapping the breeding sites using drone images (Muñiz-sánchez of these vector-borne diseases, an increase in residual (exophagic.
et al., 2022). The size of mosquito breeding sites can be smaller Drones can generate various maps, including two-dimensional
than 1 meter; therefore, the ability of drones to capture high- maps, elevation maps, thermal maps, and three-dimensional maps
precision images is critical for analysis (Hardy et al., 2022). The or models. It can also gather precise information about the landscape
drone surveillance will be conducted using the method explained with a ground resolution that is significantly higher than that of
in Carrasco-Escobar et al. (2019). In selected study areas, weekly any current satellite imaging (Budiharto et al., 2021)developing
aerial surveys will be conducted using a drone to identify suitable 3D models using photogrammetric and situation mapping uses
outdoor breeding places such as pails, vessels, bins, and bowls. Any geographic information systems. The drone used has advantages in
man-made structures outside the buildings that can serve as breeding a wider range of areas with adequate power support. The drone is
grounds directly or indirectly will also be inspected. The drone will also supported by a high-quality camera with dreadlocks for image
fly to an altitude of approximately 100 meters in the selected urban stability, so it is suitable for use in mapping activities. Conclusions:
and rural areas, resulting in a sample distance of about 0.1 meters Using Google earth data at two separate locations as a benchmark for
per pixel on the ground. To construct an orthomosaic, 100 waypoints the accuracy of measurement of the area at three variations of flying
will be automatically determined in each grid to give a 70% overlap height in taking pictures, the results obtained were 98.53% (98.68%.
between neighbouring images. AgiSoft PhotoScan Pro will be utilized for photogrammetric analysis,
which requires photographically based surface measurements
3.2 Entomological Surveillance
(Hardy et al., 2017). The generated drone photography will be
Entomological surveillance is crucial to effectively monitor and imported into PhotoScan and used to construct orthomosaics, which
assess interventions, identify regions that require further surveillance, are geo-referenced mosaics of overlapping images with topographic
and assess the possibility of vector-borne transmission (Carrasco- distortion correction for each study site. The photogrammetric
Escobar et al., 2022)global health security has been threatened by method can be utilized to create a three-dimensional landscape that
the geographical expansion of vector-borne infectious diseases contains both natural and man-made parts of the environment. Then,
such as malaria, dengue, yellow fever, Zika and chikungunya. it can be fed straight into Geographic Information System (GIS)
For a range of these vector-borne diseases, an increase in residual software for visualisation (Carrasco-Escobar et al., 2022)global
(exophagic. The proposed method is modified from Muñiz-sánchez health security has been threatened by the geographical expansion
et al. (2022). The Aedes larval surveillance data will be derived from of vector-borne infectious diseases such as malaria, dengue, yellow
weekly inspections of selected areas for both natural and artificial fever, Zika and chikungunya. For a range of these vector-borne
containers. A breeding site will be georeferenced if a positive diseases, an increase in residual (exophagic. The potential breeding
Aedes mosquito is identified or suspected. A breeding site will be sites will be categorized based on various parameters, such as size,
considered positive if the sample contains at least one Ae. aegypti water quality, and proximity to human dwellings.
or Ae. albopictus larva. Expert taxonomists will identify the Aedes
larvae by using morphological criteria. Due to the varying sizes and 3.4 Machine Learning
forms of the research area, this study will superimpose a 200-meter Integration of available technologies like drones, machine learning,
grid system on the map of the study area and use these fixed grid deep learning and big data, can be used to have dependable evidence
cells as study units to minimise the amount of normalisation about mosquito population dynamics and administering areas at
required. Additionally, surveillance will be conducted within a risk (Muñiz-sánchez et al., 2022). Machine learning demonstrates
200-meter radius of the gravid oviposition traps. After five days of a crucial role in identifying mosquito breeding sites by utilizing

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collected data to train and classify ecological and geographical

landscape associated with potential breeding sites. Machine learning
models, although are not perfect, can differentiate between breeding
and non-breeding sites by processing large datasets using algorithms
such as Random Forest and Support Vector Machines (SVM) (Joshi
& Miller, 2021). Deep learning approaches like convolutional neural
networks (CNNs) are effective in image recognition (Bravo et al.,
2021). It is anticipated that the prediction models would reasonably
recognise proper images of potential breeding sites with water
retention zones. This approach allows local authorities to manage
mosquito control efforts more effectively, thus reducing dengue
cases.

Machine learning approaches have made a significant contribution, Figure 2: Overview of the proposed framework
especially in mapping potential breeding sites for mosquitoes. In the
3 CONCLUSION
study by Hardy et al. (2022), several dominant land cover classes
Due to the geographical expansion of dengue in recent years, the
were used, such as open water, open water with sunlight, emergent
information gathered through surveillance is essential for risk
vegetation, dry, and land cover types, to assist in the classification
evaluation and epidemic management, making it a vital component
process. In another example, Rahman et al. (2021)we aimed to
of dengue prevention. Surveillance activities should ideally involve
map the spatial distribution of female adult Ae. aegypti and predict
ecological monitoring and social risk issues in addition to the early
its abundance in northeastern Thailand based on socioeconomic,
detection of human infections and vector control. In Malaysia,
climate change, and dengue knowledge, attitude and practices (KAP
rigorous dengue control measures are implemented in certain
used five supervised learning models, which are logistic regression,
localities based on the notification of lab-confirmed human cases
support vector machine, k-nearest neighbour, artificial neural
and the location of dengue hotspots. Currently, house-to-house larval
networks, and random forest based on socioeconomic, climate
inspections by the health inspector, removing mosquito breeding
change, and dengue knowledge, attitude, and practices (KAP), to
sites, larvicide activities, and fogging are among the control
predict the abundance of mosquitoes (high and low). The use of
measures taken by the Ministry of Health, Malaysia. The feasibility
machine learning models for the prediction of mosquito abundance
of using drone technology in mosquito breeding control programmes
can provide significant information to authorities to design vector
should be contemplated as an effective alternative tool, as it could
surveillance and prevention strategies for outbreaks. By using
substitute for the time-consuming conventional process of observing
available data, machine learning can train and test the data, use the
larval habitats. This proposed framework, which integrates drones
model results to predict future outcomes, and improve the prediction
and technologies, community assessment, and collaboration with
from time to time. Figure 2 shows an overview of the proposed
government agencies, will add a new dimension to dengue prevention
framework.
and control programmes in Malaysia and other endemic regions.

ACKNOWLEDGEMENT

This research is supported by the Malaysian Ministry of Higher

Education and Universiti Teknologi MARA (UiTM) under the
Academic Training Scheme for Bumiputera (SLAB).

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