Impact of climate and landuse variability based on dengue epidemic outbreak in Subang Jaya

Nazri, C.D.; Hassan, Ahmad; Latif, Zulkiflee Abd; Ismail, Rozaina

doi:10.1109/chuser.2011.6163869

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Many previous studies show the association of rainfall, temperature, relative humidity, and population density with dengue cases in high-risk areas (Sharmin et al, 2018;Zhu et al, 2016). In Malaysia, investigations revealed that dengue fever incidence was related to rainfall, temperature, relative humidity, and land use (Khushairi et al, 2021;Nazri et al, 2011;Syaza et al, 2017). Due to the climate-sensitive nature of dengue, the preventive program should denote the hotspot locations with a combination of environmental data.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial and Temporal Analysis of Dengue Cases in Peninsular Malaysia: A five-year analysis from 2016 to 2020

Nor

Dom

Abdullah

et al. 2022

E-BPJ

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Dengue fever is one of the most common vector-borne diseases spread by Aedes albopictus and Aedes aegypti mosquitos. The regional and temporal trends of dengue cases in East Malaysia are investigated in this study. The study aims to assess the prevalence of dengue cases across 91 districts in Peninsular Malaysia from 2016 to 2020 and, hence, to identify dengue disease's hotspot and cold spot regions. By using ArcGIS, summarised yearly data of dengue cases were analysed. The study results showed that dengue cases mainly occurred in the central part of Peninsular Malaysia. Keywords: GIS; Vector-borne diseases; Aedes; Spatial epidemiology eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i20.3487

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Section: Literature Reviewmentioning

confidence: 99%

Spatial and Temporal Analysis of Dengue Cases in Peninsular Malaysia: A five-year analysis from 2016 to 2020

Nor

Dom

Abdullah

et al. 2022

E-BPJ

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“…These different categories of LU have different ecological responses to mosquito and dengue dynamics (Thammapalo, et al 2007); hence, detailed maps might amplify the chances to capture fine scale variations of mosquito habitats and dengue incidence. Although labor intensive, detailed LU maps produced by local governmental agencies based on field observations can help uncover patterns of dengue disease at a fine scale by capturing the different categories of land utilization in urban areas (Nazri, et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Dengue Disease Dynamics are Modulated by the Combined Influence of Precipitation and Landscapes: A Machine Learning-based Approach

Francisco

Carvajal

Ryo

et al. 2020

Preprint

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BackgroundDengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors interact in time and space to affect mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain or flood water.ObjectivesThis study aimed to investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence.MethodsEntomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metro Manila, Philippines, from 2012 to 2014. Temperature, precipitation, and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterwards, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combinatory influences of landscape and climate factors on the ovitrap index and dengue incidence.ResultsThe MOB recursive partitioning for the ovitrap index indicated that mosquito occurrence was higher in high residential density areas, where industrial areas also exist and are well connected with roads. Precipitation was another key covariate modulating the effects of landscape factors, possibly by expanding breeding sites and activating mosquito reproduction. Moreover, the MOB recursive partitioning indicated that precipitation was the main predictor of dengue incidence, with a stronger effect in high residential density and commercial areas.DiscussionPrecipitation with floods has epidemiologically important implications by damaging shelters and causing population displacement, thus increasing exposure to dengue vectors. Our findings suggest that the intensification of vector control during the rainy season can be prioritized in residential and commercial areas to better control dengue disease dynamics.

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Dengue cases distribution based on land surface temperature and elevation

Roslan

Latif

Dom

2016

2016 7th IEEE Control and System Graduate Research Colloquium (ICSGRC)

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Impact of climate and landuse variability based on dengue epidemic outbreak in Subang Jaya

Cited by 7 publications

References 10 publications

Spatial and Temporal Analysis of Dengue Cases in Peninsular Malaysia: A five-year analysis from 2016 to 2020

Spatial and Temporal Analysis of Dengue Cases in Peninsular Malaysia: A five-year analysis from 2016 to 2020

Dengue Disease Dynamics are Modulated by the Combined Influence of Precipitation and Landscapes: A Machine Learning-based Approach

Dengue cases distribution based on land surface temperature and elevation

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