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The Effects of Meteorological Factors on Dengue Cases in Malaysia

Dengue is a vector-borne disease affected by meteorological factors and is commonly recorded from ground stations. Data from ground station have limited spatial representation and accuracy, which can be overcome using satellite-based Earth Observation (EO) recordings instead. EO-based meteorological...

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Autores principales: Singh, Sarbhan, Herng, Lai Chee, Sulaiman, Lokman Hakim, Wong, Shew Fung, Jelip, Jenarun, Mokhtar, Norhayati, Harpham, Quillon, Tsarouchi, Gina, Gill, Balvinder Singh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9180499/
https://www.ncbi.nlm.nih.gov/pubmed/35682035
http://dx.doi.org/10.3390/ijerph19116449
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author Singh, Sarbhan
Herng, Lai Chee
Sulaiman, Lokman Hakim
Wong, Shew Fung
Jelip, Jenarun
Mokhtar, Norhayati
Harpham, Quillon
Tsarouchi, Gina
Gill, Balvinder Singh
author_facet Singh, Sarbhan
Herng, Lai Chee
Sulaiman, Lokman Hakim
Wong, Shew Fung
Jelip, Jenarun
Mokhtar, Norhayati
Harpham, Quillon
Tsarouchi, Gina
Gill, Balvinder Singh
author_sort Singh, Sarbhan
collection PubMed
description Dengue is a vector-borne disease affected by meteorological factors and is commonly recorded from ground stations. Data from ground station have limited spatial representation and accuracy, which can be overcome using satellite-based Earth Observation (EO) recordings instead. EO-based meteorological recordings can help to provide a better understanding of the correlations between meteorological variables and dengue cases. This paper aimed to first validate the satellite-based (EO) data of temperature, wind speed, and rainfall using ground station data. Subsequently, we aimed to determine if the spatially matched EO data correlated with dengue fever cases from 2011 to 2019 in Malaysia. EO data were spatially matched with the data from four ground stations located at states and districts in the central (Selangor, Petaling) and east coast (Kelantan, Kota Baharu) geographical regions of Peninsular Malaysia. Spearman’s rank-order correlation coefficient (ρ) was performed to examine the correlation between EO and ground station data. A cross-correlation analysis with an eight-week lag period was performed to examine the magnitude of correlation between EO data and dengue case across the three time periods (2011–2019, 2015–2019, 2011–2014). The highest correlation between the ground-based stations and corresponding EO data were reported for temperature (mean ρ = 0.779), followed by rainfall (mean ρ = 0.687) and wind speed (mean ρ = 0.639). Overall, positive correlations were observed between weekly dengue cases and rainfall for Selangor and Petaling across all time periods with significant correlations being observed for the period from 2011 to 2019 and 2015 to 2019. In addition, positive significant correlations were also observed between weekly dengue cases and temperature for Kelantan and Kota Baharu across all time periods, while negative significant correlations between weekly dengue cases and temperature were observed in Selangor and Petaling across all time periods. Overall negative correlations were observed between weekly dengue cases and wind speed in all areas from 2011 to 2019 and 2015 to 2019, with significant correlations being observed for the period from 2015 to 2019. EO-derived meteorological variables explained 48.2% of the variation in dengue cases in Selangor. Moderate to strong correlations were observed between meteorological variables recorded from EO data derived from satellites and ground stations, thereby justifying the use of EO data as a viable alternative to ground stations for recording meteorological variables. Both rainfall and temperature were found to be positively correlated with weekly dengue cases; however, wind speed was negatively correlated with dengue cases.
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spelling pubmed-91804992022-06-10 The Effects of Meteorological Factors on Dengue Cases in Malaysia Singh, Sarbhan Herng, Lai Chee Sulaiman, Lokman Hakim Wong, Shew Fung Jelip, Jenarun Mokhtar, Norhayati Harpham, Quillon Tsarouchi, Gina Gill, Balvinder Singh Int J Environ Res Public Health Article Dengue is a vector-borne disease affected by meteorological factors and is commonly recorded from ground stations. Data from ground station have limited spatial representation and accuracy, which can be overcome using satellite-based Earth Observation (EO) recordings instead. EO-based meteorological recordings can help to provide a better understanding of the correlations between meteorological variables and dengue cases. This paper aimed to first validate the satellite-based (EO) data of temperature, wind speed, and rainfall using ground station data. Subsequently, we aimed to determine if the spatially matched EO data correlated with dengue fever cases from 2011 to 2019 in Malaysia. EO data were spatially matched with the data from four ground stations located at states and districts in the central (Selangor, Petaling) and east coast (Kelantan, Kota Baharu) geographical regions of Peninsular Malaysia. Spearman’s rank-order correlation coefficient (ρ) was performed to examine the correlation between EO and ground station data. A cross-correlation analysis with an eight-week lag period was performed to examine the magnitude of correlation between EO data and dengue case across the three time periods (2011–2019, 2015–2019, 2011–2014). The highest correlation between the ground-based stations and corresponding EO data were reported for temperature (mean ρ = 0.779), followed by rainfall (mean ρ = 0.687) and wind speed (mean ρ = 0.639). Overall, positive correlations were observed between weekly dengue cases and rainfall for Selangor and Petaling across all time periods with significant correlations being observed for the period from 2011 to 2019 and 2015 to 2019. In addition, positive significant correlations were also observed between weekly dengue cases and temperature for Kelantan and Kota Baharu across all time periods, while negative significant correlations between weekly dengue cases and temperature were observed in Selangor and Petaling across all time periods. Overall negative correlations were observed between weekly dengue cases and wind speed in all areas from 2011 to 2019 and 2015 to 2019, with significant correlations being observed for the period from 2015 to 2019. EO-derived meteorological variables explained 48.2% of the variation in dengue cases in Selangor. Moderate to strong correlations were observed between meteorological variables recorded from EO data derived from satellites and ground stations, thereby justifying the use of EO data as a viable alternative to ground stations for recording meteorological variables. Both rainfall and temperature were found to be positively correlated with weekly dengue cases; however, wind speed was negatively correlated with dengue cases. MDPI 2022-05-26 /pmc/articles/PMC9180499/ /pubmed/35682035 http://dx.doi.org/10.3390/ijerph19116449 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Singh, Sarbhan
Herng, Lai Chee
Sulaiman, Lokman Hakim
Wong, Shew Fung
Jelip, Jenarun
Mokhtar, Norhayati
Harpham, Quillon
Tsarouchi, Gina
Gill, Balvinder Singh
The Effects of Meteorological Factors on Dengue Cases in Malaysia
title The Effects of Meteorological Factors on Dengue Cases in Malaysia
title_full The Effects of Meteorological Factors on Dengue Cases in Malaysia
title_fullStr The Effects of Meteorological Factors on Dengue Cases in Malaysia
title_full_unstemmed The Effects of Meteorological Factors on Dengue Cases in Malaysia
title_short The Effects of Meteorological Factors on Dengue Cases in Malaysia
title_sort effects of meteorological factors on dengue cases in malaysia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9180499/
https://www.ncbi.nlm.nih.gov/pubmed/35682035
http://dx.doi.org/10.3390/ijerph19116449
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