Geo spatial variation of dengue risk zone in Madurai city using autocorrelation techniques

Balaji, D.; Saravanabavan, V.

doi:10.1007/s10708-020-10143-1

Cited by 11 publications

(8 citation statements)

References 35 publications

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“…Penelitian yang dilakukan di Kabupaten Lumajang, Indonesia, menunjukkan pola sebaran kasus DBD termasuk kategori dispersed atau menyebar (13). Pola sebaran kasus DBD di Kota Madurai, India, juga termasuk kategori dispersed (menyebar) (14). Selain itu, sebaran kasus DBD di wilayah Seksyen 7 Shah Alam, Malaysia, juga menunjukkan autokorelasi spasial dengan kategori clustered atau berkerumun (15).…”

Section: Pembahasan Autokorelasi Spasial Demam Berdarah Dengueunclassified

Autocorrelation of Spatial Based Dengue Hemorrhagic Fever Cases in Air Putih Area, Samarinda City

Syamsir¹,

Pangestuty²

2020

JKL

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Introduction: Dengue Hemorrhagic Fever (DHF) is the disease that spread quickly in tropical and subtropical regions. DHF can spread quickly because the dengue virus is transmitted through the Aedes aegypti and Aedes albopictus into the human body. One of the provinces that felt the impact of the dengue outbreak was East Kalimantan, especially Samarinda City. Efforts to prevent dengue have been attempted by health center officials in Samarinda City. The cause has not yet been effective in controlling DHF programs in Samarinda City because there is no mapping of DHF vulnerable areas. This study aims to map the pattern of DHF distribution in the working area of the health center to maximize the implementation of the DHF control program. Methods: The population in this study were all DHF sufferers registered at the Air Putih Health Center in 2018. Withdrawal samples using total sampling techniques. The analysis used in this study is spatial autocorrelation analysis by Moran’s I. The Moran Index method is used to determine the autocorrelation of the distribution of DHF cases. Result and Discussion: The results of the autocorrelation analysis showed a Z score <-Z α/2, meaning Ho was rejected. This shows that there is spatial autocorrelation in the distribution of DHF in the Health Center. Based on the Moran’s I value (Moran’s I = -0.045850) which has a negative value indicates that the distribution of DHF in the working area of the Health Center tends to spread or dispersed. Conclusion: This study concludes that the more cases of DHF in a densely populated area, the greater the chance of spatial autocorrelation. The closeness between DHF cases can form spatial autocorrelation with the dispersed category.

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Section: Pembahasan Autokorelasi Spasial Demam Berdarah Dengueunclassified

Autocorrelation of Spatial Based Dengue Hemorrhagic Fever Cases in Air Putih Area, Samarinda City

Syamsir¹,

Pangestuty²

2020

JKL

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“…Madurai, situated in Tamil Nadu is one of the major dengue endemic region among various regions in India [10,11]. Aedes aegypti and Ae.…”

Section: Mosquito Sample Collectionmentioning

confidence: 99%

“…An association has been reported in Madurai district of Tamil Nadu between severe dengue epidemics and an increase in Ae. albopictus population during wet season [8][9][10][11][12]. Moreover, other studies in India have also highlighted the signi cance of Aedes mosquitoes as dengue vectors, emphasizing on vectorial capacity [13,14], insecticide susceptibility [15], and genetic diversity [16].…”

Section: Introductionmentioning

confidence: 99%

Genome resequencing and genome-wide polymorphisms in mosquito vectors Aedes aegypti and Aedes albopictus from south India

Acharya,

Singh,

Rajamannar

et al. 2024

Preprint

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Aedes aegypti and Aedes albopictus mosquitoes spread major vector-borne viral diseases in tropical and sub-tropical regions of the globe. In this study, we sequenced the genome of Indian Ae. aegypti and Ae. albopictus and mapped to their reference genomes. Comparative genomics were performed between our strain and the reference strains. A total of 14,416,484 single nucleotide polymorphisms (SNPs) and 156,487 insertions and deletions (InDels) were found in Ae. aegypti, and 28,940,433 SNPs and 188,987 InDels in Ae. albopictus. A special emphasis was given to gene families involved in mosquito digestion, development and innate immunity that could be putative candidates for vector control. Serine protease cascades and their inhibitors called serpins, play a central role in these processes. We extracted high-impact variants in genes associated with serine proteases and serpins. This study reports for the first time a high coverage genome sequence data of an Indian Ae. albopictus mosquito. The results from this study will provide insights into Indian Aedes specific polymorphisms and the evolution of immune related genes in mosquitoes, that can serve as a resource for future comparative genomics and for those pursuing development of targeted biopesticides for effective mosquito control strategies.

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“…Thus, the use of global and local spatial-temporal analysis tools such as the nearest neighbour index (NNI) [ 11 ]; the Getis Ord-Gi* statistic, used to detect hot and cold dengue spots with geographically homogeneous high or low values [ 12 ]; and kernel density, applied in several studies on dengue [ 13 , 14 ] among other techniques, allow the generation of maps that highlight the geographic areas and population groups at risk [ 15 , 16 ]. Those generated maps can serve as a basis for responsible institutions to design strategies for preventing and reducing the risk of dengue epidemics.…”

Section: Introductionmentioning

confidence: 99%

Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019

et al. 2023

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Dengue is an arbovirus transmitted by mosquitoes of the genus Aedes and is one of the 15 main public health problems in the world, including Colombia. Where limited financial resources create a problem for management, there is a need for the department to prioritize target areas for public health implementation. This study focuses on a spatio-temporal analysis to determine the targeted area to manage the public health problems related to dengue cases. To this end, three phases at three different scales were carried out. First, for the departmental scale, four risk clusters were identified in Cauca (RR ≥ 1.49) using the Poisson model, and three clusters were identified through Getis-Ord Gi* hotspots analysis; among them, Patía municipality presented significantly high incidence rates in the time window (2014–2018). Second, on the municipality scale, altitude and minimum temperature were observed to be more relevant than precipitation; considering posterior means, no spatial autocorrelation for the Markov Chain Monte Carlo was found (Moran test ˂ 1.0), and convergence was reached for b1–b105 with 20,000 iterations. Finally, on the local scale, a clustered pattern was observed for dengue cases distribution (nearest neighbour index, NNI = 0.202819) and the accumulated number of pupae (G = 0.70007). Two neighbourhoods showed higher concentrations of both epidemiological and entomological hotspots. In conclusion, the municipality of Patía is in an operational scenario of a high transmission of dengue.

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Geo spatial variation of dengue risk zone in Madurai city using autocorrelation techniques

Cited by 11 publications

References 35 publications

Autocorrelation of Spatial Based Dengue Hemorrhagic Fever Cases in Air Putih Area, Samarinda City

Autocorrelation of Spatial Based Dengue Hemorrhagic Fever Cases in Air Putih Area, Samarinda City

Genome resequencing and genome-wide polymorphisms in mosquito vectors Aedes aegypti and Aedes albopictus from south India

Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019

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