Incidence of malaria is clustered and buffers around plantations: a spatial analysis

Background Malaria is re-emerging because of imported cases and the presence of potential vectors that can transmit and spread malaria. Malaria is a health problem in Banyumas District. Mapping the spread of infectious diseases is epidemiologically important. The purpose of this study was to determ...

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Main Authors: Yudhi Wibowo, Agung Saprasetya Dwi Laksana, Joko Mulyanto, Madya Ardi Wicaksono, Agus Y Purnomo
Format: Article
Language:English
Published: Faculty of Medicine Trisakti University 2015-08-01
Series:Universa Medicina
Subjects:
Online Access:http://www.univmed.org/wp-content/uploads/2015/09/yudi1.pdf
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author Yudhi Wibowo
Agung Saprasetya Dwi Laksana
Joko Mulyanto
Madya Ardi Wicaksono
Agus Y Purnomo
author_facet Yudhi Wibowo
Agung Saprasetya Dwi Laksana
Joko Mulyanto
Madya Ardi Wicaksono
Agus Y Purnomo
author_sort Yudhi Wibowo
collection DOAJ
description Background Malaria is re-emerging because of imported cases and the presence of potential vectors that can transmit and spread malaria. Malaria is a health problem in Banyumas District. Mapping the spread of infectious diseases is epidemiologically important. The purpose of this study was to determine the relationship between the variables and the epidemiology of malaria that were spatially modeled using the geographic information system (GIS). Methods This was a case-control study with ratio of 1:1. Cases were malaria-positive patients and controls were people without malaria, as diagnosed by microscopic examination. Minimum sample size was 139 per group and total sample size was 282 people. Chi-square was used to test the relationship between the variables, and GIS modeling to determine the spatial distribution of malaria cases. Results There were significant relationships between level of income below minimum wage, not using mosquito nets, not using wire netting, not using insect repellents, habit of going out at night, history of malaria, cattle sheds not located between woods and residential area, history of going to endemic areas, residence at distances <1000 m from plantations, bushes, swamps and puddles, with incidence of confirmed malaria (p<0.001). The group of cases living <1000 meters from plantations numbered 141 (100%). Conclusions Malaria incidence is clustered and buffers around plantations at <1000 m. Malaria hot spots are displayed as risk maps that are useful for monitoring and spatial targeting of prevention and control measures against the disease.
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spelling doaj.art-bd25ff1a0e184e04b431a263af8303de2022-12-22T00:21:36ZengFaculty of Medicine Trisakti UniversityUniversa Medicina1907-30622015-08-0134213814810.18051/UnivMed.2015.v34.138Incidence of malaria is clustered and buffers around plantations: a spatial analysisYudhi Wibowo0Agung Saprasetya Dwi Laksana1Joko Mulyanto2Madya Ardi Wicaksono3Agus Y Purnomo4Department of Public Health and Community Medicine, Faculty of Medicine Jenderal Soedirman UniversityDepartment of Public Health and Community Medicine, Faculty of Medicine Jenderal Soedirman UniversityDepartment of Public Health and Community Medicine, Faculty of Medicine Jenderal Soedirman UniversityDepartment of Public Health and Community Medicine, Faculty of Medicine Jenderal Soedirman UniversityStaff at Magetan District Health Office, Magetan, East JavaBackground Malaria is re-emerging because of imported cases and the presence of potential vectors that can transmit and spread malaria. Malaria is a health problem in Banyumas District. Mapping the spread of infectious diseases is epidemiologically important. The purpose of this study was to determine the relationship between the variables and the epidemiology of malaria that were spatially modeled using the geographic information system (GIS). Methods This was a case-control study with ratio of 1:1. Cases were malaria-positive patients and controls were people without malaria, as diagnosed by microscopic examination. Minimum sample size was 139 per group and total sample size was 282 people. Chi-square was used to test the relationship between the variables, and GIS modeling to determine the spatial distribution of malaria cases. Results There were significant relationships between level of income below minimum wage, not using mosquito nets, not using wire netting, not using insect repellents, habit of going out at night, history of malaria, cattle sheds not located between woods and residential area, history of going to endemic areas, residence at distances <1000 m from plantations, bushes, swamps and puddles, with incidence of confirmed malaria (p<0.001). The group of cases living <1000 meters from plantations numbered 141 (100%). Conclusions Malaria incidence is clustered and buffers around plantations at <1000 m. Malaria hot spots are displayed as risk maps that are useful for monitoring and spatial targeting of prevention and control measures against the disease.http://www.univmed.org/wp-content/uploads/2015/09/yudi1.pdfRisk factorsspatial analysismalaria incidence
spellingShingle Yudhi Wibowo
Agung Saprasetya Dwi Laksana
Joko Mulyanto
Madya Ardi Wicaksono
Agus Y Purnomo
Incidence of malaria is clustered and buffers around plantations: a spatial analysis
Universa Medicina
Risk factors
spatial analysis
malaria incidence
title Incidence of malaria is clustered and buffers around plantations: a spatial analysis
title_full Incidence of malaria is clustered and buffers around plantations: a spatial analysis
title_fullStr Incidence of malaria is clustered and buffers around plantations: a spatial analysis
title_full_unstemmed Incidence of malaria is clustered and buffers around plantations: a spatial analysis
title_short Incidence of malaria is clustered and buffers around plantations: a spatial analysis
title_sort incidence of malaria is clustered and buffers around plantations a spatial analysis
topic Risk factors
spatial analysis
malaria incidence
url http://www.univmed.org/wp-content/uploads/2015/09/yudi1.pdf
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