Estimasi Tingkat Intensitas Penularan Malaria dengan Dukungan Penginderaan Jauh (Studi Kasus di Daerah Endemis Malaria Pegunungan Menoreh Wilayah Perbatasan Provinsi Jawa Tengah dan Daerah Istimewa Yogyakarta)

Achmad, Holani and Mardihusodo, Sugeng Juwono and Sutanto, Sutanto and Hartono, Hartono (2003) Estimasi Tingkat Intensitas Penularan Malaria dengan Dukungan Penginderaan Jauh (Studi Kasus di Daerah Endemis Malaria Pegunungan Menoreh Wilayah Perbatasan Provinsi Jawa Tengah dan Daerah Istimewa Yogyakarta). Jurnal Ekologi Kesehatan, 2 (1). ISSN 1412-4025

Preview

Text 2386-819-1-PB.pdf - Published Version Download (457kB) | Preview

Abstract

Malaria transmission dynamic is naturally influenced by fluctuating environmental conditions that could be locally specific even at the level of village Remote sensing technology is increasingly recognized as a powerful tool to scan malaria endemic areas and could be used to monitor malaria vectors fluctuation and the related biogeographical environment. A study was conducted to estimate the malaria transmission intensity in eight endemic villages in Menoreh Hills Central Java. The estimation was based on environmental condition and the most of the data were obtained through remote sensing using the satellite Landsat TM, aerial photo and small format photograph taken by ultra light air craft. This study is an analytical epidemiological, non experimental study approach. The study subjects were the environmental conditions of the village considered as the risk factors for malaria transmission. Data were collected either through field observations and remote sensing. Data set was analyzed with the discriminant analysis module using the SPSS 10.0 version software. The results of the study showed that there were predictor variables of the environment risk factors should be considered in the estimation of malaria transmission intensity in certain malaria endemic villages. Those variables included: (1) air temperature; (2) relative humidity; (3) mixed garden; (4) homestead and (5) mosquito vector density. Linear discriminant function was obtained to predict the incidence of malaria outbreak. Applying this model, the malaria transmission intensity in certain villages could be estimated with a high accuracy, that could be as high accuracy as 95% as obtained in the Menoreh Hill.

Actions (login required)

View Item