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Recent Incidence of Human Malaria Caused by Plasmodium knowlesi in the Villages in Kudat Peninsula, Sabah, Malaysia: Mapping of The Infection Risk Using Remote Sensing Data
http://hdl.handle.net/10069/39446
http://hdl.handle.net/10069/394463067deb0-d470-4813-a3d8-c8c17b572e28
名前 / ファイル | ライセンス | アクション |
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IJERPH16_2954.pdf (1.3 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2019-09-24 | |||||
タイトル | ||||||
タイトル | Recent Incidence of Human Malaria Caused by Plasmodium knowlesi in the Villages in Kudat Peninsula, Sabah, Malaysia: Mapping of The Infection Risk Using Remote Sensing Data | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Bayesian inference | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | EVI phenology | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Generalised linear mixture model | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Geographical analysis | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Infection risk map | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | MODIS | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Plasmodium knowlesi | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Remote sensing | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Sato, Shigeharu
× Sato, Shigeharu× Tojo, Bumpei× Hoshi, Tomonori× Minsong, Lis Izni Fanirah× Kugan, Omar Kwang× Giloi, Nelbon× Ahmed, Kamruddin× Jeffree, Saffree Mohammad× Moji, Kazuhiko× Kita, Kiyoshi |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Plasmodium knowlesi (Pk) is a malaria parasite that naturally infects macaque monkeys in Southeast Asia. Pk malaria, the zoonosis transmitted from the infected monkeys to the humans by Anopheles mosquito vectors, is now a serious health problem in Malaysian Borneo. To create a strategic plan to control Pk malaria, it is important to estimate the occurrence of the disease correctly. The rise of Pk malaria has been explained as being due to ecological changes, especially deforestation. In this research, we analysed the time-series satellite images of MODIS (MODerate-resolution Imaging Spectroradiometer) of the Kudat Peninsula in Sabah and created the “Pk risk map” on which the Land-Use and Land-Cover (LULC) information was visualised. The case number of Pk malaria of a village appeared to have a correlation with the quantity of two specific LULC classes, the mosaic landscape of oil palm groves and the nearby land-use patches of dense forest, surrounding the village. Applying a Poisson multivariate regression with a generalised linear mixture model (GLMM), the occurrence of Pk malaria cases was estimated from the population and the quantified LULC distribution on the map. The obtained estimations explained the real case numbers well, when the contribution of another risk factor, possibly the occupation of the villagers, is considered. This implies that the occurrence of the Pk malaria cases of a village can be predictable from the population of the village and the LULC distribution shown around it on the map. The Pk risk map will help to assess the Pk malaria risk distributions quantitatively and to discover the hidden key factors behind the spread of this zoonosis. | |||||
書誌情報 |
International Journal of Environmental Research and Public Health 巻 16, 号 16, p. 2954, 発行日 2019-08-16 |
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出版者 | ||||||
出版者 | MDPI | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 16617827 | |||||
EISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 16604601 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.3390/ijerph16162954 | |||||
権利 | ||||||
権利情報 | c 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | International Journal of Environmental Research and Public Health, 16(16), art.no.2954; 2019 |