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Spatially Filtered Multilevel Analysis on Spatial Determinants for Malaria Occurrence in Korea

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  • Sehyeong Kim

    (Department of Geography, Korea University, 145 Anam-ro, Seoul 02841, Korea)

  • Youngho Kim

    (Department of Geography Education, Korea University, 145 Anam-ro, Seoul 02841, Korea)

Abstract

Since its re-emergence in 1993, the spatial patterns of malaria outbreaks in South Korea have drastically changed. It is well known that complicated interactions between humans, nature, and socio-economic factors lead to a spatial dependency of vivax malaria occurrences. This study investigates the spatial factors determining malaria occurrences in order to understand and control malaria risks in Korea. A multilevel model is applied to simultaneously analyze the variables in different spatial scales, and eigenvector spatial filtering is used to explain the spatial autocorrelation in the malaria occurrence data. The results show that housing costs, average age, rice paddy field ratio, and distance from the demilitarized zone (DMZ) are significant on the level-1 spatial scale; health budget per capita and military base area ratio are significant on the level-2 spatial scale. The results show that the spatially filtered multilevel model provides better analysis results in handling spatial issues.

Suggested Citation

  • Sehyeong Kim & Youngho Kim, 2019. "Spatially Filtered Multilevel Analysis on Spatial Determinants for Malaria Occurrence in Korea," IJERPH, MDPI, vol. 16(7), pages 1-11, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1250-:d:220843
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    References listed on IDEAS

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    1. Ian H. Langford & Alistair H. Leyland & Jon Rasbash & Harvey Goldstein, 1999. "Multilevel Modelling of the Geographical Distributions of Diseases," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(2), pages 253-268.
    2. Michael Jerrett & Sara Gale & Caitlin Kontgis, 2010. "Spatial Modeling in Environmental and Public Health Research," IJERPH, MDPI, vol. 7(4), pages 1-28, March.
    3. Corrado, L. & Fingleton, B., 2011. "Multilevel Modelling with Spatial Effects," SIRE Discussion Papers 2011-13, Scottish Institute for Research in Economics (SIRE).
    4. Zhoupeng Ren & Duoquan Wang & Jimee Hwang & Adam Bennett & Hugh J W Sturrock & Aimin Ma & Jixia Huang & Zhigui Xia & Xinyu Feng & Jinfeng Wang, 2015. "Spatial-Temporal Variation and Primary Ecological Drivers of Anopheles sinensis Human Biting Rates in Malaria Epidemic-Prone Regions of China," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-17, January.
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