JOURNAL ARTICLE

Mapping Leprosy Distribution with Geographically Weighted Bivariate Zero Inflated Poisson Regression Method

Siti Masliyah LubisHenny PramoedyoSuci AstutikSuci Astutik

Year: 2019 Journal:   International Journal of Recent Technology and Engineering (IJRTE) Vol: 8 (3)Pages: 3034-3037

Abstract

Geographically Weighted Bivariate Zero Inflated Poisson regression modelling has been developed to evaluate overdispersion and spatial heterogeneity in factors the number of PB Leprosy and MB Leprosy Cases in North Sumatera Province in 2017. The modelling results shows there are 25 different models for each district. PB Leprosy cases are mostly influenced by the percentage of poor people and the percentage of healthy houses and MB Leprosy cases are influenced by percentage of poor people, percentage of clean and healthy life behavior, the ratio of medical personnel and the percentage of healthy houses.

Keywords:
Overdispersion Leprosy Bivariate analysis Poisson regression Statistics Poisson distribution Zero-inflated model Mathematics Regression analysis Logistic regression Demography Geography Medicine Environmental health Count data Population Immunology

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Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems
Spatial and Panel Data Analysis
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
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