Open AccessMapping Leprosy Distribution with Geographically Weighted Bivariate Zero Inflated Poisson Regression Method
Author(s) -
Siti Masliyah Lubis*,
Henny Pramoedyo,
Suci Astutik
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4859.098319
Subject(s) - overdispersion , leprosy , bivariate analysis , poisson regression , statistics , poisson distribution , zero inflated model , mathematics , regression analysis , logistic regression , demography , geography , medicine , count data , environmental health , population , immunology , sociology
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.