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.
| Original language | English |
|---|---|
| Pages (from-to) | 3034-3037 |
| Number of pages | 4 |
| Journal | International Journal of Recent Technology and Engineering |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Sept 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Geographically Weighted Bivariate Zero Inflated Poisson Regression
- Leprosy
- Overdispersion
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