An Integrative Explainable Artificial Intelligence Approach to Analyze Fine-Scale Land-Cover and Land-Use Factors Associated with Spatial Distributions of Place of Residence of Reported Dengue Cases

Hsiu Yang, Thi Nhung Nguyen, Ting Wu Chuang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Dengue fever is a prevalent mosquito-borne disease that burdens communities in subtropical and tropical regions. Dengue transmission is ecologically complex; several environmental conditions are critical for the spatial and temporal distribution of dengue. Interannual variability and spatial distribution of dengue transmission are well-studied; however, the effects of land cover and use are yet to be investigated. Therefore, we applied an explainable artificial intelligence (AI) approach to integrate the EXtreme Gradient Boosting and Shapley Additive Explanation (SHAP) methods to evaluate spatial patterns of the residences of reported dengue cases based on various fine-scale land-cover land-use types, Shannon’s diversity index, and household density in Kaohsiung City, Taiwan, between 2014 and 2015. We found that the proportions of general roads and residential areas play essential roles in dengue case residences with nonlinear patterns. Agriculture-related features were negatively associated with dengue incidence. Additionally, Shannon’s diversity index showed a U-shaped relationship with dengue infection, and SHAP dependence plots showed different relationships between various land-use types and dengue incidence. Finally, landscape-based prediction maps were generated from the best-fit model and highlighted high-risk zones within the metropolitan region. The explainable AI approach delineated precise associations between spatial patterns of the residences of dengue cases and diverse land-use characteristics. This information is beneficial for resource allocation and control strategy modification.

Original languageEnglish
Article number238
JournalTropical Medicine and Infectious Disease
Volume8
Issue number4
DOIs
Publication statusPublished - Apr 2023

Keywords

  • artificial intelligence
  • dengue fever
  • EXtreme Gradient Boosting (XGBoost)
  • land cover land-use
  • Shapley Additive Explanation (SHAP)

ASJC Scopus subject areas

  • General Immunology and Microbiology
  • Public Health, Environmental and Occupational Health
  • Infectious Diseases

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