This paper is in the following e-collection/theme issue:

GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (142) Public (e)Health, Digital Epidemiology and Public Health Informatics (1032) Infectious Diseases (non-STD/STI) (1734) Use Cases in Human, Animal, and Zoonotic Communicable/Infectious Disease Surveillance (145) Statistical Methods for Surveillance and Population Health (190)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68437, first published .
Distribution and Risk Factors of Scrub Typhus in South Korea, From 2013 to 2019: Bayesian Spatiotemporal Analysis

Distribution and Risk Factors of Scrub Typhus in South Korea, From 2013 to 2019: Bayesian Spatiotemporal Analysis

Distribution and Risk Factors of Scrub Typhus in South Korea, From 2013 to 2019: Bayesian Spatiotemporal Analysis

Authors of this article:

Jeehyun Kim1 Author Orcid Image ;   Penelope Vounatsou2 Author Orcid Image ;   Byung Chul Chun1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Kim W. Integrating Environmental and Seasonal Factors in a Machine Learning Model for Predicting Scrub Typhus Incidence. Journal of Environmental Health Sciences 2025;51(6):452 View