International Journal of Environmental Research and Public Health · 2015 · 53 citations · 49 references
Veterinary MedicineInfectious DiseasesMeteorologyDisease SurveillanceEpidemiologyInfectious Disease EpidemiologyDisease EpidemiologyDisease ForecastingSeasonality In Disease OccurrenceTime Series ForecastingTime Series ModelingTime-series Analysis In EpidemiologyDisease Forecasting ModelsDisease Incidence AnalysisDisease Incidence RateForecasting Infectious Disease IncidenceGranger Causality AnalysisMeteorological Data AnalysisScrub TyphusWeather-based Disease Forecasting
Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN) model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.
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