Developing a Dengue Prediction Model based on Climate in Tawau, Malaysia.

This study analyses the relationship between weather predictors including its lagged terms, and dengue incidence in the District of Tawau over a period of 12 years, that is from 2006-2017. A forecasting model purposed to predict future outbreaks in Tawau was then developed using this data. Monthly dengue incidence data, mean temperature, maximum temperature, minimum temperature, mean relative humidity and mean rainfall over a period of 10 years from 2006-2017 in Tawau were retrieved from Tawau District Health Office and Malaysian Meteorological Department, Sabah Branch. Cross-correlation analysis between weather predictors, lagged terms of weather predictors and dengue incidences established statistically significant cross-correlation between lagged periods of weather predictors-namely maximum temperature, mean relative humidity and mean rainfall with dengue incidence at time lags of 4-6 months. These variables were then employed into 3 different methods: a multivariate Poisson regression model, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a SARIMA with external regressors for selection. Three models were selected but the SARIMA with external regressors model utilising maximum temperature at a lag of 6 months (p-value: <0.001), minimum temperature at a lag of 4 months (p-value:<0.01), mean relative humidity at a lag of 2 months (p-value: <0.001), and mean rainfall at a lag of 6 months (p-value: <0.001) produced an AICC of 841.94, and ...
Source: Acta Tropica - Category: Infectious Diseases Authors: Tags: Acta Trop Source Type: research