Prediction on the Trend of Dengue Cases with Decision Support System Using Statistical Formula

Abstract

An accurate prediction model for dengue incidences months in advance of an impending outbreak could prove useful in enhancing decision-making for health establishments and reducing the morbidity and mortality rate of this tropical disease. Therefore, a prediction model was developed to predict the trend of dengue cases in the future based on historical epidemiology cases of dengue and using the statistical formula of mean+2 Standard Deviation, where mean is the average of all the past cases and standard deviation of all the number of past cases taken into factors for the prediction of the future trend of cases. The prediction model was able to draw alert thresholds using the statistical formula and was also able to predict with an acceptable level of accuracy using the actual data as a benchmark for the predicted value. However, the system cannot predict the anomalies or exceptional cases, rather serving as a guide for Digos City Health Center operatives to create preventive measures for this alarming tropical disease. In the conclusion of this study, using the model developed and taking historical epidemiology data as the basis for the prediction of a future trend could prove as a viable source for enhanced evidence-based decision support for the Digos City Health Center operatives.