Data Analysis and Development of a Risk prediction Model for Dengue Disease in Amnatcharoen Province

Abstract

Dengue disease an the important health problem. The global incidence of dengue has grown dramatically in recent decades. The virus is transmitted to humans through the bites of infected female mosquitoes. Awareness about disease prevention and having knowledge and understanding about disease and controlling disease is important. Early detection and early access will reduced the mortality rate and severity of the disease. The purpose of this study was to analyze the situation of dengue disease outbreak in Amnatcharoen province in the years 2006-2018 and to create a risk prediction model for the dengue disease in Amnatcharoen province. Data analysis was done Using QlikView12 program to analyze the data of dengue disease patients, 2006-2018, 7,011 people in Amnat charoen Province, Findings :men more than woman and often found in childhood than adults. Patients were found in all 7 districts, Mueang district is the highest!.

The outbreak peaks every 3 years. Patients are found all year, mostly between June and August. The first diagnosis and the final diagnosis were 98.33% consistent. RStudio program was used with the Decision tree principles to select variables that were used to create a prediction model for risk of the dengue disease in Amnat charoen Province. Five models for predictive risk of Dengue Disease are age, agegroup, district, sub-district and health service unit. Therefore, the results of this research can be used to create a model to predict the risk of dengue disease so that people can use it to make timely treatment decisions to reduce the severity and death from dengue fever.