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Model Forecasting of the number of Dengue Fever Diseases in Trang during the El Niño phenomenon.
Organization(s):Princess Chulabhorn Science High School Trang
Country:Thailand
Student(s):Thanaphat parichatnon and Thanakorn Phetbua
Grade Level:Secondary School (grades 9-12, ages 14-18)
GLOBE Teacher:Patchara Pongmanawut
Contributors:Dr. Anantanit Chumsri from Rajamangala University of Technology Srivijaya Trang campus
Assoc. Prof. Dr. Mullica Jaroensutasinee and Assoc. Prof. Dr. Krisanadej Jaroensutasinee from Walailak University
The Institute for the Promotion of Teaching Science and Technology (IPST)
Report Type(s):International Virtual Science Symposium Report, Standard Research Report
Protocols:Air Temperature, Barometric Pressure, Precipitation, Relative Humidity, Wind
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Optional Badges:I am a Collaborator, I am a Data Scientist, I make an Impact
Language(s):English
Date Submitted:03/06/2024
Over the past 50 years, the world has faced a changing climate that is becoming increasingly intense due to various phenomena, such as the El Niño phenomenon, which has a significant impact on public health in Southeast Asia. This change is attributed to an increase in air temperature and a decrease in rainfall across the continent, leading to various diseases, including a rise in the incidence of dengue fever. Consequently, the researcher studied the occurrence of the El Niño phenomenon and the incidence of dengue fever in Trang Province from 1998 to 2022. It was found that in years when the El Niño phenomenon occurred, the incidence of dengue fever in Trang Province increased. When analyzing weather data, including rainfall, temperature, relative humidity, air pressure, and wind speed, and then examining the relationship with the number of dengue cases using Pearson's Correlation Coefficient with the SPSS program, it was discovered that both average air pressure and the maximum air pressure value have a negative relationship with the number of dengue cases, at a statistical significance of .05. A predictive model using a Deep Learning model from ARIMAX (1,1,1) indicated that the number of dengue cases has increased and decreased significantly in intervals corresponding to climate change. This trend began with a decrease from 1998 to 1999, followed by an increase from 1999 to 2012, a very steep decrease from 2012 to 2019, and then an increase again from 2019 to 2024. The data collection showed that the number of dengue cases corresponds with the occurrence of El Niño events. Therefore, it can be predicted that the number of dengue cases will decrease between 2025 and 2027 and will increase again in 2027-2028 due to a new wave of the El Niño phenomenon.