Analysis of forecasting malaria case with climatic factors as predictor in Mandailing Natal Regency: a time series study

4th International Conference on Operational Research

Aulia, D.^1 ; Ayu, S.F.^2 ; Matondang, A.^1

Faculty of Public Health, University of Sumatera Utara, Indonesia^1

Faculty of Agribusiness, University of Sumatera Utara, Indonesia^2

关键词: Auto-regressive;    Best model;    Climatic factors;    Malaria transmission;    P-values;    Quality of life;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/300/1/012035/pdf
DOI  :  10.1088/1757-899X/300/1/012035

来源: IOP

【 摘 要 】

Malaria is the most contagious global concern. As a public health problem with outbreaks, affect the quality of life and economy, also could lead to death. Therefore, this research is to forecast malaria cases with climatic factors as predictors in Mandailing Natal Regency. The total number of positive malaria cases on January 2008 to December 2016 were taken from health department of Mandailing Natal Regency. Climates data such as rainfall, humidity, and temperature were taken from Center of Statistic Department of Mandailing Natal Regency. E-views ver. 9 is used to analyze this study. Autoregressive integrated average, ARIMA (0,1,1) (1,0,0)12is the best model to explain the 67,2% variability data in time series study. Rainfall (P value = 0.0005), temperature (P value = 0,0029) and humidity (P value = 0.0001) are significant predictors for malaria transmission. Seasonal adjusted factor (SAF) in November and March shows peak for malaria cases.