APPLICATION OF POISSON REGRESSION IN MODELING THE NUMBER OF DENGUE CASES SUFFERERS BASED ON SOCIODEMOGRAPHIC AND TEMPERATURE IN INDONESIA

Oscar Oscar, Pamela Pamela, Ranny Febrianti, Edwin Setiawan Nugraha

Abstract


Indonesia is one of the countries with high dengue cases. Dengue dengue is an acute disease with clinical manifestations of the bleeding that causes shock that leads to death. Dengue or Demam Berdarah is a type of disease caused by one out of four dengue viruses. This disease is highly contagious. The source of the infection is originally coming from Aedes aegypti and Aedes albopictus mosquito bite. Some of the factors that are known to influence dengue cases include home environment, biological environment, and social environment. With Poisson regression, we connect other factors that have possible risk in dengue cases. In these cases, we used data on dengue cases 2015 in Indonesia. Our analysis with help of R software shows that poverty and temperature will make a significant contribution to the number of dengue 2015 cases in Indonesia. Every 1% increase in the percentage of poverty will cause a decrease in dengue cases to exp (-0.04449) = 0.9564 times from the initial DHF case assuming other predictor variables are constant. Every 10 Celsius increase in temperature will cause an increase in DHF cases to exp (0.206) = 1,306 times from the initial dengue case assuming the other predictor variables are constant. This research is expected to help the health sector and government in dengue control in Indonesia.

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