Prediction Model of Dengue Hemorrhagic Fever Incidence Using Climatic Factors in Kabupaten Gorontalo

Prediction Model Dengue Hemorrhagic Fever Climatic factor Gorontalo Regency

Authors

  • Safrudin Tolinggi
    safrudin.tolinggi@gmail.com
    2Fakultas Kesehatan Masyarakat, Universitas Gorontalo, Jl. Ahmad A. Wahab, Limboto, Gorontalo, 96211
  • Moh. Rivandi Dengo 2Fakultas Kesehatan Masyarakat, Universitas Gorontalo, Jl. Ahmad A. Wahab, Limboto, Gorontalo, 96211
October 31, 2019

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All countries of ASEAN member agree that dengue fever is one of the major problems faced by all ASEAN countries so the status of their territory has been determined to be hyperendemic in the last 10 years. Global warming is predicted to result in an increase in the average temperature of the earth's surface by 2,0OC to 4,5OC in 2100, which will have a direct impact on diseases caused by vectors. This study aims to examine the relationship of climate factors to the incidence of dengue fever and find a predictive model of dengue fever in Gorontalo regency. This research data used secondary data from 2012-2016, which included climate data (average temperature, irradiation time, rainfall, rainy days, and average wind speed) per month obtained from the Meteorology and Geophysics Agency (MGA) Gorontalo Class II and dengue fever incidence data were monthly incident data obtained from the Health Office Gorontalo regency. Based on the values of determinant values (R2) of the five models that were obtained, the value is 13,4% with p value = 0,004 and the linear regression equation using the backward method. Thus, estimated number of cases of dengue fever in Gorontalo Regency in a year reached 132 cases. Besides climate factors, the increasing number of cases of dengue fever might be caused by urbanization, population density, high population mobilization, community behavior, existence and quality of facilities and health services obtained by the community. Improvisation is needed for planning prevention programs and its implementation. As well as designing spatial-based disease prevention and control program that analyzes all climate, demographic and environmental parameters that are the causes of the high incidence of dengue fever.