Dengue Modeling Using Multiple Regression in Bandar Lampung Province, Indonesia
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Abstract
Dengue Hemorrhagic Fever remains a significant global concern, with its complex distribution influenced by geographic and demographic factors. Indonesia, particularly the city of Bandar Lampung, is an endemic area for Dengue Hemorrhagic Fever. Factors such as population density, area, and geographical coordinates are believed to influence the spread of the disease. Bandar Lampung, which has the highest population density in the region, has recorded a high population growth rate. In this context, multiple linear regression analysis is an effective approach to understanding the relationship between dependent and independent variables, including population density, area, longitude, and latitude. These factors play a crucial role in the transmission of the dengue virus, with high population density increasing human-mosquito interactions. This analysis is expected to provide comprehensive insights to design more effective and targeted intervention strategies for preventing and controlling the spread of Dengue Hemorrhagic Fever at both geographic and demographic levels
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