Variability of Local Weather as Early Warning for Dengue Hemorrhagic Fever Outbreak in Indonesia

Abstract

The incidence of Dengue Hemorrhagic Fever (DHF) is related to the alternation of environment condition, particularly weather, in which global warming may elevate the DHF case. The objective of study is to analyses the relationship between local weather and DHF, and to create prediction model by using big data in Surabaya Municipally. Employing quantitative method, monthly time series data was used during 2012-2016. Univariate, bivariate and multivariate analysis was performed in Stata 13. Local weather (mean humidity, maximum humidity, minimum humidity, rainy days and rainfall) correlates to the incidence of DHF (p <0.05), in which minimum humidity lag 1 month and rainy days lag 2 month had strong correlation (r >0.7). In addition, prediction model in the study recognize the occurrence of four peak epidemic of DHF cases in Surabaya Municipally. Therefore, utilizing local weather to create prediction model may contribute as early warning for DHF incident in order to handle the disease in Surabaya Municipally.