Abstract
The use of early warning system is potential adaptation options to reduce the impact of the climate variability and change. This study aims to develop a dengue early warning model using climate information. The model was developed through three steps of analysis. First step was to determine the length of periods used in prediction and optimal time for eradicating Aedes aegypti mosquito’s breeding sites. Second step was to identify the best prediction model of dengue incidence rate (IR). Third step was to develop an early warning model using stochastic spreadsheet.  It was found that the best predictors for predicting dengue incidence rate at week-n (IRn) were (1) rainfall index with two weeks lead time (ICHn-2). The rainfall index of week-nth is a function of three week moving averages rainfall (CH3), i.e. (CH3n-1.155*CH3n-1+0.702*CHn-2), and (2) IR with one week lead time (IRn-1). The IR model prediction was IRn = 0.795*IRn-1+0.067*ICHn-2 with R2=76.6%. These models (result model from first and third step) can be used to provide early warning on optimum time for controlling the mosquito’s breeding sites and the need for fogging action in order to avoid the dengue incidence rate beyond the critical limit defined by the Ministry of Health
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
