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An In-Depth Epidemiological Characterization of Dengue in the Philippines by Artificial Intelligence


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document An In-Depth Epidemiological Characterization of Dengue in the Philippines by Artificial Intelligence
 
2. Creator Author's name, affiliation, country Carina Joane V. Barroso; Bukidnon State University Malaybalay City, Philippines; Philippines
 
2. Creator Author's name, affiliation, country Red Robin P. Babanto; Bukidnon State University Malaybalay City, Philippines
 
3. Subject Discipline(s)
 
3. Subject Keyword(s)
 
4. Description Abstract

Previous studies regarding Dengue fever have identified various factors related to climate change and dengue transmission, but less research paper has explored whether previously identified factors are still significant. Moreover, there is no full evaluation of dengue patterns in terms of creating equations and model that can describe the dengue phenomena. The study created a mathematical model that will explain the dengue phenomena in the Philippines. The model will be used to describe the behavior exhibit in the national dengue cases. Moreover, the said mathematical equations will assist epidemiologist in forecasting dengue cases. This study used a new methodology enclosed in the Complex Adaptive System. The cases from the national surveillance report of the Department of Health (DOH) were used to analyze the monthly number of reported dengue cases. A five-year interval from 2012 to 2017 was utilized to determine changes in Dengue pattern. The said datasets were processed using symbolic regression with the used of freely downloadable software Eurega ® (Nutonian, 2015). The study showed that the Dengue Cases in the Philippines has lost its seasonality and can occur anytime in the year. The previously identified variables such as rainfall and temperature, are no longer contributory factors of Dengue Cases. A mathematical model can be used to predict the incidences of Dengue in the Philippines.


Keywords: dengue fever, complex adaptive system, dengue case model
 
5. Publisher Organizing agency, location Liceo de Cagayan University
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2019-12-27
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier https://asianscientificjournals.com/new/publication/index.php/ljher/article/view/1298
 
10. Identifier Digital Object Identifier 10.7828/ljher.v15i1.1298
 
11. Source Journal/conference title; vol., no. (year) Liceo Journal of Higher Education Research; Vol 15, No 1 (2019): June
 
12. Language English=en en
 
13. Relation Supp. Files
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
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