Publication: Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia
2
Issued Date
2018
Resource Type
Language
eng
File Type
application/pdf
No. of Pages/File Size
10 Page
Journal Title
Environment and Natural Resources Journal
Volume
16
Issue
2
Start Page
1
End Page
10
Access Rights
open access
Rights
ผลงานนี้เป็นลิขสิทธิ์ของมหาวิทยาลัยมหิดล ขอสงวนไว้สำหรับเพื่อการศึกษาเท่านั้น ต้องอ้างอิงแหล่งที่มา ห้ามดัดแปลงเนื้อหา และห้ามนำไปใช้เพื่อการค้า
Rights Holder(s)
Faculty of Environment and Resource Studies Mahidol University.
Bibliographic Citation
Environment and Natural Resources Journal. Vol. 16, No. 2 (Jul - Dec 2018), 1-10
Suggested Citation
Ramadhan Tosepu, Kraichat Tantrakarnapa, Suwalee Worakhunpiset, Kanchana Nakhapakorn Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia. Environment and Natural Resources Journal. Vol. 16, No. 2 (Jul - Dec 2018), 1-10. 10. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114027
Research Projects
Organizational Units
Authors
Journal Issue
EnNRJ Vol. 16 No. 2
(2018)
Thesis
Title
Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia
Abstract
Dengue hemorrhagic fever in Indonesia is one of the serious health problems and requires understanding the occurrence of this disease. Climate Factors have a role that needs attention in the prevention of DHF disease. Understanding of disease patterns will benefit the health surveillance system and provide a way to tackle this problem. The records of dengue fever cases and climate data for the years 2010-2015 were obtained from the Health Office Kolaka District, southeast Sulawesi province and Meteorology, Climatology and Geophysics Agency in Southeast Sulawesi province, respectively. Data for the period 2010 to 2014 were used for model development through multiple linear regressions. The prediction model was used to forecast dengue cases in 2015 and the predicted results were compared with reported dengue cases in Kolaka in the past and forecasting period. Rainfall, humidity, temperature average, minimum temperature, and maximum temperature are significantly correlated with monthly cases of dengue fever. Predicted results showed a good performance where the model was able to predict 3 out of 5 epidemic outbreak events that occurred in January-March 2015 and November-December 2015. The sensitivity of detecting the outbreaks was estimated to be 60%, the specificity was 100%, positive and negative predictive value were estimated to be 100% and 77.8%, respectively. Climate has a major influence on the occurrence of dengue hemorrhagic fever infection in Kolaka district. Although the predictive model has some limitations in predicting the number of cases of monthly dengue fever, it can estimate the possibility of an outbreak three months in advance with a fairly high accuracy. The predictive model can be used to explain the incident rate of DHF of approximately 71%.