Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia

Main Article Content

Ramadhan Tosepu
Kraichat Tantrakarnapa
Suwalee Worakhunpiset
Kanchana Nakhapakorn


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%.

Article Details

How to Cite
Tosepu, R., Tantrakarnapa, K., Worakhunpiset, S., & Nakhapakorn, K. (2018). Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia. Environment and Natural Resources Journal, 16(2), 1–10. Retrieved from
Original Research Articles


Allard R. Use of time-series analysis in infectious disease surveillance. Bulletin of the World Health Organization 1998;76:327.
Anker M, Arima Y. Male–female differences in the number of reported incident dengue fever cases in six Asian countries. Western Pacific Surveillance and Response Journal 2011;2:17.
Arcari P, Tapper N, Pfueller S. Regional variability in relationships between climate and dengue/DHF in Indonesia. Singapore Journal of Tropical Geography 2007;28:251-72.
Bangs MJ, Larasati RP, Corwin AL, Wuryadi S. Climatic factors associated with epidemic dengue in Palembang, Indonesia: implications of short-term meteorological events on virus transmission. Southeast Asian Journal of Tropical Medicine and Public Health 2006;37(6):1103-16.
Campbell KM, Haldeman K, Lehnig C, Munayco CV, Halsey ES, Laguna-Torres VA, Yagui M, Morrison AC, Lin CD, Scott TW. Weather regulates location, timing, and intensity of dengue virus transmission between humans and mosquitoes. PLoS Neglected Tropical Diseases 2015;9(9).
Chen S-C, Hsieh M-H. Modeling the transmission dynamics of dengue fever: implications of temperature effects. Science of The Total Environment 2012;431:385-91.
Colón-González FJ, Lake IR, Bentham G. Climate variability and dengue fever in warm and humid Mexico. The American Journal of Tropical Medicine and Hygiene 2011;84:757-63.
Focks DA, Haile D, Daniels E, Mount GA. Dynamic life table model for Aedes aegypti (Diptera: Culicidae): analysis of the literature and model development. Journal of Medical Entomology 1993;30:1003-17.
Horstick O, Jaenisch T, Martinez E, Kroeger A, See LLC, Farrar J, Ranzinger SR. Comparing the usefulness of the 1997 and 2009 WHO dengue case classification: a systematic literature review. The American Journal of Tropical Medicine and Hygiene 2014;91:621-34.
Karyanti MR, Uiterwaal CS, Kusriastuti R, Hadinegoro SR, Rovers MM, Heesterbeek H, Hoes AW, Bruijning-Verhagen P. The changing incidence of Dengue Haemorrhagic Fever in Indonesia: a 45-year registry-based analysis. BMC Infectious Diseases 2014;14:412.
Kuan M-M, Lin T, Chuang J-H, Wu H-S. Epidemiological trends and the effect of airport fever screening on prevention of domestic dengue fever outbreaks in Taiwan, 1998–2007. International Journal of Infectious Diseases 2010;14:693-7.
Lander JP. R for Everyone: Advanced Analytics and Graphics. Pearson Education; 2014.
Liu-Helmersson J, Stenlund H, Wilder-Smith A, Rocklov J. Vectorial capacity of Aedes aegypti: effects of temperature and implications for global dengue epidemic potential. PLoS ONE 2014;9:e89783.
Mattar S, Morales V, Cassab A, Rodríguez-Morales AJ. Effect of climate variables on dengue incidence in a tropical Caribbean municipality of Colombia, Cerete, 2003–2008. International Journal of Infectious Diseases 2013;17:358-9.
Megawati D, Masyeni S, Yohan B, Lestarini A, Hayati RF, Meutiawati F, Suryana K, Widarsa T, Budiyasa D G, Budiyasa N. Dengue in Bali: clinical characteristics and genetic diversity of circulating dengue viruses. PLoS Neglected Tropical Diseases 2017;11:e0005483.
Moeloek NF. Report of Control Diseases. Jakarta: Ministry of Health Indonesia; 2014.
Naish S, Dale P, Mackenzie J S, McBride J, Mengersen K, Tong S. Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012. PloS one 2014;9:e92524.
Phung D, Huang C, Rutherford S, Chu C, Wang X, Nguyen M, Nguyen NH, Manh CD. Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam. Acta Tropica 141, Part A: 2015;88-96.
Promprou S, Jaroensutasinee M, Jaroensutasinee K, Forecasting Dengue Haemorrhagic Fever Cases in Southern Thailand using ARIMA Models. Dengue Bulletin 2006;30:99-106.
Ramadona AL, Lazuardi L, Hii YL, Holmner Å, Kusnanto H, Rocklöv J. Prediction of dengue outbreaks based on disease surveillance and meteorological data. PLoS ONE 2016;11:e0152688.
Sharmin S, Glass K, Viennet E, Harley D. Interaction of mean temperature and daily fluctuation influences dengue incidence in Dhaka, Bangladesh. PLoS Neglected Tropical Diseases 2015;9:e0003901.
Tombili A. Indonesia Health Profile, Kendari: Health Office Southest Sulawesi Province; 2015.
World Health Organization (WHO). Indonesia: WHO Statistical Profile. Geneva, Switzerland; World Health Organization: 2016a.
World Health Organization (WHO). Indonesia Health Profile. Geneva, Switzerland; World Health Organization: 2016b.
Xiang J, Hansen A, Liu Q, Liu X, Tong MX, Sun Y, Cameron S, Hanson-Easey S, Han G-S, Williams C, Weinstein P, Bi P. Association between dengue fever incidence and meteorological factors in Guangzhou, China 2005-2014. Environmental Research 2017;153: 17-26.
Zell R. Global climate change and the emergence/re-emergence of infectious diseases. International Journal of Medical Microbiology Supplements 2004;293:16-26.