A Correlation Study between Dengue Incidence and Climatological Factors in the Philippines
Asian Research Journal of Mathematics,
Dengue is a viral mosquito-borne infection transmitted primarily by the Aedes mosquitoes. It is one of the several emerging tropical diseases which progressively spread geographically to virtually all tropical countries like the Philippines. Recent climate changes related to global warming have increased the potential risk of dengue outbreaks in the world. In this paper, we study and investigate temperature and precipitation as climatological factors affecting dengue incidence in the Philippines from the year 2015 to 2018. Monthly dengue cases and climate data were gathered for the said study period. A correlation and wavelet coherence analyses were performed to determine a relationship between dengue incidence and climatological factors in the Philippines. Results show that the amount of rainfall is strongly correlated to the increase of dengue cases in the country as compared to the temperature. Evidence shows that dengue incidence in the Philippines mostly occur during the rainy season. Thus, intensified surveillance and control of mosquitoes during the rainy season are recommended.
- Dengue incidence
- climatological factors
- correlation analysis
- wavelet coherence analysis
How to Cite
Dos Santos MAF. Rich dynamics in multi-strain models: non-linear dynamics and deterministic chaos in dengue fever epidemiology. Doctoral Dissertation. Vrije Universiteit Amsterdam; 2012.
De los Reyes VAA, J. Ma. L Escaner IV. Dengue in the Philippines: model and analysis of parameters affecting transmission. Journal of Biological Dynamics. 2018;12:1:894- 912.
Lee H, Kim JE, Lee S, Lee CH. Potential effects of climate change on dengue transmission in Korea. PLoS One. 2018;13(6):1-23.
Janreung S, Chinviriyasit W. Dengue fever with two strains in Thailand. International Journal of Applied Physics and Mathematics. 2014;4:55-61.
Kim JE, Lee H, Lee CH, Lee S. Assessment of optimal strategies in a two-patch dengue transmission model with seasonality. PLoS One. 2017;12(3):1-21.
Andraud M, Hens N, Beutels P. A simple periodic-forced model for dengue fitted to incidence data in Singapore. Mathematical Biosciences; 2013.
Chen SC, Liao CM, Chio CP, Chou HH, You SH, Cheng YH. Lagged temperature effect with mosquito transmission potential explains dengue variability in southern Taiwan: insights from a statistical analysis. Science of the Total Environment. 2010;408(19).
Chikaki E, Ishikawa H. A dengue transmission model in Thailand considering sequential infections with all four serotypes. The Journal of Infection in Developing Countries; 2009.
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.
Tran A, L’Ambert G, Lacour G, Benot R, Demarchi M, Cros M, et al. A rainfall-and temperature-driven abundance model for Aedes albopictus populations. International Journal of Environmental Research and Public Health; 2013.
Jesavel A. Iguchi, Xerxes T. Seposo, Yasushi Honda. Meteorological factors affecting dengue incidence in Davao, Philippines. BMC Public Health. 2018;18:629.
D.A. Ewing, C.A. Cobbold, B. Purse, M. Nunn and S.M. White (2016). Modelling the effect of temperature on the seasonal population dynamics of temperate mosquitoes. Journal of Theoretical Biology.
Chen SC, Hsieh MH. Modeling the transmission dynamics of dengue fever: implications of temperature effects. Science of the Total Environment; 2012.
Teixeira MG, Siqueira JB. Jr, Ferreira GL, Bricks L, Joint G. Epidemiological trends of dengue disease in Brazil (2000-2010): a systematic literature search and analysis. PLoS Neglected Tropical Diseases; 2013.
Naish S, Dale P, Mackenzie JS, McBride J, Mengersen K, Tong S. Climate change and dengue: a critical and systematic review of quantitative modelling approaches. BMC Infectious Diseases. 2014;14(1):1.
Eduardo A. Undurraga, Frances E. Edillo, Jonathan Neil V. Erasmo, Maria Theresa P. Alera, In-Kyu Yoon, Francisco M. Largo, Donald S. Shepard. Disease burden of dengue in the philippines: adjusting for underreporting by comparing active and passive dengue surveillance in Punta Princesa, Cebu City. The American Journal of Tropical Medicine and Hygiene. 2017;96(4): 887–898.
Department of Health, Public Health Surveillance Division, Philippine Integrated Disease Surveillance and Response and Epidemiology Bureau.
Philippine Demographics Profile.
Available:www.indexmundi.com/philippines/ demographics profile.html
Philippine Statistics Authority.
Philippine Atmospheric, Geophysical and Astronomical Services Administration.
Picardal J, Elnar A. Rainfall, temperature and the incidence of dengue in Central Visayas, Philippines are not correlated. CNU J. Higher Educ. Category B - CHED-JAS 6. 2012;61- 70.
Bravo L, Roque VG, Brett J, Dizon R, Lazou M. Epidemiology of dengue disease in the Philippines (2000-2011): A systematic literature review. PLoSNeglected Trop. Dis. 2014;8.
Cazelles B, Chavez M, Berteaux D, Menard F, Vik JO, Jenouvrier S, Stenseth NC. Wavelet Analysis of Ecological Time Series. Oecologia. 2008;156:287-304.
Johansson MA, Cummings DAT, Glass GE. Multiyear climate variability and Dengue—El Nin˜o Southern Oscillation, Weather, and Dengue Incidence in Puerto Rico, Mexico, and Thailand: A Longitudinal Data Analysis. PLoS Med. 2019;6(11):e1000168.
Torrence C, Compo GP. A practical guide to wavelet analysis. Program in Atmospheric and Oceanic Sciences. University of Colorado, Boulder, Colorado.
Su GIS. Correlation of climatic factors and dengue incidence in Metro Manila, Philippibes. Ambio: A Journal of the Human Environment. 2008;37:4.
Abstract View: 96 times
PDF Download: 27 times