Learning from panel data of dengue incidence and meteorological factors in Jakarta, Indonesia
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ORIGINAL PAPER
Learning from panel data of dengue incidence and meteorological factors in Jakarta, Indonesia Karunia Putra Wijaya1 • Dipo Aldila2 Miracle Amadi6 • Naleen Ganegoda7
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K. K. W. Hashita Erandi3 • Muhammad Fakhruddin4,5
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Accepted: 23 September 2020 Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Medical statistics collected by WHO indicates that dengue fever is still ravaging developing regions with climates befitting mosquito breeding amidst moderate-to-weak health systems. This work initiates a study over 2009–2017 panel data of dengue incidences and meteorological factors in Jakarta, Indonesia to bear particular understanding. Using a panel randomeffect model joined by the pooled estimator, we show positively significant relationships between the incidence level and meteorological factors. We ideate a clustering strategy to decompose the meteorological datasets into several more datasets such that more explanatory variables are present and the zero-inflated problem from the incidence data can be handled properly. The resulting new model gives good agreement with the incidence data accompanied by a high coefficient of determination and normal zero-mean error in the prediction window. A risk measure is characterized from a one-step vector autoregression model relying solely on the incidence data and a threshold incidence level separating the low-risk and high-risk regime. Its magnitude greater than unity and the weak stochastic convergence to the endemic equilibrium mark a persistent cyclicality of the disease in all the five districts in Jakarta. Moreover, all districts are shown to co-vary profoundly positively in terms of epidemics occurrence, both generally and timely. We also show that the peak of incidences propagates almost periodically every year on the districts with the most to the least recurrence: Central, South, West, East, and North Jakarta. Keywords Dengue Clustering-integrated multiple panel regression Risk measure Spatial correlation Outbreak propagation
& Dipo Aldila [email protected] 1
Mathematical Institute, University of Koblenz, 56070 Koblenz, Germany
2
Department of Mathematics, Universitas Indonesia, Depok 16424, Indonesia
3
Department of Mathematics, University of Colombo, Colombo 00700, Sri Lanka
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Department of Mathematics, Bandung Institute of Technology, Bandung 13240, Indonesia
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Department of Mathematics, Indonesia Defense University, Bogor 16810, Indonesia
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Department of Mathematics and Physics, Lappeenranta University of Technology, 53851 Lappeenranta, Finland
7
Department of Mathematics, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka
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Stochastic Environmental Research and Risk Assessment
1 Introduction Until today, dengue fever and its debilitating variants remain to be notable health burdens in Indonesia. Factors influencing the widespread of dengue diseases in big cities like Jakarta are manyfold. Environmental support for mosquito breading (Arcari et al. 2007; Morin et al. 2013), compromi
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