Title: Dengue outbreak prediction model for urban Colombo using meteorological data

Authors: K.K.W.H. Erandi; S.S.N. Perera; A.C. Mahasinghe

Addresses: Research and Development Centre for Mathematical Modelling, Department of Mathematics, University of Colombo, Colombo 03, Sri Lanka ' Research and Development Centre for Mathematical Modelling, Department of Mathematics, University of Colombo, Colombo 03, Sri Lanka ' Research and Development Centre for Mathematical Modelling, Department of Mathematics, University of Colombo, Colombo 03, Sri Lanka

Abstract: Dengue is a viral borne disease with complex transmission dynamics. Disease outbreak can exert an increasing pressure on the health system with high mortality. Understanding and predicting the outbreaks of dengue transmission is vital in controlling the spread. Mathematical models have become important tool in predicting the dynamics of dengue. Due to the complexity of the disease, general time series models do not describe the impact of the external parameters. In this work, we propose a generalised linear regression model to understand the dynamics of the dengue disease and predict the future outbreaks. To moderate the model, cross-correlation between reported dengue cases and climatic factors were identified using Pearson cross-correlation formula. Then threshold value was defined based on reported data in order to identify minimum risk level for the states of dengue outbreaks. Further, obtained results were compared.

Keywords: dengue; vector density; climate factors; cross-correlation; Pearson correlation formula; time lag; generalised linear regression formula; disease outbreak; threshold; prediction model.

DOI: 10.1504/IJDSDE.2021.120043

International Journal of Dynamical Systems and Differential Equations, 2021 Vol.11 No.5/6, pp.462 - 472

Received: 07 Jun 2019
Accepted: 28 Sep 2019
Published online: 05 Jan 2022 *

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