An ensemble prediction approach to weekly Dengue cases forecasting based on climatic and terrain conditions
Journal Title: Journal of Health and Social Sciences - Year 2017, Vol 2, Issue 3
Abstract
Introduction: Dengue fever has been one of the most concerning endemic diseases of recent times. Every year, 50-100 million people get infected by the dengue virus across the world. Historically, it has been most prevalent in Southeast Asia and the Pacific Islands. In recent years, frequent dengue epidemics have started occurring in Latin America as well. This study focused on assessing the impact of different short and long-term lagged climatic predictors on dengue cases. Additionally, it assessed the impact of building an ensemble model using multiple time series and regression models, in improving prediction accuracy. Materials and Methods: Experimental data were based on two Latin American cities, viz. San Juan (Puerto Rico) and Iquitos (Peru). Due to weather and geographic differences, San Juan recorded higher dengue incidences than Iquitos. Using lagged cross-correlations, this study confirmed the impact of temperature and vegetation on the number of dengue cases for both cities, though in varied degrees and time lags. An ensemble of multiple predictive models using an elaborate set of derived predictors was built and validated. Results: The proposed ensemble prediction achieved a mean absolute error of 21.55, 4.26 points lower than the 25.81 obtained by a standard negative binomial model. Changes in climatic conditions and urbanization were found to be strong predictors as established empirically in other researches. Some of the predictors were new and informative, which have not been explored in any other relevant studies yet. Discussion and Conclusions: Two original contributions were made in this research. Firstly, a focused and extensive feature engineering aligned with the mosquito lifecycle. Secondly, a novel covariate pattern-matching based prediction approach using past time series trend of the predictor variables. Increased accuracy of the proposed model over the benchmark model proved the appropriateness of the analytical approach for similar epidemic prediction research.
Authors and Affiliations
Sougata Deb, Cleta Milagros Libre Acedebo, Gomathypriya Dhanapal, Chua Matthew Chin Heng
Keywords
Related Articles
- EP ID EP232736
- DOI 10.19204/2017/nnsm3
- Views 117
- Downloads 0
An explanatory case report about critical differences of ‘inability to work’ in Italian welfare and social security systems
In Italy, there is a different status of ‘inability to work’ in civil invalidity and INPS social security insurance systems. These differences and overlaps cause some concerns. We show a case report of a 55-year-old woma...
Complications of tattoos and tattoos removal: state-of-the-art in Italy
Introduction: Modern tattoo removal began as a science approximately 20 years ago, and relatively few advances have been made since then. The aim of this study is twofold: first, to review the complications of tattoos an...
Acute pancreatitis mimicking myocardial ischemia: A case report and a review of the literature
In literature, acute pancreatitis has been shown to be associated with a wide range of electrocardiographic changes. In the present report, we describe a case of a young woman who presented to our emergency room with che...
Social determinants of vulnerability to ill-health: Evidences from Mendi Town, Western Ethiopia
Introduction: The premise of this study is that disparity in individuals’ degree of susceptibility to physical and mental ill-health is determined by the amount of structurally (socially) distributed resources (‘capitals...
Correlates of physical activity behaviour among nursing professionals: A systematic search and literature review
Introduction: Physical activity (PA) has been shown to protect against adverse health outcomes, and factors influencing physical activity vary among different populations. Previous research suggests nurses have an increa...