Developing a Statistical Dengue Risk Prediction Model for the State of Delhi Based on Various Environmental Variables

Bhardwaj A., Sam L. C., Joshi P.K., Sinha V. S. P.


This work investigates dengue affected localities of Delhi using static and dynamic environmental factors and their possible spatial relationships. The static variables include soil drainage, built-up area and vegetation. The dynamic variables represent seasonal precipitation and temperature data for past hundred years. Significance test (t-test) provided deterministic evidence of variable importance to model. Weighted sum and quantile classification helped to create a final risk map. The model indicated non-uniform distribution of risk across the state and showed elevated risk in urban built-up areas mainly alongside the river Yamuna. Three years (2007, 2008 and 2009) data for confirmed dengue cases for affected localities were obtained from Municipal Corporation of Delhi (MCD) for validation. 57.98% of the reported cases were observed under high risk category as modeled in this study. Modeling results indicate that environmental factors like precipitation, temperature, soil drainage, built-up area and vegetation govern mosquito breeding and are correlated with human dengue risk. The approach verified that dengue risk can be modeled at the state level and can be modified for risk predictions of other vector-borne diseases in varied ecological regions.

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