Enhanced Dengue Outbreak Prediction in Tamilnadu using Meteorological and Entomological data
This work addresses dengue forecasting for public health in Tamil Nadu, India, but appears incremental as it builds on existing LSTM methods with additional data.
The paper tackled dengue outbreak prediction in Tamil Nadu by incorporating meteorological and entomological data, resulting in a significantly improved prediction accuracy using a Bidirectional Stacked LSTM model.
This paper focuses on studying the impact of climate data and vector larval indices on dengue outbreak. After a comparative study of the various LSTM models, Bidirectional Stacked LSTM network is selected to analyze the time series climate data and health data collected for the state of Tamil Nadu (India), for the period 2014 to 2020. Prediction accuracy of the model is significantly improved by including the mosquito larval index, an indication of VBD control measure.