# Enhanced Dengue Outbreak Prediction in Tamilnadu using Meteorological and Entomological data

arXiv: https://arxiv.org/abs/2306.13456 · HTML: https://mlsanity.com/paper/2306.13456/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 20 references that are in the map.
- First posted on arXiv 23 Jun 2023.

## Builds on (most cited first, 2 of 2)

- [Modeling Dengue Vector Population Using Remotely Sensed Data and Machine Learning](https://mlsanity.com/paper/1805.02590/) (2018)
- [Next-Generation High-Resolution Vector-Borne Disease Risk Assessment](https://mlsanity.com/paper/1908.02558/) (2019)

## Abstract (arXiv)

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.