Enhanced Dengue Outbreak Prediction in Tamilnadu using Meteorological and Entomological data

Varalakshmi M, Daphne Lopez
6/23/2023
cs.LG

No confident code implementation found for this paper.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Machine Learning Models for Dengue Forecasting in Singapore

84% match2024

Multitask LSTM for Arboviral Outbreak Prediction Using Public Health Data

84% match2025

FWin transformer for dengue prediction under climate and ocean influence

83% match2024

CrossLag: Predicting Major Dengue Outbreaks with a Domain Knowledge Informed Transformer

81% match2025

Infectious Disease Forecasting in India using LLM's and Deep Learning

81% match2024

TREA-Net: A Transferable Residual Epidemiological Adaptation Network for Dengue Incidence Forecasting

81% match2026

Cite this paper

@article{m2023enhanced,
  title  = {Enhanced Dengue Outbreak Prediction in Tamilnadu using Meteorological and Entomological data},
  author = {Varalakshmi M and Daphne Lopez},
  year   = {2023},
  eprint = {2306.13456},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.13456v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2306.13456.svg)](https://codeofpaper.com/paper/2306.13456)

Discussion