# Predicting the spread of COVID-19 in Delhi, India using Deep Residual Recurrent Neural Networks

arXiv: https://arxiv.org/abs/2110.05477 · HTML: https://mlsanity.com/paper/2110.05477/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 20 references that are in the map.
- First posted on arXiv 9 Oct 2021.

## Builds on (most cited first, 6 of 6)

- [Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network](https://mlsanity.com/paper/1808.03314/) (2018)
- [A Deep Neural Network Surrogate for High-Dimensional Random Partial Differential Equations](https://mlsanity.com/paper/1806.02957/) (2018)
- [Conditional physics informed neural networks](https://mlsanity.com/paper/2104.02741/) (2021)
- [DR-RNN: A deep residual recurrent neural network for model reduction](https://mlsanity.com/paper/1709.00939/) (2017)
- [Physics-Informed Neural Network Method for Solving One-Dimensional Advection Equation Using PyTorch](https://mlsanity.com/paper/2103.09662/) (2021)
- [Gated Recurrent Neural Tensor Network](https://mlsanity.com/paper/1706.02222/) (2017)

## Built on by (most cited first, 1 of 1)

- [Wastewater Pipe Rating Model Using Natural Language Processing](https://mlsanity.com/paper/2202.13871/) (2022)

## Abstract (arXiv)

Detecting the spread of coronavirus will go a long way toward reducing human and economic loss. Unfortunately, existing Epidemiological models used for COVID 19 prediction models are too slow and fail to capture the COVID-19 development in detail. This research uses Partial Differential Equations to improve the processing speed and accuracy of forecasting of COVID 19 governed by SEIRD model equations. The dynamics of COVID 19 were extracted using Convolutional Neural Networks and Deep Residual Recurrent Neural Networks from data simulated using PDEs. The DRRNNs accuracy is measured using Mean Squared Error. The DRRNNs COVID-19 prediction model has been shown to have accurate COVID-19 predictions. In addition, we concluded that DR-RNNs can significantly advance the ability to support decision-making in real time COVID-19 prediction.