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COVID-19 SIR model estimation

Epidemic simulation models of complex network.

Stochastic Cellular Automata epidemic models in Python with 2D simulations

Python code to analyze data and predict Covid-19 infection

Provides classes to simulate epidemics on (potentially time-varying) networks using a Gillespie stochastic simulation algorithm or the classic agent based method.

Some remarks on prior modelling for the basic reproductive number in the Susceptible-Infected-Recovered (SIR) epidemic model

Python SIR-x model implementation

Official PyTorch implementation of Neural Enhanced Dynamic Message Passing in AISTATS 2022

Agent-based modelling of pandemics using the Susceptible, Infected, Recovered (SIR) framework.

Uses Markov chain Monte Carlo to estimate the parameters of an SIR model with COVID-19 data

Julia code to evaluate SIR models

I noticed that traditional methods to predict a disease outbreak was by performing sentiment analysis on Twitter posts and Google Search terms. Unfortunately, these methods were inadequate, as Twitter and Google is not popular in all countries. So, I created a system to model and predict outbreaks without the need for social media. The system wa…

This repository is meant as a facilitator for all those who want to learn agent based disease modelling using the mesa framework in python. When I started out, there were too few examples for this on the net. Thankful to the community helping me learn, here I will share some of my insights.

PyCoMod is a Python package for building and running compartment models derived from systems of differential equations such as the Susceptible-Infectious-Recovered (SIR) model of infectious diseases.

Explore strategies of social distancing on epidemic w/ SIR model and R - from Gandon, Lion, Day

Contains functions to simulate data from and fit SIR multievent models

Based of of the 3b1b video, Simulating and Epidemic, this simulation simulates a disease outbreak in a community.

Graph based epidemic simulations.

This project aims to incorporate SIRD dynamics with machine learning techniques to make long term predictions of the spread of COVID-19.