There are 3 repositories under infectious-disease-models topic.
PyRoss: inference, forecasts, and optimised control of epidemiological models in Python
Simulate a pandemic with artificial life objects.
A set of "real-time" covid19 county-level dashboards w/ national and state choropleths for monitoring localized infection resurgences as distancing, testing and tracing measures evolve.
Python code to analyze data and predict Covid-19 infection
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
Python package for statistical inference and forecast of epi models using multiple signals
Bayesian Nowcasting with application to COVID-19 fatalities in Sweden
The Flexible Epidemic Modeling Pipeline
Detecção de COVID-19 a partir de imagens de raios X de tórax utilizando uma Deep Convolutional Neural Network otimizada.
Continuous Time Distance-Based and Network-Based Individual Level Models for Epidemics
Official website @ Github with content including COVID-19.
In this repository we aim to predict the peak of coronavirus cases in Indonesia, and when this pandemic will end. The data is retrieved from https://www.kawalcovid19.id/
A Time-Dependent SEIRD Model for Forecasting the COVID-19 Transmission Dynamics
Population-level infectious disease modelling as an extension of brms.
Agent-based visual simulation of infectious diseases with customizable parameters
An infectious disease modeling study on quantifying the magnitude of infectiousness from asymptomatic cases in Wuhan, China during outbreak of COVID-19.
Asymptomatic transmission of COVID-19: differences in time-scales and reproduction numbers, and potential correlations between disease and transmission
The focus of this project is to identify factors that cause COVID-19 outbreaks in US nursing home.
Python package for infectious disease modelling
This is the official GitHub organization page for Infectious Disease Modelling Lab at SSHSPH, NUS, Singapore led by Dr. Hannah Clapham.
An R package and web application for estimating the basic reproduction number of infectious diseases.
Simulation of a SEIRVD model written in C#. Writes per day outputs to CSV for easy ingestion into a visualizer.
Simulation of the SIR model written in C#. Writes per day outputs to CSV for easy ingestion into a visualizer.
Model of hepatitis C transmission in Norway used in Whittaker, Midtbø and Kløvstad (submitted)
A dashboard for visualising the epidemiological parameters stored in the epiparameter package.
2010 U.S. Synthetic Population Ver. 1