A Basic Compartmental Epidemic Modelling API
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Updated
Jun 28, 2024 - R
A Basic Compartmental Epidemic Modelling API
[Under active development] Methods for simulating and analysing the sizes and lengths of infectious disease transmission chains from branching process models
[No longer being developed. Use the epichains package instead]. Methods for simulating and analysing the sizes and lengths of chains from branching process models
A library of published compartmental epidemic models, and classes to represent demographic structure, non-pharmaceutical interventions, and vaccination regimes, to compose epidemic scenarios.
R package to estimate disease severity and under-reporting in real-time, accounting for reporting delays in epidemic time-series
R package to calculate the final size of an SIR epidemic in populations with heterogeneity in social contacts and disease susceptibility
*Stochastic Modelling of Vector-Borne Diseases with Household Structures* Thesis submitted for the degree of Honours of Mathematical Sciences in Applied Mathematics at The University of Adelaide.
[SUSPENDED]: R package to compare epidemic scenario model outcomes.
Agent-based modelling of pandemics using the Susceptible, Infected, Recovered (SIR) framework.
DeepAR implementation for seasonal influenza cases in German districts
Collection of epidemic models. Includes ODEs, stochastic and complex networks, with non-markovian distributions (Erlang type).
Predicting COVID-19 pandemic by spatio-temporal graph neural networks https://arxiv.org/abs/2305.07731
Epidemic Models. Bayesian Estimation (MCMC) of Change-Points in COVID-19 Reported Cases in 3 European Countries
EpiSimulator: A Data-Driven Stochastic Hybrid Model for COVID-19 in Italy.
[Computer Modeling] SIR/SIRS/SIRQ/ISIR/SEIR compartmental models for numerical epidemic modelling in MATLAB.
The core library of prediksicovidjatim
Worker of prediksicovidjatim
The map of prediksicovidjatim, built with Arcgis Wep Appbuilder Developer Edition.
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