Methods for simulating and analysing the sizes and lengths of infectious disease transmission chains from branching process models

DeepAR implementation for seasonal influenza cases in German districts

R package to estimate disease severity and under-reporting in real-time, accounting for reporting delays in epidemic time-series

[No longer being developed. Use the epichains package instead]. Methods for simulating and analysing the sizes and lengths of chains from branching process models

SEIRD model project for the Programmazione per la fisica exam.

A Basic Compartmental Epidemic Modelling API

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 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.

Collection of epidemic models. Complex networks, stochastic models and ODEs, all 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