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

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

Predicting COVID-19 pandemic by spatio-temporal graph neural networks https://arxiv.org/abs/2305.07731

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

EpiSimulator: A Data-Driven Stochastic Hybrid Model for COVID-19 in Italy.

[RETIRED. Use the epichains package instead]. Methods for simulating and analysing the sizes and lengths of chains from branching process models

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

Python implementation of behavioral-epidemic models for COVID-19

Transform epidemic modeling research papers into interactive public health simulators. Powered by Claude Opus 4.6 — 1M context, extended thinking, 128K output.

D-FENSE project deals with Dengue Virus (DENV) epidemics in Brazil, enabling predictive modeling and data visualization to support decision-making in public health.

DeepAR implementation for seasonal influenza cases in German districts

Collection of epidemic models. Complex networks, stochastic models and ODEs, all with non-markovian distributions (Erlang type).

SEIRD model project for the Programmazione per la fisica exam

Epidemic visualization; Language: R.

CLiDENGO26-Dengue is a forecasting model for dengue dynamics through a mechanistic, stochastic climate-modulated β-logistic growth model for weekly dengue cases at the state (UF) level.

Automated and Early Detection of Seasonal Epidemic Onset and Burden Levels

CLiDENGO26-Chikungunya is a forecasting model for Chikungunya dynamics through a mechanistic, stochastic climate-modulated β-logistic growth model for weekly chikungunya cases at the state (UF) level.