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

R package to calculate the final size of an SIR epidemic in populations with heterogeneity in social contacts and disease susceptibility

A library of published compartmental epidemic models, and classes to represent demographic structure, non-pharmaceutical interventions, and vaccination regimes, to compose epidemic scenarios.

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

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

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

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

[Computer Modeling] SIR/SIRS/SIRQ/ISIR/SEIR compartmental models for numerical epidemic modelling in MATLAB.

D-FENSE is a repository for dengue data in Brazil, enabling predictive modeling, visualization, and public health support.

SEIRD model project for the Programmazione per la fisica exam.

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

Epidemic visualization; Language: R.

DeepAR implementation for seasonal influenza cases in German districts

A Basic Compartmental Epidemic Modelling API

Modeling of epidemic diffusion by stochastic processes, implementing neural networks to smooth data and genetic algorithms to identify diseases.

*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.

Worker of prediksicovidjatim