Modelling the disease spread
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Updated
Sep 9, 2024 - Jupyter Notebook
Modelling the disease spread
Simulate a pandemic with artificial life objects.
COVID-19 Tracing
Source code for the EpiEstim app.
Stochastic SIR models; adding age-structures and social contact data for the spread of covid-19. Lattice model for identifying and isolating hotspots. This has been further developed into a network(graph) of multiple clusters(lattices) and tracing the infection in such a population.
Python package to simulate a vast range of transmission processes on various structures
A virus simulation for pandemics based on the SIR-network concept.
Series of image recognition algorithms that can diagnose diseases by analysing a picture of the iris of the person
A simple disease spread simulation in p5.js
A GitHub repo for the generation of a network model to represent society with various components, the spread of the disease on this network, and the calculation of reproduction number on these simulation results.
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
The very first corona virus tracker for Algeria - Deployed at 09 March 2020
Detecção de COVID-19 a partir de imagens de raios X de tórax utilizando uma Deep Convolutional Neural Network otimizada.
Simulating the effect of social distancing on disease spread through a population graph.
Intelligent disease monitoring system using GIS using many Neural Network (LSTM , Conv1D , GRU , Elman , back probagation ) for forcasting future Covid-19 cases and appeare geography spread of it on the map
api dedicated to serve Coronavirus data
Based of of the 3b1b video, Simulating and Epidemic, this simulation simulates a disease outbreak in a community.
Graph based epidemic simulations.
Connecting mosquito abundance to dengue fever through mechanistic modeling
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