sars-cov-2

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

🦠 Huge collection of useful projects and resources for COVID-19 (2019 novel Coronavirus)

Models of COVID-19 outbreak trajectories and hospital demand

Nextstrain build for SARS-CoV-2

COVID-Net Open Source Initiative

Folding@home COVID-19 efforts

🫁 The world's first open-source ventilator tested on human patients. Mass-producible at a low cost (~2000€).

Models of SEIRS epidemic dynamics with extensions, including network-structured populations, testing, contact tracing, and social distancing.

query stats of infected coronavirus cases

Julia and Python complex system applications in ecology, epidemiology, sociology, economics & finance; network science models including Bianconi-Barabási, Barabási-Albert, Watts-Strogatz, Waxman Model & Erdős-Rényi; graph theory algorithms involving Gillespie, Bron Kerbosch, Ramsey, Bellman Ford, A*, Kruskal, Borůvka, Prim, Dijkstra, DSatur, Randomized Distributed, Vizing, Topological Sort, DFS, BFS

Real-time updates and information about key SARS-CoV-2 variants, plus the scripts that generate this information.

Ultra-deep search for novel viruses

A global collection of Open Source projects during COVID-19

Viral genome alignment, mutation calling, clade assignment, quality checks and phylogenetic placement

Unified COVID-19 Dataset

PyRoss: inference, forecasts, and optimised control of epidemiological models in Python. github.com/rajeshrinet/pyross

Die COVID-19-Impfung kann einen Wendepunkt in der Kontrolle der COVID-19-Pandemie darstellen und erfährt daher hohes Maß an öffentlicher Aufmerksamkeit. Einführung und Umsetzung der COVID-19-Impfung gehen mit besonderen Herausforderungen einher, die bei der Impfdatenerfassung zu berücksichtigen sind. In diesem Kontext ist es Ziel des Projekts 'D...

Assembly and intrahost/low-frequency variant calling for viral samples

V-pipe is a pipeline designed for analysing NGS data of short viral genomes

COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can upload Chest X-rays or CT Scans and get the output of possibility of COVID infection.