CSE 8803 EPI, Fall 2022
Data Science for Epidemiology
Data Science for Epidemiology
COVID specific resources
- World Health Organization (WHO): Coronavirus Disease (COVID-19)
- Center for Disease Control and Prevention (CDC): Coronavirus (COVID-19)
- National Institutes of Health (NIH): Coronavirus (COVID-19)
- Gloal Government Policy data: Coronavirus (COVID-19)
- Maps, charts, and data of COVID in the U.S. CDC COVID Data Tracker
- COVID-19 Impact Analysis Platform Link
- European Centre for Disease Prevention and Control (ECDC): Coronavirus (COVID-19)
- contributed and curated data sources for COVID-19 tracking: BNO News
- Coronavirus Cases: WorldoMeters
- Global Map of COVID: Link
- U.S. Map of COVID: Link
- UVA Biocomplexity Institute: COVID-19 Datasets
- Tracking coronavirus: Map, data and timeline: Corona Data Scraper
- COVID-19 Tracking Project - managed by Alexis Madrigal from The Atlantic - tracks US state-by-state COVID-19 progression
- Data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) : COVID-19 Datasets
- BeOutbreakPrepared nCoV 2019 public line list
- nCoV2019_2020_line_list, (@MOUGK (Oxford/Harvard))
- NY Times Github Repo: COVID-19 Datasets
- C3.ai COVID-19 Data Lake - a collection of datasets from governmental, NGO, and commercial sources
- Daily updates about COVID-19 activity across the United States: COVIDcast API
- Allen Institute for AI: COVID-19 Open Research Dataset (CORD-19)
- WHO Database: COVID-19 Database
- COVID-19 Wastewater Data: Dataset
- Twitter Social Mobility Index
- Coronavirus Twitter Data
- Apple Mobility Trend
- Google Mobility Report and Data
- Google Symptoms Trnds for COVID-19 and other diseases: Dataset
- Shaman group model (Columbia)
- Santa Clara model from Mordecai group (Stanford)
- UGA model for Georgia
- UGA model on social distancing
- Wang et al model (for China)
General Information
Aggregate Statistical Information and Visualization
Datasets and Surveillance data collections
Social media and mobility data
Models
ODE based models
Forecasting and Projection models
General epidemiological datasets
- influenza, dengue, and other epidemics: Epidata API
- Wide-ranging Online Data for Epidemiologic Research: (WONDER) API
- NYC Health Datasets: EpiQuery
- Weekly Influenza Surveillance Report and Data by CDC: Fluview
- Number of Ebola Cases and Deaths in Affected Countries: Ebola
- WHO's global tuberculosis database: Tuberculosis
- Population contact rates by age and county
- Healthcare Personnel Movement Data
- Population File for the US in county-level UPitt Data
Epidemiological surveillance data
Network datasets
Network-based models and tools
Software tools
A. WEKA
WEKA is a popular, open‐source data mining software that can be used for the project. Almost all the algorithms and topics discussed in our course are already implemented in this software. The main goal of the course project is to make use of such existing implementations for real‐world problems and datasets. This software is written in JAVA but to work with this software no knowledge of JAVA is required. You can download the software at this website Weka.B. Gephi
Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. Gephi is a tool for people that have to explore and understand graphs. You can download the software at this website Gephi.C. Python Pakages
NetworkX: NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.Numpy: NumPy is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
SciPy: SciPy is an open source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
scikit-learn : Scikit-learn is a free software machine learning library for the Python programming language.
D. Popular deep learning frameworks
PyTorch(Facebook): PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab.TensorFlow(Google): TensorFlow is an end-to-end open source platform for machine learning and deep learning. Tensorboard is a good experiment tracking software.
JAX(Google): JAX is an high-performance numerical computing and machine learning library that allows flexible computational graphs like Differential Equations and Physics Simulations.
DGL: Deep Graph Library for Graph Neural Networks.
E. Popular packages in NLP
spaCy: spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython.Stanford NLP: StanfordNLP is a Python natural language analysis package.
NLTK: The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python.
Hugging Face: Hugging Face has many pre-trained Language and Vision models and datasets.
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F. Popular packages in Julia
Flux: Flux is full-fledged base library for Machine Learning and Deep Learning.Differential Equations: DifferentialEquations.jl is a Julia library for solving differential equations.
DiffEqFlux: DiffEqFlux is a Julia library for solving differential equations using neural networks.
GeometricFlux: GeometricFlux is a Julia library for graph neural networks.
F. COVID analyses for R
This repository links to a collection of analyses on and representations of COVID19 data in R Github Link.G. COVID Insights
COVID Insights is a website intended to be a resource for those interested in analyzing data related to the COVID-19 pandemic COVID Insights.H. SIR in Python using scipy
This is a Epidemiological Models Interactive Example, just try it out by yourself here!
Note: that using these software tools is not mandatory for this course project and they are just suggestions. If someone is familiar with other programming environments like MATLAB, they are free to use any algorithms that are already implemented in these environments.