59 Open source projects that are alternatives of or similar to Python-for-Epidemiologists

Analysis with Covid-19 data

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Implement PC algorithm in Python | PC 算法的 Python 实现

Agent-based simulation model for COVID-19 spread in society and patient outcomes

R Package for individual based epidemiological models

EpiTator annotates epidemiological information in text documents. It is the natural language processing framework that powers GRITS and EIDR Connect.

MTBseq is an automated pipeline for mapping, variant calling and detection of resistance mediating and phylogenetic variants from illumina whole genome sequence data of Mycobacterium tuberculosis complex isolates.

Public Available Code and Data to Reproduce Analyses in "Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis."

COVID-19 Pandemic Data R Package

A framework for data-driven stochastic disease spread simulations

COVID-10 Analysis

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

DoubleML - Double Machine Learning in R

💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.

DoubleML - Double Machine Learning in Python

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

Repository for Global.health: a data science initiative to enable rapid sharing of trusted and open public health data to advance the response to infectious diseases.

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

Source code for the EpiEstim app.

Pyro models of SARS-CoV-2 variants

📈 Track COVID-19 (2019 novel Coronavirus) statistics via the command line.

Causal Inference: What If. R and Stata code for Exercises

A magyarországi koronavírus járvány valós idejű, kvantitatív epidemiológiája.

🎓 GSU MPA/MPP course on program evaluation and causal inference

Nonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests

Build Petri net models compositionally

Algorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.

🚦🏥. Ferramenta de monitoramento do risco de colapso no sistema de saúde em municípios brasileiros com a Covid-19 • Monitoring tool & simulation of the risk of collapse in Brazilian municipalities' health system due to Covid-19

June is a framework for agent based modelling in an epidemiological and geographical context.

A Python package for causal inference using Synthetic Controls

Policy learning via doubly robust empirical welfare maximization over trees

This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.

Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)

Portal de dados do Projeto Alerta Dengue

Must-read papers and resources related to causal inference and machine (deep) learning

Machine learning based causal inference/uplift in Python

Network Models of HIV Transmission Dynamics among MSM and Heterosexuals

Domain-Specific Modeling for Epidemiology

Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure

Bayesian spatial analysis

COVID-19 social distancing simulator

➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.

CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

SEIR+ model

[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

🎯 📕 Targeted Learning in R: A Causal Data Science Handbook

Machine-readable version of electronic health record phenotypes for Kuan V. and Denaxas S. et al.

A suite of tools for epidemiology in Python.

My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context

COVID-19 App

Analysis of the COVID19 outbreak in Brazil mainly through epidemic and hospitalization models, by the Health Analytics and Prospera consulting business units of Funcional Heatlh Tech.

This is an Covid-19 tracker especially made for India

An agent-based epidemiology simulation framework built in Rust

Coz: Causal Profiling

Uplift modeling and causal inference with machine learning algorithms

Python Library for learning (Structure and Parameter) and inference (Probabilistic and Causal) in Bayesian Networks.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Python package for the creation, manipulation, and learning of Causal DAGs

Covariate Balance Tables and Plots - An R package for assessing covariate balance