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covid-19's Introduction

Coronavirus Disease Analytics

Analysing COVID-19 (2019-nCoV) disease.

Worldwide spread over time

worldwide spread over time

infected by countries prediction

active cases dynamics

Steps

1. Load datasets

Upload the latest datasets:

. ../data/download-data.sh

2. EDA and visualization

3. Forecasting

Kernels:

Forecasting methods:

  • Previous value (naive approach)
  • Indicators: simple moving average (SMA), exponential moving average (EMA), double EMA
  • ARIMA, ETS
  • Prophet
  • Linear models: linear regression, Quasi-Poisson regression
  • Decision trees: boosting
  • Neural networks: LSTM, AR RNN
  • SIR model

References

Basics, Research Papers

  1. Coronavirus disease outbreak, World Health Organization.
  2. Coronavirus Disease 2019, Wikipedia.
  3. Here’s what coronavirus does to the body, nationalgeographic.com.
  4. COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv, medrxiv.

Datasets

  1. COVID-19 Data Repository by Johns Hopkins CSSE, GitHub.
  2. Novel Corona Virus 2019 Dataset, Kaggle.
  3. Coronavirus disease (COVID-2019) situation reports, World Health Organization.
  4. COVID-19 Open Research Dataset (CORD-19), Kaggle.
  5. COVID-19 Complete Dataset (Updated every 24hrs), Kaggle.
  6. #covid19 tag, Kaggle.

Analytics, Dashboards, Maps

  1. An interactive visualization of the exponential spread of COVID-19, 91-DIVOC.
  2. Tomas Pueyo. Coronavirus: Why You Must Act Now, Medium.
  3. COVID-19 Cases Map, Yandex.
  4. COVID-19 Animated Spread Map, healthmap.org.
  5. COVID-19 Cases Metrics, worldometers.info.
  6. Coronavirus tracked: the latest figures as the pandemic spreads, Financial Times.
  7. Understanding and tracking our progress against COVID-19, Microsoft.
  8. COVID-19 statistics, Yandex.

Timeline

  1. Timeline of the 2019–20 coronavirus pandemic, Wikipedia.
  2. Huang C., Wang Y., et. al. Timeline of the coronavirus onset, The Lancet.

Simulations

  1. Harry Stevens. These simulations show how to flatten the coronavirus growth curve, Washington Post.
  2. Kevin Simler. COVID-2019 spread simulation, Melting Asphalt.

Forecasting, Competitions

  1. The COVID-19 Vulnerability Index: post, research paper, source code, ClosedLoop.ai.
  2. COVID19 Global Forecasting: week 1, week 2, week 3, week 4, and week 5, Kaggle.
  3. Computational predictions of protein structures associated with COVID-19, DeepMind.
  4. Sberbank COVID-19 forecast, Sberbank feat. ODS.ai.
  5. COVID-19 Estimates, Imperial College London.
  6. SIR (Susceptible-Infected-Recovered) model, covid19-scenarios.org.

Collaborations

  1. Open collaboration on COVID-19, GitHub.

On God we trust. For everything else bring Data.

covid-19's People

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