https://github.com/devanshu24/covid-19-forecaster

Forecasting and finding causes of the spread of COVID-19 in India
https://github.com/devanshu24/covid-19-forecaster

bayesian-inference causal-inference machine-learning

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Forecasting and finding causes of the spread of COVID-19 in India

• Host: GitHub
• URL: https://github.com/devanshu24/covid-19-forecaster
• Owner: Devanshu24
• Created: 2021-04-01T16:16:55.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2021-05-03T04:22:11.000Z (over 3 years ago)
• Last Synced: 2024-11-02T17:42:51.798Z (2 months ago)
• Topics: bayesian-inference, causal-inference, machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 64.3 MB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# COVID-19 Forecaster

**Disclaimer: We use machine learning methods to forecast the spread of the virus, hence it is suscpetible to uncertainty and potentially errors.**

## Usage

```console

$ python src/main.py --help

usage: main.py [-h] {lstm,arima,fbprophet,nbeats,sir,glm,persistence}

Analyse various algorithms

positional arguments:

  {lstm,arima,fbprophet,nbeats,sir,glm,persistence}

                        Selection of model

optional arguments:

  -h, --help            show this help message and exit

$ python src/main.py persistence

```

*Note:* The results in the paper are reported after doing cross validation, hence running a single instance of the problem may not match the said results.

## Data

```console

data

├── raw (Raw Data from various sources)

│   ├── 2020_IN_Region_Mobility_Report.csv (https://www.google.com/covid19/mobility/)

│   ├── 2021_IN_Region_Mobility_Report.csv (https://www.google.com/covid19/mobility/)

│   ├── applemobilitytrends-2021-04-29.csv (https://covid19.apple.com/mobility)

│   ├── Global_Covid_OWID_(30-01-2020->19-04-2021).csv (https://github.com/owid/covid-19-data/tree/master/public/data)

│   ├── NIFTY_50(01-02-2020->19-04-2020).csv (https://www1.nseindia.com/)

│   ├── Region_Mobility_Report_CSVs.zip (https://www.google.com/covid19/mobility/)

│   ├── S&P_BSE_SENSEX(01-02-2020->19-04-2020).csv (https://www.bseindia.com/)

│   ├── state_wise_daily.csv (https://api.covid19india.org/)

│   └── statewise_tested_numbers_data.csv (https://api.covid19india.org/)

├── district_mobility_cases.csv (Data of Mobility statistics on a district level)

├── India_OWID.csv (Cleaned data from Our World in Data)

├── India_OWID_reduced.csv (Cleaned data from Our World in Data (reduced features))

├── India_OWID_with_mobility_data.csv (Data of Mobility statistics on a country level)

├── IN_Region_Mobility_Report.csv (Mobility data for India)

├── regional_mobility.csv (Mobility data for India on a regional level)

├── state_mobility_cases_agg=max_2020.csv (Aggregated Mobility statistics for mobility derived from district data)

├── state_mobility_cases_agg=max_2021.csv (Aggregated Mobility statistics for mobility derived from district data)

├── state_wise_cases.csv (State wise case counts)

└── UK_data.csv (Case Data for UK)

1 directory, 19 files

```

*Note:* For interactive visualizations please refer to `notebooks/Visualization.ipynb`