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CSSEGISandData logoCOVID-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

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🦠 A simple and fast (< 200ms) API for tracking the global coronavirus (COVID-19, SARS-CoV-2) outbreak. It's written in python using the 🔥 FastAPI framework. Supports multiple sources!

Quick Overview

The CSSEGISandData/COVID-19 repository is a data collection project maintained by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). It provides daily updates on COVID-19 cases, deaths, and recoveries worldwide, serving as a crucial resource for researchers, policymakers, and the public during the global pandemic.

Pros

  • Comprehensive global coverage with data from various countries and regions
  • Regularly updated, providing timely information on the pandemic's progression
  • Open-source and freely accessible, promoting transparency and collaboration
  • Widely used and cited in academic research and media reports

Cons

  • Data quality can vary depending on reporting practices of different countries
  • Occasional inconsistencies or delays in data updates
  • Limited granularity for some regions, especially at sub-national levels
  • Challenges in maintaining consistency as reporting methods change over time

Code Examples

As this is primarily a data repository rather than a code library, there are no specific code examples to provide. However, users often utilize data analysis tools and libraries to work with the data, such as pandas in Python or tidyverse in R.

Getting Started

While there's no code library to start with, you can access the data by following these steps:

  1. Visit the repository: https://github.com/CSSEGISandData/COVID-19
  2. Navigate to the csse_covid_19_data/csse_covid_19_time_series folder
  3. Download the desired CSV files (e.g., time_series_covid19_confirmed_global.csv)
  4. Use your preferred data analysis tool to load and analyze the data

For example, using Python with pandas:

import pandas as pd

# Load global confirmed cases data
url = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"
df = pd.read_csv(url)

# Display the first few rows
print(df.head())

This will load the global confirmed cases data into a pandas DataFrame for further analysis.

Competitor Comparisons

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covid-19-data

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

Pros of covid-19-data

  • More comprehensive global dataset, including testing data and excess mortality
  • Cleaner, more standardized data format
  • Includes additional calculated metrics like case fatality rates

Cons of covid-19-data

  • Less granular data for some countries (e.g., no county-level data for the US)
  • Updates may be less frequent than COVID-19
  • Smaller community of contributors

Code comparison

COVID-19 data format (CSV):

Province/State,Country/Region,Lat,Long,Date,Confirmed,Deaths,Recovered
New York,US,40.7128,-74.0060,2021-03-01,1000000,50000,900000

covid-19-data format (CSV):

location,date,total_cases,new_cases,total_deaths,new_deaths,total_vaccinations
United States,2021-03-01,28756489,56079,515151,1431,76899987

The covid-19-data repository uses a more standardized format with consistent column names and data types. It also includes additional metrics like vaccinations, which are not present in the COVID-19 repository. However, COVID-19 provides more detailed geographical information for some countries, such as province/state-level data.

Both repositories are valuable resources for COVID-19 data, with each having its strengths and weaknesses. Researchers and data analysts may choose one over the other based on their specific needs and the level of detail required for their analysis.

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COVID-19 App

Pros of WHO app

  • Official WHO-backed application, providing authoritative information
  • Multi-platform support (iOS, Android, Web) for wider accessibility
  • Includes features like symptom checker and travel advice

Cons of WHO app

  • Less frequent updates compared to COVID-19 dataset
  • Focused on general public use rather than comprehensive data for researchers
  • Limited historical data availability

Code comparison

COVID-19:

df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')
df = df.melt(id_vars=['Province/State', 'Country/Region', 'Lat', 'Long'], var_name='Date', value_name='Confirmed')

WHO app:

Future<List<CountryStats>> fetchCountryStats() async {
  final response = await http.get('https://api.who.int/country-stats');
  if (response.statusCode == 200) {
    return parseCountryStats(response.body);
  } else {
    throw Exception('Failed to load country stats');
  }
}

The COVID-19 repository provides raw CSV data that can be easily processed using data analysis tools, while the WHO app uses an API to fetch and display data within the application. The COVID-19 dataset is more suitable for researchers and data scientists, whereas the WHO app is designed for public consumption and awareness.

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CoronaTracker

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Coronavirus tracker app for iOS & macOS with maps & charts

Pros of CoronaTracker

  • Provides a user-friendly iOS app for visualizing COVID-19 data
  • Offers real-time updates and notifications for users
  • Includes additional features like news updates and prevention tips

Cons of CoronaTracker

  • Limited to iOS platform, reducing accessibility for non-Apple users
  • May have a smaller dataset compared to the comprehensive COVID-19 repository
  • Potentially slower updates due to app store approval processes

Code Comparison

COVID-19 repository (Python):

import pandas as pd

url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url)

CoronaTracker (Swift):

import Foundation

struct CovidData: Codable {
    let confirmed: Int
    let deaths: Int
    let recovered: Int
    let date: Date
}

The COVID-19 repository focuses on providing raw data in CSV format, which can be easily processed using data analysis tools. CoronaTracker, on the other hand, is designed as an iOS application, with data structures optimized for mobile app usage and user interface integration.

covid19india logo

covid19india-react

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Tracking the impact of COVID-19 in India

Pros of covid19india-react

  • More user-friendly interface with interactive visualizations
  • Focuses specifically on India, providing detailed state-level data
  • Includes additional features like vaccination tracking and testing data

Cons of covid19india-react

  • Limited to India-specific data, not suitable for global analysis
  • May have less frequent updates compared to the JHU dataset
  • Potentially less comprehensive historical data

Code Comparison

COVID-19 (Python):

import pandas as pd

url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url)

covid19india-react (JavaScript):

import axios from 'axios';

const API_ROOT_URL = 'https://api.covid19india.org/v4/min';
const fetchData = async () => {
  const response = await axios.get(`${API_ROOT_URL}/data.min.json`);
  return response.data;
};

The COVID-19 repository provides raw CSV data that can be easily processed using data analysis tools like pandas. In contrast, covid19india-react offers a more structured API approach, returning JSON data that can be directly used in web applications. The COVID-19 dataset is more suitable for researchers and data scientists, while covid19india-react is designed for developers building web-based dashboards and applications specific to India's COVID-19 situation.

ExpDev07 logo

coronavirus-tracker-api

1,592

🦠 A simple and fast (< 200ms) API for tracking the global coronavirus (COVID-19, SARS-CoV-2) outbreak. It's written in python using the 🔥 FastAPI framework. Supports multiple sources!

Pros of coronavirus-tracker-api

  • Provides a RESTful API for easy integration with other applications
  • Offers real-time data updates through API endpoints
  • Includes data visualization tools and interactive maps

Cons of coronavirus-tracker-api

  • May have less comprehensive historical data compared to COVID-19
  • Potentially slower data updates due to reliance on third-party sources
  • Limited to API access, which may not be suitable for all use cases

Code Comparison

COVID-19 (Data format example):

Province/State,Country/Region,Last Update,Confirmed,Deaths,Recovered
Hubei,Mainland China,2020-02-15T23:13:05,56249,1596,5623

coronavirus-tracker-api (API response example):

{
  "latest": {
    "confirmed": 1234567,
    "deaths": 98765,
    "recovered": 543210
  },
  "locations": [
    {
      "country": "China",
      "province": "Hubei",
      "latest": {
        "confirmed": 56249,
        "deaths": 1596,
        "recovered": 5623
      }
    }
  ]
}

The COVID-19 repository provides raw CSV data, while coronavirus-tracker-api offers structured JSON responses through its API, making it easier to integrate into applications but potentially limiting direct access to the underlying data.

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README

COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:

For more information, visit the Johns Hopkins Coronavirus Resource Center.

This is the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).

Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Visual Dashboard (mobile): http://www.arcgis.com/apps/opsdashboard/index.html#/85320e2ea5424dfaaa75ae62e5c06e61

Please cite our Lancet Article for any use of this data in a publication: An interactive web-based dashboard to track COVID-19 in real time

The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned

Provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE): https://systems.jhu.edu/

DONATE to the CSSE dashboard team: https://engineering.jhu.edu/covid-19/support-the-csse-covid-19-dashboard-team/

DATA SOURCES: This list includes a complete list of all sources ever used in the data set, since January 21, 2020. Some sources listed here (e.g. ECDC, US CDC, BNO News) are not currently relied upon as a source of data.

Embed our dashboard into your webpage:

<style>.embed-container {position: relative; padding-bottom: 80%; height: 0; max-width: 100%;} .embed-container iframe, .embed-container object, .embed-container iframe{position: absolute; top: 0; left: 0; width: 100%; height: 100%;} small{position: absolute; z-index: 40; bottom: 0; margin-bottom: -15px;}</style><div class="embed-container"><iframe width="500" height="400" frameborder="0" scrolling="no" marginheight="0" marginwidth="0" title="COVID-19" src="https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6"></iframe></div>

Acknowledgements: We are grateful to the following organizations for supporting our Center’s COVID-19 mapping and modeling efforts: Financial Support: Johns Hopkins University, National Science Foundation (NSF), Bloomberg Philanthropies, Stavros Niarchos Foundation; Resource support: AWS, Slack, Github; Technical support: Johns Hopkins Applied Physics Lab (APL), Esri Living Atlas team

Additional Information about the Visual Dashboard: https://systems.jhu.edu/research/public-health/ncov/

Contact Us:

Terms of Use:

  1. This data set is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020.

  2. Attribute the data as the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University" or "JHU CSSE COVID-19 Data" for short, and the url: https://github.com/CSSEGISandData/COVID-19.

  3. For publications that use the data, please cite the following publication: "Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1"