Curated data of the SARS-COV2 pandemic

All formatted data used by covid19_scenarios.

List of countries associated to regions, subregions, and three letter codes supplied by the U.N.

List of settings used by the default scenario by COVID-19 epidemic simulation for different regions of interest.

Within the directory ./case-counts is a structured set of tsv files containing aggregated data for select country and subregion/city. We welcome contributions to keep this data up to date. The format chosen is:

time    cases   deaths   hospitalized    ICU     recovered
2020-03-14 ...

We are actively looking for people to supply data to be used for our modeling!

Steps:

• Identify a source for case counts data that is updated frequently (at least daily) as outbreak evolves.
  • Write a script that downloads and converts raw data into TSV format
    • Columns: [time, cases, deaths, hospitalized, ICU, recovered]
    • The time column must be a string formatted as "YYYY-MM-DD"
    • Try to keep the same order of columns for hygiene, although it should ultimately matter
    • If data is missing, please leave the entry empty
  • Place the script into the parsers directory
    • The name should correspond to the region name desired in the scenario.
    • There must be a function parse() defined that outputs the TSV into the correct directory.
  • Commit the produced TSV file into the correct directory
    • The structure of the directory is Region/Sub-Region/Country/
    • Region and Sub-Region are designated as per the U.N.
    • U.N. designations are found within country_codes.csv
    • Please use only the U.N. designated name for the country, region, and sub-region.
  • All TSV files will be bundled into a json database into the app on next build
    • The case counts should be displayed as data-points onto the associated scenario
• Update the sources.json file to contain all relevant metadata.
  • The three fields are:
    • primarySource = The URL/path to the raw data
    • dataProvenance = The organization behind the data collection
    • license = The license governing the usage of data

We note that this option is not preferred relative to a script that automatically updates as outlined above. However, if there is no accessible data sources, one can manually enter the data. To do so

• Commit a manually entered TSV file into the correct directory
  • The structure of the directory is Region/Sub-Region/Country/
  • Region and Sub-Region are designated as per the U.N.
  • U.N. designations are found within country_codes.csv
  • Please use only the U.N. designated name for the country, region, and sub-region.

As of now all data used to initialize scenarios used by our model is found within populationData.tsv It has the following form: name populationServed ageDistribution hospitalBeds ICUBeds suspectedCaseMarch1st importsPerDay Switzerland ...

• Names: the U.N. designated name found within country_codes.csv
  • For a sub-region/city, please prefix the name with the three letter country code of the containing country. See country_codes.csv for the correct letters.
• populationServed: a number with the population size
• ageDistribution: name of the country the region is within. Must be U.N. designated name
• hospitalBeds: number of hospital beds within the region
• ICUBeds: number of ICU beds
• suspectedCaseMarch1st: The number of cases thought to be within the region on March 1st.
• importsPerDay: number of suspected import cases per day

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Copyright (c) 2020 neherlab