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Nima Hejazi edited this page Mar 25, 2020 · 5 revisions

https://www.kaggle.com/c/covid19-global-forecasting-week-1/overview

Covariate datasets:

Possible datasets:

  1. Number of hospital beds, per country (https://data.worldbank.org/indicator/SH.MED.BEDS.ZS)
  2. Number of doctors, per country (https://data.worldbank.org/indicator/SH.MED.BEDS.ZS)
  3. Weather info (https://www.kaggle.com/davidbnn92/weather-data/data?scriptVersionId=30695168)
  4. GDP and Crime (https://www.kaggle.com/nightranger77/covid19-demographic-predictors)
  5. Population size, density, urban population, median age, death from ling disease, dates for restrictions (https://www.kaggle.com/koryto/countryinfo)
  6. Restaurant Data, Open Table (https://www.kaggle.com/jaimeblasco/opentable-state-of-the-restaurant-industry)
  7. Pollution data (https://www.kaggle.com/kweinmeister/pm25-global-air-pollution-20102017)
  8. SARS data from 2003 (https://www.kaggle.com/imdevskp/sars-outbreak-2003-complete-dataset)
  9. Economic Freedom Index (https://www.kaggle.com/lewisduncan93/the-economic-freedom-index)
  10. Percent prison population (https://dataunodc.un.org/crime/total-prison-population)
  11. Percent population 65 and above (https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS)
  12. Port information (https://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=170027)
  13. Railways, passengers carried (https://data.worldbank.org/indicator/IS.RRS.PASG.KM)
  14. Air transport, passengers carried (https://data.worldbank.org/indicator/IS.RRS.PASG.KM)
  15. School restriction data (https://en.unesco.org/themes/education-emergencies/coronavirus-school-closures)

Possible learners:

TODO:

  • Write skeleton script for prediction
  • Research mechanistic models we could add
  • Identify and integrate covariate datasets
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