COVID-19 Visualisation And Epidemic Analysis Data
Includes demographics, daily new, remaining and cumulative cases
@kaggle.dylansp_covid19_country_level_data_for_epidemic_model
Includes demographics, daily new, remaining and cumulative cases
@kaggle.dylansp_covid19_country_level_data_for_epidemic_model
I combined several data sources to gain an integrated dataset involving country-level COVID-19 confirmed, recovered and fatalities cases which can be used to build some epidemic models such as SIR, SIR with mortality. Adding information regarding population which can be used for calculating incidence rate and prevalence rate.
One of my applications based on this dataset is published at https://dylansp.shinyapps.io/COVID19_Visualization_Analysis_Tool/.
My approach is to retrieve cumulative confirmed cases, fatalities and recovered cases since 2020-01-22 onwards from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) COVID-19 dataset, merged with country code as well as population of each country. For the purpose of building epidemic models, I calculated information regarding daily new confirmed cases, recovered cases, and fatalities, together with remaining confirmed cases which equal to cumulative confirmed cases - cumulative recovered cases - cumulative fatalities. I haven't yet to find creditable data sources regarding probable cases of various countries yet. I'll add them once I found them.
CREATE TABLE country_level_info_kaggle (
"date" TIMESTAMP,
"country_region" VARCHAR,
"alpha_3_code" VARCHAR,
"population" BIGINT,
"total_confirmed_cases" BIGINT,
"total_fatalities" BIGINT,
"total_recovered_cases" BIGINT,
"new_confirmed_cases" BIGINT,
"new_fatalities" BIGINT,
"new_recovered_cases" BIGINT,
"remaining_confirmed_cases" BIGINT
);Anyone who has the link will be able to view this.