economist_excess_deaths
Data license: CC BY 4.0 · Data source: The Economist · About: simonw/covid-19-datasette
18 rows where cadence = "monthly", country = "Hong Kong" and covid_deaths_per_100k = "0.0" sorted by end_date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Suggested facets: start_date, end_date, days, year, expected_deaths, non_covid_deaths, excess_deaths_pct_change, month, total_deaths_per_7_days, expected_deaths_per_7_days, excess_deaths_per_7_days, non_covid_deaths_per_7_days, excess_deaths_per_100k_per_7_days, end_date (date)
Link | rowid | country | region | region_code | start_date | end_date ▲ | days | year | week | population | total_deaths | covid_deaths | expected_deaths | excess_deaths | non_covid_deaths | covid_deaths_per_100k | excess_deaths_per_100k | excess_deaths_pct_change | cadence | month | total_deaths_per_7_days | covid_deaths_per_7_days | expected_deaths_per_7_days | excess_deaths_per_7_days | non_covid_deaths_per_7_days | covid_deaths_per_100k_per_7_days | excess_deaths_per_100k_per_7_days | quarter |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
624 | 624 | Hong Kong | Hong Kong | 0 | 2022-01-01 | 2022-01-31 | 31 | 2022 | 7488863 | 4736 | 0 | 4842.81112753148 | -106.811127531481 | 4736 | 0.0 | -1.42626627742397 | -0.0220556046310082 | monthly | 1 | 1069.41935483871 | 0.0 | 1093.53799653937 | -24.1186417006571 | 1069.41935483871 | 0.0 | -0.322060127160252 | ||
21994 | 21994 | Hong Kong | Hong Kong | 0 | 2022-01-01 | 2022-01-31 | 31 | 2022 | 7488863 | 4736 | 0 | 4842.81112753148 | -106.811127531481 | 4736 | 0.0 | -1.42626627742397 | -0.022055604631008 | monthly | 1 | 1069.41935483871 | 0.0 | 1093.53799653937 | -24.1186417006571 | 1069.41935483871 | 0.0 | -0.322060127160252 | ||
623 | 623 | Hong Kong | Hong Kong | 0 | 2021-12-01 | 2021-12-31 | 31 | 2021 | 7488863 | 4754 | 0 | 4465.92840965762 | 288.071590342377 | 4754 | 0.0 | 3.84666658132719 | 0.0645043009913502 | monthly | 12 | 1073.48387096774 | 0.0 | 1008.43544734204 | 65.048423625698 | 1073.48387096774 | 0.0 | 0.86860213126743 | ||
21993 | 21993 | Hong Kong | Hong Kong | 0 | 2021-12-01 | 2021-12-31 | 31 | 2021 | 7488863 | 4754 | 0 | 4465.92840965762 | 288.071590342377 | 4754 | 0.0 | 3.84666658132719 | 0.0645043009913508 | monthly | 12 | 1073.48387096774 | 0.0 | 1008.43544734204 | 65.048423625698 | 1073.48387096774 | 0.0 | 0.86860213126743 | ||
622 | 622 | Hong Kong | Hong Kong | 0 | 2021-11-01 | 2021-11-30 | 30 | 2021 | 7488863 | 4252 | 0 | 3880.44039644286 | 371.559603557138 | 4252 | 0.0 | 4.96149553753538 | 0.0957519161736746 | monthly | 11 | 992.133333333333 | 0.0 | 905.436092503334 | 86.6972408299989 | 992.133333333333 | 0.0 | 1.15768229209159 | ||
21992 | 21992 | Hong Kong | Hong Kong | 0 | 2021-11-01 | 2021-11-30 | 30 | 2021 | 7488863 | 4252 | 0 | 3880.44039644286 | 371.559603557138 | 4252 | 0.0 | 4.96149553753538 | 0.0957519161736753 | monthly | 11 | 992.133333333333 | 0.0 | 905.436092503334 | 86.6972408299989 | 992.133333333333 | 0.0 | 1.15768229209159 | ||
621 | 621 | Hong Kong | Hong Kong | 0 | 2021-10-01 | 2021-10-31 | 31 | 2021 | 7488863 | 4256 | 0 | 3999.52840965762 | 256.471590342377 | 4256 | 0.0 | 3.42470666564974 | 0.0641254578222465 | monthly | 10 | 961.032258064516 | 0.0 | 903.119318309786 | 57.9129397547303 | 961.032258064516 | 0.0 | 0.773320859985425 | ||
21991 | 21991 | Hong Kong | Hong Kong | 0 | 2021-10-01 | 2021-10-31 | 31 | 2021 | 7488863 | 4256 | 0 | 3999.52840965762 | 256.471590342377 | 4256 | 0.0 | 3.42470666564974 | 0.0641254578222474 | monthly | 10 | 961.032258064516 | 0.0 | 903.119318309786 | 57.9129397547303 | 961.032258064516 | 0.0 | 0.773320859985425 | ||
619 | 619 | Hong Kong | Hong Kong | 0 | 2021-08-01 | 2021-08-31 | 31 | 2021 | 7488863 | 4063 | 0 | 3931.92840965762 | 131.071590342377 | 4063 | 0.0 | 1.75022016482846 | 0.0333351924771668 | monthly | 8 | 917.451612903226 | 0.0 | 887.854802180753 | 29.5968107224723 | 917.451612903226 | 0.0 | 0.395211004961265 | ||
21989 | 21989 | Hong Kong | Hong Kong | 0 | 2021-08-01 | 2021-08-31 | 31 | 2021 | 7488863 | 4063 | 0 | 3931.92840965762 | 131.071590342377 | 4063 | 0.0 | 1.75022016482845 | 0.0333351924771677 | monthly | 8 | 917.451612903226 | 0.0 | 887.854802180753 | 29.5968107224723 | 917.451612903226 | 0.0 | 0.395211004961265 | ||
609 | 609 | Hong Kong | Hong Kong | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 7488863 | 4184 | 0 | 3941.49630724321 | 242.503692756788 | 4184 | 0.0 | 3.23819106794701 | 0.0615257947371775 | monthly | 10 | 944.774193548387 | 0.0 | 890.015295183951 | 54.7588983644361 | 944.774193548387 | 0.0 | 0.731204434697712 | ||
21979 | 21979 | Hong Kong | Hong Kong | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 7488863 | 4184 | 0 | 3941.49630724321 | 242.503692756788 | 4184 | 0.0 | 3.238191067947 | 0.0615257947371777 | monthly | 10 | 944.774193548387 | 0.0 | 890.015295183951 | 54.7588983644361 | 944.774193548387 | 0.0 | 0.731204434697712 | ||
604 | 604 | Hong Kong | Hong Kong | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 7488863 | 4091 | 0 | 4048.69630724321 | 42.3036927567882 | 4091 | 0.0 | 0.5648880578639 | 0.0104487196733196 | monthly | 5 | 923.774193548387 | 0.0 | 914.221746796854 | 9.55244675153283 | 923.774193548387 | 0.0 | 0.127555367904752 | ||
21974 | 21974 | Hong Kong | Hong Kong | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 7488863 | 4091 | 0 | 4048.69630724321 | 42.3036927567882 | 4091 | 0.0 | 0.5648880578639 | 0.0104487196733201 | monthly | 5 | 923.774193548387 | 0.0 | 914.221746796854 | 9.55244675153283 | 923.774193548387 | 0.0 | 0.127555367904752 | ||
603 | 603 | Hong Kong | Hong Kong | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 7488863 | 3899 | 0 | 4070.08029733214 | -171.08029733214 | 3899 | 0.0 | -2.2844629062134 | -0.0420336418041384 | monthly | 4 | 909.766666666667 | 0.0 | 949.685402710833 | -39.918736044166 | 909.766666666667 | 0.0 | -0.533041344783127 | ||
21973 | 21973 | Hong Kong | Hong Kong | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 7488863 | 3899 | 0 | 4070.08029733214 | -171.08029733214 | 3899 | 0.0 | -2.2844629062134 | -0.0420336418041384 | monthly | 4 | 909.766666666667 | 0.0 | 949.685402710833 | -39.918736044166 | 909.766666666667 | 0.0 | -0.533041344783127 | ||
600 | 600 | Hong Kong | Hong Kong | 0 | 2020-01-01 | 2020-01-31 | 31 | 2020 | 7488863 | 4749 | 0 | 4726.74692270266 | 22.2530772973414 | 4749 | 0.0 | 0.297148943669305 | 0.00470790538635768 | monthly | 1 | 1072.35483870968 | 0.0 | 1067.3299502877 | 5.02488842198032 | 1072.35483870968 | 0.0 | 0.0670981485704882 | ||
21970 | 21970 | Hong Kong | Hong Kong | 0 | 2020-01-01 | 2020-01-31 | 31 | 2020 | 7488863 | 4749 | 0 | 4726.74692270266 | 22.2530772973414 | 4749 | 0.0 | 0.297148943669305 | 0.00470790538635724 | monthly | 1 | 1072.35483870968 | 0.0 | 1067.3299502877 | 5.02488842198032 | 1072.35483870968 | 0.0 | 0.0670981485704882 |
Advanced export
JSON shape: default, array, newline-delimited
CREATE TABLE [economist_excess_deaths] ( [country] TEXT, [region] TEXT, [region_code] INTEGER, [start_date] TEXT, [end_date] TEXT, [days] INTEGER, [year] INTEGER, [week] INTEGER, [population] INTEGER, [total_deaths] INTEGER, [covid_deaths] INTEGER, [expected_deaths] FLOAT, [excess_deaths] FLOAT, [non_covid_deaths] INTEGER, [covid_deaths_per_100k] FLOAT, [excess_deaths_per_100k] FLOAT, [excess_deaths_pct_change] FLOAT, [cadence] TEXT , [month] INTEGER, [total_deaths_per_7_days] FLOAT, [covid_deaths_per_7_days] FLOAT, [expected_deaths_per_7_days] FLOAT, [excess_deaths_per_7_days] FLOAT, [non_covid_deaths_per_7_days] FLOAT, [covid_deaths_per_100k_per_7_days] FLOAT, [excess_deaths_per_100k_per_7_days] FLOAT, [quarter] INTEGER);