economist_excess_deaths
Data license: CC BY 4.0 · Data source: The Economist · About: simonw/covid-19-datasette
22 rows where cadence = "monthly" and covid_deaths = 12 sorted by end_date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Suggested facets: region, end_date, days, year, population, expected_deaths, excess_deaths, covid_deaths_per_100k, excess_deaths_per_100k, excess_deaths_pct_change, 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)
country 10
cadence 1
- monthly · 22 ✖
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
19300 | 19300 | Taiwan | Taiwan | 0 | 2022-04-01 | 2022-04-30 | 30 | 2022 | 23893396 | 14655 | 12 | 15203.6033258588 | -548.603325858834 | 14643 | 0.0502230825622276 | -2.29604584404341 | -0.0360837700182397 | monthly | 4 | 3419.5 | 2.8 | 3547.50744270039 | -128.007442700395 | 3416.7 | 0.0117187192645198 | -0.535744030276795 | ||
22971 | 22971 | Taiwan | Taiwan | 0 | 2022-04-01 | 2022-04-30 | 30 | 2022 | 23893396 | 14655 | 12 | 15203.6033258588 | -548.603325858834 | 14643 | 0.0502230825622276 | -2.29604584404341 | -0.0360837700182375 | monthly | 4 | 3419.5 | 2.8 | 3547.50744270039 | -128.007442700395 | 3416.7 | 0.0117187192645198 | -0.535744030276795 | ||
22497 | 22497 | Mongolia | Mongolia | 0 | 2022-03-01 | 2022-03-31 | 31 | 2022 | 3398373 | 1496 | 12 | 1535.934397616 | -39.934397616001 | 1484 | 0.353110150062986 | -1.17510342790509 | -0.0260000672411428 | monthly | 3 | 337.806451612903 | 2.70967741935484 | 346.823896235871 | -9.01744462296796 | 335.096774193548 | 0.0797345500142227 | -0.265345935333407 | ||
23874 | 23874 | Mongolia | Mongolia | 0 | 2022-03-01 | 2022-03-31 | 31 | 2022 | 3398373 | 1496 | 12 | 1535.934397616 | -39.934397616001 | 1484 | 0.353110150062986 | -1.17510342790509 | -0.0260000672411433 | monthly | 3 | 337.806451612903 | 2.70967741935484 | 346.823896235871 | -9.01744462296796 | 335.096774193548 | 0.0797345500142227 | -0.265345935333407 | ||
992 | 992 | Kuwait | Kuwait | 0 | 2021-10-01 | 2021-10-31 | 31 | 2021 | 4268886 | 602 | 12 | 587.710699993916 | 14.2893000060835 | 590 | 0.281103782110836 | 0.33473135628554 | 0.0243134930268096 | monthly | 10 | 135.935483870968 | 2.70967741935484 | 132.708867740562 | 3.22661613040596 | 133.225806451613 | 0.0634750475734147 | 0.0755844998064122 | ||
22206 | 22206 | Kuwait | Kuwait | 0 | 2021-10-01 | 2021-10-31 | 31 | 2021 | 4268886 | 602 | 12 | 587.710699993916 | 14.2893000060835 | 590 | 0.281103782110836 | 0.334731356285539 | 0.0243134930268105 | monthly | 10 | 135.935483870968 | 2.70967741935484 | 132.708867740562 | 3.22661613040596 | 133.225806451613 | 0.0634750475734147 | 0.0755844998064122 | ||
21440 | 21440 | Aruba | Aruba | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 106459 | 71 | 12 | 55.7398932676515 | 15.2601067323485 | 59 | 11.2719450680544 | 14.3342570683066 | 0.273773519067799 | monthly | 10 | 16.0322580645161 | 2.70967741935484 | 12.5864275120503 | 3.44583055246579 | 13.3225806451613 | 2.54527791859292 | 3.23676772510148 | ||
24512 | 24512 | Aruba | Aruba | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 106459 | 71 | 12 | 55.7398932676515 | 15.2601067323485 | 59 | 11.2719450680544 | 14.3342570683066 | 0.273773519067799 | monthly | 10 | 16.0322580645161 | 2.70967741935484 | 12.5864275120503 | 3.44583055246579 | 13.3225806451613 | 2.54527791859292 | 3.23676772510148 | ||
22370 | 22370 | Maldives | Maldives | 0 | 2020-08-01 | 2020-08-31 | 31 | 2020 | 523798 | 129 | 12 | 88.5801578179159 | 40.4198421820841 | 117 | 2.29095949201792 | 7.71668509274264 | 0.456308084990891 | monthly | 8 | 29.1290322580645 | 2.70967741935484 | 20.0019711201746 | 9.12706113788995 | 26.4193548387097 | 0.517313433681465 | 1.7424772790064 | ||
23111 | 23111 | Maldives | Maldives | 0 | 2020-08-01 | 2020-08-31 | 31 | 2020 | 523798 | 129 | 12 | 88.5801578179159 | 40.4198421820841 | 117 | 2.29095949201792 | 7.71668509274263 | 0.45630808499089 | monthly | 8 | 29.1290322580645 | 2.70967741935484 | 20.0019711201746 | 9.12706113788995 | 26.4193548387097 | 0.517313433681465 | 1.7424772790064 | ||
22937 | 22937 | Suriname | Suriname | 0 | 2020-06-01 | 2020-06-30 | 30 | 2020 | 618046 | 327 | 12 | 300.988157917966 | 26.0118420820339 | 315 | 1.9416030522 | 4.20872266498511 | 0.0864214800408309 | monthly | 6 | 76.3 | 2.8 | 70.2305701808587 | 6.06942981914125 | 73.5 | 0.45304071218 | 0.982035288496528 | ||
23304 | 23304 | Suriname | Suriname | 0 | 2020-06-01 | 2020-06-30 | 30 | 2020 | 618046 | 327 | 12 | 300.988157917966 | 26.0118420820339 | 315 | 1.9416030522 | 4.20872266498512 | 0.0864214800408307 | monthly | 6 | 76.3 | 2.8 | 70.2305701808587 | 6.06942981914125 | 73.5 | 0.45304071218 | 0.982035288496528 | ||
10182 | 10182 | Malaysia | Malaysia | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 33938216 | 13886 | 12 | 15238.892247765 | -1352.89224776499 | 13874 | 0.0353583700451432 | -3.98633872730666 | -0.088778910288798 | monthly | 5 | 3135.54838709677 | 2.70967741935484 | 3441.04018497919 | -305.491797882416 | 3132.83870967742 | 0.00798414807470976 | -0.900141002940214 | ||
22334 | 22334 | Malaysia | Malaysia | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 33938216 | 13886 | 12 | 15238.892247765 | -1352.89224776499 | 13874 | 0.0353583700451432 | -3.98633872730667 | -0.0887789102887987 | monthly | 5 | 3135.54838709677 | 2.70967741935484 | 3441.04018497919 | -305.491797882416 | 3132.83870967742 | 0.00798414807470976 | -0.900141002940214 | ||
350 | 350 | Singapore | Singapore | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 5637022 | 1913 | 12 | 1796.04986934336 | 116.950130656635 | 1901 | 0.212878360240567 | 2.07467933700871 | 0.0651151912053489 | monthly | 4 | 446.366666666667 | 2.8 | 419.078302846785 | 27.2883638198815 | 443.566666666667 | 0.0496716173894656 | 0.484091845302032 | ||
950 | 950 | Lebanon | Lebanon | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 5489744 | 1836 | 12 | 2109.87731341702 | -273.877313417017 | 1824 | 0.218589427849459 | -4.98889043673106 | -0.129807222285102 | monthly | 4 | 428.4 | 2.8 | 492.304706463971 | -63.9047064639706 | 425.6 | 0.0510041998315404 | -1.16407443523725 | ||
22246 | 22246 | Lebanon | Lebanon | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 5489744 | 1836 | 12 | 2109.87731341702 | -273.877313417017 | 1824 | 0.218589427849459 | -4.98889043673106 | -0.129807222285103 | monthly | 4 | 428.4 | 2.8 | 492.304706463971 | -63.9047064639706 | 425.6 | 0.0510041998315404 | -1.16407443523725 | ||
22902 | 22902 | Singapore | Singapore | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 5637022 | 1913 | 12 | 1796.04986934336 | 116.950130656635 | 1901 | 0.212878360240567 | 2.07467933700871 | 0.0651151912053518 | monthly | 4 | 446.366666666667 | 2.8 | 419.078302846785 | 27.2883638198815 | 443.566666666667 | 0.0496716173894656 | 0.484091845302032 | ||
949 | 949 | Lebanon | Lebanon | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 5489744 | 2222 | 12 | 2479.19989053092 | -257.199890530917 | 2210 | 0.218589427849459 | -4.68509807617473 | -0.103743103375113 | monthly | 3 | 501.741935483871 | 2.70967741935484 | 559.819330119885 | -58.0773946360136 | 499.032258064516 | 0.049358903062781 | -1.05792537203945 | ||
20287 | 20287 | Andorra | Andorra | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 79843 | 40 | 12 | 32.9374283889796 | 7.06257161102035 | 28 | 15.0294953846925 | 8.84557395265753 | 0.214423892709954 | monthly | 3 | 9.03225806451613 | 2.70967741935484 | 7.4374838297696 | 1.59477423474653 | 6.32258064516129 | 3.39375702234991 | 1.99738766672912 | ||
21351 | 21351 | Andorra | Andorra | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 79843 | 40 | 12 | 32.9374283889796 | 7.06257161102035 | 28 | 15.0294953846925 | 8.84557395265753 | 0.214423892709956 | monthly | 3 | 9.03225806451613 | 2.70967741935484 | 7.4374838297696 | 1.59477423474653 | 6.32258064516129 | 3.39375702234991 | 1.99738766672912 | ||
22245 | 22245 | Lebanon | Lebanon | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 5489744 | 2222 | 12 | 2479.19989053092 | -257.199890530917 | 2210 | 0.218589427849459 | -4.68509807617472 | -0.103743103375114 | monthly | 3 | 501.741935483871 | 2.70967741935484 | 559.819330119885 | -58.0773946360136 | 499.032258064516 | 0.049358903062781 | -1.05792537203945 |
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);