economist_excess_deaths
Data license: CC BY 4.0 · Data source: The Economist · About: simonw/covid-19-datasette
18 rows where cadence = "monthly" and covid_deaths = 16 sorted by end_date descending
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Suggested facets: start_date, days, year, population, total_deaths, excess_deaths, non_covid_deaths, covid_deaths_per_100k, total_deaths_per_7_days, covid_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, start_date (date)
country 9
- Albania 2
- Bahamas 2
- Barbados 2
- Bermuda 2
- Hong Kong 2
- Kazakhstan 2
- Seychelles 2
- Thailand 2
- Uruguay 2
cadence 1
- monthly · 18 ✖
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
18023 | 18023 | Barbados | Barbados | 0 | 2022-07-01 | 2022-07-31 | 31 | 2022 | 281646 | 178 | 16 | 235.689677978477 | -57.6896779784767 | 162 | 5.68089019549363 | -20.4830453755696 | -0.244769641476386 | monthly | 7 | 40.1935483870968 | 3.61290322580645 | 53.2202498661077 | -13.0267014790109 | 36.5806451612903 | 1.28278165704695 | -4.62520379448346 | ||
21543 | 21543 | Barbados | Barbados | 0 | 2022-07-01 | 2022-07-31 | 31 | 2022 | 281646 | 178 | 16 | 235.689677978477 | -57.6896779784767 | 162 | 5.68089019549363 | -20.4830453755696 | -0.244769641476387 | monthly | 7 | 40.1935483870968 | 3.61290322580645 | 53.2202498661077 | -13.0267014790109 | 36.5806451612903 | 1.28278165704695 | -4.62520379448346 | ||
19890 | 19890 | Bahamas | Bahamas | 0 | 2021-06-01 | 2021-06-30 | 30 | 2021 | 409989 | 233 | 16 | 224.742326276699 | 8.25767372330117 | 217 | 3.90254372678291 | 2.01412079916807 | 0.0367428506241163 | monthly | 6 | 54.3666666666667 | 3.73333333333333 | 52.4398761312297 | 1.92679053543694 | 50.6333333333333 | 0.910593536249346 | 0.469961519805882 | ||
21506 | 21506 | Bahamas | Bahamas | 0 | 2021-06-01 | 2021-06-30 | 30 | 2021 | 409989 | 233 | 16 | 224.742326276699 | 8.25767372330117 | 217 | 3.90254372678291 | 2.01412079916807 | 0.0367428506241156 | monthly | 6 | 54.3666666666667 | 3.73333333333333 | 52.4398761312297 | 1.92679053543694 | 50.6333333333333 | 0.910593536249346 | 0.469961519805882 | ||
22892 | 22892 | Seychelles | Seychelles | 0 | 2021-06-01 | 2021-06-30 | 30 | 2021 | 107135 | 108 | 16 | 71.563655090017 | 36.436344909983 | 92 | 14.9344285247585 | 34.0097492975993 | 0.509145946558364 | monthly | 6 | 25.2 | 3.73333333333333 | 16.6981861876706 | 8.50181381232936 | 21.4666666666667 | 3.48469998911031 | 7.93560816943983 | ||
23628 | 23628 | Seychelles | Seychelles | 0 | 2021-06-01 | 2021-06-30 | 30 | 2021 | 107135 | 108 | 16 | 71.563655090017 | 36.436344909983 | 92 | 14.9344285247585 | 34.0097492975993 | 0.509145946558363 | monthly | 6 | 25.2 | 3.73333333333333 | 16.6981861876706 | 8.50181381232936 | 21.4666666666667 | 3.48469998911031 | 7.93560816943983 | ||
19936 | 19936 | Bermuda | Bermuda | 0 | 2021-04-01 | 2021-04-30 | 30 | 2021 | 64207 | 62 | 16 | 45.40730264668 | 16.59269735332 | 46 | 24.9194013113835 | 25.8425052616069 | 0.365419137146944 | monthly | 4 | 14.4666666666667 | 3.73333333333333 | 10.5950372842253 | 3.87162938244132 | 10.7333333333333 | 5.81452697265615 | 6.02991789437495 | ||
21600 | 21600 | Bermuda | Bermuda | 0 | 2021-04-01 | 2021-04-30 | 30 | 2021 | 64207 | 62 | 16 | 45.40730264668 | 16.59269735332 | 46 | 24.9194013113835 | 25.842505261607 | 0.365419137146945 | monthly | 4 | 14.4666666666667 | 3.73333333333333 | 10.5950372842253 | 3.87162938244132 | 10.7333333333333 | 5.81452697265615 | 6.02991789437495 | ||
10407 | 10407 | Thailand | Thailand | 0 | 2021-01-01 | 2021-01-31 | 31 | 2021 | 71697024 | 46685 | 16 | 45736.0483556831 | 948.951644316854 | 46669 | 0.022316128490912 | 1.32355792663982 | 0.0207484397632471 | monthly | 1 | 10541.7741935484 | 3.61290322580645 | 10327.494789993 | 214.279403555419 | 10538.1612903226 | 0.00503912578827045 | 0.298867918918669 | ||
22991 | 22991 | Thailand | Thailand | 0 | 2021-01-01 | 2021-01-31 | 31 | 2021 | 71697024 | 46685 | 16 | 45736.0483556831 | 948.951644316854 | 46669 | 0.022316128490912 | 1.32355792663982 | 0.0207484397632482 | monthly | 1 | 10541.7741935484 | 3.61290322580645 | 10327.494789993 | 214.279403555419 | 10538.1612903226 | 0.00503912578827045 | 0.298867918918669 | ||
608 | 608 | Hong Kong | Hong Kong | 0 | 2020-09-01 | 2020-09-30 | 30 | 2020 | 7488863 | 3849 | 16 | 3665.88029733214 | 183.11970266786 | 3833 | 0.213650590216432 | 2.44522703470286 | 0.0499524501116759 | monthly | 9 | 898.1 | 3.73333333333333 | 855.372069377499 | 42.7279306225006 | 894.366666666667 | 0.0498518043838341 | 0.570552974764001 | ||
21978 | 21978 | Hong Kong | Hong Kong | 0 | 2020-09-01 | 2020-09-30 | 30 | 2020 | 7488863 | 3849 | 16 | 3665.88029733214 | 183.11970266786 | 3833 | 0.213650590216432 | 2.44522703470286 | 0.0499524501116761 | monthly | 9 | 898.1 | 3.73333333333333 | 855.372069377499 | 42.7279306225006 | 894.366666666667 | 0.0498518043838341 | 0.570552974764001 | ||
384 | 384 | Kazakhstan | Kazakhstan | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 19397998 | 14358 | 16 | 11175.5315526364 | 3182.46844736363 | 14342 | 0.0824827386826208 | 16.4061695818488 | 0.284771103045463 | monthly | 5 | 3242.12903225806 | 3.61290322580645 | 2523.50712478886 | 718.621907469207 | 3238.51612903226 | 0.0186251345412369 | 3.70461893783682 | ||
22122 | 22122 | Kazakhstan | Kazakhstan | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 19397998 | 14358 | 16 | 11175.5315526364 | 3182.46844736363 | 14342 | 0.0824827386826208 | 16.4061695818488 | 0.284771103045459 | monthly | 5 | 3242.12903225806 | 3.61290322580645 | 2523.50712478886 | 718.621907469207 | 3238.51612903226 | 0.0186251345412369 | 3.70461893783682 | ||
11150 | 11150 | Albania | Albania | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 2842318 | 1804 | 16 | 1722.10033635256 | 81.8996636474358 | 1788 | 0.562920827296594 | 2.88143915098296 | 0.0475580092045627 | monthly | 4 | 420.933333333333 | 3.73333333333333 | 401.823411815598 | 19.109921517735 | 417.2 | 0.131348193035872 | 0.672335801896023 | ||
21310 | 21310 | Albania | Albania | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 2842318 | 1804 | 16 | 1722.10033635256 | 81.8996636474358 | 1788 | 0.562920827296594 | 2.88143915098296 | 0.0475580092045653 | monthly | 4 | 420.933333333333 | 3.73333333333333 | 401.823411815598 | 19.109921517735 | 417.2 | 0.131348193035872 | 0.672335801896023 | ||
23042 | 23042 | Uruguay | Uruguay | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 3422796 | 2511 | 16 | 2576.1670542225 | -65.1670542225029 | 2495 | 0.467454093086471 | -1.90391288941856 | -0.0252961290362312 | monthly | 4 | 585.9 | 3.73333333333333 | 601.105645985251 | -15.2056459852507 | 582.166666666667 | 0.109072621720177 | -0.444246340864331 | ||
23270 | 23270 | Uruguay | Uruguay | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 3422796 | 2511 | 16 | 2576.1670542225 | -65.1670542225029 | 2495 | 0.467454093086471 | -1.90391288941856 | -0.0252961290362324 | monthly | 4 | 585.9 | 3.73333333333333 | 601.105645985251 | -15.2056459852507 | 582.166666666667 | 0.109072621720177 | -0.444246340864331 |
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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);