economist_excess_deaths
Data license: CC BY 4.0 · Data source: The Economist · About: simonw/covid-19-datasette
24 rows where country = "Brazil" and year = 2020 sorted by non_covid_deaths
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Suggested facets: start_date, end_date, days, total_deaths, covid_deaths, expected_deaths, excess_deaths, non_covid_deaths, excess_deaths_per_100k, 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
start_date (date) 12 ✖
- 2020-01-01 2
- 2020-02-01 2
- 2020-03-01 2
- 2020-04-01 2
- 2020-05-01 2
- 2020-06-01 2
- 2020-07-01 2
- 2020-08-01 2
- 2020-09-01 2
- 2020-10-01 2
- 2020-11-01 2
- 2020-12-01 2
country 1
- Brazil · 24 ✖
cadence 1
- monthly 24
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
414 | 414 | Brazil | Brazil | 0 | 2020-02-01 | 2020-02-29 | 29 | 2020 | 215313504 | 104255 | 0 | 103772.004836576 | 482.995163424057 | 104255 | 0.0 | 0.224321816537832 | 0.00465438789762906 | monthly | 2 | 25165.0 | 0.0 | 25048.4149605528 | 116.585039447186 | 25165.0 | 0.0 | 0.0541466453712008 | ||
21668 | 21668 | Brazil | Brazil | 0 | 2020-02-01 | 2020-02-29 | 29 | 2020 | 215313504 | 104255 | 0 | 103772.004836576 | 482.995163424057 | 104255 | 0.0 | 0.224321816537832 | 0.0046543878976284 | monthly | 2 | 25165.0 | 0.0 | 25048.4149605528 | 116.585039447186 | 25165.0 | 0.0 | 0.0541466453712008 | ||
421 | 421 | Brazil | Brazil | 0 | 2020-09-01 | 2020-09-30 | 30 | 2020 | 215313504 | 127115 | 22460 | 111372.087284814 | 15742.9127151864 | 104655 | 10.4313011412419 | 7.31162348051631 | 0.141354203723657 | monthly | 9 | 29660.1666666667 | 5240.66666666667 | 25986.8203664565 | 3673.34630021017 | 24419.5 | 2.43397026628978 | 1.70604547878714 | ||
21675 | 21675 | Brazil | Brazil | 0 | 2020-09-01 | 2020-09-30 | 30 | 2020 | 215313504 | 127115 | 22460 | 111372.087284814 | 15742.9127151864 | 104655 | 10.4313011412419 | 7.3116234805163 | 0.141354203723652 | monthly | 9 | 29660.1666666667 | 5240.66666666667 | 25986.8203664565 | 3673.34630021017 | 24419.5 | 2.43397026628978 | 1.70604547878714 | ||
423 | 423 | Brazil | Brazil | 0 | 2020-11-01 | 2020-11-30 | 30 | 2020 | 215313504 | 122598 | 13296 | 106828.287284814 | 15769.7127151864 | 109302 | 6.17518165511811 | 7.32407044714967 | 0.147617387828591 | monthly | 11 | 28606.2 | 3102.4 | 24926.6003664565 | 3679.5996335435 | 25503.8 | 1.44087571952756 | 1.70894977100159 | ||
21677 | 21677 | Brazil | Brazil | 0 | 2020-11-01 | 2020-11-30 | 30 | 2020 | 215313504 | 122598 | 13296 | 106828.287284814 | 15769.7127151864 | 109302 | 6.17518165511811 | 7.32407044714966 | 0.147617387828586 | monthly | 11 | 28606.2 | 3102.4 | 24926.6003664565 | 3679.5996335435 | 25503.8 | 1.44087571952756 | 1.70894977100159 | ||
418 | 418 | Brazil | Brazil | 0 | 2020-06-01 | 2020-06-30 | 30 | 2020 | 215313504 | 140663 | 30425 | 119789.687284814 | 20873.3127151864 | 110238 | 14.1305582022389 | 9.69438160050863 | 0.174249663625532 | monthly | 6 | 32821.3666666667 | 7099.16666666667 | 27950.9270331232 | 4870.4396335435 | 25722.2 | 3.29713024718908 | 2.26202237345201 | ||
21672 | 21672 | Brazil | Brazil | 0 | 2020-06-01 | 2020-06-30 | 30 | 2020 | 215313504 | 140663 | 30425 | 119789.687284814 | 20873.3127151864 | 110238 | 14.1305582022389 | 9.69438160050862 | 0.174249663625528 | monthly | 6 | 32821.3666666667 | 7099.16666666667 | 27950.9270331232 | 4870.4396335435 | 25722.2 | 3.29713024718908 | 2.26202237345201 | ||
413 | 413 | Brazil | Brazil | 0 | 2020-01-01 | 2020-01-31 | 31 | 2020 | 215313504 | 110932 | 0 | 111661.575161922 | -729.575161922316 | 110932 | 0.0 | -0.338843197648354 | -0.0065338068253501 | monthly | 1 | 25049.1612903226 | 0.0 | 25213.9040688212 | -164.742778498587 | 25049.1612903226 | 0.0 | -0.0765129801141444 | ||
21667 | 21667 | Brazil | Brazil | 0 | 2020-01-01 | 2020-01-31 | 31 | 2020 | 215313504 | 110932 | 0 | 111661.575161922 | -729.575161922316 | 110932 | 0.0 | -0.338843197648354 | -0.00653380682534732 | monthly | 1 | 25049.1612903226 | 0.0 | 25213.9040688212 | -164.742778498587 | 25049.1612903226 | 0.0 | -0.0765129801141444 | ||
419 | 419 | Brazil | Brazil | 0 | 2020-07-01 | 2020-07-31 | 31 | 2020 | 215313504 | 145262 | 32936 | 124265.890194307 | 20996.1098056926 | 112326 | 15.2967646655363 | 9.75141336499388 | 0.168961166840412 | monthly | 7 | 32801.0967741935 | 7437.16129032258 | 28060.0397212952 | 4741.05705289834 | 25363.935483871 | 3.45410815028238 | 2.20193205015991 | ||
21673 | 21673 | Brazil | Brazil | 0 | 2020-07-01 | 2020-07-31 | 31 | 2020 | 215313504 | 145262 | 32936 | 124265.890194307 | 20996.1098056926 | 112326 | 15.2967646655363 | 9.75141336499386 | 0.168961166840415 | monthly | 7 | 32801.0967741935 | 7437.16129032258 | 28060.0397212952 | 4741.05705289834 | 25363.935483871 | 3.45410815028238 | 2.20193205015991 | ||
420 | 420 | Brazil | Brazil | 0 | 2020-08-01 | 2020-08-31 | 31 | 2020 | 215313504 | 141329 | 28890 | 118019.690194307 | 23309.3098056926 | 112439 | 13.4176442551416 | 10.8257537835122 | 0.197503567136265 | monthly | 8 | 31913.0 | 6523.54838709677 | 26649.6074632307 | 5263.3925367693 | 25389.4516129032 | 3.02979063825777 | 2.44452504788984 | ||
21674 | 21674 | Brazil | Brazil | 0 | 2020-08-01 | 2020-08-31 | 31 | 2020 | 215313504 | 141329 | 28890 | 118019.690194307 | 23309.3098056926 | 112439 | 13.4176442551416 | 10.8257537835122 | 0.197503567136269 | monthly | 8 | 31913.0 | 6523.54838709677 | 26649.6074632307 | 5263.3925367693 | 25389.4516129032 | 3.02979063825777 | 2.44452504788984 | ||
422 | 422 | Brazil | Brazil | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 215313504 | 128797 | 15894 | 112825.090194307 | 15971.9098056926 | 112903 | 7.38179431606854 | 7.41797867248151 | 0.141563457012849 | monthly | 10 | 29083.1935483871 | 3588.96774193548 | 25476.6332696823 | 3606.56027870479 | 25494.2258064516 | 1.66685678104773 | 1.67502744217324 | ||
21676 | 21676 | Brazil | Brazil | 0 | 2020-10-01 | 2020-10-31 | 31 | 2020 | 215313504 | 128797 | 15894 | 112825.090194307 | 15971.9098056926 | 112903 | 7.38179431606854 | 7.4179786724815 | 0.141563457012853 | monthly | 10 | 29083.1935483871 | 3588.96774193548 | 25476.6332696823 | 3606.56027870479 | 25494.2258064516 | 1.66685678104773 | 1.67502744217324 | ||
415 | 415 | Brazil | Brazil | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 215313504 | 117888 | 201 | 112985.290194307 | 4902.70980569263 | 117687 | 0.0933522497502061 | 2.27700990166071 | 0.043392461065163 | monthly | 3 | 26619.8709677419 | 45.3870967741935 | 25512.8074632307 | 1107.06350451124 | 26574.4838709677 | 0.0210795402661756 | 0.514163526181451 | ||
21669 | 21669 | Brazil | Brazil | 0 | 2020-03-01 | 2020-03-31 | 31 | 2020 | 215313504 | 117888 | 201 | 112985.290194307 | 4902.70980569263 | 117687 | 0.0933522497502061 | 2.27700990166071 | 0.0433924610651664 | monthly | 3 | 26619.8709677419 | 45.3870967741935 | 25512.8074632307 | 1107.06350451124 | 26574.4838709677 | 0.0210795402661756 | 0.514163526181451 | ||
416 | 416 | Brazil | Brazil | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 215313504 | 123596 | 5805 | 112962.687284814 | 10633.3127151864 | 117791 | 2.69606870547237 | 4.93852569283643 | 0.0941311947402292 | monthly | 4 | 28839.0666666667 | 1354.5 | 26357.9603664565 | 2481.10630021016 | 27484.5666666667 | 0.629082697943553 | 1.15232266166183 | ||
21670 | 21670 | Brazil | Brazil | 0 | 2020-04-01 | 2020-04-30 | 30 | 2020 | 215313504 | 123596 | 5805 | 112962.687284814 | 10633.3127151864 | 117791 | 2.69606870547237 | 4.93852569283643 | 0.0941311947402252 | monthly | 4 | 28839.0666666667 | 1354.5 | 26357.9603664565 | 2481.10630021016 | 27484.5666666667 | 0.629082697943553 | 1.15232266166183 | ||
424 | 424 | Brazil | Brazil | 0 | 2020-12-01 | 2020-12-31 | 31 | 2020 | 215313504 | 139878 | 21804 | 113007.090194307 | 26870.9098056926 | 118074 | 10.1266291221567 | 12.4798999163994 | 0.237780742425011 | monthly | 12 | 31585.3548387097 | 4923.48387096774 | 25517.7300438759 | 6067.62479483382 | 26661.8709677419 | 2.28665818887409 | 2.81804191660632 | ||
21678 | 21678 | Brazil | Brazil | 0 | 2020-12-01 | 2020-12-31 | 31 | 2020 | 215313504 | 139878 | 21804 | 113007.090194307 | 26870.9098056926 | 118074 | 10.1266291221567 | 12.4798999163994 | 0.237780742425015 | monthly | 12 | 31585.3548387097 | 4923.48387096774 | 25517.7300438759 | 6067.62479483382 | 26661.8709677419 | 2.28665818887409 | 2.81804191660632 | ||
417 | 417 | Brazil | Brazil | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 215313504 | 154511 | 23361 | 120193.690194307 | 34317.3098056926 | 131150 | 10.8497607284307 | 15.9382988842598 | 0.285516733450938 | monthly | 5 | 34889.5806451613 | 5275.06451612903 | 27140.5106890371 | 7749.06995612414 | 29614.5161290323 | 2.44994597093596 | 3.59897071580059 | ||
21671 | 21671 | Brazil | Brazil | 0 | 2020-05-01 | 2020-05-31 | 31 | 2020 | 215313504 | 154511 | 23361 | 120193.690194307 | 34317.3098056926 | 131150 | 10.8497607284307 | 15.9382988842598 | 0.285516733450942 | monthly | 5 | 34889.5806451613 | 5275.06451612903 | 27140.5106890371 | 7749.06995612414 | 29614.5161290323 | 2.44994597093596 | 3.59897071580059 |
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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);