COVID-19 short-term forecasts Confirmed 2022-01-29 Latin American Countries


General information

  • Forecasts produced by Jennie Castle, Jurgen Doornik, and David Hendry, researchers at the University of Oxford. These are our forecasts, and should not be considered official forecasts from, or endorsed by, any of: University of Oxford, Oxford Martin School, Nuffield College, or Magdalen College.
  • These forecasts are short term time-series extrapolations of the data. They are not based on epidemiological modelling or simulations. All forecasts are uncertain: their success can only be determined afterwards. Many mitigation strategies are in place, which, if successful, invalidate our forecasts. An explanation of our methods is provided below.
  • A list of notes is below. The most recent note:
    [2021-04-29]The `legacy' download for areas of England is stuck at April 26, so we switched to the newer downloads. The results now include Scotland, Wales, and Northern Ireland. The map, however, only shows England.

Peak increase in estimated trend of Confirmed in Latin America 2022-01-29

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-232022-01-09 --2022-01-242022-01-16 -- --2022-01-232022-01-252022-01-142022-01-14 --2022-01-072022-01-162022-01-172022-01-172022-01-16 --2021-08-19 -- --2022-01-222022-01-18 --2022-01-25 --
Peak daily increment 114460 864 862 10178 29997 7507 5975 17968 2199 894 566 972 1298 167 49801 895 12297
Days since peak 6 20 5 13 6 4 15 15 22 13 12 12 13 163 7 11 4
Last total 8313614 32486 43481 50487 847180 25256198 2107612 5855858 682480 552831 691898 133262 688326 59450 28875 391874 123047 4916143 17650 692634 570469 3160732 73162 110741 653853 481375
Last daily increment 41978 67 630 0 5423 205597 31909 18450 0 1303 0 6250 2784 846 0 0 0 42582 0 7004 5101 40331 219 1081 9222 2364
Last week 451078 418 4269 4734 42503 1201793 142219 115679 38984 13251 33853 6250 18496 2223 404 4359 3482 248314 46 47951 53914 214581 3088 4324 64858 11809
Previous peak date2021-06-052021-07-262021-10-292021-10-142021-06-102021-06-182021-06-122021-06-262021-09-062021-06-052021-07-292021-11-062021-08-242021-09-182021-06-232021-08-132021-08-232021-08-1205-262021-07-062021-06-072021-07-042021-09-15 -- --2021-10-06
Previous peak daily increment 25320 172 347 370 2614 79238 6997 29569 2470 1203 3070 1526 3774 232 153 1515 759 19208 176 1068 2667 2786 485 1509
Low between peaks 898 -2 -8 287 1351 -347 163 -850 160 31 3 -67 27 -35 -2266 16

Confirmed count forecast Latin America (bold red line in graphs) 2022-01-30 to 2022-02-05

DateArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-01-29 8313614 32486 43481 50487 847180 25256198 2107612 5855858 682480 552831 691898 133262 688326 59450 28875 391874 123047 4916143 692634 570469 3160732 73162 110741 653853 481375
2022-01-30 8397000 32600 43570 50560 855200 25408000 2108000 5901000 682500 553900 698700 133300 688300 61420 28950 391900 126000 4989000 701200 570500 3197000 73790 111100 663700 483900
2022-01-31 8553000 33020 43770 51870 871700 25530000 2130000 5927000 683000 557000 704000 133900 688300 62180 29050 392200 127700 5000000 704800 583400 3210000 75270 111400 673300 486900
2022-02-01 8675000 33290 44340 52930 883900 25718000 2151000 5948000 691900 559100 709000 134700 690500 62890 29050 394600 129000 5029000 710400 583600 3234000 76370 111900 682900 489500
2022-02-02 8779000 33480 45020 53660 894000 25923000 2173000 5968000 698300 560800 714300 135500 693300 63600 29060 394600 129800 5071000 717000 588300 3262000 77260 112600 692300 492000
2022-02-03 8879000 33650 45590 54320 903600 26123000 2195000 5988000 702500 562300 719700 136300 696300 64240 29280 394900 130500 5093000 724000 589800 3293000 78100 113300 701600 494400
2022-02-04 8968000 33780 46260 55040 912100 26334000 2221000 6008000 708700 563600 725100 137100 700200 64460 29280 394900 131100 5172000 731700 592400 3326000 78830 114300 711000 496800
2022-02-05 9055000 33890 46770 55040 920200 26525000 2245000 6030000 708700 564700 730700 137800 702800 65310 29320 394900 131500 5199000 739600 594200 3360000 79510 115100 720400 499200

Confirmed count average forecast Latin America (bold black line in graphs) 2022-01-30 to 2022-02-05

DateArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-01-29 8313614 32486 43481 50487 847180 25256198 2107612 5855858 682480 552831 691898 133262 688326 59450 28875 391874 123047 4916143 692634 570469 3160732 73162 110741 653853 481375
2022-01-30 8344000 32720 44070 50460 852900 25421000 2130000 5878000 683300 553500 692300 134700 689800 59980 28990 391900 123900 4978000 701100 573200 3188000 73590 111200 664200 483800
2022-01-31 8457000 33120 44510 51710 863400 25539000 2150000 5900000 684800 557800 695600 135100 690400 60340 29120 392100 125200 5003000 705200 588400 3205000 74770 111500 676300 485800
2022-02-01 8574000 33420 45190 52880 872000 25732000 2168000 5919000 695000 561500 699200 135400 693100 60830 29140 394200 126200 5043000 710500 591000 3228000 75710 112100 688100 487800
2022-02-02 8679000 33660 45950 53760 880300 25936000 2187000 5939000 700000 564800 707500 135700 696300 61380 29180 394300 127100 5076000 721300 594900 3255000 76480 112800 699800 490600
2022-02-03 8798000 33880 46610 54640 890400 26141000 2208000 5965000 705400 569800 711900 135900 699400 62200 29370 394600 127900 5113000 730100 599800 3284000 77420 113600 712900 492800
2022-02-04 8926000 34080 47170 55480 898600 26355000 2231000 5990000 711100 575200 723700 136400 702700 62950 29450 394800 128700 5192000 741600 602600 3323000 78270 114600 726300 495000
2022-02-05 9045000 34270 47650 55610 905700 26544000 2252000 6018000 712300 579700 727100 136900 705200 64030 29510 394800 129700 5226000 746900 603400 3354000 78940 115400 738100 497300

Further information

  • We believe these forecasts fill a useful gap in the short run. They give an indication of what is likely to happen in the next few days, removing some aspect of surprise. Moreover, a noticeable drop in comparison to the extrapolations could be an indication that the implemented policies are having some impact. It is difficult to understand exponential growth. We hope that these forecasts may help to convince viewers to adhere to the policies implemented by their respective governments, and keep all arguments factual and measured.
  • We use the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering. This is updated daily, but we tend to update our forecasts only every other day.
    US state data as of 2020-03-28 is courtesy of the New York Times.
  • We can only provide forecasts of what is measured. If confirmed cases are an underestimate of actual cases, then our forecasts will also be underestimates. No other epidemiological data is used. Data definition and collection differs between countries and may change over time.
  • We will update the methodology as we learn what is happening in the next few days or weeks. Once the number of cases levels off, there is no need to provide these forecasts anymore.
  • Countries where the counts are very low or stable have been omitted.
  • The graphs have dates on the horizontal axis (yyyy-mm-dd) and cumulative counts on the vertical axis. They show
    1. bold dark grey line (with circles): observed counts (Johns Hopkins CSSE);
    2. many light grey lines (with open circles): forecasts using different model settings and starting up to four periods back;
    3. red line (with open circles): single forecasts path using default model settings;
    4. black line (with crosses): average of all forecasts, recentered on the last observation;
    5. thin green lines: some indication of uncertainty around the red forecasts, but we do not know how reliable that is.
    Both the red line forecasts and the black lines are also given in the tables above. These forecasts differ, we are currently inclined to use the average forecasts.
  • The forecasts are constructed as follows:
    1. An overall `trend' is extracted by taking a window of the data at a time. In each window we draw `straight lines' which are selected using an automatic econometric procedure (`machine learning'). All straight lines are collected and averaged, giving the trend.
    2. Forecasts are made using the estimated trend, but we note that this must be done carefully, because simply extrapolating the flexible insample trend would lead to wildly fluctuating forecast. We use the `Cardt' method, which has been found to work well in other settings.
    3. Residuals from the trend are also forecast, and combined with trend forecasts into an overall forecast.
  • Scenario forecasts are constructed very differently: smooth versions of the Chinese experience are matched at different lag lengths with the path of each country. This probably works best from the peak, or the slowdown just before (but we include it for the UK nonetheless).
  • The forecast evaluation shows past forecasts, together with the outcomes (in the grey line with circles).
  • EU-BS is Estonia, Latvia, and Lithuania together.
  • This paper describes the methodology and gives further references. Also available as Nuffield Economics Discussion Paper 2020-W06. Still preliminary is the documentation of the medium term forecasts.

Recent changes and notes

[2021-04-29]The `legacy' download for areas of England is stuck at April 26, so we switched to the newer downloads. The results now include Scotland, Wales, and Northern Ireland. The map, however, only shows England.
[2021-01-07]Slideshow of forecasts, errors, and actuals 2020-06-30 to 2021-01-02: how England lost the battle.
[2020-10-27]Statistical short-term forecasting of the COVID-19 Pandemic (Jurgen Doornik, Jennie Castle, and David Hendry) is now published at the Journal of Clinical Immunology and Immunotherapy. open access
[2020-10-11]Short-term forecasting of the coronavirus pandemic (Jurgen Doornik, Jennie Castle, and David Hendry) is now in press at the International Journal of Forecasting. open access
[2020-10-10]Removed forecasts from the Chinese scenarios, while investigating possibility to use own history from the first wave.
Added information on the previous peak (if present) to the peak tables.
Local forecasts for England: now dropping last four observations.
[2020-07-01] Modified the short-term model to allow for (slowly changing) seasonality. Many countries show clear seasonality after the initial period, likely caused by institutional factors regarding data collection. This seasonality was also getting in the way of peak detection. As a consequence estimates of the peak date may have changed for countries with strong seasonality.
Added forecasts of cumulative confirmed cases for lower tier local authorities of England. The data is available from 2020-07-02 including all tests (pillar one and two). Only authorities with more than 5 cases in the previous week are included.
[2020-06-29] Tables in April included the world, but not the world as we know it (double counting China and the US). So removed the world from those old tables.
Why short-term forecasts can be better than models for predicting how pandemics evolve just appeared at The Conversation.
Thursday 2 July webinar at the FGV EESP - São Paolo School of Economics. This starts at 16:00 UK time (UTC+01:00) and streamed here.
[2020-06-24] Research presentation on short-term COVID-19 forecasting on 26 June (14:00 UK time) at the Quarterly Forecasting Forum of the IIF UK Chapter.
[2020-06-06] Removed Brazil from yesterday's forecasts (only; last observation 2020-06-05).
[2020-06-04] Data issues with confirmed cases for France.
Added an appendix to the short term paper with further forecast comparisons for European and Latin American countries.
Both Sweden and Iran have lost their peak in confirmed cases. For Sweden the previous peak was on 24 April (daily peak of 656 cases), for Iran it was on 31 March (peak of 3116). For Iran this looks like a second wave, with increasing daily counts for the last four weeks. For Sweden this is a sudden jump in confirmed cases in the last two days, compared to a fairly steady weekly pattern over the previous six weeks.
[2020-05-20] Problem with UK confirmed cases: negative daily count. This makes the forecasts temporarily unreliable.
Updated the second paper.
[2020-05-18] Minor fixes to the improved version of scenario forecasting, backported to 2020-05-13.
[2020-05-13] We now omit countries with fewer than 200 confirmed cases in the last week (25 for deaths).
The short-term paper has some small updates, including further comparisons with other models.
Data for Ecuador are not reliable enough for forecasting.
Switched to an improved version of scenario forecasting.
[2020-05-06] The New York Times is in the process of redefining its US state data. Unfortunately, at the moment only the last observation has changed (e.g New York deaths jumped from 19645 on 2020-05-05 to 25956 a day later). This means the data is currently useless; however it does bring it close to the Johns Hopkins/CSSE count (25626 on 2020-05-06). The aggregate US count is based on JH/CSSE so unaffected. We now use Johns Hopkins/CSSE US state data, including all states with sufficient counts. So the new forecasts cannot be compared to those previously.
A minor change is that we show the graph without scenario forecast if no peak has been detected yet.
[2020-04-29] See our blog entry at the International Institute of Forecasters.
US history of death counts revised in Johns Hopkins/CSSE data.
UK death counts have been revised to include the deaths in care homes. In the Johns Hopkins/CSSE data set, which we use, the entire history has been revised. So forecasts made up to 2020-04-29 cannot be compared to later outcomes. In the ECDC data set only the last observation has changed, causing a jump in the series.
[2020-04-27] Our short-term COVID-19 forecasting paper is now available as Nuffield Economics Discussion Paper 2020-W06.
A small adjustment has been made to the scenario forecast methodology, and will be documented shortly.
[2020-04-24] A summary of our work on short-term COVID-19 forecasting appeared as a voxeu.
[2020-04-17] Bird and Nielsen look into nowcasting death counts in England.
[2020-04-16] Added scenario forecasts to all graphs now. This would now be the preferred forecast for most.
This is the first time with a peak in confirmed UK cases (also for deaths, but this is uncertain because it is at the same date).
[2020-04-10] Updated documentation with better description of short-term estimates and peak determination.
[2020-04-09] Added table with estimated peak dates (if happened) and dates to and since the peak. Note that this can be a local peak, and subsequent re-acceleration (or data revisions) can result in a new peak later.
[2020-04-08] Minor correction to peak estimates. Added table with scenario forecasts.
[2020-04-06] Added a post hoc estimate of the peak number of cases. This needs at least three confirmed observations (four for deaths) after the event. It is based on the averaged smooth trend, and can change later or be a local peak. It is marked with a vertical line with the date label, or a date with left arrow in the bottom left corner of the graph. This is backported to 2020-04-04.
[2020-04-02] Now including more US States, based on New York Times data.
[2020-03-31] Scenario forecasts, based on what happened in China earlier this year, are presented for several countries (line marked with x). Created more plausible 90% confidence bands (dotted line in same colour).
[2020-03-26] Scenario forecasts that are based on what happened in China earlier this year, only for Italy.
[2020-03-24] Our forecasts are starting to overestimate in some cases. This was always expected to happen when the increase starts to slow down. Scenario forecasts that are based on what happened in China earlier this year, but only for Italy and Spain sofar.

Initial visual evaluation of forecasts of Confirmed