COVID-19 short-term forecasts Confirmed 2022-02-17 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 2022-02-17

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-152022-01-092022-01-192022-01-172022-01-162022-01-282022-02-112022-01-152022-01-252022-01-152022-01-182022-02-142022-02-102022-01-162022-01-17 --2022-01-162022-01-192021-08-192022-01-142022-01-172022-01-182022-01-182021-12-092022-01-202022-01-25
Peak daily increment 112866 997 869 895 10940 174616 37272 30785 6243 6256 8797 8207 3233 939 463 1369 44117 167 10293 8299 49223 1007 788 10949 2067
Days since peak 33 39 29 31 32 20 6 33 23 33 30 3 7 32 31 32 29 182 34 31 30 30 70 28 23
Last total 8799858 33005 52909 55975 887089 27940119 2747552 6035143 779323 570889 808925 147786 749257 62537 30162 404764 127377 5366405 17895 747916 632444 3474965 77549 122093 800833 508968
Last daily increment 16650 0 272 172 0 120123 37698 4013 4005 253 8605 0 4503 72 41 0 83 21565 0 1221 1726 18176 99 822 5517 926
Last week 82918 102 2029 792 6198 640783 201733 27152 22230 2994 27455 12677 19280 381 223 12890 645 140136 104 8146 11736 50071 673 2867 34873 7382
Previous peak date2021-06-052021-10-182021-10-262021-10-142021-06-102021-09-182021-11-132021-06-262021-09-062021-06-052021-06-292021-11-062021-08-242021-09-182021-06-232021-08-162021-08-232021-08-1105-262021-06-292021-06-082021-06-052021-09-152021-06-052021-06-062021-10-05
Previous peak daily increment 25322 184 347 370 2614 92851 2476 29569 2470 1203 1229 1526 3774 232 153 1672 759 18309 176 1107 2668 3718 485 365 3221 1476
Low between peaks 898 -2 41 -8 287 2340 968 1351 -225 163 197 5 203 31 3 27 617 -35 129 -154 60 16 170 95 69

Confirmed count forecast Latin America (bold red line in graphs) 2022-02-18 to 2022-02-24

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-02-17 8799858 52909 55975 887089 27940119 2747552 6035143 779323 570889 808925 147786 749257 62537 30162 404764 127377 5366405 747916 632444 3474965 77549 122093 800833 508968
2022-02-18 8849000 53030 57070 889600 28256000 2780000 6046000 792300 571200 812800 147900 752400 62670 30340 406600 127600 5423000 750300 635300 3486000 77840 123200 806500 510300
2022-02-19 8871000 53310 57460 897400 28467000 2807000 6054000 793900 571700 819600 148400 755600 63250 30400 408700 128000 5474000 761700 644000 3540000 78610 124000 812600 513100
2022-02-20 8875000 53530 57630 902100 28552000 2836000 6060000 794700 572100 825200 148700 756300 63620 30450 411000 128200 5482000 768800 649800 3573000 79150 124400 818500 515200
2022-02-21 8886000 53720 58100 905200 28627000 2865000 6065000 805200 572400 829900 149100 756800 63880 30530 413300 128400 5490000 773500 654100 3596000 79550 124900 824000 516800
2022-02-22 8897000 53890 58460 907900 28779000 2895000 6071000 811400 572700 834400 149900 760500 64110 30610 415000 128700 5504000 777700 658100 3616000 79920 125400 829400 518400
2022-02-23 8903000 54050 58570 909900 28917000 2925000 6075000 816400 573000 838600 150200 765100 64280 30630 422200 128800 5527000 780600 661300 3630000 80220 125600 834600 519800
2022-02-24 8921000 54200 58790 911600 29060000 2955000 6080000 821000 573200 842600 150600 769300 64440 30680 422200 129000 5547000 783100 664200 3643000 80500 126300 839900 521100

Confirmed count average forecast Latin America (bold black line in graphs) 2022-02-18 to 2022-02-24

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-02-17 8799858 52909 55975 887089 27940119 2747552 6035143 779323 570889 808925 147786 749257 62537 30162 404764 127377 5366405 747916 632444 3474965 77549 122093 800833 508968
2022-02-18 8815000 53120 56100 890100 28087000 2786000 6040000 784400 571200 813000 148100 753500 62670 30220 407700 127600 5414000 750500 632900 3493000 77710 122900 807000 510200
2022-02-19 8827000 53530 56200 893400 28228000 2822000 6045000 784600 571800 816600 148800 757200 62870 30230 408600 127900 5462000 754300 636500 3523000 77920 123700 812800 511800
2022-02-20 8833000 53810 56270 895800 28272000 2859000 6049000 784700 572300 819800 149200 758200 63020 30260 409700 128100 5474000 757000 639700 3545000 78080 124000 817300 513100
2022-02-21 8843000 54030 56520 897700 28314000 2892000 6053000 792300 572700 825300 152400 758700 63130 30330 410700 128300 5484000 759000 643200 3561000 78260 124500 822000 514400
2022-02-22 8856000 54630 56880 899400 28470000 2919000 6056000 798300 573100 828200 153300 762400 63230 30410 411700 128400 5503000 760900 647000 3576000 78390 125000 827800 515600
2022-02-23 8869000 55170 57160 900900 28642000 2953000 6060000 803900 573700 831000 153700 766700 63330 30450 414100 128500 5536000 762500 649800 3590000 78550 125400 833900 516800
2022-02-24 8887000 55670 57380 902400 28810000 2992000 6065000 809500 574200 834900 154100 771100 63420 30490 414600 128600 5553000 764000 653400 3605000 78730 126200 839900 518000

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