COVID-19 short-term forecasts Confirmed 2022-03-01 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 2022-03-01

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-132022-01-092022-01-192022-01-172022-01-142022-01-292022-02-112022-01-152022-01-252022-01-142022-01-152022-02-142022-02-142022-01-152022-01-172022-02-162022-01-142022-01-192021-08-192022-01-142022-01-242022-01-192022-01-182021-12-092022-01-202022-01-25
Peak daily increment 112478 997 826 814 10699 188932 34726 30553 6209 6246 8554 7522 3314 919 482 9585 1352 43483 167 10293 8637 47144 944 788 11003 2156
Days since peak 47 51 41 43 46 31 18 45 35 46 45 15 15 45 43 13 46 41 194 46 36 41 42 82 40 35
Last total 8904176 33146 55385 56773 893512 28818850 3061019 6065801 809131 574912 827760 156364 780815 62946 30342 412733 128053 5521744 18105 755853 642184 3517260 78294 128145 844400 515124
Last daily increment 3520 11 220 79 117 22279 0 1218 2203 356 0 0 3824 25 0 1521 67 13115 101 355 863 0 78 378 1938 0
Last week 35988 65 1041 323 1661 325514 139888 11494 12101 2316 7219 8578 14340 167 43 3025 312 66507 101 2946 4031 13368 359 2935 16586 2564
Previous peak date2021-06-052021-10-182021-10-262021-10-142021-06-102021-09-182021-11-132021-06-262021-09-062021-06-052021-06-292021-11-062021-08-242021-09-152021-06-082021-08-132021-08-232021-08-1105-262021-06-292021-06-082021-06-052021-09-152021-06-052021-06-062021-10-05
Previous peak daily increment 25322 184 347 370 2614 92852 2476 29569 2470 1203 1229 1526 3774 229 180 1515 759 18310 176 1107 2669 3719 485 365 3221 1476
Low between peaks 898 -2 41 -8 287 2340 968 1351 -225 163 197 5 203 28 4 -82 27 617 -35 129 -154 60 16 170 95 69

Confirmed count forecast Latin America (bold red line in graphs) 2022-03-02 to 2022-03-08

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-03-01 8904176 55385 56773 893512 28818850 3061019 6065801 809131 574912 827760 156364 780815 412733 128053 5521744 755853 642184 3517260 78294 128145 844400 515124
2022-03-02 8925000 55810 56990 894600 29071000 3092000 6067000 817000 575000 834300 156400 786200 414100 128100 5561000 756900 646000 3522000 78290 128800 851800 515700
2022-03-03 8939000 56070 57210 897700 29235000 3121000 6071000 822600 575700 844600 156400 790600 415100 128200 5583000 760900 648900 3543000 78360 129600 857200 517900
2022-03-04 8952000 56310 57340 899600 29361000 3146000 6073000 826700 576000 845300 156400 794200 415100 128200 5603000 763300 649900 3555000 78400 130300 861300 519200
2022-03-05 8959000 56490 57350 901100 29458000 3171000 6076000 827500 576300 845400 156400 797100 415100 128300 5628000 764900 650600 3562000 78440 130800 864300 520200
2022-03-06 8968000 56700 57380 902400 29486000 3188000 6078000 827500 576400 845400 156400 798000 415300 128300 5632000 766200 652900 3569000 78560 131200 866800 521100
2022-03-07 8969000 56850 57500 903500 29486000 3197000 6079000 832400 576800 849700 161300 798000 415700 128400 5632000 767200 652900 3573000 78620 131500 868600 521800
2022-03-08 8978000 57060 57550 904400 29530000 3203000 6081000 834700 577100 849700 161300 801500 416300 128400 5639000 768000 653800 3577000 78690 131900 871600 522400

Confirmed count average forecast Latin America (bold black line in graphs) 2022-03-02 to 2022-03-08

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-03-01 8904176 55385 56773 893512 28818850 3061019 6065801 809131 574912 827760 156364 780815 412733 128053 5521744 755853 642184 3517260 78294 128145 844400 515124
2022-03-02 8910000 55570 56900 894000 28921000 3079000 6067000 811300 575100 827200 157700 784800 414000 128100 5551000 756900 643700 3520000 78350 128600 847700 515800
2022-03-03 8918000 55730 57090 894800 29019000 3110000 6068000 814900 575300 833700 157800 788700 415400 128100 5566000 759200 645600 3528000 78440 129300 851500 517000
2022-03-04 8926000 55900 57210 895400 29113000 3139000 6069000 817900 575500 834500 158000 792000 415800 128200 5582000 760700 646000 3533000 78520 129900 855100 518000
2022-03-05 8931000 56040 57260 895900 29187000 3167000 6071000 818100 575600 835000 158100 794700 416000 128200 5605000 761800 646500 3538000 78580 130300 858000 518700
2022-03-06 8935000 56190 57300 896400 29216000 3192000 6072000 818700 575700 835800 158700 795800 416100 128200 5609000 762800 648600 3541000 78610 130700 860100 519400
2022-03-07 8938000 56330 57550 896800 29250000 3213000 6073000 825500 575900 841700 161400 796500 416500 128300 5613000 763300 649200 3544000 78720 131100 862200 520100
2022-03-08 8948000 56510 57690 897200 29338000 3226000 6074000 829200 576100 843000 161400 800300 416800 128300 5618000 764600 650700 3547000 78780 131400 865900 520700

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