COVID-19 short-term forecasts Confirmed 2022-02-04 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 2022-02-04

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-142022-01-092022-01-192022-01-172022-01-07 -- --2022-01-15 --2022-01-122022-01-142022-01-292022-01-072022-01-162022-01-172021-08-132022-01-112022-01-272021-08-192022-01-142022-01-312022-01-272022-01-142021-12-092022-01-25 --
Peak daily increment 109822 1022 811 768 9932 29726 6171 14442 4575 2198 889 475 1499 1328 42054 167 9634 8142 47568 857 788 11064
Days since peak 21 26 16 18 28 20 23 21 6 28 19 18 175 24 8 169 21 4 8 21 57 10
Last total 8555379 32680 47124 53544 867071 26326454 2296712 5943783 721971 560037 732038 135109 705614 61108 29593 391874 125517 5106048 17709 721479 598170 3331290 75252 113898 710874 492678
Last daily increment 40094 0 618 346 0 218560 38707 13390 6222 1101 0 0 3304 432 270 0 267 78178 0 4308 0 22597 394 581 10363 1662
Last week 241765 194 3643 3057 19891 1070256 189100 87925 39491 7206 40140 1847 17288 1658 718 0 2470 189905 59 28845 27701 170558 2090 3157 57021 11303
Previous peak date2021-06-052021-10-182021-10-262021-10-142021-06-102021-06-162021-06-122021-06-262021-09-062021-06-052021-07-292021-11-062021-08-242021-09-182021-06-232021-02-032021-08-232021-08-1205-262021-06-292021-06-082021-06-052021-09-152021-06-052021-06-062021-10-05
Previous peak daily increment 25321 184 347 370 2614 72652 6997 29569 2553 1203 3070 1526 3774 232 153 1308 759 18191 176 1107 2669 3719 485 365 3221 1476
Low between peaks 898 -2 41 -8 287 1351 163 175 10 203 31 3 551 27 617 -35 129 -154 -1464 16 170 95

Confirmed count forecast Latin America (bold red line in graphs) 2022-02-05 to 2022-02-11

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-02-04 8555379 47124 53544 867071 26326454 2296712 5943783 721971 560037 732038 135109 705614 61108 29593 125517 5106048 721479 598170 3331290 75252 113898 710874 492678
2022-02-05 8618000 47500 54460 872300 26477000 2334000 5958000 725100 563100 745800 135600 707500 61750 29590 125800 5165000 729000 604700 3410000 75740 115200 721100 494700
2022-02-06 8640000 47840 54730 890300 26565000 2367000 5977000 726200 564700 746600 135600 708000 62060 29630 126400 5194000 741800 604700 3477000 77210 115700 731400 495900
2022-02-07 8673000 48160 55320 902000 26659000 2397000 5993000 734900 566100 771400 135600 708200 62160 29870 126800 5207000 751800 620600 3495000 78210 116000 741500 497500
2022-02-08 8718000 48760 56720 910500 26818000 2424000 6008000 743700 567500 773900 135600 711500 62430 29920 127100 5244000 760300 624700 3519000 78950 116500 751300 499100
2022-02-09 8762000 49370 57550 918300 27003000 2454000 6022000 750200 569400 780400 135700 714800 62710 29940 127400 5259000 768400 628200 3555000 79630 117200 761200 500800
2022-02-10 8797000 49920 58000 924400 27256000 2488000 6036000 756800 570500 780400 135700 718800 63020 30030 127700 5297000 775800 632800 3593000 80190 117800 771100 502500
2022-02-11 8839000 50490 58390 929900 27465000 2525000 6049000 763500 572200 785300 135900 721900 63360 30210 127900 5371000 783000 633200 3619000 80690 118400 781000 504300

Confirmed count average forecast Latin America (bold black line in graphs) 2022-02-05 to 2022-02-11

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-02-04 8555379 47124 53544 867071 26326454 2296712 5943783 721971 560037 732038 135109 705614 61108 29593 125517 5106048 721479 598170 3331290 75252 113898 710874 492678
2022-02-05 8578000 47650 53470 871500 26522000 2334000 5958000 722800 561100 737600 136200 708200 61410 29620 125700 5144000 724100 600100 3380000 75640 114800 719700 494800
2022-02-06 8590000 48150 53620 879200 26636000 2363000 5972000 723400 561900 744200 136500 709000 61610 29640 126200 5169000 732800 601900 3438000 76150 115200 728200 496500
2022-02-07 8626000 48580 54150 885400 26740000 2392000 5985000 731600 562700 753500 136800 709400 61760 29910 126500 5182000 734600 613300 3464000 76750 115500 735900 498300
2022-02-08 8677000 49280 55460 890800 26913000 2416000 5997000 741300 563500 760000 137200 712600 61930 29950 126800 5219000 742300 618100 3495000 77220 116000 746500 500100
2022-02-09 8726000 50060 56390 895800 27125000 2444000 6010000 747500 564600 767000 137700 715800 62100 29960 127000 5241000 751400 623800 3534000 77730 116700 757800 501900
2022-02-10 8774000 50770 57160 900600 27367000 2476000 6023000 754600 565900 773300 137900 719100 62290 30120 127200 5279000 762600 629500 3592000 78120 117400 768100 503700
2022-02-11 8819000 51520 57910 905300 27609000 2509000 6036000 762300 567000 780100 138200 722800 62460 30190 127400 5363000 774100 633300 3631000 78480 118300 779800 505500

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