COVID-19 short-term forecasts Confirmed 2021-11-28 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 2021-11-28

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-10-182021-10-282021-10-142021-06-012021-09-182021-06-042021-06-262021-09-062021-01-182021-07-292021-11-062021-08-242021-09-182021-06-082021-08-132021-08-232021-08-182021-09-282021-07-032021-11-152021-04-092021-09-152021-11-252021-10-282021-05-16
Peak daily increment 32513 188 357 377 2893 112363 7273 29826 2471 1589 3111 1612 3774 232 179 1515 763 18308 162 1075 228 8725 486 730 240 1698
Days since peak 185 41 31 45 180 71 177 155 83 314 122 22 96 71 173 107 97 102 61 148 13 233 74 3 31 196
Last total 5326448 22734 24923 30165 536472 22080906 1759405 5065373 566560 406803 524432 119803 617610 37773 25027 377859 91169 3882792 17152 477306 462605 2234075 50760 70136 399348 430696
Last daily increment 888 0 154 0 1357 4043 2328 2196 0 292 0 884 115 66 0 0 47 2956 0 0 0 1326 19 456 167 650
Last week 10459 69 979 483 6103 61036 14100 15118 608 3365 79 1762 3660 417 77 332 362 18514 129 1177 274 8958 229 3843 1358 4682
Previous peak date10-192021-07-262021-02-1812-032021-01-222021-03-2406-062021-01-162021-05-1707-2604-242021-04-1107-182021-06-2406-042021-02-032021-03-1810-0505-262021-01-072021-06-0208-022021-06-082021-05-242021-04-0909-08
Previous peak daily increment 14378 172 106 1122 2113 74844 7348 17013 2464 1405 7778 675 2590 194 177 1356 662 22831 177 3354 2948 8380 262 529 5275 1085
Low between peaks 5479 24 1 2 704 16636 1343 3454 1145 400 -4305 33 423 58 5 553 42 2145 2 294 22 1490 77 177 95 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-11-29 to 2021-12-05

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-11-28 5326448 24923 30165 536472 22080906 1759405 5065373 566560 406803 119803 617610 37773 377859 91169 3882792 477306 462605 2234075 50760 70136 399348 430696
2021-11-29 5327000 25120 30360 536900 22087000 1762000 5068000 567100 407500 120100 618000 37880 378000 91240 3884000 477400 462700 2234000 50810 70140 399400 431500
2021-11-30 5328000 25600 30550 537500 22097000 1764000 5070000 567400 408100 120400 618900 37960 378100 91330 3885000 477600 462700 2235000 50920 70250 399600 432400
2021-12-01 5329000 25940 30710 537700 22111000 1766000 5072000 567600 408400 120700 619700 38060 378200 91410 3888000 477800 462800 2236000 51000 70560 399800 433200
2021-12-02 5331000 26200 30810 539500 22122000 1768000 5075000 567800 409000 120900 620300 38150 378200 91490 3895000 478000 462800 2238000 51070 70680 400000 434000
2021-12-03 5333000 26450 30900 540400 22134000 1771000 5077000 568000 409700 121000 621000 38220 378400 91560 3897000 478100 462900 2239000 51130 71020 400200 434800
2021-12-04 5334000 26670 30900 540600 22144000 1773000 5080000 568000 410100 121600 621500 38250 378400 91620 3898000 478400 462900 2240000 51180 71360 400400 435500
2021-12-05 5335000 26870 30900 541600 22148000 1775000 5082000 568000 410500 121900 621600 38320 378400 91690 3901000 478400 462900 2241000 51230 71800 400600 436300

Confirmed count average forecast Latin America (bold black line in graphs) 2021-11-29 to 2021-12-05

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-11-28 5326448 24923 30165 536472 22080906 1759405 5065373 566560 406803 119803 617610 37773 377859 91169 3882792 477306 462605 2234075 50760 70136 399348 430696
2021-11-29 5328000 25110 30320 537300 22084000 1762000 5068000 566800 407200 120200 617800 37830 377900 91230 3885000 477400 462700 2235000 50800 70620 399500 431400
2021-11-30 5329000 25360 30470 537900 22093000 1763000 5070000 567100 408000 120300 618300 37880 378000 91270 3886000 477500 462700 2236000 50850 71150 399600 431900
2021-12-01 5330000 25580 30600 538100 22105000 1765000 5072000 567200 408600 120400 618800 37950 378100 91300 3889000 477600 462700 2237000 50900 71680 399700 432300
2021-12-02 5332000 25780 30700 539200 22116000 1768000 5075000 567400 409300 120500 619200 38010 378100 91340 3894000 477700 462800 2239000 50940 72110 399800 432700
2021-12-03 5333000 25970 30800 539600 22128000 1770000 5077000 567600 410100 120500 619700 38060 378200 91370 3896000 477800 462800 2240000 50970 72660 399900 433100
2021-12-04 5335000 26150 30860 539900 22138000 1773000 5079000 567700 410900 120700 620200 38100 378200 91410 3898000 477900 462800 2241000 51010 73150 400000 433500
2021-12-05 5335000 26340 30900 540300 22143000 1775000 5081000 567800 411600 120800 620400 38160 378200 91440 3900000 478000 462800 2242000 51040 73660 400000 433900

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