COVID-19 short-term forecasts Confirmed 2021-12-27 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 2021-12-27

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-12-152021-10-182021-10-262021-10-142021-11-232021-09-18 --2021-06-262021-09-062021-11-132021-12-202021-11-062021-08-242021-09-182021-06-082021-12-032021-08-232021-08-112021-10-19 --2021-11-15 --2021-09-152021-12-102021-10-282021-10-05
Peak daily increment 5489 170 347 370 911 92852 29569 2470 1083 621 1526 3774 232 179 122 759 18310 141 163 485 749 232 1476
Days since peak 12 70 62 74 34 100 184 112 44 7 51 125 100 202 24 126 138 69 42 103 17 60 83
Last total 5480305 23539 27724 31503 577808 22250218 1801033 5127971 568860 414704 542341 121741 625257 39119 25974 379276 92705 3951003 17442 488341 465564 2279299 51683 90004 407981 443332
Last daily increment 20263 0 51 0 1206 6952 753 3281 0 478 2219 0 91 12 24 203 0 803 0 574 536 492 105 175 600 0
Last week 75925 404 506 181 8841 26275 7247 17183 0 2682 4123 118 1086 193 51 591 578 16901 0 4703 771 11584 185 3408 2745 1395
Previous peak date2021-06-052021-07-262021-07-1112-032021-06-102021-06-16 -- --2021-05-172021-06-052021-07-292021-04-11 --2021-06-2406-042021-08-13 -- --05-262021-07-062021-06-08 --2021-06-052021-06-052021-06-06 --
Previous peak daily increment 25322 172 36 1113 2614 72652 2460 1203 3070 674 193 177 1515 145 1068 2669 261 365 3221
Low between peaks 898 28 7 2 287 17910 1145 245 175 124 58 5 42 4 22 77 170 95

Confirmed count forecast Latin America (bold red line in graphs) 2021-12-28 to 2022-01-03

DateArgentinaBahamasBarbadosBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2021-12-27 5480305 23539 27724 577808 22250218 1801033 5127971 414704 542341 625257 379276 92705 3951003 488341 465564 2279299 90004 407981 443332
2021-12-28 5499000 23560 27780 580100 22251000 1803000 5131000 415100 542500 625800 379300 92710 3951000 489100 465600 2281000 91180 408200 443800
2021-12-29 5513000 23570 27910 580100 22254000 1804000 5133000 415500 542600 626200 379300 92710 3955000 490100 465600 2282000 91830 408200 444600
2021-12-30 5530000 23590 28000 581300 22257000 1805000 5136000 415900 542800 626600 379300 92710 3958000 491000 465600 2284000 92660 408200 445200
2021-12-31 5547000 23610 28070 584400 22260000 1807000 5138000 416400 544100 626800 379300 92730 3962000 491700 465600 2285000 93520 408200 445700
2022-01-01 5560000 23620 28140 584900 22262000 1808000 5140000 416800 544100 627000 379500 92760 3965000 492900 465600 2288000 94080 408200 446100
2022-01-02 5572000 23620 28200 586100 22265000 1809000 5143000 417100 544300 627000 379500 92820 3965000 493700 465600 2289000 94520 408200 446400
2022-01-03 5585000 23650 28260 586800 22270000 1810000 5145000 417400 545800 627000 379700 92850 3966000 493800 466000 2289000 94730 408300 446700

Confirmed count average forecast Latin America (bold black line in graphs) 2021-12-28 to 2022-01-03

DateArgentinaBahamasBarbadosBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2021-12-27 5480305 23539 27724 577808 22250218 1801033 5127971 414704 542341 625257 379276 92705 3951003 488341 465564 2279299 90004 407981 443332
2021-12-28 5493000 23540 27780 580800 22255000 1802000 5131000 415100 543200 625600 379300 92770 3951000 489000 465700 2281000 90740 408400 443600
2021-12-29 5503000 23580 27850 581100 22259000 1803000 5133000 415400 543400 626000 379400 92830 3955000 489700 465700 2283000 91270 408700 444000
2021-12-30 5514000 23630 27950 582600 22262000 1804000 5135000 415700 543600 626300 379400 92880 3958000 490300 465800 2285000 92050 409000 444400
2021-12-31 5527000 23700 27990 585800 22265000 1805000 5137000 416100 544900 626600 379400 92950 3962000 490600 465800 2285000 92880 409300 444700
2022-01-01 5538000 23730 28050 586900 22267000 1807000 5139000 416400 544900 626800 379600 93020 3964000 491300 465800 2289000 93470 409600 445000
2022-01-02 5544000 23760 28080 587900 22269000 1808000 5141000 416700 545100 626800 379600 93080 3965000 491700 465900 2290000 93990 409800 445300
2022-01-03 5552000 23810 28120 588200 22272000 1809000 5143000 416900 546200 626900 379600 93130 3966000 491900 466000 2291000 94310 410100 445600

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