COVID-19 short-term forecasts Confirmed 2021-12-07 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 2021-12-07

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-10-182021-10-262021-10-142021-06-012021-09-182021-06-042021-06-262021-09-062021-01-182021-07-292021-11-062021-08-242021-09-182021-06-082021-08-132021-08-232021-08-112021-10-192021-07-032021-11-152021-04-102021-09-15 --2021-10-282021-05-16
Peak daily increment 32516 170 347 370 2893 109124 7273 29826 2470 1589 3070 1535 3774 232 179 1515 759 18312 141 1075 151 8699 485 232 1699
Days since peak 194 50 42 54 189 80 186 164 92 323 131 31 105 80 182 116 106 118 49 157 22 241 83 40 205
Last total 5346242 22846 26306 30888 546155 22157726 1775212 5084466 567706 409002 529456 119803 620435 38261 25638 378251 91554 3902015 17328 479231 463479 2246633 51052 76601 401340 435461
Last daily increment 3089 7 106 64 1489 10250 1164 1704 92 254 107 0 544 44 0 0 18 0 74 178 52 3218 0 666 237 543
Last week 13613 44 877 371 7508 51854 10938 12649 747 1528 2586 0 1999 310 287 392 282 10797 74 1241 358 8791 170 4582 1374 2947
Previous peak date10-192021-07-262021-02-1812-032021-01-222021-03-2406-062021-01-162021-05-1707-2604-242021-04-1107-182021-06-2406-042021-02-032021-03-1810-0505-262021-01-072021-06-0208-022021-06-052021-05-242021-04-0909-08
Previous peak daily increment 14376 172 105 1113 2113 74829 7360 17013 2460 1408 7756 674 2699 193 177 1356 660 23277 145 3350 2953 8364 261 529 5270 1086
Low between peaks 5479 28 1 2 704 16748 1343 3453 1145 400 -4346 124 424 58 5 553 42 2152 4 294 22 1487 77 95 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-12-08 to 2021-12-14

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2021-12-07 5346242 26306 30888 546155 22157726 1775212 5084466 567706 409002 529456 620435 38261 25638 378251 91554 3902015 479231 463479 2246633 76601 401340 435461
2021-12-08 5346000 26460 31010 546200 22167000 1779000 5087000 567900 409200 529900 621300 38360 25710 378300 91600 3908000 479500 463600 2250000 76760 401500 436200
2021-12-09 5347000 26770 31130 547200 22179000 1782000 5090000 568200 409400 529900 621800 38450 25750 378300 91710 3911000 479700 463700 2252000 77140 401700 437400
2021-12-10 5349000 27000 31200 548000 22189000 1785000 5092000 568400 409700 530000 622400 38510 25810 378400 91790 3915000 479900 463700 2254000 77820 401900 438200
2021-12-11 5350000 27190 31210 549200 22197000 1787000 5095000 568400 410000 530300 622900 38550 25860 378400 91850 3915000 480000 463700 2257000 78340 402100 438900
2021-12-12 5351000 27370 31210 549800 22201000 1790000 5097000 568400 410300 530500 623200 38610 25920 378400 91910 3918000 480300 463700 2258000 78890 402200 439600
2021-12-13 5353000 27530 31350 550700 22204000 1792000 5098000 568500 410500 532900 623200 38640 25980 378400 91970 3919000 480300 463900 2259000 79530 402400 440200
2021-12-14 5356000 27670 31430 551900 22213000 1793000 5100000 568700 410700 532900 623700 38690 26040 378400 92020 3919000 480500 464000 2261000 80150 402600 440800

Confirmed count average forecast Latin America (bold black line in graphs) 2021-12-08 to 2021-12-14

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2021-12-07 5346242 26306 30888 546155 22157726 1775212 5084466 567706 409002 529456 620435 38261 25638 378251 91554 3902015 479231 463479 2246633 76601 401340 435461
2021-12-08 5348000 26460 30960 547100 22169000 1777000 5086000 567800 409100 529800 620900 38320 25700 378300 91590 3906000 479400 463500 2248000 77240 401500 435900
2021-12-09 5350000 26650 31050 547900 22181000 1779000 5089000 568000 409300 529800 621100 38370 25720 378300 91630 3908000 479600 463600 2250000 77820 401700 436400
2021-12-10 5352000 26830 31120 548500 22192000 1781000 5091000 568000 409400 529800 621500 38410 25770 378400 91660 3912000 479700 463600 2251000 78500 401800 436800
2021-12-11 5353000 26990 31150 549200 22200000 1783000 5093000 568100 409600 529900 621800 38440 25810 378400 91690 3913000 479800 463600 2252000 79060 401900 437200
2021-12-12 5355000 27150 31190 549600 22204000 1785000 5095000 568100 409800 530000 622100 38480 25840 378500 91720 3916000 479900 463600 2253000 79640 401900 437500
2021-12-13 5356000 27310 31300 550100 22207000 1787000 5097000 568200 409900 531000 622200 38510 25900 378500 91750 3918000 480000 463800 2254000 80170 402000 437900
2021-12-14 5358000 27460 31380 550600 22215000 1788000 5099000 568300 410100 531100 622600 38540 25930 378500 91770 3919000 480100 463800 2256000 80690 402100 438200

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