COVID-19 short-term forecasts Confirmed 2021-06-24 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 2021-06-24

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-04-252021-02-1812-032021-05-27 --2021-06-04 --2021-05-172021-01-182021-04-232021-04-112021-04-19 -- --2021-02-032021-03-182021-01-2005-262021-01-072021-06-022021-04-092021-06-082021-05-242021-04-09 --
Peak daily increment 32803 60 106 1122 2866 7162 2464 1589 2035 675 1349 1356 662 16980 177 3354 2913 8725 259 550 5275
Days since peak 28 60 126 203 28 20 38 157 62 74 66 141 98 155 394 168 22 76 16 31 76
Last total 4350564 12407 4057 13104 429178 18243483 1531872 4060013 359266 320136 449483 77484 286708 19565 17603 256818 49841 2493087 7920 397727 413457 2036449 20723 31429 361994 265642
Last daily increment 24463 0 5 21 2430 73602 3463 32997 1743 882 376 0 1967 331 0 1155 46 5340 0 1201 1842 2843 174 222 1747 2270
Last week 107801 165 17 100 11983 442021 26871 171399 8636 6105 5088 787 8299 728 744 5669 277 21346 224 5561 10065 13270 1147 1246 10616 7502
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-01-1509-1407-2604-2408-0507-1809-2106-0206-2809-2210-05 -- -- --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2113 45270 7348 18367 1226 1405 7778 420 2590 77 175 795 160 22832 8380 89 119 1085
Low between peaks 5479 7 704 1343 308 400 -4305 70 423 305 50 4599 1490 1 4

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-25 to 2021-07-01

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-24 4350564 429178 18243483 1531872 4060013 359266 320136 449483 77484 286708 19565 17603 256818 49841 2493087 7920 397727 413457 2036449 20723 31429 361994 265642
2021-06-25 4389000 432200 18297000 1537000 4087000 361800 321600 450900 77780 287800 19600 17730 257600 49890 2495000 7920 398200 415700 2045000 21110 32040 364300 267100
2021-06-26 4413000 436800 18360000 1543000 4110000 362100 323300 451900 77960 289100 19670 17870 258000 49960 2495000 7921 398800 417300 2046000 21370 32510 369700 268700
2021-06-27 4427000 438200 18393000 1547000 4131000 362300 324300 452800 78120 289500 19750 18000 258600 50010 2498000 7922 399200 418200 2050000 21640 32750 373600 270100
2021-06-28 4444000 439500 18424000 1551000 4150000 365800 325100 452900 78280 289700 19840 18110 259300 50060 2499000 7922 399600 419600 2053000 21790 33000 376700 271500
2021-06-29 4466000 441900 18497000 1555000 4167000 367400 325900 453400 78430 291300 19920 18230 259900 50110 2503000 8101 400500 421400 2053000 21970 33160 379600 272900
2021-06-30 4488000 443700 18599000 1556000 4184000 369200 326800 455100 78590 293100 20000 18350 260700 50160 2507000 8101 401500 423300 2056000 22200 33370 382100 274200
2021-07-01 4510000 446500 18671000 1560000 4199000 370900 327700 455900 78750 294900 20090 18470 261400 50200 2511000 8101 402400 425100 2061000 22380 33630 384500 275600

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-25 to 2021-07-01

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-24 4350564 429178 18243483 1531872 4060013 359266 320136 449483 77484 286708 19565 17603 256818 49841 2493087 7920 397727 413457 2036449 20723 31429 361994 265642
2021-06-25 4374000 430000 18327000 1536000 4090000 360800 321100 450400 77600 288300 19700 17740 257700 49890 2497000 7933 398600 415200 2039000 20940 31750 364300 266800
2021-06-26 4390000 433200 18397000 1542000 4117000 361300 322400 451000 77760 289600 19800 17840 258300 49930 2499000 7934 399200 416800 2040000 21160 32010 367200 267700
2021-06-27 4402000 434300 18432000 1547000 4144000 361700 323300 451400 77930 290400 19890 17940 259000 49960 2502000 7936 399600 418000 2043000 21390 32230 369600 268600
2021-06-28 4418000 435100 18465000 1552000 4169000 363800 324200 451500 78100 291000 19980 18080 259700 50000 2504000 7939 399900 419300 2045000 21560 32450 371800 269500
2021-06-29 4438000 437200 18533000 1556000 4195000 365000 325100 451800 78260 292300 20070 18220 260500 50020 2508000 8091 400400 421100 2046000 21750 32640 374000 270300
2021-06-30 4455000 438800 18622000 1560000 4221000 366300 326100 452500 78430 293600 20150 18350 261200 50050 2511000 8092 400900 423000 2048000 21980 32850 376200 271100
2021-07-01 4476000 441700 18692000 1566000 4248000 367600 327100 453100 78600 294900 20240 18470 261900 50070 2514000 8092 401400 424700 2054000 22190 33060 378300 271900

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