COVID-19 short-term forecasts Confirmed 2021-06-29 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 2021-06-29

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-04-252021-02-1812-03 --2021-06-252021-05-30 --2021-05-172021-01-182021-04-232021-04-112021-04-192021-06-242021-06-082021-02-032021-03-182021-01-2005-262021-01-072021-05-292021-04-092021-06-042021-05-242021-04-09 --
Peak daily increment 33205 60 106 1122 76055 7313 2464 1589 2035 675 1349 219 171 1356 662 16980 177 3354 2973 8725 259 529 5275
Days since peak 33 65 131 208 4 30 43 162 67 79 71 5 21 146 103 160 399 173 31 81 25 36 81
Last total 4447701 12586 4079 13227 437623 18513305 1553774 4213074 366161 324364 457489 78766 292674 19959 18341 262069 50080 2513164 8178 402581 421589 2048115 21519 32528 368178 270654
Last daily increment 24065 119 2 38 2055 64903 2637 25880 1857 714 1746 0 697 68 129 1738 26 5711 258 1249 1825 0 159 185 1263 1019
Last week 121600 179 27 144 10875 343424 25365 186058 8638 5110 8382 1282 7933 725 738 6406 285 25417 258 6055 9974 14509 970 1321 7931 7282
Previous peak date10-1910-17 -- --2021-01-2708-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2107 45270 7348 17013 1226 1405 7778 420 2590 66 177 795 160 22832 8380 89 119 1085
Low between peaks 5479 7 19228 1343 308 400 -4305 70 423 13 5 305 50 4599 1490 1 4

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-30 to 2021-07-06

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-29 4447701 437623 18513305 1553774 4213074 366161 324364 457489 78766 292674 19959 18341 262069 50080 2513164 8178 402581 421589 2048115 21519 32528 368178 270654
2021-06-30 4473000 439700 18626000 1555000 4231000 367900 325900 457700 78920 294400 20040 18460 263000 50130 2515000 8178 403000 422500 2053000 21660 32750 371300 271900
2021-07-01 4498000 443100 18698000 1557000 4257000 369700 327000 457800 78980 296000 20170 18540 263400 50190 2517000 8179 403700 423900 2058000 21810 33200 373400 273800
2021-07-02 4522000 445700 18773000 1560000 4284000 371400 328100 459800 79010 297900 20260 18650 264000 50240 2521000 8179 404600 425300 2063000 21950 33530 375300 275300
2021-07-03 4540000 447900 18834000 1562000 4313000 371400 329200 460600 79010 299400 20340 18750 264600 50290 2524000 8181 405400 426900 2063000 22090 33800 377300 276700
2021-07-04 4546000 450000 18867000 1565000 4340000 371500 330000 461300 79710 299900 20440 18860 265400 50340 2526000 8208 406100 428000 2066000 22220 34060 378400 278000
2021-07-05 4559000 451900 18894000 1566000 4365000 374600 330700 462200 79900 300200 20470 18970 266100 50380 2527000 8208 406700 429000 2068000 22360 34290 379100 279200
2021-07-06 4581000 453700 18958000 1569000 4388000 376200 331400 463300 80040 301200 20520 19090 267000 50430 2532000 8484 407700 430700 2068000 22490 34510 380600 280400

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-30 to 2021-07-06

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-29 4447701 437623 18513305 1553774 4213074 366161 324364 457489 78766 292674 19959 18341 262069 50080 2513164 8178 402581 421589 2048115 21519 32528 368178 270654
2021-06-30 4470000 439700 18607000 1556000 4241000 367700 325300 458800 78910 293900 20010 18470 263100 50120 2517000 8200 403400 423200 2050000 21660 32730 369700 271400
2021-07-01 4489000 441800 18675000 1560000 4268000 369000 326200 459200 79030 295300 20130 18570 263900 50160 2521000 8201 404100 424400 2054000 21820 32970 371000 272500
2021-07-02 4508000 443400 18747000 1565000 4297000 370300 327200 460300 79140 296700 20230 18670 264600 50190 2525000 8202 404700 425700 2059000 21970 33190 372200 273400
2021-07-03 4525000 445000 18807000 1569000 4326000 370800 328100 460800 79240 298000 20310 18780 265400 50220 2529000 8206 405300 427000 2059000 22120 33400 373500 274200
2021-07-04 4536000 446300 18847000 1575000 4353000 371300 329000 461200 79610 298700 20410 18890 266200 50250 2531000 8212 405700 428000 2062000 22270 33600 374600 275000
2021-07-05 4549000 447600 18876000 1579000 4378000 373300 329900 461500 79760 299300 20490 19010 267000 50280 2534000 8212 406100 429200 2064000 22410 33800 375700 275800
2021-07-06 4568000 448800 18951000 1582000 4404000 374500 330700 461800 79940 300400 20570 19120 267700 50300 2537000 8322 406600 430500 2065000 22560 34000 376800 276500

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