COVID-19 short-term forecasts Confirmed 2021-06-15 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 2021-06-15

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-262021-04-252021-02-1812-032021-06-012021-03-24 -- --2021-05-162021-01-182021-04-232021-04-112021-04-192021-05-132021-06-082021-02-032021-03-182021-01-2005-262021-01-072021-06-022021-04-092021-06-092021-05-192021-04-092021-05-16
Peak daily increment 31573 60 106 1122 2835 74846 2525 1589 2035 675 1349 131 279 1356 662 16980 177 3354 2932 8725 273 518 5275 1648
Days since peak 20 51 117 194 14 83 30 148 53 65 57 33 7 132 89 146 385 159 13 67 6 27 67 30
Last total 4172742 12225 4038 12989 411677 17533221 1487239 3802052 345312 310391 439374 76297 273730 18530 16662 249118 49379 2459601 7696 389173 396149 2007477 18825 29309 343615 254116
Last daily increment 27260 26 1 18 2571 80609 4576 24452 1708 914 235 946 1740 84 101 1003 23 4250 34 848 2667 3852 226 327 2797 1233
Last week 134214 198 6 73 18702 410344 41471 168571 9305 5963 5504 1314 8068 591 661 5651 289 17735 34 4661 13918 19544 1512 1776 17210 7352
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2113 45270 7790 17013 1226 1405 7778 420 2590 66 177 795 160 22832 8380 89 119 1085
Low between peaks 5479 7 704 19228 308 400 -4305 70 423 13 5 305 50 4599 1490 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-16 to 2021-06-22

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-15 4172742 411677 17533221 1487239 3802052 345312 310391 439374 76297 273730 18530 16662 249118 49379 2459601 389173 396149 2007477 18825 29309 343615 254116
2021-06-16 4216000 413500 17585000 1496000 3827000 348000 312200 440400 76300 274400 18700 16800 249800 49430 2462000 389300 400200 2014000 19040 29660 348800 255400
2021-06-17 4252000 418700 17658000 1504000 3849000 350500 313500 442400 76600 275400 18840 16810 250100 49530 2465000 389800 403400 2020000 19200 30360 352800 256800
2021-06-18 4282000 419700 17718000 1511000 3871000 352500 314700 443500 76680 276700 18920 16870 250600 49610 2467000 390500 406300 2023000 19390 30900 356200 258000
2021-06-19 4303000 423600 17785000 1519000 3894000 352500 315800 444500 76680 278000 19040 16950 251200 49680 2470000 391200 408500 2025000 19580 31330 359700 259300
2021-06-20 4319000 425000 17820000 1526000 3918000 352700 316700 445400 76680 278300 19110 17040 251800 49740 2471000 391800 410300 2029000 19780 31750 362200 260500
2021-06-21 4336000 426400 17852000 1532000 3942000 356300 317400 445500 76720 278500 19150 17150 252400 49790 2472000 392200 412300 2030000 19980 32120 364100 261800
2021-06-22 4363000 429800 17924000 1537000 3966000 358000 318300 446100 77540 280000 19240 17260 253100 49840 2477000 392900 415000 2032000 20190 32470 367000 263000

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-16 to 2021-06-22

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-15 4172742 411677 17533221 1487239 3802052 345312 310391 439374 76297 273730 18530 16662 249118 49379 2459601 389173 396149 2007477 18825 29309 343615 254116
2021-06-16 4199000 413000 17617000 1492000 3828000 347100 311600 439900 76470 275000 18650 16830 249800 49420 2463000 389700 398800 2011000 19060 29640 346600 255300
2021-06-17 4226000 417100 17696000 1500000 3855000 348900 312900 440800 76670 276100 18760 16940 250300 49470 2466000 390100 401500 2016000 19320 30020 349900 256400
2021-06-18 4251000 418100 17760000 1507000 3882000 350600 314100 441400 76780 277300 18840 17060 250800 49520 2469000 390600 404000 2019000 19560 30360 353000 257500
2021-06-19 4272000 421200 17828000 1514000 3908000 351300 315200 441900 76850 278500 18930 17170 251400 49560 2472000 391000 406200 2021000 19810 30680 356200 258500
2021-06-20 4292000 422400 17865000 1520000 3933000 352100 316300 442400 76920 279000 19010 17290 251900 49600 2474000 391400 408100 2024000 20050 30990 359100 259500
2021-06-21 4315000 423300 17894000 1526000 3958000 354600 317400 442500 77010 279700 19070 17410 252500 49640 2475000 391600 410500 2026000 20290 31300 361700 260500
2021-06-22 4342000 426400 17955000 1530000 3982000 356200 318500 442900 77410 280700 19160 17530 253100 49660 2479000 392000 413200 2028000 20540 31600 365100 261500

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