COVID-19 short-term forecasts Confirmed 2020-08-04 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:
    [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.

Peak increase in estimated trend of Confirmed in Latin America 2020-08-04

ArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
Peak date --07-17 --06-06 --07-27 --04-24 --07-1806-0606-2808-0105-2607-13 -- -- --
Peak daily increment 1555 7346 573 7778 2537 179 795 6976 184 1075
Days from 100 to peak 108 83 128 38 99 31 91 137 7 116
Days from peak/2 to peak 83 64 120 18 66 32 75 114 8 109
Last total 213535 83361 2801921 362962 334979 19837 74295 87963 18262 52365 7511 44299 449961 3902 69424 5852 439890 21438
Last daily increment 6792 1515 51603 1469 7129 435 1178 922 419 823 0 505 6148 230 968 128 6790 684
Last week 34539 9827 249656 11387 58924 3037 8113 4770 2421 4760 133 3355 41512 230 6155 986 39207 4280
Days since peak 18 59 8 102 17 59 37 3 70 22

Confirmed count forecast Latin America (bold red line in graphs) 2020-08-05 to 2020-08-11

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-08-04 213535 83361 2801921 362962 334979 19837 74295 87963 18262 52365 44299 449961 3902 69424 5852 439890 21438
2020-08-05 221600 84880 2913000 365600 341300 20380 75490 88890 18890 53060 44950 455100 3902 70420 5974 449400 22340
2020-08-06 230000 86360 3016000 367500 347500 20920 77140 89800 19410 53810 45600 462700 3902 71390 6101 459900 23200
2020-08-07 238500 87850 3115000 369600 353700 21460 78720 90680 19970 54420 46250 470500 3902 72370 6220 470300 24130
2020-08-08 247500 89320 3214000 371300 359800 22000 80360 91550 20550 55290 46910 478700 3902 73330 6342 481300 25100
2020-08-09 256900 90800 3292000 373100 366000 22540 81420 92420 21110 55380 47560 483400 3902 74300 6467 492700 25990
2020-08-10 266600 92290 3366000 374800 372200 23100 82410 93290 21690 55380 48230 488000 3902 75280 6593 504300 26690
2020-08-11 276600 93800 3463000 376300 378600 23660 83460 94160 22290 56290 48890 494400 3902 76260 6720 516300 27600

Confirmed count average forecast Latin America (bold black line in graphs) 2020-08-05 to 2020-08-11

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-08-04 213535 83361 2801921 362962 334979 19837 74295 87963 18262 52365 44299 449961 3902 69424 5852 439890 21438
2020-08-05 220500 84710 2891000 364400 343100 20330 75510 88660 18740 53100 44870 455800 3872 70300 5998 447300 22190
2020-08-06 228300 86280 2990000 366400 352900 20900 77050 89460 19280 54080 45510 462900 3880 71240 6228 457300 23050
2020-08-07 236400 87880 3086000 368500 362900 21460 78560 90270 19830 54980 46160 470300 3882 72210 6389 469300 23940
2020-08-08 244900 89630 3178000 370400 373100 22030 80140 91060 20400 56020 46810 477900 3886 73190 6552 479700 24900
2020-08-09 253600 91220 3252000 372400 382900 22650 81520 91860 20990 56720 47470 483700 3898 74160 6697 495400 25790
2020-08-10 262700 92940 3325000 374300 393500 23240 82910 92660 21610 57370 48150 489600 3904 75170 6799 506800 26710
2020-08-11 272200 94630 3423000 376000 404500 23860 84240 93460 22250 58520 48830 496600 4125 76130 6955 518700 27680

Confirmed count scenario forecast (bold purple line in graphs) 2020-08-05 to 2020-08-13

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-08-04 213535 83361 2801921 362962 334979 19837 74295 87963 18262 52365 44299 449961 3902 69424 5852 439890 21438
2020-08-05 220400 84400 2865000 365100 344800 20410 76050 88700 18690 53340 44860 458900 3902 70170 6036 445700 22230
2020-08-06 228600 85750 2924000 366900 354400 20890 77760 89420 19200 54010 45320 466200 3902 70920 6240 452500 23120
2020-08-07 232400 87000 2961000 368800 360900 21390 78880 90160 19500 54650 45730 471100 3902 71640 6342 457700 23710
2020-08-08 238200 88080 3005000 370200 369900 21850 80100 90780 19890 55340 46140 477300 3902 72310 6501 463200 24240
2020-08-09 242900 88950 3018000 371300 376800 22310 81610 91430 20270 55950 46490 482100 3902 73030 6603 468600 24750
2020-08-10 248300 89970 3039000 372400 383600 22730 82560 92020 20580 56560 46810 485300 3902 73560 6719 473200 25120
2020-08-11 252600 90930 3061000 373400 389800 23130 83780 92610 20880 57140 47110 489100 3902 74130 6854 478600 25710
2020-08-12 258400 91960 3071000 373800 398700 23520 85150 93210 21230 57660 47350 491400 3902 74670 7017 482200 26240
2020-08-13 263300 92870 3090000 374100 405600 23880 86180 93790 21470 58090 47440 494800 3902 75220 7141 485600 26700

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

[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