COVID-19 short-term forecasts Confirmed 2020-08-15 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:
    [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 2020-08-15

ArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruSurinameVenezuela
Peak date -- --08-0606-06 -- --07-2604-2408-1007-1806-0606-2807-3105-26 -- -- -- -- --
Peak daily increment 45361 7347 1365 7778 422 2649 179 795 6655 184
Days from 100 to peak 147 83 126 38 123 99 31 91 135 7
Days from peak/2 to peak 115 64 119 18 112 65 33 75 113 8
Last total 289100 99146 3317096 383902 456689 27737 85545 100688 22619 62313 7831 49979 517714 4115 80665 9381 516296 2961 32607
Last daily increment 6663 1196 90653 1791 11578 806 1057 1279 305 885 21 512 6345 0 1263 359 0 123 1226
Last week 42601 9147 281674 10846 69208 4451 5813 6229 2196 5708 197 2525 37436 213 6173 2474 38272 570 6802
Days since peak 9 70 20 113 5 28 70 48 15 81

Confirmed count forecast Latin America (bold red line in graphs) 2020-08-16 to 2020-08-22

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruSurinameVenezuela
2020-08-15 289100 99146 3317096 383902 456689 27737 85545 100688 22619 62313 49979 517714 4115 80665 9381 516296 2961 32607
2020-08-16 296800 101300 3345000 386200 474200 28690 86620 101700 22920 62740 50490 524200 4192 83420 9610 534800 3059 33840
2020-08-17 305300 103600 3365000 388000 489200 29670 87660 102600 23210 63020 50990 529000 4193 85520 9840 545600 3169 35120
2020-08-18 313800 105900 3413000 389400 505700 30680 88720 103600 23510 64040 51490 535200 4452 87650 10080 557300 3263 36430
2020-08-19 322400 108300 3470000 390900 521700 31720 89760 104500 23800 65120 51980 540700 4452 89750 10330 565700 3393 37790
2020-08-20 330400 110800 3527000 392700 538600 32800 90810 105500 24090 66190 52480 547600 4452 92010 10590 578000 3506 39200
2020-08-21 338600 113400 3545000 394500 555000 33910 91870 106400 24390 67210 52980 553300 4452 94280 10850 598100 3625 40680
2020-08-22 344800 116000 3620000 396300 573000 35050 92930 107300 24690 68190 53480 559800 4452 96420 11120 604700 3809 42210

Confirmed count average forecast Latin America (bold black line in graphs) 2020-08-16 to 2020-08-22

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruSurinameVenezuela
2020-08-15 289100 99146 3317096 383902 456689 27737 85545 100688 22619 62313 49979 517714 4115 80665 9381 516296 2961 32607
2020-08-16 295300 101000 3333000 385700 470700 28330 86170 101200 22960 62690 50400 522300 4127 82180 9500 529400 3037 33650
2020-08-17 302200 103500 3348000 387500 486500 29200 87060 102200 23340 63110 50860 527500 4140 83900 9780 542700 3139 34880
2020-08-18 309200 106100 3391000 388800 503100 30110 87930 103100 23710 63950 51310 533500 4370 85650 10130 556100 3241 36190
2020-08-19 316200 108800 3450000 390300 520000 31050 88870 104000 24100 64900 51770 539100 4373 87400 10590 568600 3361 37570
2020-08-20 323400 111500 3509000 392100 537600 32020 89950 104900 24480 65840 52240 545600 4375 89260 11020 583100 3459 38970
2020-08-21 330700 114400 3545000 394100 555600 33020 90910 105800 24870 66800 52710 551800 4386 91230 11430 599800 3586 40440
2020-08-22 337800 117200 3606000 396000 575000 34050 91880 106700 25290 67750 53180 558400 4398 93190 11770 612700 3738 41950

Confirmed count scenario forecast (bold purple line in graphs) 2020-08-16 to 2020-08-24

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoNicaraguaPanamaParaguayPeruSurinameVenezuela
2020-08-15 289100 99146 3317096 383902 456689 27737 85545 100688 22619 62313 49979 517714 4115 80665 9381 516296 2961 32607
2020-08-16 295600 101500 3359000 385400 468900 28280 86360 101600 23180 62790 50330 528700 4250 82320 9600 531400 3047 33580
2020-08-17 301700 103100 3414000 386700 479600 28780 87060 102600 23630 63350 50630 536800 4274 83950 9840 540800 3133 34520
2020-08-18 307900 104700 3479000 387700 490700 29240 87810 103800 24080 63980 50940 544100 4313 85370 10250 550800 3224 35540
2020-08-19 313300 106000 3519000 388600 500700 29810 88470 105000 24480 64460 51240 551400 4353 86770 10610 558200 3300 36370
2020-08-20 318500 107200 3559000 389000 509200 30420 89100 106200 24720 64990 51500 553500 4357 87790 10970 567400 3363 37180
2020-08-21 323900 108700 3616000 389600 518100 31010 89620 107000 25170 65520 51770 562100 4357 89030 11170 574100 3439 37970
2020-08-22 328000 110200 3655000 390000 526200 31440 90200 107900 25480 65820 52040 567800 4357 90190 11370 581200 3499 38650
2020-08-23 333100 111600 3709000 390100 534600 31930 90680 108500 25850 66270 52260 573700 4357 91210 11590 589200 3549 39370
2020-08-24 337500 112800 3748000 390200 541500 32360 91170 109800 26150 66590 52480 578600 4357 92240 11760 596500 3624 40020

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