COVID-19 short-term forecasts Confirmed 2021-10-12 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 2021-10-12

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-07-26 --2021-10-042021-06-012021-09-182021-06-042021-06-262021-09-062021-01-182021-07-292021-09-092021-08-242021-09-112021-06-082021-08-132021-08-232021-08-18 --2021-07-032021-06-022021-04-092021-09-142021-05-242021-04-09 --
Peak daily increment 32513 172 192 2893 117665 7273 29826 2471 1589 3111 505 3774 234 179 1515 763 18308 1075 2948 8725 487 529 5275
Days since peak 138 78 8 133 24 130 108 36 267 75 33 49 31 126 60 50 55 101 132 186 28 141 186
Last total 5267339 21580 11474 22187 504601 21590097 1663992 4974400 547914 366711 512071 107664 581498 33823 22675 370968 86456 3732429 15737 469440 460244 2185355 44873 52999 390234 384668
Last daily increment 1064 0 342 0 480 7359 609 1075 1319 520 27 0 1724 75 61 706 72 7187 603 250 26 679 567 152 119 0
Last week 4120 122 1651 294 2051 73130 5548 8553 6878 3862 754 329 9395 872 321 1938 1195 40505 603 1115 131 4172 2157 1186 729 6835
Previous peak date10-1910-172021-02-1812-032021-01-222021-03-2406-062021-01-162021-05-1707-2604-242021-04-1107-182021-06-2406-042021-02-032021-03-1810-05 --2021-01-07 --08-022021-06-0809-19 --09-08
Previous peak daily increment 14378 104 87 1122 2113 74845 7348 17013 2464 1405 7778 675 2590 194 177 1356 662 22832 3354 8380 262 119 1085
Low between peaks 5479 7 2 704 16394 1343 3454 1145 400 -4305 33 423 58 5 553 42 2145 294 1490 77 4

Confirmed count forecast Latin America (bold red line in graphs) 2021-10-13 to 2021-10-19

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-10-12 5267339 11474 22187 504601 21590097 1663992 4974400 547914 366711 512071 107664 581498 33823 22675 370968 86456 3732429 15737 469440 2185355 44873 52999 390234 384668
2021-10-13 5271000 11990 22730 504900 21613000 1664000 4976000 551200 367400 512800 109300 586300 34210 22740 372000 86640 3742000 15990 469700 2187000 45140 53190 390300 386700
2021-10-14 5273000 12390 23080 504900 21634000 1665000 4978000 553900 368100 513200 109400 589800 34460 22740 372400 86890 3756000 16030 470000 2187000 45640 53440 390400 387900
2021-10-15 5275000 12800 23170 505200 21650000 1665000 4979000 555800 368700 513400 109400 592600 34540 22740 373100 87110 3763000 16060 470200 2188000 46030 53610 390600 389100
2021-10-16 5276000 13210 23180 505500 21662000 1666000 4981000 555900 369300 513500 109400 594700 34870 22770 373200 87310 3764000 16240 470400 2189000 46360 53790 390700 390400
2021-10-17 5277000 13630 23190 505700 21676000 1667000 4982000 555900 369800 513900 109400 595600 35020 22810 373400 87500 3773000 16580 470600 2190000 46670 53970 390700 391600
2021-10-18 5278000 14070 23290 506100 21680000 1668000 4983000 559200 370300 514300 109700 595600 35020 22860 374200 87680 3774000 16670 470600 2190000 46960 54070 390800 392800
2021-10-19 5279000 14520 23370 506500 21689000 1668000 4984000 560300 370900 514400 109700 597500 35100 22910 375000 87860 3780000 16670 470900 2191000 47230 54230 390900 394100

Confirmed count average forecast Latin America (bold black line in graphs) 2021-10-13 to 2021-10-19

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-10-12 5267339 11474 22187 504601 21590097 1663992 4974400 547914 366711 512071 107664 581498 33823 22675 370968 86456 3732429 15737 469440 2185355 44873 52999 390234 384668
2021-10-13 5268000 11760 22300 505000 21604000 1665000 4976000 549200 367400 512300 108500 583800 34010 22760 371400 86580 3739000 15780 469600 2186000 45170 53190 390300 385700
2021-10-14 5269000 12010 22540 505000 21623000 1666000 4977000 550900 368100 512400 108800 586100 34180 22810 371700 86710 3748000 15790 469800 2187000 45470 53400 390400 386800
2021-10-15 5270000 12270 22640 505300 21638000 1667000 4979000 552200 368700 512500 109000 588100 34270 22860 372200 86870 3754000 15790 469900 2187000 45740 53560 390500 387900
2021-10-16 5271000 12520 22700 505400 21652000 1667000 4980000 552700 369400 512600 109100 589800 34480 22900 372500 87040 3757000 15810 470000 2188000 45990 53720 390500 388900
2021-10-17 5272000 12790 22760 505600 21668000 1668000 4981000 553400 369900 512800 109300 591100 34620 22960 372800 87180 3764000 15860 470100 2189000 46230 53890 390500 389800
2021-10-18 5272000 13050 22930 505800 21674000 1669000 4982000 555600 370500 513100 109600 592100 34690 23010 373600 87310 3768000 15870 470200 2189000 46460 54000 390600 390800
2021-10-19 5273000 13330 23150 506000 21687000 1669000 4984000 556900 371200 513200 109700 594100 34820 23070 374200 87430 3773000 16240 470400 2190000 46700 54170 390600 391700

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