COVID-19 short-term forecasts Confirmed 2021-08-09 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 2021-08-09

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-27 --2021-02-1812-032021-06-012021-03-242021-06-042021-06-262021-05-172021-01-182021-07-292021-04-112021-08-062021-06-242021-06-082021-08-062021-03-182021-01-2005-262021-07-032021-06-022021-04-102021-06-052021-05-242021-04-092021-05-16
Peak daily increment 32516 105 1113 2893 74830 7273 29826 2460 1589 2969 674 3405 193 179 1525 660 16926 145 1075 2953 8699 261 529 5270 1699
Days since peak 74 172 249 69 138 66 44 84 203 11 120 3 46 62 3 144 201 440 37 68 121 65 77 122 85
Last total 5029075 15794 4480 14499 478671 20177757 1624316 4843007 420462 344625 491831 88371 391118 22992 20389 305936 55140 2978330 9853 442818 455389 2125848 26046 40361 382607 312931
Last daily increment 10180 257 9 61 975 12085 953 4023 3785 130 0 0 604 10 63 0 281 6513 0 523 269 503 44 128 101 816
Last week 67195 783 58 215 3406 191940 5859 35028 9339 1775 4129 873 18071 349 82 5364 1597 97921 0 5074 2022 9196 497 1199 754 4479
Previous peak date10-1910-16 -- --2021-01-2208-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-042021-02-0309-2210-05 --2021-01-07 --08-0208-1309-19 --09-08
Previous peak daily increment 14376 107 2113 45351 7360 17013 1225 1408 7756 420 2699 66 177 1356 160 23278 3350 8364 89 119 1086
Low between peaks 5479 704 19228 1343 3453 262 400 -4346 71 424 13 5 553 50 4595 294 1487 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-08-10 to 2021-08-16

DateArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-08-09 5029075 15794 14499 478671 20177757 1624316 4843007 420462 344625 491831 88371 391118 22992 305936 55140 2978330 442818 455389 2125848 26046 40361 382607 312931
2021-08-10 5046000 15940 14530 480000 20213000 1626000 4849000 420500 345000 492800 89120 392200 23100 308200 55350 2990000 443900 455800 2127000 26150 40510 382900 313900
2021-08-11 5060000 16060 14560 481100 20255000 1627000 4853000 421600 345500 494100 89360 394700 23140 310800 55350 3003000 445000 456200 2129000 26220 40720 383200 315300
2021-08-12 5073000 16190 14590 482100 20293000 1628000 4857000 423100 345800 495800 89880 397200 23260 311900 55350 3021000 445900 456600 2131000 26310 40950 383400 316400
2021-08-13 5086000 16310 14620 482200 20331000 1630000 4861000 424600 346100 496900 90050 399400 23320 313600 55350 3035000 446300 456900 2132000 26430 41040 383500 317300
2021-08-14 5096000 16430 14650 483000 20366000 1631000 4866000 424600 346400 497400 90050 402100 23420 313600 55410 3053000 447700 457100 2133000 26490 41440 383600 318200
2021-08-15 5101000 16540 14680 483300 20379000 1632000 4868000 424600 346700 498000 90050 402100 23460 313600 55560 3059000 448500 457300 2135000 26550 41560 383700 319100
2021-08-16 5109000 16660 14710 483900 20390000 1632000 4872000 427100 346900 498000 90080 402800 23460 314600 55730 3062000 449000 457600 2135000 26580 41670 383800 319900

Confirmed count average forecast Latin America (bold black line in graphs) 2021-08-10 to 2021-08-16

DateArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-08-09 5029075 15794 14499 478671 20177757 1624316 4843007 420462 344625 491831 88371 391118 22992 305936 55140 2978330 442818 455389 2125848 26046 40361 382607 312931
2021-08-10 5041000 15940 14540 479200 20206000 1625000 4847000 423100 344900 492200 88580 393100 23060 306400 55370 2994000 443600 455600 2127000 26120 40520 382700 313600
2021-08-11 5054000 16070 14570 479800 20248000 1626000 4853000 424300 345200 492800 88840 396000 23100 308000 55440 3010000 444400 455900 2129000 26190 40720 382900 314500
2021-08-12 5066000 16140 14600 480300 20286000 1627000 4858000 425600 345500 493500 89120 398800 23170 309100 55540 3028000 445000 456100 2130000 26260 40930 383000 315100
2021-08-13 5077000 16300 14640 480400 20330000 1628000 4863000 426800 345800 493900 89350 401400 23220 310400 55680 3043000 445300 456400 2131000 26330 41060 383200 315800
2021-08-14 5088000 16400 14670 481000 20364000 1629000 4870000 427200 346100 494200 89560 404100 23300 311200 55820 3060000 446200 456500 2132000 26390 41310 383300 316300
2021-08-15 5096000 16480 14690 481300 20381000 1630000 4875000 427600 346400 494400 89770 405800 23330 312100 56000 3070000 446700 456700 2133000 26460 41500 383500 316900
2021-08-16 5107000 16610 14720 481700 20392000 1631000 4881000 428400 346700 494400 89980 407500 23360 313400 56100 3078000 447100 456900 2134000 26510 41640 383600 317400

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