COVID-19 short-term forecasts Confirmed 2021-11-01 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 2021-11-01

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-10-18 --2021-10-142021-06-012021-09-182021-06-042021-06-262021-09-062021-01-182021-07-292021-09-092021-08-242021-09-182021-06-082021-08-132021-08-232021-08-182021-10-262021-07-032021-10-182021-04-092021-09-152021-05-242021-04-092021-05-16
Peak daily increment 32513 147 360 2893 112363 7273 29826 2471 1589 3111 498 3774 232 179 1515 763 18308 210 1075 138 8725 486 529 5275 1698
Days since peak 158 14 18 153 44 150 128 56 287 95 53 69 44 146 80 70 75 6 121 14 206 47 161 206 169
Last total 5289945 22407 18023 27149 513810 21814693 1696786 5003977 560563 382476 515859 113422 601657 35657 23960 375381 89123 3807211 16422 472664 461086 2202189 49019 57419 394053 407866
Last daily increment 1138 56 260 351 226 3838 1738 1590 865 809 0 0 85 109 0 0 109 0 0 0 80 393 0 90 154 715
Last week 6945 148 1990 997 3340 65709 12178 9963 2641 5091 200 0 5240 487 341 598 643 22763 0 780 271 5137 471 1406 1468 6607
Previous peak date10-192021-07-262021-02-1712-032021-01-222021-03-2406-062021-01-162021-05-1707-2604-242021-04-1107-182021-06-2406-042021-02-032021-03-1810-05 --2021-01-072021-06-0208-022021-06-0809-19 --09-08
Previous peak daily increment 14378 172 92 1122 2113 74845 7348 17013 2464 1405 7778 675 2590 194 177 1356 662 22832 3354 2948 8380 262 119 1085
Low between peaks 5479 34 2 704 16636 1343 3454 1145 400 -4305 33 423 58 5 553 42 2145 294 19 1490 77 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-11-02 to 2021-11-08

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-11-01 5289945 18023 27149 513810 21814693 1696786 5003977 560563 382476 515859 601657 35657 23960 375381 89123 3807211 472664 461086 2202189 49019 57419 394053 407866
2021-11-02 5291000 18070 27270 514000 21827000 1698000 5005000 562000 382900 516800 603300 35700 24120 376400 89240 3811000 473000 461100 2203000 49140 57580 394300 409000
2021-11-03 5292000 18290 27490 514900 21842000 1700000 5007000 563200 383600 517000 605000 35790 24240 376600 89470 3818000 473200 461200 2204000 49670 57710 394600 410400
2021-11-04 5293000 18530 27710 515000 21856000 1702000 5008000 563900 384600 517200 606100 35880 24280 377000 89650 3827000 473300 461200 2204000 50000 58000 394800 411600
2021-11-05 5294000 18780 27820 515500 21867000 1705000 5010000 564600 385300 517300 607500 35940 24280 377000 89790 3831000 473500 461200 2205000 50240 58260 395100 412600
2021-11-06 5295000 19030 27820 516200 21877000 1707000 5011000 564900 386000 517400 608500 36040 24360 377300 89920 3835000 473600 461200 2206000 50460 58490 395300 413600
2021-11-07 5295000 19290 27820 516300 21882000 1709000 5013000 564900 386600 517700 608500 36040 24360 377300 90040 3835000 473700 461300 2207000 50620 58700 395500 414600
2021-11-08 5296000 19560 28100 516500 21886000 1710000 5014000 565600 387300 517800 608600 36110 24410 377300 90160 3836000 473800 461300 2207000 50760 58770 395700 415600

Confirmed count average forecast Latin America (bold black line in graphs) 2021-11-02 to 2021-11-08

DateArgentinaBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-11-01 5289945 18023 27149 513810 21814693 1696786 5003977 560563 382476 515859 601657 35657 23960 375381 89123 3807211 472664 461086 2202189 49019 57419 394053 407866
2021-11-02 5291000 18310 27320 514100 21826000 1698000 5005000 561200 383200 515900 602600 35720 24010 375800 89190 3809000 472800 461100 2203000 49130 57590 394200 408700
2021-11-03 5292000 18600 27570 514700 21842000 1700000 5006000 562000 384000 516000 603700 35790 24100 375900 89270 3812000 472900 461200 2204000 49360 57760 394400 409500
2021-11-04 5293000 18890 27800 514800 21856000 1702000 5007000 562500 384800 516100 604500 35860 24150 376200 89350 3818000 473000 461200 2204000 49540 58010 394500 410200
2021-11-05 5294000 19180 27950 515200 21868000 1704000 5008000 563000 385600 516200 605400 35910 24180 376300 89420 3821000 473100 461200 2205000 49690 58240 394700 410800
2021-11-06 5295000 19480 28040 515500 21878000 1706000 5009000 563500 386300 516200 606300 35990 24250 376400 89500 3824000 473200 461200 2206000 49820 58430 394800 411300
2021-11-07 5296000 19790 28130 515600 21884000 1708000 5010000 563800 387000 516500 606700 36040 24280 376500 89580 3826000 473300 461200 2207000 49950 58620 394900 411900
2021-11-08 5297000 20090 28410 515700 21888000 1709000 5011000 564500 387700 516700 607000 36080 24370 376700 89660 3828000 473400 461200 2207000 50070 58750 395000 412400

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