COVID-19 short-term forecasts Confirmed 2021-07-16 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 2021-07-16

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-04-252021-02-1812-032021-06-012021-03-242021-06-042021-07-122021-05-172021-01-182021-04-232021-04-11 --2021-06-242021-06-082021-02-032021-03-182021-01-20 --2021-07-032021-06-022021-04-102021-06-132021-05-242021-04-092021-05-16
Peak daily increment 32516 60 105 1113 2893 74829 7273 55421 2460 1589 2035 674 190 179 1356 660 16926 1067 2953 8699 264 529 5270 1699
Days since peak 50 82 148 225 45 114 42 4 60 179 84 96 22 38 163 120 177 13 44 97 33 53 98 61
Last total 4737213 13404 4241 13683 459579 19308109 1596549 4601335 389798 336693 473647 82852 330651 21351 19374 277974 50983 2642068 8767 420916 443378 2090175 24055 35679 378480 290524
Last daily increment 17261 130 11 39 0 45591 2053 17893 1500 549 925 247 2896 77 0 0 70 12420 0 1087 1171 2032 194 251 439 1162
Last week 98115 380 105 165 5984 239106 11389 129713 9316 3640 5671 1920 13340 427 154 4272 354 55347 306 6269 6754 11360 762 1102 2199 6782
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-04-2209-1407-2604-2408-0507-1809-2106-0206-2809-2210-05 --2021-01-07 --08-0208-1309-19 --09-08
Previous peak daily increment 14376 104 2113 45350 7360 17205 1225 1408 7756 420 2699 66 175 795 160 23278 3350 8364 89 119 1086
Low between peaks 5479 7 704 19228 1343 472 262 400 -4346 71 13 5 305 50 4595 294 1487 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-07-17 to 2021-07-23

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-07-16 4737213 13404 459579 19308109 1596549 4601335 389798 336693 473647 82852 330651 21351 277974 50983 2642068 8767 420916 443378 2090175 24055 35679 378480 290524
2021-07-17 4759000 13400 462700 19390000 1600000 4614000 390400 337900 475100 83010 331900 21430 278800 51030 2657000 9032 422000 444700 2094000 24190 35870 379200 291600
2021-07-18 4771000 13400 463800 19426000 1603000 4627000 390500 338800 475800 83140 332000 21470 280300 51050 2666000 9062 422800 445700 2097000 24380 36050 379600 292700
2021-07-19 4788000 13400 465100 19451000 1606000 4640000 391700 339600 476200 83320 332100 21480 281500 51090 2674000 9103 423400 446700 2099000 24540 36130 379900 293800
2021-07-20 4809000 13510 466600 19506000 1608000 4652000 395100 340200 478300 83520 334200 21530 282500 51130 2687000 9406 424300 447900 2100000 24690 36340 380400 294900
2021-07-21 4828000 13570 467200 19564000 1609000 4663000 396600 340800 479400 83720 336500 21630 283400 51180 2699000 9406 425600 449300 2103000 24830 36520 380800 295900
2021-07-22 4845000 13590 469300 19609000 1611000 4675000 398200 341300 480200 83930 339300 21680 284300 51220 2714000 9412 426800 450300 2105000 24960 36730 381100 296900
2021-07-23 4861000 13660 469500 19655000 1613000 4686000 399400 341900 481400 84150 341900 21750 285200 51270 2722000 9412 427800 451400 2107000 25100 36940 381600 297900

Confirmed count average forecast Latin America (bold black line in graphs) 2021-07-17 to 2021-07-23

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-07-16 4737213 13404 459579 19308109 1596549 4601335 389798 336693 473647 82852 330651 21351 277974 50983 2642068 8767 420916 443378 2090175 24055 35679 378480 290524
2021-07-17 4752000 13440 461300 19353000 1599000 4620000 390500 337300 474400 83060 333100 21420 278600 51030 2654000 8815 421900 444300 2092000 24170 35860 378800 291500
2021-07-18 4764000 13460 462100 19375000 1601000 4641000 391000 338000 474600 83310 334300 21480 279700 51060 2659000 8823 422400 445200 2095000 24300 36010 379000 292400
2021-07-19 4778000 13490 463100 19390000 1603000 4660000 391900 338700 474800 83510 335500 21520 280600 51090 2664000 8836 422900 446100 2096000 24400 36130 379300 293200
2021-07-20 4796000 13580 464100 19437000 1604000 4678000 394000 339300 475800 83720 337600 21580 281400 51110 2672000 9083 423500 447000 2098000 24520 36290 379700 294000
2021-07-21 4813000 13640 464900 19486000 1605000 4695000 395200 339900 476300 83920 339500 21660 282300 51140 2680000 9090 424200 448100 2100000 24660 36450 380100 294700
2021-07-22 4830000 13690 466300 19532000 1608000 4712000 396300 340500 476800 84150 341500 21720 283100 51160 2688000 9105 424900 449300 2102000 24800 36630 380500 295400
2021-07-23 4846000 13730 466800 19584000 1610000 4729000 397500 341200 477500 84350 343500 21790 283900 51180 2695000 9105 425500 450200 2103000 24940 36780 381000 296200

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