COVID-19 short-term forecasts Confirmed 2021-06-01 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 2021-06-01

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-04-252021-02-1812-03 --2021-03-24 -- -- --2021-01-182021-05-012021-04-112021-04-192021-05-222021-05-242021-02-032021-03-182021-01-2005-262021-01-07 --2021-04-09 --2021-05-292021-04-092021-05-16
Peak daily increment 35203 60 106 1122 74847 1589 2092 675 1349 128 66 1356 662 16980 177 3354 8725 624 5275 1637
Days since peak 5 37 103 180 69 134 31 51 43 10 8 118 75 132 371 145 53 3 53 16
Last total 3817139 11796 4017 12819 374718 16624480 1389357 3432422 321279 294021 427690 73702 255833 17114 14565 238820 48594 2420659 7481 378828 358244 1955469 15128 24314 298006 235567
Last daily increment 35355 0 0 10 3439 78926 5011 25966 2293 1235 1653 0 1416 162 214 593 37 6917 157 731 2860 0 174 405 3503 1402
Last week 195004 199 13 35 16156 349785 44739 138321 11793 7752 6459 881 5537 558 528 3897 493 17937 157 3228 16023 18224 1408 2853 21571 8160
Previous peak date10-1910-17 -- --2021-01-2808-0406-062021-01-1509-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- --06-2708-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2232 45270 7349 18368 1226 1405 7778 420 2590 66 177 795 160 22832 155 8380 89 119 1085
Low between peaks 5479 7 19229 400 -4305 70 423 13 5 305 50 4599 1490 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-02 to 2021-06-08

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-01 3817139 374718 16624480 1389357 3432422 321279 294021 427690 73702 255833 17114 14565 238820 48594 2420659 378828 358244 1955469 15128 24314 298006 235567
2021-06-02 3832000 379700 16703000 1390000 3457000 324400 294100 429200 73830 256700 17350 14630 239600 48670 2426000 379100 360900 1969000 15340 24790 301400 236900
2021-06-03 3858000 383700 16772000 1394000 3479000 327200 295100 430800 73930 257600 17460 14630 240800 48780 2431000 379600 363400 1974000 15540 25220 303500 237900
2021-06-04 3888000 387500 16832000 1400000 3502000 329600 295900 431800 74050 258900 17510 14630 241800 48880 2435000 380100 365800 1977000 15750 25670 306100 239000
2021-06-05 3914000 391200 16903000 1405000 3525000 329600 296800 433500 74170 259700 17640 14630 242600 48960 2440000 380600 368100 1983000 15950 26140 309100 240200
2021-06-06 3938000 394900 16942000 1410000 3548000 329600 297700 434500 74290 260000 17730 14630 243400 49040 2443000 380900 370400 1986000 16160 26600 312100 241400
2021-06-07 3964000 398500 16966000 1414000 3571000 334500 298500 434800 74430 260100 17760 14630 244100 49120 2445000 381100 372600 1990000 16370 27080 315300 242600
2021-06-08 3992000 402200 17038000 1418000 3595000 336700 299400 436000 74560 261400 17890 14680 244800 49190 2449000 381800 374900 1991000 16580 27570 318600 243900

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-02 to 2021-06-08

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-01 3817139 374718 16624480 1389357 3432422 321279 294021 427690 73702 255833 17114 14565 238820 48594 2420659 378828 358244 1955469 15128 24314 298006 235567
2021-06-02 3848000 377600 16697000 1395000 3455000 323800 295100 428600 73850 256900 17290 14670 239500 48650 2425000 379300 361300 1960000 15350 24810 301300 236700
2021-06-03 3877000 380100 16766000 1402000 3474000 326200 296300 429400 73960 257800 17400 14700 240400 48720 2427000 379600 363900 1963000 15580 25340 304600 237700
2021-06-04 3907000 382700 16822000 1410000 3493000 328300 297300 429900 74090 258700 17480 14750 241100 48800 2430000 380000 366300 1965000 15810 25880 307800 238600
2021-06-05 3935000 385000 16891000 1417000 3511000 329300 298300 430700 74210 259500 17590 14800 241800 48860 2432000 380300 368500 1970000 16030 26350 311400 239500
2021-06-06 3964000 387300 16934000 1423000 3530000 330400 299300 431300 74340 259900 17700 14850 242500 48920 2434000 380400 370500 1973000 16240 26850 314700 240500
2021-06-07 3989000 389300 16967000 1428000 3547000 333900 300100 431600 74470 260200 17770 14900 243100 48980 2435000 380600 372700 1976000 16440 27300 318100 241400
2021-06-08 4017000 391900 17044000 1433000 3567000 335900 301000 432100 74600 261100 17870 14970 243800 49020 2438000 380900 375100 1980000 16650 27830 321800 242400

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