COVID-19 short-term forecasts Confirmed 2021-06-21 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 2021-06-21

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-212021-04-252021-02-1812-032021-06-012021-06-182021-06-04 --2021-05-172021-01-182021-04-232021-04-112021-04-192021-05-262021-06-082021-02-032021-03-182021-01-2005-262021-06-102021-05-262021-04-092021-06-082021-05-212021-04-092021-05-16
Peak daily increment 31708 60 106 1122 2805 74948 7186 2464 1589 2035 675 1349 133 185 1356 662 16980 177 757 2906 8725 260 537 5275 1698
Days since peak 31 57 123 200 20 3 17 35 154 59 71 63 26 13 138 95 152 391 11 26 73 13 31 73 36
Last total 4277395 12364 4045 13039 422811 17966831 1522223 3968405 354095 317645 446633 77484 280854 19144 17061 254194 49712 2478551 7696 394241 407721 2030611 20141 30767 356382 262038
Last daily increment 8606 69 2 35 764 38903 5205 23239 3465 858 192 384 347 48 202 319 44 1268 0 514 1501 3882 116 148 1517 1298
Last week 104653 139 7 50 11134 433610 34984 166353 8783 7254 7259 1187 7124 614 399 5076 333 18950 0 5068 11572 23134 1316 1458 12767 7922
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 --2021-01-07 --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2113 45270 7348 17013 1226 1405 7778 420 2590 66 177 795 160 22832 3354 8380 89 119 1085
Low between peaks 5479 7 704 19229 1343 308 400 -4305 70 423 13 5 305 50 4599 294 1490 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-22 to 2021-06-28

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-21 4277395 422811 17966831 1522223 3968405 354095 317645 446633 77484 280854 19144 17061 254194 49712 2478551 394241 407721 2030611 20141 30767 356382 262038
2021-06-22 4303000 428100 18015000 1531000 3988000 356300 318700 446700 77480 282300 19240 17410 254900 49760 2481000 394700 410300 2032000 20370 30850 358900 263300
2021-06-23 4324000 430500 18090000 1537000 4011000 358500 320200 448100 77530 283600 19380 17510 255300 49840 2484000 395400 412600 2035000 20690 31050 364500 264600
2021-06-24 4341000 433800 18156000 1545000 4038000 360500 321300 449400 77650 285100 19470 17680 255800 49910 2488000 396100 414600 2044000 20960 31210 368600 265900
2021-06-25 4356000 434100 18229000 1552000 4064000 362200 322400 450900 77780 286400 19570 17720 256400 49960 2491000 396900 416700 2047000 21210 31340 372000 267100
2021-06-26 4366000 437700 18295000 1558000 4090000 362300 323900 452000 77930 287700 19700 17750 257100 50020 2491000 397600 418700 2048000 21450 31460 375200 268400
2021-06-27 4366000 438500 18334000 1564000 4116000 362300 324800 452800 78090 288100 19790 17770 257800 50070 2495000 398200 419500 2051000 21680 31570 378000 269600
2021-06-28 4378000 439500 18367000 1569000 4138000 365400 325500 453000 78250 288400 19820 18000 258500 50120 2497000 398600 420900 2054000 21900 31670 380600 270800

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-22 to 2021-06-28

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-21 4277395 422811 17966831 1522223 3968405 354095 317645 446633 77484 280854 19144 17061 254194 49712 2478551 394241 407721 2030611 20141 30767 356382 262038
2021-06-22 4294000 425400 18037000 1527000 3993000 355500 318600 447000 77980 282000 19230 17200 254800 49750 2482000 394900 409600 2033000 20350 30980 358700 263200
2021-06-23 4316000 427400 18121000 1532000 4018000 357100 319800 447800 78110 283300 19340 17310 255400 49790 2485000 395500 411800 2035000 20600 31240 361900 264300
2021-06-24 4336000 429900 18190000 1539000 4046000 358600 320800 448400 78260 284600 19430 17440 256100 49830 2488000 396000 413800 2042000 20840 31480 364700 265300
2021-06-25 4355000 430700 18267000 1546000 4072000 359900 321800 449200 78410 285800 19510 17520 256800 49870 2491000 396500 415800 2045000 21070 31710 367300 266300
2021-06-26 4375000 433200 18338000 1553000 4099000 360600 323000 449700 78530 286900 19610 17600 257500 49900 2493000 397000 417800 2046000 21300 31940 370300 267300
2021-06-27 4386000 434500 18370000 1560000 4124000 361100 324000 450100 78680 287600 19690 17680 258100 49930 2496000 397400 419100 2049000 21520 32170 372700 268200
2021-06-28 4405000 435800 18402000 1566000 4148000 363400 324900 450200 78800 288200 19740 17870 258800 49960 2498000 397700 420800 2051000 21750 32400 375100 269100

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