COVID-19 short-term forecasts Confirmed 2021-05-28 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 2021-05-28

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd) --2021-04-252021-02-1812-03 --2021-03-242021-04-09 --2021-05-172021-01-182021-04-262021-04-112021-04-19 --2021-01-232021-02-032021-03-182021-01-2005-262021-01-07 --2021-04-09 --2021-05-252021-04-092021-05-16
Peak daily increment 62 106 1122 74846 7144 2435 1589 2059 675 1349 63 1356 662 16980 177 3354 8725 649 5275 1629
Days since peak 33 99 176 65 49 11 130 32 47 39 125 114 71 128 367 141 49 3 49 12
Last total 3702422 11684 4009 12791 364570 16391930 1361381 3342567 314102 289288 423165 73246 252929 16724 14037 236451 48288 2408778 7324 376854 348184 1942054 14305 22620 282198 230147
Last daily increment 39207 62 3 2 2990 49768 8658 23374 2180 1254 836 425 1593 70 0 852 108 3006 0 617 2827 0 293 633 1826 1319
Last week 187739 288 18 27 18500 344491 37968 131780 14883 6603 5325 1026 5823 710 413 4310 389 13448 131 3080 17727 21203 1377 3176 20189 8095
Previous peak date10-2110-17 -- --2021-01-2708-0406-062021-01-1509-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1309-19 --09-08
Previous peak daily increment 14881 104 2107 45270 7349 18367 1226 1405 7778 420 2590 77 177 795 160 22832 8380 94 119 1085
Low between peaks 7 19228 1343 308 400 -4305 70 423 6 305 50 4599 1490 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-05-29 to 2021-06-04

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-28 3702422 11684 364570 16391930 1361381 3342567 314102 289288 423165 73246 252929 16724 14037 236451 48288 2408778 376854 348184 1942054 14305 22620 282198 230147
2021-05-29 3736000 11700 367000 16480000 1366000 3363000 315300 289400 425900 73250 253700 16880 14130 237400 48360 2411000 377300 351200 1956000 14530 22630 285200 231400
2021-05-30 3769000 11710 367000 16517000 1370000 3378000 315400 289900 427500 73330 253900 17010 14270 238400 48490 2412000 377700 353500 1962000 14740 22760 287100 232400
2021-05-31 3801000 11830 367700 16548000 1375000 3395000 321200 290400 428300 73450 254100 17130 14390 239300 48590 2413000 377900 356000 1962000 14960 22780 289600 233500
2021-06-01 3833000 11900 369300 16618000 1378000 3413000 323300 290900 429400 73570 255200 17250 14500 240100 48680 2415000 378500 359100 1967000 15150 23050 292400 234600
2021-06-02 3865000 11910 371000 16692000 1382000 3431000 325800 291800 430800 73700 256500 17370 14600 240900 48770 2418000 379000 361500 1973000 15360 23470 295200 235700
2021-06-03 3897000 11960 373000 16761000 1390000 3450000 328200 293300 432000 73830 257600 17480 14700 241700 48840 2421000 379700 364500 1976000 15610 23820 298200 236800
2021-06-04 3930000 12000 375200 16815000 1398000 3470000 330400 294200 432900 73970 258900 17590 14790 242500 48920 2424000 380200 367100 1979000 15840 24440 301300 238000

Confirmed count average forecast Latin America (bold black line in graphs) 2021-05-29 to 2021-06-04

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-28 3702422 11684 364570 16391930 1361381 3342567 314102 289288 423165 73246 252929 16724 14037 236451 48288 2408778 376854 348184 1942054 14305 22620 282198 230147
2021-05-29 3738000 11710 367200 16459000 1369000 3363000 315100 290300 424200 73400 253900 16840 14060 237200 48380 2411000 377300 351000 1948000 14540 23130 284900 231300
2021-05-30 3770000 11730 368700 16490000 1374000 3378000 316000 291200 424800 73520 254300 16940 14110 238100 48450 2413000 377500 353100 1953000 14720 23580 287600 232200
2021-05-31 3801000 11810 369700 16519000 1379000 3393000 319500 292000 425200 73650 254600 17050 14150 238800 48530 2414000 377700 355300 1955000 14910 23890 290500 233100
2021-06-01 3833000 11860 371900 16590000 1383000 3410000 321400 292700 425700 73780 255500 17150 14190 239600 48580 2416000 378000 358000 1959000 15080 24320 293500 234000
2021-06-02 3864000 11890 373500 16659000 1387000 3426000 323600 293600 426400 73920 256300 17250 14230 240300 48630 2418000 378400 360100 1964000 15260 24810 296800 234900
2021-06-03 3896000 11950 375200 16726000 1394000 3442000 325700 294700 427300 74050 257100 17350 14270 241100 48690 2420000 378700 362800 1966000 15460 25300 300100 235800
2021-06-04 3929000 11980 377100 16794000 1401000 3459000 327900 295500 428000 74190 257900 17450 14310 241800 48750 2422000 379000 365400 1971000 15650 25870 303400 236600

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