COVID-19 short-term forecasts Deaths 2020-08-26 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:
    [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.

Peak increase in estimated trend of Deaths in Latin America 2020-08-26

ArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaParaguayPeruVenezuela
Peak date --08-0107-2207-17 --08-0704-1205-1007-2906-0507-29 --07-24 --07-2308-13
Peak daily increment 78 1062 785 10 22 167 10 43 36 28 2947 8
Days from 100 to peak 85 116 93 12 5 39 37 5 82 99 107 28
Days from peak/2 to peak 101 107 63 108 17 40 108 29 113 117 78 133
Last total 7839 4726 117665 10990 18184 386 1613 6410 687 2662 1747 62076 1932 247 28001 351
Last daily increment 276 62 1085 32 295 10 28 42 9 32 44 626 13 16 188 8
Last week 1322 421 5361 319 2001 53 108 210 47 156 128 2970 88 77 1167 40
Days since peak 25 35 40 19 136 108 28 82 28 33 34 13

Deaths count forecast Latin America (bold red line in graphs) 2020-08-27 to 2020-09-02

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaParaguayPeruVenezuela
2020-08-26 7839 4726 117665 10990 18184 386 1613 6410 687 2662 1747 62076 1932 247 28001 351
2020-08-27 8090 4789 118900 11080 18450 395 1631 6439 695 2692 1762 62950 1941 266 28080 358
2020-08-28 8340 4850 119900 11130 18700 404 1649 6467 703 2723 1776 63440 1950 285 28190 366
2020-08-29 8591 4911 120700 11190 18960 413 1666 6496 711 2757 1790 64020 1959 304 28310 373
2020-08-30 8850 4970 121200 11250 19210 422 1683 6523 719 2771 1804 64210 1968 323 28440 380
2020-08-31 9117 5030 121700 11320 19460 431 1700 6551 727 2785 1818 64540 1977 343 28570 388
2020-09-01 9393 5090 123000 11350 19710 440 1717 6579 735 2802 1831 65170 1987 363 28700 395
2020-09-02 9678 5150 124000 11390 19960 449 1734 6607 743 2838 1845 65800 1996 385 28830 403

Deaths count average forecast Latin America (bold black line in graphs) 2020-08-27 to 2020-09-02

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaParaguayPeruVenezuela
2020-08-26 7839 4726 117665 10990 18184 386 1613 6410 687 2662 1747 62076 1932 247 28001 351
2020-08-27 8004 4765 118600 11060 18380 391 1624 6422 693 2690 1751 62650 1944 255 28230 358
2020-08-28 8245 4824 119600 11120 18710 399 1641 6449 701 2719 1755 63160 1957 267 28530 366
2020-08-29 8467 4889 120400 11190 18990 408 1657 6478 709 2751 1762 63780 1971 280 28830 373
2020-08-30 8696 4951 121000 11250 19320 417 1674 6502 717 2773 1772 63950 1985 291 29130 381
2020-08-31 8977 5015 121700 11320 19650 426 1691 6524 725 2794 1784 64350 1999 306 29430 389
2020-09-01 9247 5083 122800 11380 19940 436 1708 6550 734 2820 1798 65200 2013 321 29750 397
2020-09-02 9548 5148 123900 11430 20300 446 1725 6581 742 2854 1813 65860 2028 334 30070 406

Deaths count scenario forecast (bold purple line in graphs) 2020-08-27 to 2020-09-04

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaParaguayPeruVenezuela
2020-08-26 7839 4726 117665 10990 18184 386 1613 6410 687 2662 1747 62076 1932 247 28001 351
2020-08-27 8010 4770 118500 11050 18570 392 1623 6430 693 2687 1747 62780 1945 265 28310 357
2020-08-28 8240 4831 119200 11100 18900 400 1626 6460 700 2710 1747 63340 1956 281 28600 364
2020-08-29 8470 4883 119800 11150 19220 408 1631 6489 706 2732 1751 63830 1967 296 28850 370
2020-08-30 8730 4957 120500 11200 19570 417 1631 6516 712 2753 1763 64450 1977 311 29130 376
2020-08-31 8990 5017 120900 11230 19930 425 1631 6549 718 2775 1774 65060 1986 328 29360 381
2020-09-01 9260 5081 121500 11280 20330 433 1631 6571 725 2797 1787 65510 1994 342 29570 386
2020-09-02 9530 5146 122000 11310 20690 442 1631 6594 732 2817 1790 66010 2001 358 29720 391
2020-09-03 9800 5209 122500 11340 21050 451 1631 6614 737 2837 1795 66400 2008 378 29880 396
2020-09-04 10070 5265 122900 11380 21400 460 1631 6631 742 2856 1801 66690 2014 393 30080 400

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

[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 Deaths