COVID-19 short-term forecasts Deaths 2020-08-20 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 2020-08-20

ArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeruVenezuela
Peak date --08-0107-2107-1708-0508-0704-1205-1008-1006-0507-2806-2407-2007-23 --
Peak daily increment 77 1082 789 314 10 22 170 11 43 32 683 28 2725
Days from 100 to peak 85 115 92 115 12 5 39 49 5 81 79 95 107
Days from peak/2 to peak 101 106 62 109 109 17 40 119 29 113 72 113 79
Last total 6517 4305 112304 10671 16183 333 1505 6200 640 2506 1619 59106 1844 26834 311
Last daily increment 187 72 1204 93 204 12 4 54 7 39 11 625 17 176 8
Last week 990 366 5781 331 1691 52 96 170 45 165 71 3198 110 978 45
Days since peak 19 30 34 15 13 130 102 10 76 23 57 31 28

Deaths count forecast Latin America (bold red line in graphs) 2020-08-21 to 2020-08-27

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeruVenezuela
2020-08-20 6517 4305 112304 10671 16183 333 1505 6200 640 2506 1619 59106 1844 26834 311
2020-08-21 6702 4368 113400 10750 16490 343 1523 6224 649 2553 1625 59990 1863 27170 320
2020-08-22 6892 4430 114200 10800 16790 352 1540 6246 658 2569 1629 60620 1882 27440 328
2020-08-23 7092 4492 114700 10860 17080 362 1557 6269 667 2589 1634 60800 1900 27700 337
2020-08-24 7294 4553 115400 10930 17380 371 1574 6291 676 2599 1638 61140 1919 27950 347
2020-08-25 7503 4614 116600 10960 17680 381 1591 6314 684 2623 1642 61910 1937 28190 356
2020-08-26 7719 4675 117800 10990 17980 391 1608 6336 693 2663 1646 62580 1956 28440 366
2020-08-27 7942 4737 118900 11090 18280 401 1625 6359 702 2696 1649 63190 1975 28680 376

Deaths count average forecast Latin America (bold black line in graphs) 2020-08-21 to 2020-08-27

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeruVenezuela
2020-08-20 6517 4305 112304 10671 16183 333 1505 6200 640 2506 1619 59106 1844 26834 311
2020-08-21 6642 4350 113100 10700 16470 340 1518 6206 648 2528 1623 59720 1860 27770 319
2020-08-22 6825 4409 113900 10760 16770 349 1537 6214 658 2544 1628 60340 1877 27990 328
2020-08-23 7012 4469 114500 10820 17060 358 1556 6231 667 2564 1634 60530 1895 28320 337
2020-08-24 7216 4531 115200 10890 17370 367 1575 6249 677 2581 1641 60850 1913 28600 346
2020-08-25 7439 4593 116300 10950 17660 377 1595 6270 687 2608 1648 61710 1931 28850 356
2020-08-26 7670 4656 117500 11000 18000 387 1614 6292 698 2642 1657 62450 1949 29080 365
2020-08-27 7900 4720 118600 11090 18320 397 1634 6311 708 2672 1665 63140 1967 29320 375

Deaths count scenario forecast (bold purple line in graphs) 2020-08-21 to 2020-08-29

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeruVenezuela
2020-08-20 6517 4305 112304 10671 16183 333 1505 6200 640 2506 1619 59106 1844 26834 311
2020-08-21 6681 4363 112900 10720 16530 339 1534 6202 650 2519 1619 59630 1860 27210 321
2020-08-22 6869 4420 113800 10760 16780 347 1546 6225 657 2545 1620 60140 1875 27440 329
2020-08-23 7048 4480 114500 10790 17040 354 1559 6240 666 2565 1621 60640 1888 27730 338
2020-08-24 7246 4539 115400 10820 17280 362 1573 6250 672 2588 1622 61160 1902 27970 347
2020-08-25 7441 4598 116000 10860 17520 369 1582 6262 678 2610 1622 61610 1914 28230 356
2020-08-26 7665 4653 116600 10880 17760 377 1591 6279 683 2632 1623 61900 1927 28470 363
2020-08-27 7891 4709 117200 10910 17960 383 1604 6295 689 2659 1623 62250 1938 28750 370
2020-08-28 8091 4780 117700 10930 18160 390 1609 6312 695 2687 1624 62530 1948 28910 377
2020-08-29 8311 4849 118200 10950 18320 397 1618 6326 700 2716 1624 62850 1957 29260 387

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