COVID-19 short-term forecasts Confirmed 2022-05-04 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 2022-05-04

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-132022-01-092022-04-252022-01-102022-01-142022-01-282022-02-082022-01-152022-01-252022-01-142022-01-152022-02-142022-02-082022-01-162022-01-172022-02-162022-01-142022-04-072021-09-282022-01-142022-01-242022-01-192022-01-182021-12-092022-01-202022-01-25
Peak daily increment 112477 929 414 763 10699 182433 36050 30553 6209 6246 8554 8731 3374 916 482 8075 1352 22317 137 10293 8637 47145 911 788 11003 2156
Days since peak 111 115 9 114 110 96 85 109 99 110 109 79 85 108 107 77 110 27 218 110 100 105 106 146 104 99
Last total 9083673 33626 71127 57561 905150 30502501 3566183 6092667 857290 579572 869956 162089 847491 63518 30703 423775 130473 5739680 18491 780148 649455 3567863 79393 149532 899723 522564
Last daily increment 0 25 0 26 53 20072 2533 0 5216 129 260 0 706 27 6 596 85 0 0 1838 0 692 0 555 0 50
Last week 11443 99 1782 70 392 83581 12227 500 5216 324 832 0 2502 61 48 656 611 1869 0 5599 421 3934 57 2590 3948 301
Previous peak date2021-06-052021-07-262022-01-1912-032021-06-102021-09-182021-11-132021-06-262021-09-062021-06-052021-06-292021-11-062021-08-242021-09-1806-012021-08-132021-08-232022-01-1905-262021-06-292021-06-082021-06-052021-09-212021-06-052021-06-062021-10-05
Previous peak daily increment 25322 182 826 1122 2614 92852 2476 29569 2470 1203 1229 1490 3774 229 178 1515 759 43483 213 1107 2669 3719 478 365 3221 1476
Low between peaks 898 -11 84 2 287 2340 968 1351 -225 163 197 9 203 31 5 5 27 2342 4 129 -154 60 12 170 95 69

Confirmed count forecast Latin America (bold red line in graphs) 2022-05-05 to 2022-05-11

DateArgentinaBarbadosBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2022-05-04 9083673 71127 905150 30502501 3566183 6092667 857290 579572 869956 847491 423775 130473 5739680 780148 649455 3567863 149532 899723 522564
2022-05-05 9084000 71920 905200 30517000 3569000 6093000 857300 579600 870600 848400 425300 130500 5741000 781100 649500 3569000 149900 900300 522600
2022-05-06 9084000 72220 905300 30529000 3572000 6093000 857300 579600 870600 849000 426500 130600 5741000 781300 649800 3569000 150000 900800 522600
2022-05-07 9084000 72660 905400 30540000 3574000 6093000 857300 579600 871100 849600 426900 130700 5742000 781800 649800 3570000 150200 901300 522700
2022-05-08 9084000 72930 905400 30545000 3576000 6093000 857300 579700 871100 849600 426900 130700 5742000 782500 649800 3570000 150500 901800 522700
2022-05-09 9084000 73240 905500 30551000 3577000 6093000 857600 579700 871400 849700 427100 130800 5742000 783100 649900 3571000 150800 902300 522700
2022-05-10 9085000 73580 905600 30570000 3578000 6093000 857600 579700 871400 850000 427100 130900 5742000 783900 650000 3571000 151200 902700 522800
2022-05-11 9085000 73730 905600 30590000 3580000 6093000 863600 579800 871500 850600 427100 130900 5742000 784700 650000 3572000 151600 903200 522800

Confirmed count average forecast Latin America (bold black line in graphs) 2022-05-05 to 2022-05-11

DateArgentinaBarbadosBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruTrinidad and TobagoUruguayVenezuela
2022-05-04 9083673 71127 905150 30502501 3566183 6092667 857290 579572 869956 847491 423775 130473 5739680 780148 649455 3567863 149532 899723 522564
2022-05-05 9084000 71540 905200 30519000 3569000 6093000 857800 579600 870300 848200 423500 130600 5740000 781200 649500 3569000 150200 900200 522600
2022-05-06 9085000 71840 905300 30529000 3571000 6093000 857800 579700 870400 848800 424000 130700 5742000 781900 649700 3569000 150600 900500 522600
2022-05-07 9086000 72250 905300 30538000 3573000 6093000 857800 579700 870800 849400 424200 130800 5742000 782600 649800 3570000 150900 900800 522600
2022-05-08 9091000 72560 905400 30542000 3575000 6093000 857900 579700 870800 849500 424200 130800 5743000 783200 649800 3570000 151300 901000 522700
2022-05-09 9093000 72900 905400 30548000 3576000 6093000 857900 579800 871100 849600 424300 130900 5743000 783700 649800 3571000 151500 901300 522700
2022-05-10 9093000 73300 905500 30564000 3577000 6093000 858000 579800 871200 849900 424400 131000 5743000 784400 649900 3572000 151800 901600 522700
2022-05-11 9094000 73660 905600 30583000 3579000 6093000 861300 579900 871300 850700 424700 131100 5744000 785300 649900 3572000 152300 901900 522700

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