COVID-19 short-term forecasts Confirmed 2022-01-24 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 2022-01-24

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-202022-01-092022-01-19 --2022-01-192022-01-19 --2022-01-212022-01-192022-01-202022-01-142022-01-212022-01-072022-01-202022-01-172022-01-172022-01-18 --2021-08-192022-01-142022-01-17 --2022-01-18 --2022-01-20 --
Peak daily increment 123305 870 878 11068 165214 33001 4240 6813 26017 2615 2271 1042 602 1190 1505 167 11666 20247 1032 12314
Days since peak 4 15 5 5 5 3 5 4 10 3 17 4 7 7 6 158 10 7 6 4
Last total 7940657 32137 39709 47147 820583 24142032 1984190 5761398 643496 542056 658045 127012 670489 57400 28561 387515 120682 4685767 17604 644683 542388 2976260 70937 106806 599040 469566
Last daily increment 78121 69 497 1394 15906 87627 18797 21219 0 2476 0 0 659 173 90 0 1117 17938 0 0 25833 30109 863 389 10045 0
Last week 622352 1032 3975 4032 57191 912181 91075 164481 17544 31598 28538 3435 14033 4222 742 1551 5696 300352 0 52840 38008 308036 4304 4782 67588 12925
Previous peak date2021-06-052021-07-262021-10-272021-10-142021-06-102021-09-182021-06-122021-06-262021-09-062021-06-052021-07-292021-11-062021-08-242021-09-182021-06-232021-08-132021-08-232021-08-1205-262021-06-292021-06-092021-07-042021-09-15 --2021-06-062021-10-05
Previous peak daily increment 25321 172 364 370 2614 92852 6997 29569 2470 1203 3070 1526 3774 232 153 1515 759 18192 176 1107 2707 2786 485 3221 1476
Low between peaks 898 -2 38 287 1162 1351 -293 163 -333 7 203 21 -7 -16 27 -35 129 19 16 95

Confirmed count forecast Latin America (bold red line in graphs) 2022-01-25 to 2022-01-31

DateArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-01-24 7940657 32137 39709 47147 820583 24142032 1984190 5761398 643496 542056 658045 127012 670489 57400 28561 387515 120682 4685767 644683 542388 2976260 70937 106806 599040 469566
2022-01-25 8053000 32330 40220 47400 830700 24326000 2000000 5787000 648800 550200 671600 127500 670500 58600 28740 388800 122900 4721000 644700 542400 3007000 71650 107000 609300 470100
2022-01-26 8166000 32750 41360 47940 839800 24490000 2014000 5817000 651800 557400 672000 127600 671200 59380 28920 388800 124300 4721000 644700 549000 3044000 72300 107500 616600 470100
2022-01-27 8281000 33040 41970 48560 848800 24638000 2030000 5845000 656200 563800 673900 127700 672300 60210 29070 389800 125300 4723000 646800 555700 3084000 72770 108300 625200 470100
2022-01-28 8392000 33280 42410 49260 857800 24797000 2047000 5871000 660300 570000 686600 127700 674000 60990 29200 390100 126200 4743000 652700 555700 3122000 73280 109200 634400 470100
2022-01-29 8481000 33500 42860 49410 866900 24943000 2063000 5898000 660300 575900 689800 127700 675300 61910 29340 391000 127400 4765000 652700 555700 3164000 73600 109800 643900 470100
2022-01-30 8538000 33690 43360 49410 876100 25040000 2078000 5923000 660300 579400 689800 127800 675300 62550 29470 391200 128400 4793000 658700 557700 3202000 73730 110200 653800 470300
2022-01-31 8612000 33880 43800 50640 885400 25142000 2094000 5948000 662200 582800 689800 128000 675900 62860 29600 391400 129400 4823000 660400 572600 3237000 74680 110500 664000 470900

Confirmed count average forecast Latin America (bold black line in graphs) 2022-01-25 to 2022-01-31

DateArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-01-24 7940657 32137 39709 47147 820583 24142032 1984190 5761398 643496 542056 658045 127012 670489 57400 28561 387515 120682 4685767 644683 542388 2976260 70937 106806 599040 469566
2022-01-25 8060000 32320 40230 48080 828900 24279000 1998000 5790000 645700 547300 664500 127100 673000 58280 28590 387800 121800 4709000 652300 548100 3023000 71990 107400 609800 470600
2022-01-26 8192000 32780 41160 48900 838900 24433000 2011000 5822000 648600 555100 666000 127500 675800 59290 28710 387900 123100 4758000 659900 551400 3063000 73120 108100 621100 472100
2022-01-27 8321000 33100 41750 49680 849900 24578000 2024000 5852000 652700 562100 667400 127700 678400 60270 28780 388600 124300 4777000 667900 555900 3102000 73900 109000 632300 473300
2022-01-28 8448000 33380 42280 50410 860000 24726000 2038000 5882000 657400 568700 681500 128800 681300 61210 28850 388800 125300 4831000 677400 556600 3141000 74660 110100 643100 474800
2022-01-29 8566000 33740 42790 50740 868200 24852000 2053000 5916000 658100 575100 683400 129100 683800 62390 28930 389100 126700 4863000 683400 557200 3180000 75300 110600 654300 476000
2022-01-30 8639000 34040 43290 50810 878100 24955000 2066000 5948000 658400 580700 684600 129200 684800 63450 29040 389600 128400 4892000 691700 558300 3221000 75730 111000 666100 477300
2022-01-31 8749000 34350 43840 51580 888500 25068000 2079000 5975000 661300 586800 685700 129400 685600 64230 29230 390500 129900 4913000 698900 566200 3254000 77030 111300 676700 478600

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