COVID-19 short-term forecasts Confirmed 2022-03-07 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 2022-03-07

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2022-01-132022-01-092022-01-192022-01-102022-01-142022-01-282022-02-052022-01-152022-01-252022-01-142022-01-152022-02-142022-02-082022-01-152022-01-172022-02-162022-01-132022-01-192021-08-192022-01-142022-01-242022-01-192022-01-182021-12-092022-01-202022-01-25
Peak daily increment 112477 997 826 759 10699 182432 35597 30553 6209 6246 8554 8027 3352 919 482 8205 1343 43483 167 10293 8637 47146 944 788 11003 2156
Days since peak 53 57 47 56 52 38 30 51 41 52 51 21 27 51 49 19 53 47 200 52 42 47 48 88 46 41
Last total 8942888 33176 56220 56876 895098 29077831 3202562 6072656 817538 576003 841575 156364 792961 63062 30385 413699 128213 5566669 18105 757930 644199 3528038 78579 130532 855883 516817
Last daily increment 6286 5 96 0 0 21306 14114 952 2955 54 5359 0 458 7 0 0 34 1684 0 443 320 489 68 132 1508 0
Last week 38712 30 835 103 1586 258981 141543 6855 8407 1091 13815 0 12146 116 43 966 160 44925 0 2077 2015 9317 285 2387 11483 1693
Previous peak date2021-06-052021-10-182021-10-2612-032021-06-102021-09-182021-11-182021-06-262021-09-062021-06-052021-06-292021-11-062021-08-242021-09-152021-06-082021-08-132021-08-232021-08-1105-262021-06-292021-06-082021-06-052021-09-152021-06-052021-06-062021-10-05
Previous peak daily increment 25322 184 347 1136 2614 92852 2475 29569 2470 1203 1229 1386 3774 229 180 1515 731 18310 176 1107 2669 3719 485 365 3221 1476
Low between peaks 898 -2 41 2 287 2340 968 1351 -225 163 197 21 203 28 4 -124 17 617 -35 129 -154 60 16 170 95 69

Confirmed count forecast Latin America (bold red line in graphs) 2022-03-08 to 2022-03-14

DateArgentinaBarbadosBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-03-07 8942888 56220 895098 29077831 3202562 6072656 817538 576003 841575 792961 413699 5566669 757930 644199 3528038 78579 130532 855883 516817
2022-03-08 8959000 56280 895400 29144000 3225000 6075000 823300 576700 843600 798900 414400 5593000 758100 645000 3529000 78740 131200 858300 517000
2022-03-09 8975000 56420 897000 29192000 3272000 6078000 827700 577100 848400 803900 415300 5618000 760100 645900 3540000 78860 131800 860300 517700
2022-03-10 8988000 56520 898000 29223000 3307000 6080000 830700 577500 851700 807800 416100 5636000 761200 646500 3546000 78960 132200 862100 518200
2022-03-11 8997000 56590 898700 29274000 3336000 6082000 833100 577600 854200 811400 416100 5646000 762000 646800 3549000 79010 132700 864100 518500
2022-03-12 9003000 56660 899200 29330000 3364000 6084000 834000 577900 856600 814900 416400 5667000 762600 647200 3552000 79070 133200 866500 518800
2022-03-13 9004000 56720 899600 29330000 3388000 6085000 834000 578000 858600 815800 416400 5671000 763000 647500 3554000 79100 133600 867400 519000
2022-03-14 9010000 56780 899900 29330000 3412000 6087000 836800 578200 860500 815800 416500 5673000 763400 648000 3555000 79170 133800 869000 519200

Confirmed count average forecast Latin America (bold black line in graphs) 2022-03-08 to 2022-03-14

DateArgentinaBarbadosBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2022-03-07 8942888 56220 895098 29077831 3202562 6072656 817538 576003 841575 792961 413699 5566669 757930 644199 3528038 78579 130532 855883 516817
2022-03-08 8949000 56370 895400 29111000 3217000 6074000 819400 576200 842800 796500 414000 5572000 758800 644700 3530000 78650 130900 857500 517300
2022-03-09 8958000 56530 896200 29172000 3254000 6075000 822500 576400 845500 800200 414600 5586000 759800 645500 3534000 78700 131400 859400 518000
2022-03-10 8966000 56670 896800 29225000 3285000 6076000 824800 576600 848300 803300 415700 5598000 760500 646200 3537000 78760 131800 861200 518500
2022-03-11 8974000 56810 897300 29292000 3312000 6078000 826600 576800 849700 805900 415700 5607000 761400 646700 3539000 78800 132200 863200 519000
2022-03-12 8979000 56930 897700 29376000 3343000 6079000 827500 577000 850900 808900 416300 5628000 761800 647100 3541000 78830 132700 864800 519400
2022-03-13 8982000 57030 898200 29403000 3366000 6080000 828600 577200 852100 809700 416900 5634000 762600 648000 3543000 78850 133100 866100 519800
2022-03-14 8988000 57120 898600 29427000 3391000 6081000 833500 577400 854800 810000 417200 5637000 762900 648600 3544000 78900 133400 867300 520200

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