COVID-19 short-term forecasts Confirmed 2021-08-20 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:
    [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 2021-08-20

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-272021-07-262021-02-1812-032021-06-012021-03-242021-06-042021-06-262021-05-172021-01-182021-07-29 -- --2021-06-242021-06-08 --2021-03-182021-08-112021-08-172021-07-032021-06-022021-04-102021-06-052021-05-242021-04-092021-05-16
Peak daily increment 32516 157 105 1113 2893 74829 7273 29826 2460 1589 3067 193 179 660 17853 157 1075 2953 8699 261 529 5270 1699
Days since peak 85 25 183 260 80 149 77 55 95 214 22 57 73 155 9 3 48 79 132 76 88 133 96
Last total 5124963 16962 4628 15415 485184 20528099 1632441 4883932 440647 347370 495115 92686 433339 24047 20689 326830 60488 3197108 10672 451293 457472 2140062 27210 42839 383903 322757
Last daily increment 8160 114 19 81 738 33887 752 3416 2060 373 0 270 5243 252 0 3205 556 21734 0 669 123 1396 140 257 145 0
Last week 44055 821 103 568 3553 177957 4148 19303 12352 1410 1348 2557 21608 592 182 10595 3199 105137 421 4032 883 7228 671 1163 691 4572
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-01-1609-1407-2604-2408-0407-1809-2106-042021-02-0309-2210-05 --2021-01-07 --08-0208-1309-19 --09-08
Previous peak daily increment 14376 104 2113 45350 7360 17013 1225 1408 7756 425 2642 66 177 1356 160 23278 3350 8364 89 119 1086
Low between peaks 5479 7 704 19228 1343 3453 262 400 -4346 13 5 50 2152 294 1487 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-08-21 to 2021-08-27

DateArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-08-20 5124963 16962 15415 485184 20528099 1632441 4883932 440647 347370 495115 92686 433339 24047 326830 60488 3197108 10672 451293 457472 2140062 27210 42839 383903 322757
2021-08-21 5149000 16980 15480 485900 20567000 1634000 4892000 440600 347800 496200 92690 436600 24050 326800 61050 3214000 10670 452700 457600 2142000 27220 43120 384100 323800
2021-08-22 5162000 17000 15480 486600 20585000 1635000 4896000 440600 348100 496800 92700 438200 24070 326800 61660 3214000 10860 453400 457700 2144000 27240 43260 384200 324700
2021-08-23 5173000 17410 15480 486900 20600000 1636000 4900000 443200 348300 497100 92850 440500 24070 329500 62230 3224000 10950 453800 457800 2144000 27270 43340 384300 325500
2021-08-24 5186000 17440 15480 487800 20636000 1636000 4906000 445200 348500 497200 93040 443100 24120 331200 62770 3239000 10950 454600 458000 2146000 27380 43560 384500 326300
2021-08-25 5202000 17460 15490 488700 20673000 1637000 4910000 447000 348700 497600 93240 445900 24210 333400 63320 3263000 10950 455400 458200 2147000 27480 43760 384700 327000
2021-08-26 5216000 17620 15540 488800 20708000 1638000 4914000 449100 348900 499000 93470 448800 24260 333500 63860 3285000 11250 456200 458400 2148000 27610 43950 384800 327800
2021-08-27 5222000 17720 15590 489500 20740000 1638000 4917000 450800 349300 499400 93710 451900 24430 336700 64400 3307000 11370 456700 458500 2150000 27740 44170 384900 328600

Confirmed count average forecast Latin America (bold black line in graphs) 2021-08-21 to 2021-08-27

DateArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-08-20 5124963 16962 15415 485184 20528099 1632441 4883932 440647 347370 495115 92686 433339 24047 326830 60488 3197108 10672 451293 457472 2140062 27210 42839 383903 322757
2021-08-21 5133000 17030 15480 485500 20560000 1633000 4887000 441800 347700 495300 93040 437500 24160 327700 61020 3220000 10720 452200 457500 2142000 27310 43060 384000 323500
2021-08-22 5140000 17080 15500 485900 20574000 1634000 4889000 442400 347900 495500 93140 440200 24210 328400 61550 3227000 10740 452700 457600 2143000 27360 43230 384100 324100
2021-08-23 5146000 17380 15550 486000 20587000 1635000 4892000 444400 348100 495600 93290 443000 24240 330200 62000 3241000 10770 453000 457700 2143000 27420 43360 384200 324700
2021-08-24 5154000 17440 15600 486600 20618000 1635000 4895000 446000 348300 495600 93440 446200 24300 331700 62480 3257000 10780 453500 457800 2145000 27510 43560 384300 325300
2021-08-25 5164000 17500 15640 487100 20657000 1636000 4897000 447500 348500 495900 93950 449600 24360 333400 62850 3278000 10810 454000 458000 2146000 27590 43750 384400 325800
2021-08-26 5175000 17640 15710 487200 20691000 1637000 4900000 449100 348800 496700 94140 453100 24410 334100 63280 3298000 11010 454600 458200 2147000 27680 43940 384500 326300
2021-08-27 5182000 17740 15760 487700 20725000 1637000 4902000 450500 349000 497000 94300 456700 24490 336200 63740 3316000 11030 455000 458300 2148000 27760 44150 384600 326800

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