COVID-19 short-term forecasts Confirmed 2021-07-13 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 2021-07-13

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-27 --2021-02-1812-032021-06-012021-03-242021-06-04 --2021-05-172021-01-182021-04-232021-04-11 --2021-06-242021-06-082021-02-032021-03-182021-01-2005-262021-07-032021-06-022021-04-092021-06-132021-05-242021-04-092021-05-16
Peak daily increment 32513 106 1122 2893 74846 7274 2464 1589 2035 675 191 179 1356 662 16980 177 1074 2948 8725 267 529 5275 1698
Days since peak 47 145 222 42 111 39 57 176 81 93 19 35 160 117 174 413 10 41 95 30 50 95 58
Last total 4682960 13233 4196 13587 456815 19151993 1589623 4530610 385069 335079 470882 82130 322120 21055 19220 275675 50793 2604711 8767 417087 439897 2081557 23594 35046 377297 286990
Last daily increment 20023 209 10 26 1379 45022 0 0 4587 535 2468 486 2963 53 0 698 36 11137 306 855 1133 0 131 224 421 1080
Last week 89197 268 88 143 7128 242956 13287 103799 7978 4138 5853 1895 13847 410 48 4986 337 46342 306 5861 7096 9920 806 1126 2632 6010
Previous peak date10-1910-17 -- --2021-01-2208-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 --2021-01-07 --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2113 45269 7348 17013 1226 1405 7778 420 2669 66 177 795 160 22832 3354 8380 89 119 1085
Low between peaks 5479 704 19228 1343 308 400 -4305 70 13 5 305 50 4599 294 1490 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-07-14 to 2021-07-20

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-07-13 4682960 13233 456815 19151993 1589623 4530610 385069 335079 470882 82130 322120 21055 275675 50793 2604711 8767 417087 439897 2081557 23594 35046 377297 286990
2021-07-14 4709000 13440 459500 19243000 1591000 4583000 386300 336000 472200 82130 324700 21140 276700 50840 2605000 8767 418300 442100 2087000 23850 35230 377700 288100
2021-07-15 4732000 13600 461500 19317000 1594000 4617000 388100 336900 473200 82500 327300 21240 277900 50870 2608000 8767 419400 443900 2091000 24080 35540 378200 289400
2021-07-16 4749000 13680 462100 19385000 1596000 4645000 389700 337600 474800 82500 329500 21310 279000 50910 2612000 8767 420400 445400 2092000 24240 35720 378600 290500
2021-07-17 4762000 13760 464100 19437000 1598000 4665000 389700 338400 475800 82690 331500 21380 280000 50950 2619000 8767 421400 446600 2094000 24350 35900 378900 291600
2021-07-18 4772000 13830 464800 19463000 1598000 4682000 389900 338900 476300 83290 333400 21440 281000 50990 2624000 8767 422100 447700 2097000 24480 36060 379100 292700
2021-07-19 4785000 13930 465800 19473000 1599000 4715000 390700 339500 476500 83440 335100 21460 281900 51040 2627000 8767 422700 448700 2098000 24540 36130 379100 293700
2021-07-20 4805000 14050 467300 19520000 1600000 4721000 394100 340100 478500 83640 336800 21540 282800 51080 2635000 9035 423600 449900 2098000 24670 36320 379600 294700

Confirmed count average forecast Latin America (bold black line in graphs) 2021-07-14 to 2021-07-20

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-07-13 4682960 13233 456815 19151993 1589623 4530610 385069 335079 470882 82130 322120 21055 275675 50793 2604711 8767 417087 439897 2081557 23594 35046 377297 286990
2021-07-14 4701000 13320 458000 19203000 1591000 4558000 386500 335800 471900 82390 324300 21110 276500 50830 2611000 8787 418000 441100 2083000 23740 35200 377700 288000
2021-07-15 4719000 13380 459200 19255000 1593000 4583000 387800 336500 472400 82610 326300 21180 277600 50860 2617000 8788 418800 442500 2086000 23900 35400 378100 288900
2021-07-16 4735000 13410 459600 19311000 1596000 4605000 389100 337200 473100 82790 328400 21250 278500 50890 2623000 8800 419500 443600 2087000 24040 35560 378600 289800
2021-07-17 4748000 13440 460800 19356000 1599000 4625000 389500 337900 473600 82990 330400 21310 279400 50920 2629000 8811 420100 444600 2089000 24160 35710 379000 290500
2021-07-18 4761000 13460 461300 19377000 1601000 4646000 390000 338600 473900 83250 332200 21370 280300 50950 2635000 8825 420600 445600 2091000 24300 35860 379300 291300
2021-07-19 4776000 13500 462100 19388000 1603000 4667000 391400 339200 474300 83460 334100 21400 281200 50980 2639000 8825 421000 446700 2093000 24400 35980 379700 292000
2021-07-20 4795000 13570 463000 19444000 1605000 4686000 392900 339800 475100 83670 335900 21480 282100 51010 2645000 8962 421700 447900 2094000 24540 36150 380300 292700

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