COVID-19 short-term forecasts Confirmed 2021-05-03 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 2021-05-03

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-04-2710-172021-02-1812-032021-01-222021-03-242021-04-052021-04-29 --2021-01-182021-04-232021-04-112021-04-20 --2021-01-232021-02-032021-03-182021-01-2005-262021-01-07 --2021-03-282021-04-21 --2021-04-092021-04-05
Peak daily increment 23884 104 105 1113 2113 74831 7057 17903 1589 1959 672 1358 63 1356 660 16927 145 3350 8676 82 5022 1369
Days since peak 6 198 74 151 101 40 28 4 105 10 22 13 100 89 46 103 342 116 36 12 24 28
Last total 3021179 10576 3881 12674 308984 14779529 1215815 2905254 256676 267681 388046 69727 228871 13564 13094 214475 46039 2349900 6898 365299 284453 1814127 10543 11471 204120 200931
Last daily increment 15920 57 15 6 2457 24619 4895 11599 5685 226 747 529 187 46 0 1308 172 1027 0 195 1910 3129 54 158 1628 864
Last week 116007 356 53 43 8726 337966 36043 100373 13509 2200 12717 805 5846 738 95 7155 827 16774 0 1766 12639 45941 386 1524 14024 7210
Previous peak date10-19 -- -- --07-1708-0406-062021-01-1609-1807-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1309-18 --09-08
Previous peak daily increment 14376 1578 45351 7360 17013 1298 1408 7756 420 2699 66 177 795 160 23278 8364 89 117 1086
Low between peaks 5479 93 19228 1343 3453 400 -4346 82 424 6 305 50 4595 1487 1 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-05-04 to 2021-05-10

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-03 3021179 10576 308984 14779529 1215815 2905254 256676 267681 388046 69727 228871 13564 214475 46039 2349900 365299 284453 1814127 10543 11471 204120 200931
2021-05-04 3054000 10630 309300 14854000 1223000 2920000 259000 268300 388600 69730 230900 13630 215300 46180 2355000 365600 287200 1824000 10610 11490 206500 202000
2021-05-05 3079000 10650 310300 14935000 1229000 2935000 261700 268900 390700 69860 232700 13740 215600 46440 2360000 366000 289400 1836000 10690 11730 210500 203200
2021-05-06 3104000 10690 310400 14997000 1236000 2950000 264100 269400 393600 69970 234400 13860 216100 46640 2363000 366300 291900 1840000 10770 11960 213700 204400
2021-05-07 3128000 10730 311900 15062000 1243000 2965000 266300 269800 395400 70080 236000 14020 216800 46810 2367000 366600 293800 1853000 10840 12170 216600 205500
2021-05-08 3144000 10770 313700 15126000 1249000 2980000 268400 270200 397500 70190 236900 14120 217500 46970 2370000 366900 295800 1858000 10900 12380 219300 206600
2021-05-09 3153000 10820 314000 15149000 1255000 2994000 270400 270800 399500 70300 236900 14230 218300 47110 2371000 367100 297200 1866000 10970 12590 221900 207600
2021-05-10 3168000 10870 315800 15172000 1260000 3009000 272400 271100 400100 70400 237100 14270 219100 47240 2372000 367300 299200 1870000 11030 12800 224500 208700

Confirmed count average forecast Latin America (bold black line in graphs) 2021-05-04 to 2021-05-10

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-03 3021179 10576 308984 14779529 1215815 2905254 256676 267681 388046 69727 228871 13564 214475 46039 2349900 365299 284453 1814127 10543 11471 204120 200931
2021-05-04 3044000 10620 310300 14848000 1220000 2920000 258700 267900 389100 69930 229900 13650 215300 46160 2353000 365500 286700 1818000 10600 11660 206400 201900
2021-05-05 3069000 10670 311300 14927000 1225000 2937000 260300 268400 390600 70060 231500 13770 215900 46280 2357000 365800 289000 1827000 10670 11830 209100 202900
2021-05-06 3094000 10720 311700 14988000 1231000 2954000 261900 268800 392500 70180 232900 13890 216600 46410 2361000 366000 291400 1831000 10730 12010 211700 203900
2021-05-07 3118000 10770 312900 15053000 1238000 2970000 263500 269200 393800 70300 234200 14020 217400 46540 2364000 366200 293400 1841000 10790 12190 214300 204800
2021-05-08 3138000 10820 314200 15119000 1244000 2986000 264800 269600 395300 70410 235200 14130 218100 46670 2368000 366300 295500 1846000 10860 12380 216600 205800
2021-05-09 3156000 10880 314600 15154000 1251000 3003000 266100 270100 396500 70520 235900 14230 218900 46790 2370000 366500 297300 1853000 10920 12570 219000 206700
2021-05-10 3176000 10950 315500 15183000 1257000 3019000 267500 270500 397200 70630 236500 14310 219700 46910 2372000 366600 299300 1859000 10970 12760 221300 207600

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