COVID-19 short-term forecasts Confirmed 2021-05-24 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 2021-05-24

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd) --2021-04-252021-02-1812-03 --2021-03-242021-04-09 -- --2021-01-182021-04-232021-04-112021-04-19 --2021-01-232021-02-032021-03-182021-01-2005-262021-01-07 --2021-04-09 -- --2021-04-092021-05-16
Peak daily increment 60 106 1122 74847 7144 1589 2109 675 1349 63 1356 662 16980 177 3354 8725 5275 1672
Days since peak 29 95 172 61 45 126 31 43 35 121 110 67 124 363 137 45 45 8
Last total 3562135 11499 3995 12764 349653 16120756 1335261 3249433 304529 284567 419198 72220 247644 16130 13906 233116 48054 2397307 7193 374356 335691 1925289 13302 20267 267888 224819
Last daily increment 22651 103 0 0 0 37498 5343 16977 5310 838 347 0 190 0 171 444 95 703 0 235 2720 0 191 250 2790 1474
Last week 190627 221 23 19 14829 387920 39399 104886 13609 6018 7732 741 4860 676 386 4829 575 11795 0 2672 17440 31955 1051 3117 21862 7216
Previous peak date10-1610-17 -- --2021-01-2808-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1309-18 --09-08
Previous peak daily increment 14332 104 2232 45271 7349 17013 1226 1405 7778 420 2590 66 177 795 160 22832 8380 94 144 1085
Low between peaks 7 19229 1343 400 -4305 70 423 6 305 50 4599 1490 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-05-25 to 2021-05-31

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-24 3562135 11499 349653 16120756 1335261 3249433 304529 284567 419198 72220 247644 16130 13906 233116 48054 2397307 374356 335691 1925289 13302 20267 267888 224819
2021-05-25 3599000 11560 352300 16179000 1338000 3260000 306500 284900 421400 72400 248800 16280 14040 234000 48140 2400000 374700 338900 1931000 13450 20800 268600 226000
2021-05-26 3635000 11600 354200 16246000 1341000 3274000 309300 285500 423700 72540 249900 16430 14130 235200 48270 2403000 375100 342100 1941000 13590 21340 270500 227000
2021-05-27 3668000 11670 356300 16316000 1348000 3290000 311900 286400 426200 72660 251100 16570 14230 236200 48380 2406000 375600 345600 1942000 13750 21850 273900 228000
2021-05-28 3700000 11680 358300 16385000 1354000 3304000 314500 286900 427500 72770 252100 16610 14320 237100 48480 2408000 376000 348800 1949000 13910 22510 276900 229100
2021-05-29 3728000 11690 360300 16447000 1360000 3320000 314500 287400 429300 72890 252900 16820 14420 238000 48580 2411000 376300 351900 1958000 14060 23050 279900 230200
2021-05-30 3751000 11690 362300 16479000 1366000 3338000 314500 288300 430100 73000 253000 16930 14530 238800 48670 2412000 376700 354600 1963000 14210 23500 282700 231300
2021-05-31 3773000 11790 364300 16508000 1371000 3353000 319600 289000 430700 73110 253300 16960 14630 239600 48760 2412000 376900 356700 1963000 14360 23690 285200 232400

Confirmed count average forecast Latin America (bold black line in graphs) 2021-05-25 to 2021-05-31

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-24 3562135 11499 349653 16120756 1335261 3249433 304529 284567 419198 72220 247644 16130 13906 233116 48054 2397307 374356 335691 1925289 13302 20267 267888 224819
2021-05-25 3591000 11530 351300 16196000 1339000 3265000 306700 285400 419900 72310 248500 16220 13990 233800 48130 2399000 374700 338600 1929000 13460 20860 270800 226000
2021-05-26 3618000 11570 353500 16268000 1343000 3280000 309200 286300 421000 72430 249400 16360 14020 234700 48210 2402000 374900 340900 1936000 13610 21440 273500 226900
2021-05-27 3644000 11630 355600 16340000 1349000 3296000 311500 287200 422200 72550 250400 16490 14050 235500 48290 2404000 375200 343500 1938000 13760 21970 276900 227700
2021-05-28 3672000 11650 357700 16415000 1356000 3311000 313800 288000 423000 72680 251100 16560 14090 236300 48370 2406000 375500 346000 1943000 13900 22660 280000 228600
2021-05-29 3698000 11670 359800 16480000 1362000 3327000 314800 288900 424100 72800 251900 16720 14130 237100 48450 2409000 375700 348000 1950000 14040 23210 283100 229400
2021-05-30 3722000 11690 361800 16513000 1368000 3343000 315800 289800 424800 72920 252300 16840 14170 237900 48520 2410000 375900 350000 1955000 14180 23630 285600 230200
2021-05-31 3749000 11780 363900 16538000 1372000 3357000 319500 290600 425400 73040 252700 16920 14220 238700 48580 2412000 376100 351900 1957000 14330 23910 287800 231000

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