COVID-19 short-term forecasts Confirmed 2021-06-19 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 2021-06-19

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-05-202021-04-252021-02-1812-03 -- --2021-06-04 --2021-05-172021-01-182021-04-232021-04-112021-04-192021-05-132021-06-082021-02-032021-03-182021-01-2005-262021-06-102021-06-022021-04-092021-06-112021-05-192021-04-092021-05-16
Peak daily increment 31572 60 106 1122 7205 2538 1589 2035 675 1349 129 201 1356 662 16980 177 748 2899 8725 261 539 5275 1698
Days since peak 30 55 121 198 15 33 152 57 69 61 37 11 136 93 150 389 9 17 71 8 31 71 34
Last total 4258394 12295 4041 13004 420961 17883750 1511275 3917348 350630 315815 445586 76697 279947 18973 16859 253128 49607 2471741 7696 393144 405075 2023179 19748 30513 353377 259413
Last daily increment 15631 53 1 0 3766 82288 6274 28734 0 1784 1191 0 1538 136 0 1979 43 0 0 978 1683 0 172 330 1999 1273
Last week 134204 203 5 66 14007 470984 34802 164124 10730 7165 6652 1346 8244 587 780 5400 330 17565 34 5302 13639 19554 1376 1790 14864 7727
Previous peak date10-1910-17 -- --2021-01-2707-2906-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 --2021-01-07 --08-0208-1409-19 --09-08
Previous peak daily increment 14378 104 2107 48655 7349 17013 1226 1405 7778 420 2590 66 177 795 160 22832 3354 8380 89 119 1085
Low between peaks 5479 7 1343 308 400 -4305 70 423 13 5 305 50 4599 294 1490 1 4 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-06-20 to 2021-06-26

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-19 4258394 12295 420961 17883750 1511275 3917348 350630 315815 445586 76697 279947 18973 16859 253128 49607 2471741 393144 405075 2023179 19748 30513 353377 259413
2021-06-20 4264000 12300 424300 17897000 1522000 3936000 351400 317000 446000 76700 280500 19040 16980 254000 49660 2474000 393900 406100 2028000 19990 30820 356200 260700
2021-06-21 4275000 12400 425900 17929000 1529000 3956000 355700 317900 446200 76730 280500 19090 17350 254000 49740 2475000 394500 407400 2030000 20270 31420 361400 262000
2021-06-22 4291000 12420 429400 17999000 1534000 3977000 357600 318900 446600 77520 282000 19170 17510 254300 49810 2479000 395400 409100 2033000 20540 31880 365400 263300
2021-06-23 4308000 12440 431600 18073000 1538000 4000000 359500 320300 448100 77590 283400 19290 17550 254800 49870 2483000 396400 411000 2035000 20790 32260 368800 264500
2021-06-24 4324000 12450 435000 18139000 1545000 4030000 361300 321400 449400 77700 284800 19380 17680 255300 49920 2486000 397300 412800 2044000 21040 32630 372100 265800
2021-06-25 4335000 12450 435300 18215000 1552000 4058000 362700 322500 451000 77830 286300 19470 17720 256000 49980 2490000 398400 414200 2047000 21280 32950 375100 267000
2021-06-26 4350000 12490 438800 18294000 1558000 4085000 362800 324000 452100 77850 287700 19590 17740 256700 50030 2491000 399200 415900 2048000 21530 33270 378000 268200

Confirmed count average forecast Latin America (bold black line in graphs) 2021-06-20 to 2021-06-26

DateArgentinaBahamasBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-06-19 4258394 12295 420961 17883750 1511275 3917348 350630 315815 445586 76697 279947 18973 16859 253128 49607 2471741 393144 405075 2023179 19748 30513 353377 259413
2021-06-20 4271000 12310 422800 17929000 1518000 3943000 351400 317000 446400 76780 280900 19070 16950 254200 49650 2474000 393800 406500 2026000 19970 30820 355300 260600
2021-06-21 4290000 12360 424300 17966000 1524000 3966000 354200 317900 446500 76860 281600 19140 17130 254700 49700 2475000 394200 408600 2028000 20220 31130 358100 261700
2021-06-22 4312000 12380 427000 18034000 1529000 3990000 355800 318800 446800 77320 282900 19220 17270 255200 49730 2479000 394700 410900 2030000 20460 31420 361000 262700
2021-06-23 4333000 12400 428800 18110000 1533000 4015000 357400 320000 447500 77440 284100 19330 17390 255900 49760 2482000 395200 413200 2032000 20700 31700 363800 263700
2021-06-24 4356000 12420 431400 18173000 1540000 4042000 359000 321100 448100 77580 285300 19420 17520 256500 49790 2485000 395700 415500 2038000 20940 31980 366800 264700
2021-06-25 4378000 12450 432400 18233000 1547000 4067000 360600 322200 448800 77710 286400 19500 17640 257100 49830 2488000 396100 417800 2040000 21180 32250 369800 265700
2021-06-26 4399000 12470 435200 18299000 1554000 4094000 361300 323300 449200 77790 287600 19600 17750 257700 49860 2490000 396600 420000 2041000 21420 32520 373100 266600

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