COVID-19 short-term forecasts Confirmed 2021-05-09 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 2021-05-09

ArgentinaBahamasBarbadosBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)2021-04-202021-05-022021-02-1812-032021-01-222021-03-242021-04-092021-04-242021-05-052021-01-182021-04-232021-04-112021-04-19 --2021-01-232021-02-032021-03-182021-01-2005-262021-01-072021-04-172021-04-082021-01-10 --2021-04-092021-04-05
Peak daily increment 23242 59 106 1122 2113 74847 7245 17141 2075 1589 1972 649 1297 63 1356 662 16981 177 3354 2585 8909 81 5556 1368
Days since peak 19 7 80 157 107 46 30 15 4 111 16 28 20 106 95 52 109 348 122 22 31 119 30 34
Last total 3147740 10773 3942 12686 317547 15184790 1247469 3002758 265486 271548 400296 70380 235098 14362 13164 219288 46708 2365792 6989 367656 297789 1850290 11112 13355 220683 207870
Last daily increment 11582 0 9 0 0 38911 5493 17222 0 948 1375 125 215 159 0 0 120 1175 0 386 1483 5234 92 233 1883 1321
Last week 126561 197 61 12 8563 405261 31654 97504 8810 3867 12250 653 6227 798 70 4813 669 15892 91 2357 13336 36163 569 1884 16563 6939
Previous peak date10-1910-17 -- --07-1708-0406-062021-01-1609-1407-2604-2408-0507-1809-2106-0406-2809-2210-05 -- -- --08-0208-1409-18 --09-08
Previous peak daily increment 14378 104 1578 45270 7349 17013 1226 1405 7778 420 2590 66 177 795 160 22833 8380 89 117 1085
Low between peaks 5479 7 93 19229 1343 3454 308 400 -4305 68 423 6 305 50 4599 1490 1 276

Confirmed count forecast Latin America (bold red line in graphs) 2021-05-10 to 2021-05-16

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-09 3147740 317547 15184790 1247469 3002758 265486 271548 400296 70380 235098 14362 219288 46708 2365792 367656 297789 1850290 11112 13355 220683 207870
2021-05-10 3163000 318700 15209000 1256000 3019000 268900 271500 401800 70540 236000 14420 220200 46830 2369000 367700 300200 1861000 11190 13360 223200 209000
2021-05-11 3188000 318700 15280000 1260000 3035000 269500 271800 404000 70690 237600 14490 221200 47020 2373000 367900 302700 1867000 11220 13580 226200 210100
2021-05-12 3210000 320000 15350000 1265000 3051000 271300 272200 405800 70830 239100 14640 222200 47170 2376000 368300 304900 1871000 11280 13890 229000 211200
2021-05-13 3233000 322200 15412000 1271000 3067000 273300 272700 408300 70960 240400 14760 223000 47300 2380000 368600 307400 1877000 11340 14130 231500 212300
2021-05-14 3256000 322500 15480000 1277000 3082000 275100 273200 410100 71080 241800 14890 223900 47430 2383000 368900 309600 1882000 11400 14390 234000 213300
2021-05-15 3272000 325200 15540000 1283000 3097000 275200 273800 412000 71210 242700 15020 224700 47550 2385000 369300 311500 1896000 11470 14700 236500 214400
2021-05-16 3281000 325300 15572000 1289000 3112000 275200 274600 413400 71330 242900 15140 225500 47660 2386000 369600 313000 1902000 11540 14930 238900 215500

Confirmed count average forecast Latin America (bold black line in graphs) 2021-05-10 to 2021-05-16

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
2021-05-09 3147740 317547 15184790 1247469 3002758 265486 271548 400296 70380 235098 14362 219288 46708 2365792 367656 297789 1850290 11112 13355 220683 207870
2021-05-10 3163000 319100 15214000 1252000 3018000 267600 272000 401300 70480 235600 14460 220000 46850 2367000 367900 299800 1856000 11190 13630 222600 209000
2021-05-11 3185000 319600 15288000 1256000 3034000 268800 272300 402900 70610 236700 14550 220900 46940 2370000 368100 302000 1860000 11250 13900 225000 209900
2021-05-12 3205000 320600 15359000 1260000 3049000 270400 272700 404200 70740 237900 14670 221800 47030 2373000 368300 304200 1863000 11310 14180 227500 210800
2021-05-13 3225000 322200 15422000 1266000 3064000 272300 273100 405900 70860 238900 14780 222600 47140 2376000 368500 306500 1868000 11370 14450 230200 211600
2021-05-14 3246000 322600 15489000 1272000 3079000 273800 273600 407200 70990 240000 14900 223500 47230 2379000 368700 308700 1874000 11440 14720 232700 212500
2021-05-15 3263000 324100 15551000 1278000 3095000 274600 274000 408500 71110 241000 15010 224300 47340 2382000 368900 310700 1882000 11510 15000 235200 213300
2021-05-16 3277000 324400 15579000 1284000 3110000 275300 274500 409800 71230 241400 15120 225200 47430 2384000 369100 312500 1888000 11580 15270 237300 214100

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