COVID-19 short-term forecasts Confirmed 2020-12-01 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:
    [2020-10-11]Short-term forecasting of the coronavirus pandemic (with Jennie Castle and David Hendry) is now in press at the International Journal of Forecasting.

Peak increase in estimated trend of Confirmed in Latin America 2020-12-01

ArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)10-1910-1711-2807-1708-0406-0608-1311-2307-2609-2311-0107-1809-2111-0406-2809-2210-0505-26 -- --08-0208-1309-19 --09-08
Peak daily increment 14377 104 85 1578 45354 7361 11286 1351 1408 1225 182 2699 66 18 795 160 23280 145 8364 89 119 1086
Days since peak 43 45 3 137 119 178 110 8 128 69 30 136 71 27 156 70 57 189 121 110 73 84
Last total 1432570 7543 5854 144810 6386787 552864 1324792 140172 144302 193673 39130 122774 5423 9296 108253 10810 1122362 5838 167311 83479 963605 5319 6685 6024 102621
Last daily increment 8037 2 0 102 50909 1121 7986 534 314 988 725 712 17 2 0 47 8819 54 1505 1055 1075 7 16 167 227
Last week 42182 74 431 534 220181 8772 53801 5652 4906 6443 1246 2785 187 48 2137 322 51875 54 8779 4601 11166 14 182 1036 1804
Previous peak date -- -- -- -- -- -- -- -- --04-2408-05 -- --06-06 -- -- -- -- -- -- -- -- -- -- --
Previous peak daily increment 7756 420 179
Low between peaks -4346 90 6

Confirmed count forecast Latin America (bold red line in graphs) 2020-12-02 to 2020-12-08

DateArgentinaBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruUruguayVenezuela
2020-12-01 1432570 5854 144810 6386787 552864 1324792 140172 144302 193673 39130 122774 108253 10810 1122362 167311 83479 963605 6024 102621
2020-12-02 1439000 5921 144900 6405000 553800 1333000 141200 144300 194500 39130 123400 108600 10870 1129000 168600 84180 965800 6191 102900
2020-12-03 1446000 5987 145000 6442000 555300 1340000 142300 145600 195300 39280 124100 108900 10920 1136000 169800 84860 966000 6352 103200
2020-12-04 1453000 6051 145100 6479000 556800 1348000 143500 146400 196100 39650 124500 109200 10980 1143000 171000 85540 969100 6510 103500
2020-12-05 1459000 6115 145200 6520000 558300 1355000 143700 147100 196900 39690 125200 109600 11030 1149000 172100 86210 972400 6665 103900
2020-12-06 1462000 6179 145300 6539000 559600 1362000 143700 147800 197700 39750 125300 109900 11090 1156000 173300 86880 973700 6820 104200
2020-12-07 1466000 6243 145300 6558000 560900 1370000 146000 148300 198500 39770 125400 110200 11140 1163000 174500 87550 974200 6976 104500
2020-12-08 1474000 6308 145400 6599000 561800 1377000 146700 148500 199300 40260 126200 110500 11200 1169000 175700 88220 975200 7135 104800

Confirmed count average forecast Latin America (bold black line in graphs) 2020-12-02 to 2020-12-08

DateArgentinaBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasJamaicaMexicoPanamaParaguayPeruUruguayVenezuela
2020-12-01 1432570 5854 144810 6386787 552864 1324792 140172 144302 193673 39130 122774 108253 10810 1122362 167311 83479 963605 6024 102621
2020-12-02 1439000 5911 144900 6436000 553800 1333000 141200 144800 194600 39280 123300 108500 10870 1131000 168600 84260 965100 6178 102900
2020-12-03 1446000 5983 145000 6471000 555300 1340000 142200 145700 195200 39420 123900 108900 10920 1139000 169800 84970 966400 6315 103200
2020-12-04 1453000 6045 145000 6506000 556800 1348000 143300 146500 195900 39660 124400 109200 10980 1146000 170900 85700 968200 6456 103500
2020-12-05 1459000 6107 145100 6550000 558400 1356000 143900 147300 196600 39740 124900 109500 11040 1156000 172000 86410 970100 6599 103800
2020-12-06 1463000 6179 145100 6568000 559700 1363000 144400 147900 197100 39860 125300 109900 11100 1164000 173100 87130 971500 6744 104200
2020-12-07 1469000 6242 145200 6584000 561000 1371000 145800 148500 197500 39960 125600 110200 11150 1170000 174200 87830 972700 6879 104500
2020-12-08 1476000 6307 145200 6616000 561900 1379000 146700 149000 197800 40170 126200 110500 11210 1177000 175200 88590 974000 7024 104800

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

[2020-10-11]Short-term forecasting of the coronavirus pandemic (with Jennie Castle and David Hendry) is now in press at the International Journal of Forecasting.
[2020-10-10]Temporarily 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