COVID-19 short-term forecasts Confirmed 2020-12-06 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 2020-12-06

ArgentinaBahamasBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHaitiHondurasJamaicaMexicoNicaraguaPanamaParaguayPeruSurinameTrinidad and TobagoUruguayVenezuela
Peak date (mm-dd)10-1910-1712-0307-1708-0406-0608-1309-1407-2609-2311-0507-1809-2111-0406-2809-2210-0505-26 -- --08-0208-1311-22 --09-08
Peak daily increment 14377 104 1282 1578 45353 7362 11286 1225 1408 1225 195 2699 66 17 795 160 23280 145 8364 89 42 1086
Days since peak 48 50 3 142 124 183 115 83 133 74 31 141 76 32 161 75 62 194 126 115 14 89
Last total 1463110 7570 7769 145560 6603540 560382 1371103 143685 148453 197998 40131 125550 5665 9370 111023 11120 1175850 5838 177719 87920 972688 5324 6767 7303 104442
Last daily increment 3278 0 168 68 26363 1714 8854 0 798 607 413 198 28 0 1063 57 7455 0 1812 707 1828 0 16 338 265
Last week 38577 29 1915 852 267662 8639 54297 4047 4465 5313 1726 3488 259 76 2770 357 62307 54 11913 5496 10158 12 98 1446 2048
Previous peak date -- -- -- -- -- -- -- -- --04-2408-05 -- --06-06 -- -- -- -- --06-27 -- --09-19 -- --
Previous peak daily increment 7756 420 179 155 119
Low between peaks -4346 90 6 20

Confirmed count forecast Latin America (bold red line in graphs) 2020-12-07 to 2020-12-13

DateArgentinaBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruUruguayVenezuela
2020-12-06 1463110 7769 145560 6603540 560382 1371103 143685 148453 197998 40131 125550 5665 111023 11120 1175850 177719 87920 972688 7303 104442
2020-12-07 1469000 7909 145700 6604000 561600 1379000 146300 148900 198600 40130 125700 5704 111400 11180 1188000 179600 89190 974800 7578 104800
2020-12-08 1476000 8037 145800 6650000 562600 1387000 146800 149300 199400 40630 126400 5743 111700 11240 1200000 181400 90190 975700 7841 105100
2020-12-09 1484000 8173 145900 6699000 563600 1396000 147900 149900 200400 40670 127000 5782 112000 11300 1211000 183200 91190 976200 8104 105400
2020-12-10 1491000 8300 146000 6742000 565000 1403000 149000 150800 201400 40710 127600 5820 112400 11350 1222000 185000 92160 978200 8360 105700
2020-12-11 1498000 8428 146100 6778000 566500 1411000 150100 151500 202100 41190 128300 5859 112800 11410 1233000 186900 93140 979600 8620 106000
2020-12-12 1502000 8556 146200 6823000 568000 1419000 150100 152400 203100 41200 128900 5897 113100 11470 1244000 188700 94120 983200 8884 106300
2020-12-13 1506000 8685 146300 6845000 569500 1427000 150100 153100 203800 41480 129000 5936 113500 11520 1256000 190600 95110 984700 9154 106700

Confirmed count average forecast Latin America (bold black line in graphs) 2020-12-07 to 2020-12-13

DateArgentinaBelizeBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaGuyanaHondurasJamaicaMexicoPanamaParaguayPeruUruguayVenezuela
2020-12-06 1463110 7769 145560 6603540 560382 1371103 143685 148453 197998 40131 125550 5665 111023 11120 1175850 177719 87920 972688 7303 104442
2020-12-07 1468000 7980 145600 6626000 561800 1380000 145200 149100 198600 40300 125800 5702 111500 11180 1185000 179400 88630 974200 7561 104700
2020-12-08 1474000 8320 145700 6670000 562800 1388000 146000 149700 199200 40620 126400 5740 111900 11230 1194000 180800 89570 975300 7777 105000
2020-12-09 1480000 8670 145800 6717000 563700 1396000 147100 150400 199800 40710 126900 5777 112200 11280 1203000 182300 90520 976300 7996 105400
2020-12-10 1487000 9060 145900 6761000 565100 1404000 148100 151200 200400 40790 127400 5815 112600 11330 1211000 183700 91400 977800 8216 105700
2020-12-11 1492000 9430 145900 6797000 566600 1413000 149200 151900 201000 41100 128000 5852 112900 11390 1220000 185100 92310 979000 8432 106000
2020-12-12 1499000 9820 146000 6838000 568100 1421000 149800 152600 201600 41180 128500 5891 113300 11450 1228000 186500 93130 980800 8666 106300
2020-12-13 1503000 10250 146000 6861000 569400 1429000 150300 153300 202100 41300 128800 5929 113700 11510 1236000 187700 93950 982300 8907 106600

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