COVID-19 short-term forecasts Confirmed 2020-07-11 Latin American Countries


Gnereal 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:
    [2020-07-01] 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.

Peak increase in estimated trend of Confirmed in Latin America 2020-07-11

ArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
Peak date -- -- --06-17 -- -- --04-24 -- --06-1007-05 -- --07-07 --05-30 --
Peak daily increment 31997 7778 181 884 1007 5882
Days from 100 to peak 92 38 35 99 110 73
Days from peak/2 to peak 48 18 36 79 103 53
Last total 97509 47200 1839850 312029 140776 7231 43114 67209 9391 28598 6690 27583 295268 2846 44332 2820 322710 9178
Last daily increment 3449 1635 39023 2755 6803 386 1199 2191 249 979 73 530 6094 0 1075 84 3064 375
Last week 19694 7903 236795 16497 27091 2235 5689 5251 1614 5350 357 3640 38420 327 6183 393 19992 2009
Days since peak 24 78 31 6 4 42

Confirmed count forecast Latin America (bold red line in graphs) 2020-07-12 to 2020-07-18

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-07-11 97509 47200 1839850 312029 140776 7231 43114 67209 9391 28598 6690 27583 295268 2846 44332 2820 322710 9178
2020-07-12 100700 49110 1865000 313700 143500 7487 44520 67940 9850 29750 6759 28310 298100 3114 45280 3046 325900 9570
2020-07-13 104100 51100 1888000 315300 148200 7754 45980 68670 10220 30960 6824 29030 303100 3137 46190 3112 329100 9880
2020-07-14 107700 53150 1931000 317100 153200 8032 47480 69450 10630 32190 6892 29750 309300 3527 47110 3193 332300 10240
2020-07-15 111700 55310 1975000 318800 158400 8316 49050 70190 11040 33490 6956 30470 315600 3527 48010 3338 335400 10680
2020-07-16 115400 57550 2015000 320500 163800 8610 50670 70940 11460 34840 7022 31200 322300 3527 48920 3338 338500 11030
2020-07-17 119500 59880 2064000 322200 169400 8915 52360 71690 11910 36250 7087 31940 329200 3527 49840 3438 341700 11490
2020-07-18 122800 62300 2101000 323900 175200 9232 54090 72440 12260 37710 7153 32680 335100 3527 50760 3555 344800 11980

Confirmed count average forecast Latin America (bold black line in graphs) 2020-07-12 to 2020-07-18

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-07-11 97509 47200 1839850 312029 140776 7231 43114 67209 9391 28598 6690 27583 295268 2846 44332 2820 322710 9178
2020-07-12 99800 48900 1862000 313800 144700 7540 44580 67420 9710 29650 6718 28210 299400 2893 45140 2917 325000 9530
2020-07-13 102800 50750 1885000 316500 149200 7930 45890 67930 10040 30870 6762 28970 305100 2912 46110 2972 327900 9900
2020-07-14 106200 52690 1929000 319200 154400 8360 47120 68680 10400 32160 6815 29750 311100 3306 47040 3037 330800 10290
2020-07-15 109700 54740 1976000 321900 160000 8820 48680 69510 10760 33480 6872 30540 317300 3309 48010 3138 333800 10720
2020-07-16 113000 56860 2021000 324600 166200 9310 50220 70340 11140 34920 6933 31350 323700 3314 49060 3234 336800 11180
2020-07-17 116800 59090 2073000 327400 172500 9830 51830 71190 11530 36460 6997 32190 330100 3332 50050 3369 339800 11650
2020-07-18 120200 61420 2116000 330200 178800 10360 53550 72040 11910 38040 7064 33050 336200 3347 51080 3488 342900 12170

Confirmed count scenario forecast (bold purple line in graphs) 2020-07-12 to 2020-07-20

DateArgentinaBoliviaBrazilChileColombiaCosta RicaDominican RepublicEcuadorEl SalvadorGuatemalaHaitiHondurasMexicoNicaraguaPanamaParaguayPeruVenezuela
2020-07-11 97509 47200 1839850 312029 140776 7231 43114 67209 9391 28598 6690 27583 295268 2846 44332 2820 322710 9178
2020-07-12 100200 48580 1882000 312900 143200 7830 44210 67210 9690 29530 6732 28310 299500 2959 45200 2953 324600 9580
2020-07-13 102600 49570 1920000 314200 147500 8340 45240 67930 9930 30430 6765 28860 304800 3043 46060 3137 326500 9910
2020-07-14 104700 50660 1944000 314500 149700 8650 46100 68480 10110 31180 6794 29400 309000 3043 46750 3144 328400 10160
2020-07-15 107100 51630 1970000 314700 152800 9200 46980 69000 10280 31880 6819 29810 314400 3043 47600 3145 329700 10360
2020-07-16 108500 52360 1997000 315900 155000 9620 47760 69430 10450 32680 6849 30260 318300 3043 48120 3192 331300 10620
2020-07-17 109900 53020 2020000 317400 156800 9990 48440 69840 10560 33380 6879 30850 321800 3043 48800 3254 332300 10780
2020-07-18 111600 53620 2048000 318200 158900 10430 48810 70390 10700 34050 6900 31250 326600 3043 49600 3288 333700 10900
2020-07-19 112800 54320 2072000 319200 160300 10870 49040 70390 10860 34640 6920 31580 329700 3043 50330 3314 334600 11050
2020-07-20 114200 54790 2097000 320100 162400 11240 49350 70390 10970 35260 6948 32080 333500 3043 50880 3349 335200 11190

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

[2020-07-01] 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