COVID-19 short-term forecasts Deaths 2020-04-13


Disclaimer

  • 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. The documentation that is provided is still in progress and not peer reviewed. 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.

Recent changes

[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.
[2020-03-26] Scenario forecasts that are based on what happened in China earlier this year, only for Italy.
[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).
[2020-04-02] Now including more US States, based on New York Times data. And the world.
[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.
[2020-04-08] Minor correction to peak estimates. Added table with scenario forecasts.
[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.
[2020-04-10] Updated documentation with better description of short-term estimates and peak determination.

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.
  • 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, but remains preliminary. Also preliminary is the documentation of the medium term forecasts.

Deaths count average forecast Europe (bold black line in graphs) 2020-04-14 to 2020-04-18

DateUKEUATBEDEDKESFRIEITNLPLPTROSECH
2020-04-13 11329 66821 368 3903 3194 285 17756 14967 365 20465 2823 245 535 331 919 1138
2020-04-14 12200 69500 390 4280 3380 300 18300 15600 390 21000 2930 270 570 350 960 1190
2020-04-15 13200 72500 410 4790 3580 310 18900 16400 430 21500 3060 290 600 380 1030 1240
2020-04-16 14300 75600 430 5340 3790 320 19400 17200 470 22000 3190 310 640 400 1120 1290
2020-04-17 15500 78900 460 5960 4010 330 20000 18000 510 22600 3330 340 680 430 1210 1350
2020-04-18 16700 82300 490 6660 4240 340 20600 18900 550 23200 3470 360 720 450 1310 1410

Deaths count average forecast (bold black line in graphs) 2020-04-14 to 2020-04-18

DateBrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WAWorld
2020-04-13 1328 779 4585 315 23529 725 308 602 498 479 800 884 844 1601 2443 10056 525 147209
2020-04-14 1440 850 4700 350 25500 780 330 670 530 500 880 930 940 1730 2630 10900 540 156000
2020-04-15 1580 930 4820 370 28000 830 360 750 570 520 960 980 1070 1900 2870 11700 560 166000
2020-04-16 1730 1010 4930 400 30700 890 390 840 610 540 1060 1030 1210 2080 3120 12600 580 177000
2020-04-17 1890 1100 5050 430 33700 960 430 950 650 570 1160 1090 1380 2290 3400 13500 600 188000
2020-04-18 2080 1200 5180 460 37000 1030 470 1070 700 590 1270 1150 1570 2510 3690 14600 630 200000

Deaths count forecast Europe (bold red line in graphs) 2020-04-14 to 2020-04-18

DateUKEUATBEDEDKESFRIEITNLPLPTROSECH
2020-04-13 11329 66821 368 3903 3194 285 17756 14967 365 20465 2823 245 535 331 919 1138
2020-04-14 12200 69300 380 4270 3350 290 18300 15600 390 21000 2910 270 570 350 950 1180
2020-04-15 13100 72000 400 4630 3510 300 18800 16200 420 21500 3010 280 610 370 990 1230
2020-04-16 14100 74600 410 5010 3680 320 19400 16800 440 22000 3100 300 650 390 1020 1270
2020-04-17 15100 77300 430 5410 3840 330 19900 17400 470 22500 3190 330 690 400 1050 1320
2020-04-18 16200 80200 450 5860 4010 340 20500 18000 500 23100 3280 350 730 420 1080 1370

Deaths count forecast (bold red line in graphs) 2020-04-14 to 2020-04-18

DateBrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WAWorld
2020-04-13 1328 779 4585 315 23529 725 308 602 498 479 800 884 844 1601 2443 10056 525 147209
2020-04-14 1410 860 4690 360 25400 770 330 640 530 490 890 920 930 1700 2580 10800 540 156000
2020-04-15 1500 940 4800 390 27300 820 350 690 560 510 980 970 1030 1820 2730 11500 550 165000
2020-04-16 1590 1030 4900 430 29300 860 370 740 590 530 1080 1010 1140 1940 2880 12300 560 174000
2020-04-17 1690 1120 5010 480 31500 910 390 790 620 540 1180 1050 1250 2070 3030 13100 580 183000
2020-04-18 1790 1210 5120 520 33800 960 420 850 650 560 1300 1090 1380 2210 3190 14000 590 193000

Deaths count scenario forecast (bold green line in graphs) 2020-04-14 to 2020-04-22

DateEUATDKESITNLPTCH
2020-04-13 66821 368 285 17756 20465 2823 535 1138
2020-04-14 69300 390 300 18300 20800 2960 570 1180
2020-04-15 71500 410 310 18900 21200 3060 610 1230
2020-04-16 73800 420 320 19300 21600 3150 650 1270
2020-04-17 76000 440 330 19800 22000 3250 690 1310
2020-04-18 78100 460 340 20200 22400 3330 730 1340
2020-04-19 80100 470 340 20500 22800 3400 760 1370
2020-04-20 82100 490 350 20800 23100 3470 800 1400
2020-04-21 83900 500 350 21100 23300 3550 830 1430
2020-04-22 85600 520 360 21400 23600 3610 860 1460

Peak increase in estimated trend of Deaths in Europe 2020-04-13

UKEUATBEDEDKESFRIEITNLPLPTROSECH
Peak date --04-07 -- --04-0804-0403-3004-06 --03-2804-07 -- -- -- --04-04
Peak daily increment 3245 233 18 893 1049 826 160 61
Days from 100 to peak 34 16 3 17 22 24 18 12
Days from peak/2 to peak 24 16 14 13 15 19 18 17
Days since peak 6 5 9 14 7 16 6 9

Peak increase in estimated trend of Deaths 2020-04-13

BrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WAWorld
Peak date04-09 --03-19 -- --04-08 -- --04-0904-06 --04-07 -- -- -- --04-06 --
Peak daily increment 115 150 49 37 38 59 30
Days from 100 to peak 12 14 11 8 7 11 15
Days from peak/2 to peak 15 16 18 16 15 15 30
Days since peak 4 25 5 4 7 6 7

Initial visual evaluation of forecasts of Deaths