COVID-19 short-term forecasts Deaths 2020-04-10


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 The documentation that is provided is still in progress and not peer reviewed.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) 2020-04-11 to 2020-04-15

DateUKEUATBEDEDKESFRIEITNLPTROSECH
2020-04-10 8958 59577 319 3019 2767 247 16081 13197 287 18849 2511 435 270 870 1002
2020-04-11 10000 62900 350 3420 3030 260 16700 14300 320 19400 2660 470 290 980 1060
2020-04-12 11000 66400 370 3780 3320 280 17300 15500 350 19900 2810 500 320 1100 1110
2020-04-13 12200 70100 400 4180 3640 290 17900 16900 390 20400 2970 530 340 1230 1170
2020-04-14 13500 74000 430 4620 3980 310 18500 18400 430 21000 3140 570 370 1380 1230
2020-04-15 14900 78100 470 5120 4370 330 19200 20000 470 21500 3320 610 390 1550 1290

Deaths count average forecast (bold black line in graphs) 2020-04-11 to 2020-04-15

DateBrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WA
2020-04-10 1057 557 4232 221 18586 624 253 448 418 425 607 755 599 1280 1932 7844 483
2020-04-11 1180 620 4360 240 20800 690 280 520 470 460 690 820 700 1440 2170 8700 510
2020-04-12 1320 700 4480 250 23200 750 310 590 520 510 770 890 800 1570 2420 9500 550
2020-04-13 1460 780 4620 270 25900 820 340 680 570 570 860 970 910 1720 2700 10500 590
2020-04-14 1620 870 4750 290 28800 900 370 770 640 630 960 1050 1040 1880 3010 11500 630
2020-04-15 1800 980 4890 310 32200 980 410 890 700 700 1070 1140 1190 2060 3350 12700 670

Deaths count forecast Europe (bold red line in graphs) 2020-04-11 to 2020-04-15

DateUKEUATBEDEDKESFRIEITNLPTROSECH
2020-04-10 8958 59577 319 3019 2767 247 16081 13197 287 18849 2511 435 270 870 1002
2020-04-11 9700 62500 340 3690 3010 260 16700 13900 310 19400 2640 460 290 960 1050
2020-04-12 10500 65600 370 4380 3250 270 17200 14800 330 19900 2780 480 320 1060 1100
2020-04-13 11300 68900 400 5190 3520 280 17800 15700 350 20400 2930 510 350 1180 1150
2020-04-14 12200 72300 430 6110 3800 290 18300 16700 370 21000 3080 530 380 1300 1200
2020-04-15 13100 75900 470 7180 4110 300 18900 17700 400 21500 3240 560 410 1440 1260

Deaths count forecast (bold red line in graphs) 2020-04-11 to 2020-04-15

DateBrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WA
2020-04-10 1057 557 4232 221 18586 624 253 448 418 425 607 755 599 1280 1932 7844 483
2020-04-11 1170 600 4350 240 20500 710 290 630 500 450 680 810 790 1470 2160 8200 510
2020-04-12 1280 660 4480 260 22600 790 320 810 580 470 750 860 990 1700 2410 8800 540
2020-04-13 1410 710 4600 280 24900 880 360 1040 660 500 840 920 1250 1940 2680 9400 570
2020-04-14 1550 770 4720 300 27400 980 400 1310 750 520 930 980 1550 2210 2970 10100 610
2020-04-15 1700 830 4850 330 30200 1090 450 1650 860 550 1030 1050 1930 2520 3290 10800 640

Deaths count scenario forecast (bold green line in graphs) 2020-04-11 to 2020-04-19

DateEUATDKESITNLPTCH
2020-04-10 59577 319 247 16081 18849 2511 435 1002
2020-04-11 62300 340 260 16700 19300 2660 470 1050
2020-04-12 65000 340 270 17300 19700 2820 490 1100
2020-04-13 67500 350 280 17800 20100 3010 520 1140
2020-04-14 69900 350 300 18400 20400 3150 560 1180
2020-04-15 72100 350 310 18900 20700 3150 570 1220
2020-04-16 74400 350 320 19400 21000 3180 590 1260
2020-04-17 76600 350 330 19800 21300 3250 610 1300
2020-04-18 78600 350 330 20200 21600 3340 630 1330
2020-04-19 80700 350 340 20600 21900 3410 650 1370

Peak increase in estimated trend of Deaths in Europe 2020-04-10

UKEUATBEDEDKESFRIEITNLPTROSECH
Peak date --04-04 -- -- --04-0404-02 -- --03-2804-04 -- -- --04-04
Peak daily increment 3211 18 899 827 155 61
Days from 100 to peak 31 3 20 24 15 12
Days from peak/2 to peak 21 14 16 19 15 17
Days since peak 6 6 8 13 6 6

Peak increase in estimated trend of Deaths 2020-04-10

BrazilCanadaIranPhilippinesUSUS-CAUS-COUS-CTUS-FLUS-GAUS-ILUS-LAUS-MAUS-MIUS-NJUS-NYUS-WA
Peak date -- --03-19 -- -- -- -- -- -- -- -- -- -- -- -- -- --
Peak daily increment 150
Days from 100 to peak 14
Days from peak/2 to peak 16
Days since peak 22

Initial visual evaluation of forecasts of Deaths