COVID-19 short-term forecasts Deaths 2020-03-31


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 The documentation that is provided is still in progress and not peer reviewed.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

Moderation of forecast

[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.
[2020-03-29] Now including some 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 +). Created more plausible 90% confidence bands (dotted line in same colour).

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 it seems that our forecasts need slightly less frequent updating.
    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. Again: no other epidemiological data is used.
  • We will probably revise or 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.
  • We will probably revise or 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 forecasted, and combined with trend forecasts into an overall forecast.
  • EU-BS is Estonia, Latvia, and Lithuania together.
  • This paper describes the methodology and gives further references, but is still preliminary.

Deaths count forecast average (bold black line in graphs) 2020-04-01 to 2020-04-05

DateUKEUATBEBSCZDEDKESFRGRIEITNLPLPTROSENOCH
2020-03-31 1789 27863 128 705 35 31 775 90 8464 3523 49 71 12428 1039 33 160 82 180 39 433
2020-04-01 2070 30900 140 820 40 40 890 100 9400 3950 50 80 13400 1170 40 180 90 210 40 490
2020-04-02 2320 34300 160 920 40 40 1000 110 10400 4330 60 90 14500 1300 40 200 100 220 50 530
2020-04-03 2610 38000 170 1030 50 40 1120 110 11400 4750 60 110 15700 1440 40 220 110 240 50 580
2020-04-04 2940 42200 190 1160 50 50 1260 120 12600 5210 60 120 16900 1590 50 240 120 260 60 630
2020-04-05 3310 46800 200 1310 60 60 1420 130 14000 5730 70 140 18300 1760 50 270 140 290 60 690

Deaths count forecast average (bold black line in graphs) 2020-04-01 to 2020-04-05

DateBrazilCanadaIranMalaysiaPhilippinesUSUS-CAUS-NJUS-NYUS-WA
2020-03-31 201 101 2898 43 88 3873 183 267 1550 226
2020-04-01 230 110 3050 50 90 4550 200 310 1840 240
2020-04-02 250 120 3230 50 100 5150 220 350 2130 250
2020-04-03 270 140 3430 50 110 5850 240 390 2480 270
2020-04-04 290 150 3630 60 120 6650 260 440 2890 290
2020-04-05 310 160 3850 60 130 7570 290 490 3380 310

Deaths count forecast (bold red line in graphs) 2020-04-01 to 2020-04-05

DateUKEUATBEBSCZDEDKESFRGRIEITNLPLPTROSENOCH
2020-03-31 1789 27863 128 705 35 31 775 90 8464 3523 49 71 12428 1039 33 160 82 180 39 433
2020-04-01 2030 30700 140 860 40 40 860 100 9200 3960 50 80 13400 1160 40 170 80 200 40 480
2020-04-02 2340 33900 160 1050 40 50 950 110 10100 4450 60 90 14400 1300 40 180 90 230 50 540
2020-04-03 2690 37400 170 1280 40 60 1050 120 11000 4990 60 100 15400 1460 40 200 90 260 60 610
2020-04-04 3090 41200 190 1550 40 70 1160 130 12100 5590 70 120 16600 1640 50 210 100 290 60 690
2020-04-05 3540 45500 210 1880 40 80 1280 140 13200 6260 70 130 17800 1830 50 220 100 320 70 770

Deaths count forecast (bold red line in graphs) 2020-04-01 to 2020-04-05

DateBrazilCanadaIranMalaysiaPhilippinesUSUS-CAUS-NJUS-NYUS-WA
2020-03-31 201 101 2898 43 88 3873 183 267 1550 226
2020-04-01 230 110 3040 40 90 4530 200 300 1700 240
2020-04-02 260 120 3200 50 100 5340 230 330 1910 250
2020-04-03 290 140 3360 50 100 6300 250 370 2170 260
2020-04-04 330 160 3540 50 110 7400 280 410 2440 270
2020-04-05 380 180 3730 50 110 8680 320 450 2740 290

Initial visual evaluation of forecasts of Deaths