COVID-19 short-term forecasts Deaths 2020-03-30


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 The documentation that is provided is still in progress and not peer reviewed.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) 2020-03-31 to 2020-04-04

DateUKEUATBEBSDEDKESFRGRIEITNLPLPTROSENOCH
2020-03-30 1408 25132 108 513 32 645 77 7716 3024 43 54 11591 864 31 140 65 146 32 359
2020-03-31 1630 28000 120 590 40 750 80 8600 3370 50 60 12600 980 40 160 80 170 40 400
2020-04-01 1830 31200 140 660 40 850 90 9600 3740 50 70 13700 1090 40 180 80 190 40 440
2020-04-02 2070 34900 150 740 40 960 100 10700 4150 50 80 14900 1220 40 190 90 210 40 480
2020-04-03 2340 38900 160 830 50 1080 110 11900 4610 60 100 16300 1360 40 210 100 240 40 520
2020-04-04 2650 43500 180 930 50 1220 120 13300 5130 60 110 17800 1520 50 230 110 270 50 570

Deaths count forecast average (bold black line in graphs) 2020-03-31 to 2020-04-04

DateBrazilCanadaIranMalaysiaPhilippinesUSUS-CAUS-NJUS-NYUS-WA
2020-03-30 159 80 2757 37 78 2978 146 199 1224 221
2020-03-31 180 90 2910 40 80 3460 160 230 1460 240
2020-04-01 190 100 3090 40 90 3930 180 260 1680 250
2020-04-02 200 110 3290 50 100 4470 190 300 1930 270
2020-04-03 220 120 3500 50 110 5080 210 340 2230 290
2020-04-04 230 130 3720 50 120 5780 230 390 2580 310

Deaths count forecast (bold red line in graphs) 2020-03-31 to 2020-04-04

DateUKEUATBEBSDEDKESFRGRIEITNLPLPTROSENOCH
2020-03-30 1408 25132 108 513 32 645 77 7716 3024 43 54 11591 864 31 140 65 146 32 359
2020-03-31 1650 27700 120 570 30 750 80 8300 3220 40 60 12500 960 30 150 90 160 30 370
2020-04-01 1910 30600 140 640 30 860 80 9100 3510 50 70 13500 1070 40 170 110 180 40 410
2020-04-02 2210 33700 160 720 40 990 90 10000 3820 50 80 14600 1190 50 180 140 200 40 440
2020-04-03 2530 37200 180 800 40 1140 90 10900 4160 50 100 15800 1320 50 200 180 220 40 480
2020-04-04 2900 41000 200 900 40 1310 100 11900 4530 60 110 17000 1460 60 220 230 250 50 520

Deaths count forecast (bold red line in graphs) 2020-03-31 to 2020-04-04

DateBrazilCanadaIranMalaysiaPhilippinesUSUS-CAUS-NJUS-NYUS-WA
2020-03-30 159 80 2757 37 78 2978 146 199 1224 221
2020-03-31 180 90 2910 40 80 3360 160 220 1390 230
2020-04-01 200 110 3080 40 90 3820 170 250 1590 240
2020-04-02 220 120 3260 50 90 4340 180 290 1820 260
2020-04-03 240 140 3450 50 100 4920 200 320 2070 270
2020-04-04 260 160 3650 50 100 5570 210 360 2360 280

Initial visual evaluation of forecasts of Deaths