COVID-19 short-term forecasts Confirmed 2020-04-02


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 The documentation that is provided is still in progress and not peer reviewed.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.
[2020-03-31] 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).
[2020-04-02] Now including more US States, based on New York Times data. And the world.

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 remains preliminary. Also preliminary is the documentation of the medium term forecasts.

Confirmed count forecast average (bold black line in graphs) 2020-04-03 to 2020-04-07

DateUKEUATBEBSCZDEDKESFRIEITNLPLPTROSENOCH
2020-04-02 33718 455201 11129 15348 3994 3858 84794 3386 112065 59105 3849 115242 14697 2946 9034 2738 5568 5147 18827
2020-04-03 38200 495000 11800 16700 4290 4150 92000 3660 122000 65000 4170 120000 15900 3260 9900 2990 6090 5430 20000
2020-04-04 42800 544000 12600 18300 4590 4460 100000 3940 134000 72000 4520 124000 17200 3540 10800 3270 6590 5730 21300
2020-04-05 48100 597000 13500 19900 4920 4790 109000 4230 146000 81000 4900 129000 18700 3840 11800 3560 7120 6060 22700
2020-04-06 54000 656000 14400 21800 5270 5150 119000 4550 161000 90000 5310 134000 20300 4170 12800 3890 7700 6410 24200
2020-04-07 60700 719000 15400 23800 5650 5540 129000 4900 176000 100000 5760 139000 22100 4540 14000 4250 8340 6770 25900

Confirmed count forecast average (bold black line in graphs) 2020-04-03 to 2020-04-07

DateAustraliaBrazilCanadaIranMalaysiaPhilippinesUSWorld
2020-04-02 5116 8044 11284 50468 3116 2633 243453 1356163
2020-04-03 5470 9100 12800 54100 3310 2980 276000 1477000
2020-04-04 5930 10000 14200 58500 3520 3330 314000 1607000
2020-04-05 6440 10900 15800 63300 3750 3720 356000 1747000
2020-04-06 7000 12000 17600 68500 3990 4160 406000 1896000
2020-04-07 7600 13100 19600 74100 4250 4650 462000 2058000

Confirmed count forecast (bold red line in graphs) 2020-04-03 to 2020-04-07

DateUKEUATBEBSCZDEDKESFRIEITNLPLPTROSENOCH
2020-04-02 33718 455201 11129 15348 3994 3858 84794 3386 112065 59105 3849 115242 14697 2946 9034 2738 5568 5147 18827
2020-04-03 37900 495000 11700 16700 4340 4110 91000 3640 121000 64500 4080 119000 15900 3280 9700 2970 5990 5430 20000
2020-04-04 42800 540000 12400 18100 4710 4420 98000 3920 132000 70300 4410 123000 17200 3660 10600 3240 6530 5760 21400
2020-04-05 48200 588000 13100 19600 5100 4730 105000 4230 143000 76900 4760 127000 18600 4070 11500 3520 7120 6090 22900
2020-04-06 54400 642000 13900 21300 5520 5080 113000 4560 155000 84200 5140 131000 20100 4530 12500 3830 7770 6460 24500
2020-04-07 61300 701000 14700 23100 5990 5450 122000 4920 169000 92300 5550 136000 21800 5030 13600 4170 8470 6840 26200

Confirmed count forecast (bold red line in graphs) 2020-04-03 to 2020-04-07

DateAustraliaBrazilCanadaIranMalaysiaPhilippinesUSWorld
2020-04-02 5116 8044 11284 50468 3116 2633 243453 1356163
2020-04-03 5500 8800 12700 53800 3320 2820 274000 1488000
2020-04-04 5930 9800 14500 57700 3550 3070 312000 1621000
2020-04-05 6410 10900 16500 61700 3800 3340 355000 1764000
2020-04-06 6940 12200 18800 66100 4070 3620 406000 1914000
2020-04-07 7520 13600 21500 70900 4350 3940 466000 2076000

Initial visual evaluation of forecasts of Confirmed