COVID-19 short-term forecasts Confirmed 2020-04-27


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 The documentation that is provided is still in progress and not peer reviewed.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.
[2020-04-16] Added scenario forecasts to all graphs now. This would now be the preferred forecast for most.
This is the first time with a peak in confirmed UK cases (also for deaths, but this is uncertain because it is at the same date).
[2020-04-17] Bird and Nielsen look into nowcasting death counts in England.
[2020-04-24] A summary of our work on short-term COVID-19 forecasting appeared as a voxeu.
[2020-04-27] Our short-term COVID-19 forecasting paper is now available as Nuffield Economics Discussion Paper 2020-W06.
A small adjustment has been made to the scenario forecast methodology, and will be documented shortly.

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. Data definition and collection differs between countries and may change over time.
  • 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. Also available as Nuffield Economics Discussion Paper 2020-W06. Still preliminary is the documentation of the medium term forecasts.

Confirmed count average forecast Latin America (bold black line in graphs) 2020-04-28 to 2020-05-04

DateArgentinaBrazilChileColombiaDominican RepublicEcuadorMexicoPanamaPeru
2020-04-27 4003 67446 13813 5597 6293 23240 15529 6021 28699
2020-04-28 4180 72000 14400 5840 6470 26000 16500 6250 31200
2020-04-29 4400 78000 15100 6090 6650 32000 17700 6460 33800
2020-04-30 4640 84000 15900 6360 6840 40000 19000 6680 36600
2020-05-01 4900 90000 16700 6630 7030 50000 20300 6910 39700
2020-05-02 5170 97000 17500 6920 7230 64000 21800 7150 43100
2020-05-03 5450 105000 18400 7220 7430 80000 23400 7390 46800
2020-05-04 5740 113000 19300 7540 7650 103000 25100 7650 50700

Confirmed count forecast Latin America (bold red line in graphs) 2020-04-28 to 2020-05-04

DateArgentinaBrazilChileColombiaDominican RepublicEcuadorMexicoPanamaPeru
2020-04-27 4003 67446 13813 5597 6293 23240 15529 6021 28699
2020-04-28 4190 72000 14500 5810 6440 24700 16500 6220 31900
2020-04-29 4390 78000 15200 6040 6600 26200 17500 6440 34800
2020-04-30 4600 83000 15900 6280 6770 27900 18600 6670 37900
2020-05-01 4830 89000 16700 6530 6930 29600 19700 6900 41300
2020-05-02 5060 96000 17500 6790 7100 31500 20900 7140 45000
2020-05-03 5310 103000 18400 7060 7270 33500 22200 7390 49000
2020-05-04 5570 110000 19300 7340 7450 35600 23500 7650 53400

Confirmed count scenario forecast (bold purple line in graphs) 2020-04-28 to 2020-05-06

DateArgentinaBrazilChileColombiaDominican RepublicEcuadorMexicoPanamaPeru
2020-04-27 4003 67446 13813 5597 6293 23240 15529 6021 28699
2020-04-28 4190 70500 14200 5780 6410 25500 16400 6150 30500
2020-04-29 4330 73600 14600 5940 6550 27100 17200 6290 32200
2020-04-30 4470 76700 15000 6090 6680 28700 17900 6420 33600
2020-05-01 4580 79600 15300 6220 6820 29600 18500 6540 34900
2020-05-02 4660 82200 15600 6340 6950 30100 19000 6640 36200
2020-05-03 4750 84200 15900 6430 7080 30500 19500 6740 37400
2020-05-04 4840 86300 16100 6500 7200 31500 20000 6810 38400
2020-05-05 4920 88600 16400 6570 7330 31500 20300 6890 39000
2020-05-06 4980 90400 16600 6630 7440 32700 20800 6940 39500

Peak increase in estimated trend of Confirmed in Latin America 2020-04-27

ArgentinaBrazilChileColombiaDominican RepublicEcuadorMexicoPanamaPeru
Peak date -- -- --04-2404-1904-24 -- -- --
Peak daily increment 254 277 7006
Days from 100 to peak 36 29 37
Days from peak/2 to peak 35 28 19
Days since peak 3 8 3

Initial visual evaluation of forecasts of Confirmed