COVID-19 short-term forecasts Confirmed 2020-05-23


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 The documentation that is provided is still in progress and not peer reviewed.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.
[2020-04-29] See our blog entry at the International Institute of Forecasters.
US history of death counts revised in Johns Hopkins/CSSE data.
UK death counts have been revised to include the deaths in care homes. In the Johns Hopkins/CSSE data set, which we use, the entire history has been revised. So forecasts made up to 2020-04-29 cannot be compared to later outcomes. In the ECDC data set only the last observation has changed, causing a jump in the series.
[2020-05-06] The New York Times is in the process of redefining its US state data. Unfortunately, at the moment only the last observation has changed (e.g New York deaths jumped from 19645 on 2020-05-05 to 25956 a day later). This means the data is currently useless; however it does bring it close to the Johns Hopkins/CSSE count (25626 on 2020-05-06). The aggregate US count is based on JH/CSSE so unaffected. We now use Johns Hopkins/CSSE US state data, including all states with sufficient counts. So the new forecasts cannot be compared to those previously.
A minor change is that we show the graph without scenario forecast if no peak has been detected yet.
[2020-05-13] We now omit countries with fewer than 200 confirmed cases in the last week (25 for deaths).
The short-term paper has some small updates, including further comparisons with other models.
Data for Ecuador are not reliable enough for forecasting.
Switched to an improved version of scenario forecasting.
[2020-05-18] Minor fixes to the improved version of scenario forecasting, backported to 2020-05-13.
[2020-05-20] Problem with UK confirmed cases: negative daily count. This makes the forecasts temporarily unreliable.
Updated the second paper.

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) 2020-05-24 to 2020-05-30

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaPeru
2020-05-23 11353 5915 347398 65393 20177 14422 36258 3054 3477 65856 10577 115754
2020-05-24 11800 6230 370000 70000 21000 14600 36600 3140 3600 69300 10600 119000
2020-05-25 12400 6610 396000 75000 22000 15000 37000 3300 3760 73100 10700 123000
2020-05-26 13100 7010 423000 80000 23000 15300 37500 3510 3930 77000 10900 127000
2020-05-27 13800 7430 452000 86000 24100 15600 38000 3740 4120 81200 11000 132000
2020-05-28 14600 7890 484000 91000 25200 15900 38400 4000 4310 85600 11200 136000
2020-05-29 15500 8360 517000 98000 26400 16300 38900 4270 4510 90300 11300 141000
2020-05-30 16300 8870 553000 105000 27700 16600 39400 4550 4720 95200 11500 145000

Confirmed count forecast Latin America (bold red line in graphs) 2020-05-24 to 2020-05-30

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaPeru
2020-05-23 11353 5915 347398 65393 20177 14422 36258 3054 3477 65856 10577 115754
2020-05-24 12100 6240 372000 70000 21100 14700 36600 3310 3690 69000 10800 119000
2020-05-25 12900 6590 397000 75000 22100 15000 37000 3590 3850 72600 11000 123000
2020-05-26 13800 6970 423000 81000 23200 15300 37400 3890 4030 76300 11200 126000
2020-05-27 14700 7360 452000 87000 24400 15700 37800 4210 4210 80300 11500 130000
2020-05-28 15700 7780 482000 93000 25600 16000 38200 4550 4400 84400 11700 134000
2020-05-29 16700 8220 515000 99000 26800 16400 38600 4920 4590 88800 11900 138000
2020-05-30 17800 8680 549000 107000 28100 16700 39000 5310 4800 93400 12200 142000

Confirmed count scenario forecast (bold purple line in graphs) 2020-05-24 to 2020-06-01

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaPeru
2020-05-23 11353 5915 347398 65393 20177 14422 36258 3054 3477 65856 10577 115754
2020-05-24 11900 6190 367000 69400 20800 14600 36400 3220 3670 68100 10700 118000
2020-05-25 12400 6480 382000 73400 21500 14800 36500 3430 3800 70500 10900 121000
2020-05-26 12900 6730 397000 76400 22200 14900 36700 3620 4000 72900 10900 124000
2020-05-27 13400 7010 409000 79600 22800 15100 36800 3800 4150 75100 10900 126000
2020-05-28 13900 7170 422000 82500 23300 15200 37000 4000 4250 77100 11000 129000
2020-05-29 14400 7430 434000 85300 24000 15400 37100 4140 4350 78800 11000 132000
2020-05-30 14700 7670 446000 87300 24500 15600 37200 4270 4390 80500 11000 134000
2020-05-31 15000 7850 455000 89600 25200 15900 37200 4430 4450 82100 11100 136000
2020-06-01 15300 8120 468000 91700 25900 16100 37200 4550 4520 83600 11100 138000

Peak increase in estimated trend of Confirmed in Latin America 2020-05-23

ArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorGuatemalaHondurasMexicoPanamaPeru
Peak date -- -- -- -- --05-1004-24 -- -- -- -- --
Peak daily increment 372 3817
Days from 100 to peak 50 37
Days from peak/2 to peak 48 26
Days since peak 13 29

Initial visual evaluation of forecasts of Confirmed