COVID-19 short-term forecasts Confirmed 2020-05-16


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 The documentation that is provided is still in progress and not peer reviewed.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

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) 2020-05-17 to 2020-05-23

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorHondurasMexicoPanamaPeru
2020-05-16 7805 3826 233511 41428 14939 12110 32763 2565 47144 9449 88541
2020-05-17 8200 4010 246000 43900 15700 12300 32900 2590 49700 9600 93000
2020-05-18 8600 4250 262000 46800 16500 12500 33100 2660 52500 9700 98000
2020-05-19 9000 4510 279000 50000 17400 12800 33400 2730 55500 9900 104000
2020-05-20 9400 4790 297000 53300 18400 13000 33600 2820 58600 10000 110000
2020-05-21 9800 5080 316000 56900 19400 13300 33900 2900 62000 10200 116000
2020-05-22 10300 5400 337000 60700 20400 13600 34200 2990 65500 10400 122000
2020-05-23 10800 5720 359000 64700 21500 13900 34500 3090 69200 10500 129000

Confirmed count forecast Latin America (bold red line in graphs) 2020-05-17 to 2020-05-23

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorHondurasMexicoPanamaPeru
2020-05-16 7805 3826 233511 41428 14939 12110 32763 2565 47144 9449 88541
2020-05-17 8200 4120 250000 44500 15700 12300 33400 2630 49500 9600 95000
2020-05-18 8500 4400 268000 47400 16600 12600 34000 2710 51900 9700 101000
2020-05-19 8900 4700 288000 50500 17500 12900 34600 2800 54500 9900 107000
2020-05-20 9300 5010 308000 53800 18400 13200 35300 2890 57200 10000 114000
2020-05-21 9700 5350 330000 57300 19300 13500 35900 2980 60100 10200 122000
2020-05-22 10200 5700 353000 61000 20400 13800 36600 3070 63100 10300 130000
2020-05-23 10600 6080 379000 65000 21500 14100 37300 3170 66300 10500 138000

Confirmed count scenario forecast (bold purple line in graphs) 2020-05-17 to 2020-05-25

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorHondurasMexicoPanamaPeru
2020-05-16 7805 3826 233511 41428 14939 12110 32763 2565 47144 9449 88541
2020-05-17 8080 4060 245000 43900 15500 12300 32800 2640 49100 9500 92000
2020-05-18 8310 4290 257000 47000 16000 12600 33100 2730 51000 9600 95000
2020-05-19 8470 4540 265000 49400 16400 12900 33400 2810 52100 9700 98000
2020-05-20 8670 4810 276000 52400 17100 13200 33900 2910 54000 9800 101000
2020-05-21 8790 5010 285000 54100 17500 13400 34500 2990 55200 9900 104000
2020-05-22 8900 5200 295000 56200 17900 13700 34700 3060 56600 10000 107000
2020-05-23 9050 5360 303000 57900 18300 13900 34800 3130 58200 10000 109000
2020-05-24 9160 5530 311000 59400 18700 14100 34800 3190 59400 10100 112000
2020-05-25 9300 5690 318000 60800 19000 14400 34800 3260 60600 10100 114000

Peak increase in estimated trend of Confirmed in Latin America 2020-05-16

ArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorHondurasMexicoPanamaPeru
Peak date -- -- -- -- --05-0904-2405-07 --04-23 --
Peak daily increment 372 5080 155 226
Days from 100 to peak 49 37 39 35
Days from peak/2 to peak 47 23 40 35
Days since peak 7 22 9 23

Initial visual evaluation of forecasts of Confirmed