COVID-19 short-term forecasts Confirmed 2020-05-30


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 The documentation that is provided is still in progress and not peer reviewed.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

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) 2020-05-31 to 2020-06-06

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-30 16214 9592 498440 94858 26734 16908 38571 2395 4739 5094 87512 13018 155671
2020-05-31 17100 10100 522000 99000 27200 17400 38800 2470 4930 5180 90000 13500 161000
2020-06-01 18000 10800 553000 103000 27900 18000 39100 2570 5150 5330 93000 14000 168000
2020-06-02 19000 11500 586000 108000 28700 18500 39400 2670 5370 5520 96000 14500 176000
2020-06-03 20000 12200 621000 113000 29400 19100 39700 2780 5590 5710 100000 15000 185000
2020-06-04 21100 13000 658000 118000 30300 19800 40000 2890 5830 5910 103000 15600 194000
2020-06-05 22300 13900 697000 124000 31200 20400 40400 3000 6090 6120 107000 16200 203000
2020-06-06 23500 14800 738000 130000 32200 21100 40700 3120 6350 6340 111000 16800 213000

Confirmed count forecast Latin America (bold red line in graphs) 2020-05-31 to 2020-06-06

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-30 16214 9592 498440 94858 26734 16908 38571 2395 4739 5094 87512 13018 155671
2020-05-31 17200 10200 529000 98000 27500 17400 38900 2520 4900 5260 90000 13500 161000
2020-06-01 18200 10900 560000 102000 28400 17900 39100 2640 5060 5460 93000 14100 170000
2020-06-02 19300 11700 593000 106000 29400 18500 39300 2780 5210 5650 96000 14600 179000
2020-06-03 20500 12400 627000 110000 30300 19100 39500 2910 5370 5850 99000 15200 188000
2020-06-04 21700 13300 664000 115000 31300 19700 39700 3060 5520 6060 102000 15800 198000
2020-06-05 23000 14200 703000 119000 32400 20300 39900 3210 5680 6280 106000 16400 208000
2020-06-06 24400 15100 744000 124000 33400 21000 40100 3370 5840 6500 109000 17100 219000

Confirmed count scenario forecast (bold purple line in graphs) 2020-05-31 to 2020-06-08

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-30 16214 9592 498440 94858 26734 16908 38571 2395 4739 5094 87512 13018 155671
2020-05-31 17000 10100 514000 98000 27100 17200 38900 2450 4960 5160 91000 13300 157000
2020-06-01 17900 10600 536000 102000 27800 17600 39000 2530 5150 5280 94000 13700 161000
2020-06-02 18600 11100 558000 105000 28400 17800 39200 2610 5330 5400 97000 13900 164000
2020-06-03 19400 11800 576000 108000 29000 18000 39400 2640 5510 5540 100000 14200 168000
2020-06-04 20100 12200 599000 112000 29600 18200 39500 2740 5720 5670 104000 14400 171000
2020-06-05 20700 12500 612000 115000 30100 18400 39600 2760 5920 5790 106000 14600 173000
2020-06-06 21400 12800 630000 119000 30600 18600 39700 2760 6100 5980 109000 14800 176000
2020-06-07 22000 13000 649000 123000 31400 18700 39800 2800 6350 6230 113000 15000 177000
2020-06-08 23100 13500 664000 126000 32000 19000 39900 2840 6570 6450 115000 15100 179000

Peak increase in estimated trend of Confirmed in Latin America 2020-05-30

ArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
Peak date -- -- --05-25 -- --04-24 --05-2505-25 -- -- --
Peak daily increment 4458 3949 304 241
Days from 100 to peak 70 37 46 57
Days from peak/2 to peak 56 25 42 56
Days since peak 5 36 5 5

Initial visual evaluation of forecasts of Confirmed