COVID-19 short-term forecasts Confirmed 2020-05-27


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 The documentation that is provided is still in progress and not peer reviewed.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.
[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) 2020-05-28 to 2020-06-03

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-27 13933 7768 411821 82289 24104 15723 38103 2109 4145 4640 78023 11728 135905
2020-05-28 14700 8100 426000 87000 25200 16000 38400 2180 4440 4840 82000 12100 141000
2020-05-29 15500 8600 443000 93000 26400 16200 38700 2260 4790 5090 86000 12500 148000
2020-05-30 16500 9100 461000 99000 27700 16500 39100 2340 5150 5350 90000 12900 154000
2020-05-31 17400 9700 480000 105000 29100 16900 39500 2430 5550 5630 95000 13300 162000
2020-06-01 18500 10300 500000 112000 30500 17200 39900 2520 5970 5930 100000 13800 169000
2020-06-02 19500 10900 521000 119000 31900 17500 40400 2610 6430 6240 105000 14300 177000
2020-06-03 20700 11600 542000 127000 33500 17800 40800 2710 6920 6570 111000 14800 186000

Confirmed count forecast Latin America (bold red line in graphs) 2020-05-28 to 2020-06-03

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-27 13933 7768 411821 82289 24104 15723 38103 2109 4145 4640 78023 11728 135905
2020-05-28 14700 8300 427000 87000 25300 16100 38400 2180 4490 4860 82000 12100 142000
2020-05-29 15500 8800 444000 93000 26500 16400 38800 2260 4800 5100 87000 12500 149000
2020-05-30 16300 9400 461000 98000 27800 16700 39200 2330 5130 5360 91000 13000 156000
2020-05-31 17200 10000 479000 104000 29200 17000 39600 2410 5460 5630 96000 13400 164000
2020-06-01 18100 10700 497000 110000 30600 17300 40000 2490 5820 5910 101000 13900 172000
2020-06-02 19000 11400 516000 117000 32100 17600 40400 2570 6200 6210 107000 14400 181000
2020-06-03 20000 12100 536000 124000 33700 18000 40800 2660 6610 6520 112000 14900 190000

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

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-27 13933 7768 411821 82289 24104 15723 38103 2109 4145 4640 78023 11728 135905
2020-05-28 14500 8100 420000 86000 24800 15900 38200 2160 4590 4820 80200 12000 139000
2020-05-29 14900 8400 432000 89000 25500 16100 38600 2220 4950 4940 82200 12100 142000
2020-05-30 15300 8800 446000 91000 26300 16300 38800 2260 5250 5050 84200 12300 145000
2020-05-31 15700 9100 457000 94000 26900 16500 39000 2310 5520 5210 86000 12400 148000
2020-06-01 16000 9400 469000 97000 27700 16800 39200 2350 5790 5340 87500 12400 150000
2020-06-02 16500 9700 480000 100000 28200 16900 39400 2390 6020 5490 89000 12400 152000
2020-06-03 17000 10000 493000 102000 28900 17100 39600 2430 6190 5570 90400 12500 155000
2020-06-04 17400 10200 508000 105000 29500 17300 39700 2480 6390 5730 92000 12500 158000
2020-06-05 17800 10500 522000 108000 30200 17500 39800 2520 6590 5890 93800 12500 162000

Peak increase in estimated trend of Confirmed in Latin America 2020-05-27

ArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
Peak date -- --05-22 -- --05-1004-2405-22 -- -- -- -- --
Peak daily increment 18437 369 3949 83
Days from 100 to peak 69 50 37 43
Days from peak/2 to peak 48 48 25 49
Days since peak 5 17 33 5

Initial visual evaluation of forecasts of Confirmed