COVID-19 short-term forecasts Confirmed 2020-05-29


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 The documentation that is provided is still in progress and not peer reviewed.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) 2020-05-30 to 2020-06-05

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-29 15419 8731 465166 90638 25406 16531 38571 2278 4607 4752 84627 12531 141779
2020-05-30 16200 9200 489000 95000 26000 17000 38800 2330 4810 4880 89000 12900 145000
2020-05-31 17100 9800 517000 100000 26700 17600 39100 2410 5080 5080 93000 13400 149000
2020-06-01 18100 10500 547000 104000 27500 18100 39400 2480 5360 5280 98000 13900 154000
2020-06-02 19000 11100 579000 110000 28400 18700 39700 2560 5660 5490 103000 14400 158000
2020-06-03 20100 11900 613000 115000 29300 19300 40100 2640 5970 5720 108000 14900 163000
2020-06-04 21200 12600 648000 121000 30200 19900 40400 2730 6310 5950 114000 15400 168000
2020-06-05 22400 13400 686000 127000 31200 20600 40800 2820 6660 6200 119000 15900 173000

Confirmed count forecast Latin America (bold red line in graphs) 2020-05-30 to 2020-06-05

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-29 15419 8731 465166 90638 25406 16531 38571 2278 4607 4752 84627 12531 141779
2020-05-30 16100 9400 491000 95000 26200 17100 38800 2340 4790 4900 88000 13000 144000
2020-05-31 16800 9900 519000 99000 27000 17700 39100 2410 4990 5020 93000 13500 146000
2020-06-01 17500 10600 548000 103000 27900 18400 39300 2480 5180 5150 97000 14000 148000
2020-06-02 18300 11200 579000 107000 28800 19000 39600 2550 5370 5270 101000 14500 150000
2020-06-03 19100 11900 611000 112000 29700 19700 39800 2630 5570 5400 106000 15100 152000
2020-06-04 19900 12600 645000 116000 30700 20400 40000 2700 5780 5530 111000 15700 155000
2020-06-05 20800 13300 681000 121000 31600 21100 40300 2780 5990 5670 116000 16300 157000

Confirmed count scenario forecast (bold purple line in graphs) 2020-05-30 to 2020-06-07

DateArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
2020-05-29 15419 8731 465166 90638 25406 16531 38571 2278 4607 4752 84627 12531 141779
2020-05-30 16000 9400 485000 93000 25800 16800 38900 2320 4760 4910 88000 12800 146000
2020-05-31 16500 9800 507000 96000 26400 17000 39200 2380 4920 5060 90000 13000 149000
2020-06-01 16900 10400 530000 98000 26700 17200 39400 2430 5110 5170 93000 13200 152000
2020-06-02 17400 10900 551000 102000 27200 17500 39600 2510 5300 5350 95000 13400 155000
2020-06-03 17800 11300 571000 104000 27400 17600 39700 2560 5480 5450 97000 13400 159000
2020-06-04 18300 11700 590000 109000 27700 17700 39800 2620 5710 5590 99000 13800 162000
2020-06-05 18700 12100 608000 111000 28100 17800 39900 2670 5920 5670 101000 13800 164000
2020-06-06 19200 12500 627000 115000 28600 17900 40100 2730 6130 5910 103000 13800 168000
2020-06-07 19700 12800 645000 118000 29000 18000 40200 2770 6350 6130 105000 13900 170000

Peak increase in estimated trend of Confirmed in Latin America 2020-05-29

ArgentinaBoliviaBrazilChileColombiaDominican RepublicEcuadorEl SalvadorGuatemalaHondurasMexicoPanamaPeru
Peak date -- -- --05-25 -- --04-2405-2205-2505-24 -- -- --
Peak daily increment 4510 3949 83 312 253
Days from 100 to peak 70 37 43 46 56
Days from peak/2 to peak 56 25 49 42 55
Days since peak 4 35 7 4 5

Initial visual evaluation of forecasts of Confirmed