A mathematical model and forecast for the coronavirus disease COVID-19 in Ukraine (M1)
(A.B. Alyokhin, B.V. Burkynskyi, A.N. Grabovoi, V.A, Dilenko, N.I. Khumarova)
Forecast Monitor
13/10/2020. No F-233.
https://www.facebook.com/ab.alyokhin
Today we present the second assessment results of the COVID-19 epidemic forecast in Ukraine. This is our first forecast for Ukraine, which has not lost its relevance after the expiration of the main 10-day period.
This forecast was compiled 16 days ago using the M1 model framework based on statistics up to and including September 27th for the period from September 28th to October 7th, 2020 (see https://www.facebook.com/ab .alyokhin / posts / 184338443209059).
The results of evaluating the accuracy of the current 16-day forecast M1 presented in table. 1–2 and fig. 1–11.
Table 1 shows the calculated and actual values of the main indicators of the COVID-19 epidemic in Ukraine for a 16-day forecast period. The absolute and relative errors of daily forecasts, as well as the average absolute error of MAE and the average absolute error in percent MAPE, including the same MAPE * estimate on an accrual basis, the forecast as a whole.
Table 2 shows the same data for case fatality rates I (TC), I (CC) and the IP progress indicator.
Average absolute percentage errors (MAPE estimates *) for the main indicators of the COVID-19 epidemic in Ukraine are at the following level:
- total number of infected — 1.04%;
- total number of deaths — 0.67%;
- total number of recovered — 0.69%;
- number of active cases — 2.05%.
The errors in forecasting the most important derived indicators of the COVID-19 epidemic in Ukraine (MAPE * estimates) are as showing in Table. 2:
- mortality rate I (TC) — 1.44%;
- mortality rate I (CC) — 0.79%;
- IP progress indicator — 1.25%,
Visually, the degree of correspondence of statistical and forecast data allows you to evaluate the diagrams in Fig. 1–11.
Fig. 1–4 indicate:
- actual trajectories of the main indicators of the COVID-19 epidemic in Ukraine;
- calculated trajectories of these indicators for the same period;
- boundaries of confidence intervals (ranges of possible deviations of the point forecast with a significance level of p = 0.01).
In Fig. 1 the boundaries of the confidence interval are hidden due to their imposition on the main graphs.
The diagrams in Fig. 5–8 reflected:
- actual trajectories of changes in the daily indicators of the COVID-19 epidemic in Ukraine over the entire observation period;
- calculated trajectories of these indicators for the same period;
- boundaries of the confidence intervals of the 10-day forecast (p = 0.3).
Diagrams Fig. 9–11 reflect:
- actual trajectories of lethality indicators I (TC) and I (CC), as well as the IP progress indicator for the entire observation period;
- calculated trajectories of indicators for the same observation period, as well as for a forecasting period of 30 days.
All these diagrams clearly demonstrate the preservation of a sufficiently high accuracy of this forecast for 16 days, which clearly indicates that over the past forecast period, no tangible corrective effects exerted on the negative trends in the development of the epidemiological situation in Ukraine.
Moreover, the dynamics of the daily increase in infected (Fig. 5), recovered (Fig. 7) and the number of active cases (Fig. 8) tends to worsen (relative to the forecast), to which the progress indicator (Fig. 11).
Sources of statistical data:
https://www.worldometers.info/coronavirus/#countries
Our materials also:
https://www.facebook.com/MATHMODELCOVID19
Accuracy of our forecasts:
https://www.facebook.com/ab.alyokhin/posts/154698732839697 (Germany)
https://www.facebook.com/ab.alyokhin/posts/142548897388014 (Spain)
https://www.facebook.com/ab.alyokhin/posts/150095069966730 (Italy)
https://www.facebook.com/ab.alyokhin/posts/148450556797848 (USA)
https://www.facebook.com/ab.alyokhin/posts/154364292873141 (Ukraine)
https://www.facebook.com/ab.alyokhin/posts/144983953811175 (France)
https://www.facebook.com/ab.alyokhin/posts/152284093081161 (South Korea)
Publications on case fatality rates and progress indicator
https://www.facebook.com/ab.alyokhin/posts/105684827741088