A mathematical model and forecast for the coronavirus disease COVID-19 in Ukraine (Мc)

5 min readNov 29, 2020

(A.B. Alyokhin, B.V. Burkynskyi, A.N. Grabovoi, V.A, Dilenko, N.I. Khumarova)

Forecast Monitor

29/11/2020. No F-272.

https://www.facebook.com/ab.alyokhin/posts/207117104264526

This monitor dedicated to the accuracy analysis of the weekly component of the MS consensus forecast, compiled for the period from 23rd to 29th November 2020 and published on 22nd November 2020 (https://www.facebook.com/ab.alyokhin / posts / 198051235171113).

Recall that the MS consensus forecast is an averaging of private forecasts obtained using various models and techniques used by our Working Group in predicting the COVID-19 epidemic.

The results of assessing the accuracy of the consensus forecast are showing in table. 1–3.

Table 1 shows the calculated and actual values of the main cumulative indicators of the COVID-19 epidemic in Ukraine for 7 days of the forecast period, the absolute (AE) and relative (PE) errors of daily forecasts, as well as the average absolute error (MAE) and the average absolute error in percentage (MAPE ), including the same cumulative MAPE estimate.

Table 2 shows the same data for similar daily indicators of the COVID-19 epidemic in Ukraine.

Since these estimates of the accuracy average forecast, these tables are also supplementing by the MAPE estimates (see MAPE (min)) of the best forecasts.

Table 3 shows similar data for mortality rates I (TC), I (CC), IP progress indicator and the average absolute increase in AAG infected.

Mean absolute percentage errors (MAPE) of the consensus forecast for the main cumulative indicators of the epidemic (Table 1):

- total number of infected people — 0.60%;

- total number of deaths — 1.02%;

- total number of recovered — 0.62%;

- number of active cases — 0.57%.

Mean absolute percentage errors (MAPE) for the main daily indicators of the epidemic (Table 2):

- total number of infected people — 7.51%;

- total number of deaths — 23.83%;

- total number of recovered — 12.74%;

- number of active cases — 10.32%.

It also follows from the data in these tables that among the particular forecasts there are some one with a significantly lower error.

MAPE estimates for the derived synthetic indicators of the COVID-19 epidemic in Ukraine (Table 3):

- mortality rate I (TC) — 0.58%;

- mortality rate I (CC) — 0.56%;

- IP progress indicator — 0.10%;

- average absolute increase in infected with AAG — 0.60%.

In comparison with the previous forecast (see https://www.facebook.com/ab.alyokhin/posts/201920844784152), this one demonstrated higher forecasting accuracy for some indicators, and lower accuracy for others.

You can visually assess the degree of compliance of the actual data with the forecasted data using the diagrams in Fig. 1–12. The index “c” marks the numbers of figures corresponding to the consensus forecast, the index “i” — the interval forecast.

Fig. 1–4 displayed:

- actual trajectories of the main cumulative indicators of the COVID-19 epidemic in Ukraine for the entire observation period;

- calculated trajectories of these indicators for the 28-day forecast period.

Diagrams Fig. 5–8 reflect for consensus forecast and interval forecast:

- actual trajectories of the main daily indicators of the COVID-19 epidemic in Ukraine for the entire observation period.

- calculated trajectories of these indicators for the 28-day forecast period.

Fig. 9–12 are given:

- actual trajectories of the main synthetic indicators of the epidemic (the average absolute increase in the number of infected, mortality rates I (TC) and (I (CC), IP progress indicator) for the entire observation period;

- calculated trajectory of these indicators for a 28-day (4-week) forecasting period.

Diagrams Fig. 5c-8c show that the nature of changes in daily indicators was forecasted very accurately, however, the actual variability of these indicators turned out to be higher due to the minimum values that were lower than forecasted. The only exception is the growth rate of deaths, which turned out to be more optimistic, not having reached the maximum forecast knowledge.

Diagrams Fig. 5i-8i show that the development of the COVID-19 epidemic in Ukraine last week followed a more optimistic forecast. The same charts explain the reasons for the level of accuracy noted above for the current consensus forecast. Some of the private projections forecasted a more pessimistic course of the epidemic, contributing mainly to the decline in overall estimates of consensus forecast accuracy.

Cumulative (Fig. 1–4) and synthetic indicators of the epidemic (Fig. 9–12) reacted poorly to deviations of the actual course of development of the epidemic from the calculated one, demonstrating quite an acceptable level of compliance with the forecasted values.

Noted above deviations (of actual data from forecasted) of a positive nature can be considered as harbingers of shifts in the trends of the epidemic development only if they deepen and consolidate in the near future. This cautious conclusion is because the actual parameters of the COVID-19 epidemic practically did not go beyond the forecast corridor (interval forecast), which was formed by models that take into account the patterns of the epidemic development at the time of the forecast development. In the meantime, the COVID-19 epidemic in Ukraine as a whole is developing in accordance with the previously established patterns.

Sources of statistical data:

https://www.worldometers.info/coronavirus/#countries

https://covid19.rnbo.gov.ua/

Our materials also:

https://www.facebook.com/MATHMODELCOVID19

https://t.me/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)