Ukraine. If someone had 100 additional contacts, the probability of meeting at least
one infected person is approximately 0.03 (see Eq. (4.22)). There is also a visible
jump in second derivative on October 25 (see “dots” in Fig. 10.1).
Further consequences of election holding will be noticeable in November. But
already on October 31, we see the highest value of the second derivative (“dots” in
Fig. 10.1). Thus, we can conclude that elections and the presidential poll caused the
new epidemic waves in Ukraine and a significant increase in the number of cases.
To have reliable predictions for Ukraine, we have to continue calculations taking
into account new epidemic waves. In particular, we can assume that the eighth
epidemic wave had started on October 31. Some approximate estimation for the
final size of this wave and its duration will be presented in Chap. 13.
We must understand also that different parameter identification procedures can
yield different optimal values of the SIR model parameters (see, e.g., [56]). The
fastest verification method is to compare calculated SIR curves for V = I + R with
V j values, obtained after the calculations have been completed. It is possible also to
use dV/dt curve (Eq. (9.11), dotted line in Fig. 10.1). For example, corresponding
dotted line in Fig. 10.1 demonstrates that according to the prediction of seventh
Table 10.2 Official cumulative numbers of confirmed COVID-19 cases in Ukraine [95, 96]
Day in October and November
2020
Time in days
t j
Accumulated number of cases in
Ukraine V j
19
373
309,107
20
374
315,826
21
375
322,879
22
376
330,396
23
377
337,410
24
378
343,498
25
379
348,924
26
380
355,601
27
381
363,075
28
382
370,417
29
383
378,729
30
384
387,481
31
385
395,440
1
386
402,194
2
387
411,093
3
388
420,617
4
389
430,467
5
390
440,188
6
391
450,934
7
392
460,331
8
393
469,018
9
394
479,197
138
10 Procedures of Parameter Identification …
one infected person is approximately 0.03 (see Eq. (4.22)). There is also a visible
jump in second derivative on October 25 (see “dots” in Fig. 10.1).
Further consequences of election holding will be noticeable in November. But
already on October 31, we see the highest value of the second derivative (“dots” in
Fig. 10.1). Thus, we can conclude that elections and the presidential poll caused the
new epidemic waves in Ukraine and a significant increase in the number of cases.
To have reliable predictions for Ukraine, we have to continue calculations taking
into account new epidemic waves. In particular, we can assume that the eighth
epidemic wave had started on October 31. Some approximate estimation for the
final size of this wave and its duration will be presented in Chap. 13.
We must understand also that different parameter identification procedures can
yield different optimal values of the SIR model parameters (see, e.g., [56]). The
fastest verification method is to compare calculated SIR curves for V = I + R with
V j values, obtained after the calculations have been completed. It is possible also to
use dV/dt curve (Eq. (9.11), dotted line in Fig. 10.1). For example, corresponding
dotted line in Fig. 10.1 demonstrates that according to the prediction of seventh
Table 10.2 Official cumulative numbers of confirmed COVID-19 cases in Ukraine [95, 96]
Day in October and November
2020
Time in days
t j
Accumulated number of cases in
Ukraine V j
19
373
309,107
20
374
315,826
21
375
322,879
22
376
330,396
23
377
337,410
24
378
343,498
25
379
348,924
26
380
355,601
27
381
363,075
28
382
370,417
29
383
378,729
30
384
387,481
31
385
395,440
1
386
402,194
2
387
411,093
3
388
420,617
4
389
430,467
5
390
440,188
6
391
450,934
7
392
460,331
8
393
469,018
9
394
479,197
138
10 Procedures of Parameter Identification …