The average time of spreading infection 1=q in Austria was estimated as
0.77 days (compare with the almost twice higher value—1.47 days—in Italy,
shown in Table 6.7 for corresponding prediction 6). The proper testing, identification and isolation of infected persons in Austria could be the main reason of the
relative low number of cases in this country.
In Figs. 6.15 and 6.16, prediction 6 for Austria is compared with the situation in
Ukraine. It can be seen that the real numbers of cases V j (“red stars” in Fig. 6.16)
recorded in Austria after the period T c used for the calculations (“red circles” in
Fig. 6.16) correspond very well to the theoretical curve V. Minor deviations begin
only after April 29, 2020.
This is in line with the fact that national lockdown in Austria was canceled on
April 14 (e.g., small shops were opened). This changed the characteristics of the
epidemic, and after a certain incubation period we see more cases than the classical
SIR theory predicted.
Figure 6.15 illustrates that real epidemic outbreak in Austria occurred much later
than in Ukraine (compare solid lines). The registered numbers of cases in Austria
(red “triangles”) tend rather fast to the theoretical estimation V(t) (red solid line).
Unfortunately, in Ukraine many COVID-19 cases were not identified long time
(compare blue solid blue and “triangles” in Fig. 6.15). This situation and the delay
with proper testing caused much higher number of infected people in Ukraine
visible in Fig. 6.16.
Fig. 6.14 Austria, first epidemic wave, prediction 6: SIR curves (lines) and accumulated number
of cases (markers) versus time. Numbers of infected I (green), removed R (black) and the number
of victims V = I + R (blue line); “circles” show the cases taken for calculations; “triangles”
correspond to the cases during initial stage of the epidemic; “stars”—the last data points used only
for a verification of the prediction
60
6 SIR Simulations for the First Waves of the COVID-19 …
0.77 days (compare with the almost twice higher value—1.47 days—in Italy,
shown in Table 6.7 for corresponding prediction 6). The proper testing, identification and isolation of infected persons in Austria could be the main reason of the
relative low number of cases in this country.
In Figs. 6.15 and 6.16, prediction 6 for Austria is compared with the situation in
Ukraine. It can be seen that the real numbers of cases V j (“red stars” in Fig. 6.16)
recorded in Austria after the period T c used for the calculations (“red circles” in
Fig. 6.16) correspond very well to the theoretical curve V. Minor deviations begin
only after April 29, 2020.
This is in line with the fact that national lockdown in Austria was canceled on
April 14 (e.g., small shops were opened). This changed the characteristics of the
epidemic, and after a certain incubation period we see more cases than the classical
SIR theory predicted.
Figure 6.15 illustrates that real epidemic outbreak in Austria occurred much later
than in Ukraine (compare solid lines). The registered numbers of cases in Austria
(red “triangles”) tend rather fast to the theoretical estimation V(t) (red solid line).
Unfortunately, in Ukraine many COVID-19 cases were not identified long time
(compare blue solid blue and “triangles” in Fig. 6.15). This situation and the delay
with proper testing caused much higher number of infected people in Ukraine
visible in Fig. 6.16.
Fig. 6.14 Austria, first epidemic wave, prediction 6: SIR curves (lines) and accumulated number
of cases (markers) versus time. Numbers of infected I (green), removed R (black) and the number
of victims V = I + R (blue line); “circles” show the cases taken for calculations; “triangles”
correspond to the cases during initial stage of the epidemic; “stars”—the last data points used only
for a verification of the prediction
60
6 SIR Simulations for the First Waves of the COVID-19 …