Chapter 13
Long-Time Predictions for the Pandemic
Dynamics
In this chapter, we will discuss the problems of long-time predictions of the
COVID-19 pandemic dynamics with the use of mathematical models. Some
approximate formulas will be proposed in order to estimate the final size and
duration of the epidemic with the use of limited data sets at the beginning of new
waves. Prediction for the world dynamics, USA, Germany, the UK, the Republic of
Korea, Italy, Austria, Spain, France, Sweden, the Republic of Moldova, Ukraine,
and the city of Kyiv will be presented.
Any mathematical modeling of the epidemic dynamics will be of particular value
if we make an accurate long-term forecast of its duration and number of diseases
using statistics data sets obtained immediately after the outbreak. That is why many
authors were trying to predict the COVID-19 pandemic dynamics in many countries
and regions [7, 11, 17, 19–32, 38–51, 57–78, 81, 83, 89, 90, 94, 97–134].
Unfortunately, the correct mathematical simulation of the COVID-19 pandemic is
very difficult for at least two reasons.
First, data on the number of cases were clearly incomplete immediately after
outbreaks, and there were quite long hidden periods (we discussed this problem in
previous chapters; see, for example, Fig. 6.29). The reason is the large number of
asymptomatic patients and the lack of skills to detect a new disease. If the symptoms are obvious (as was, for example, in the case of the mysterious children illness
in the Ukrainian city of Chernivtsi), the number of reported cases immediately after
the epidemic outbreak may correspond to the actual number and allow adequate
long-term prognosis [35].
It must be noted that large discrepancy between registered and actual number of
cases occurred even for later periods of the COVID-19 pandemic. Total testing in
Slovakia (65.5% of population tested on October 31–November 1, 2020) revealed a
number of previously undetected cases, equal to about 1% of the population [135].
According to the WHO report at the end of October, the number of detected cases
was also approximately 1% of the country’s population [1]. Thus, even six months
after the detection of the first patient, half of the cases remained undetected.
Probably, we have a similar situation not only in Slovakia.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
I. Nesteruk, COVID-19 Pandemic Dynamics,
https://doi.org/10.1007/978-981-33-6416-5_13
153
Long-Time Predictions for the Pandemic
Dynamics
In this chapter, we will discuss the problems of long-time predictions of the
COVID-19 pandemic dynamics with the use of mathematical models. Some
approximate formulas will be proposed in order to estimate the final size and
duration of the epidemic with the use of limited data sets at the beginning of new
waves. Prediction for the world dynamics, USA, Germany, the UK, the Republic of
Korea, Italy, Austria, Spain, France, Sweden, the Republic of Moldova, Ukraine,
and the city of Kyiv will be presented.
Any mathematical modeling of the epidemic dynamics will be of particular value
if we make an accurate long-term forecast of its duration and number of diseases
using statistics data sets obtained immediately after the outbreak. That is why many
authors were trying to predict the COVID-19 pandemic dynamics in many countries
and regions [7, 11, 17, 19–32, 38–51, 57–78, 81, 83, 89, 90, 94, 97–134].
Unfortunately, the correct mathematical simulation of the COVID-19 pandemic is
very difficult for at least two reasons.
First, data on the number of cases were clearly incomplete immediately after
outbreaks, and there were quite long hidden periods (we discussed this problem in
previous chapters; see, for example, Fig. 6.29). The reason is the large number of
asymptomatic patients and the lack of skills to detect a new disease. If the symptoms are obvious (as was, for example, in the case of the mysterious children illness
in the Ukrainian city of Chernivtsi), the number of reported cases immediately after
the epidemic outbreak may correspond to the actual number and allow adequate
long-term prognosis [35].
It must be noted that large discrepancy between registered and actual number of
cases occurred even for later periods of the COVID-19 pandemic. Total testing in
Slovakia (65.5% of population tested on October 31–November 1, 2020) revealed a
number of previously undetected cases, equal to about 1% of the population [135].
According to the WHO report at the end of October, the number of detected cases
was also approximately 1% of the country’s population [1]. Thus, even six months
after the detection of the first patient, half of the cases remained undetected.
Probably, we have a similar situation not only in Slovakia.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
I. Nesteruk, COVID-19 Pandemic Dynamics,
https://doi.org/10.1007/978-981-33-6416-5_13
153