DEVELOPMENT OF A MODEL OF GENERALIZED ASSESSMENT OF THE SERIOUSITY OF THE EPIDEMIOLOGICAL SITUATION IN THE CENTRAL CHERNOZEM REGION ON THE BASIS OF CALCULATION OF RELATIVE INDICATORS OF INCIDENTITY

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RELEVANCE: A comparative assessment of the epidemiological situation in the regions implies a comparison of statistical indicators characterizing the level of morbidity. Since February 2020, Covid-19 morbidity statistics have been constantly covered in the media. In particular, daily reports are published on the number of new cases of infection, deaths and recovery in the Russian Federation as a whole and in the regional context. However, based on these indicators, it is difficult to conclude in which regions the situation seems more or less favorable, as well as the presence/absence of a trend in its change. However, it is the comparative analysis of the incidence of Covid-19 by region that is one of the main conditions for identifying the factors of the spread/localization of the disease, evaluating the effectiveness of the efforts made and developing a system of measures to counter the spread of the disease. This is due to the relevance of this study.
purpose: This article proposes an approach to the construction of a generalized morbidity assessment, which allows comparing the severity of the epidemiological situation in the regions and demonstrated to determine the rating of the regions of the Central Chernozem region in terms of the incidence of Covid-19.
MATERIALS AND METHODS: As a statistical base, the daily morbidity indicators presented on the website "Coronavirus Statistics by regions of Russia" [1] for the regions of the Chernozem region are taken:
- The total number of infections (OZ), deaths (OS) and recoveries(s) since the beginning of the pandemic;
- The number of new infections (NC), deaths (NC), recoveries (HC) and the number of infected (H).
Based on these absolute indicators, it is proposed to calculate relative morbidity rates that allow comparing the incidence rate by region. When calculating the relative indicators, data on the average population of the Chernozem regions for 2021 were used, which was denoted by N.
Let's list the relative indicators:
- NZ/NV – the number of new cases of infection per one new case of recovery;
- (NS/W)1000 – mortality rate, i.e. the number of new deaths per 1000 infected
- NZ/(N-OZ)10001000 – the level of new cases of infection, i.e. the number of new cases of infection per 1000 people who have not yet been sick (secondary cases of infection are rare, so the number of people who have not been sick is defined as the difference between the population and the total number of infections);
- (S/N)1000 - the level of morbidity (the number of infected per 1000 people of the population)
In medical research, various approaches are used to calculate generalized estimates. For example, in [3, p.121], the values for each indicator are ranked, and the average value of the ranks acts as a generalized assessment of the object. Such an assessment determines the rating of objects, but does not allow us to determine whether the indicators of an object with a high rating significantly exceed the indicators of an object with a low rating. In [4, p.138], the average value of the percentage deviation of the object indicator from the average value of the indicator for the entire group of objects is considered as a generalized estimate. However, such an assessment largely reflects the comparison of objects (regions) with a common object (federal district), and not with each other. Therefore, we propose to use the methodology for calculating the generalized assessment used to determine the rating of innovative development of the subjects of the Russian Federation [2, p. 3263]. The essence of the technique is as follows. For each value of the initial (relative) indicator, its normalized value is calculated using the formula:
X norm= (X-X min)/(X max⁡〖- X min〗 )
where x is the actual value, and xmax and xmin are the largest and smallest values of the indicator, respectively. Normalized indicators take values from 0 to 1. A value of 0 for a normalized indicator corresponds to the best (smallest) value, and a value of 1 corresponds to the worst (largest). The generalized estimate for each region is calculated as the average value of the normalized indicators. Then the generalized estimates are ranked – the lower the rank corresponds to the region, the more severe the epidemiological situation in it.
Note that the situation with the incidence of Covid-19 is changing very quickly. The number of new cases of infections, deaths and recoveries varies significantly in each of the regions, therefore, in order to identify the trend in the incidence rate, it is advisable to carry out a preliminary alignment of the dynamic series (for example, using the method of enlarging intervals). As an enlarged interval, it is proposed to take not the "traditional time period" (for example, a month or a year), but the average duration of the incubation period of the disease. This will allow us to assess the effect of the measures introduced to counteract the spread of the disease. Therefore, it is proposed to divide each month into decades and use the average values of absolute indicators for decades when calculating relative indicators. Let's consider the time period from 01.02.2022 to 10.02.2022, corresponding to the beginning of the fifth wave, and calculate a generalized assessment of the incidence of Covid-19 in the regions of the Chernozem region.
results:
A comparative analysis of relative indicators shows that for the 1st decade of February in all regions, the number of new cases of the disease exceeded the number of new cases of recovery, especially the Tambov region stood out with an indicator of 4.78. The lowest mortality rate was observed in the Voronezh region – 2.24, the highest - in the Lipetsk region with an indicator of 5.94. The level of new cases of infection is the lowest in the Kursk and Belgorod regions, and the highest in the Voronezh region. The level of infection is the lowest in the Kursk and Belgorod regions, and the highest in the Lipetsk and Voronezh regions..
Similarly, the values of relative indicators for the next decade were calculated.
An analysis of their dynamics showed that the trend towards a decrease in the ratio of NW/NV took place in the Lipetsk and Tambov regions. The trend towards a steady increase in the NZ indicator/NV was observed in the Voronezh region. Throughout the period under review, the highest mortality rate was recorded in the Lipetsk region, and the lowest in the Voronezh region. In all regions, except the Kursk region, there was a tendency to increase the level of new infections. At the same time, the highest value and the largest growth of this indicator were observed in the Voronezh and Lipetsk regions. The highest level of Covid-19 infection was recorded in the Voronezh region.
A comparison of individual indicators shows that regions have different ratings for different indicators. Therefore, to determine the rating of regions, a generalized assessment is calculated according to the proposed formula. The Kursk Region receives the largest number of rating points, the Voronezh Region receives the least.
DISCUSSION: Consequently, the most favorable situation in the second decade of February 2022 was in the Kursk region, and the most unfavorable - in the Voronezh region. Note that according to the derived formula, it is possible to calculate a generalized assessment of morbidity in the Central Chernozem region as a whole and, thus, identify regions in which the situation is better / worse on average in the district.
CONCLUSION: The proposed approach to the construction of a generalized assessment of morbidity is quite simple from a mathematical point of view. It allows you to modify the assessment model taking into account the specifics of the disease by introducing new indicators into it. For example, to assess the incidence of Covid-19, data on the number of hospitalized, the number of patients connected to ventilators, etc. can be entered as initial indicators. The analysis of the dynamics of generalized assessments of the epidemiological situation makes it possible to assess the effectiveness of measures to counteract the spread of the disease and to make the right management decisions.

About the authors

Sofya Rakhimova

Voronezh State Medical University named after N. N. Burdenko

Author for correspondence.
Email: sofarahimova1999@gmail.com
ORCID iD: 0000-0002-6965-0461
SPIN-code: 7139-3558

medical student

Russian Federation, 394036, Voronezh, st. Student, d. 10.

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