Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model
The objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronav...
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| Format: | Article |
| Language: | Russian |
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Sankt-Peterburg : NIIÈM imeni Pastera
2022-11-01
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| Series: | Инфекция и иммунитет |
| Subjects: | |
| Online Access: | https://iimmun.ru/iimm/article/viewFile/1846/1489 |
| _version_ | 1797986930130944000 |
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| author | Vladimir S. Stepanov |
| author_facet | Vladimir S. Stepanov |
| author_sort | Vladimir S. Stepanov |
| collection | DOAJ |
| description | The objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronavirus (SARS-CoV-2). The mathematical methods consist of correlation and regression analysis, methods of testing statistical hypotheses. First, a multiple Variable Structure Regression should be specified. The intercept in the model differs from region to region, depending on the combination of values for dummy variables. The role of the dependent variable Y t was chosen as the cumulative mortality published by the operational headquarters for the regions that has been linked to day t, so that COVID-19 was considered the main cause of death. The complex of explanatory variables included two factorial variables that changed daily, and had a lag relative to t value. Also, this complex included a number of variables that did not change with the growth of t: the explanatory variable with the regions availability with doctors of certain specialties; and four dummy variables. One of them coded the regions belonging to the two southern Russian Federal Districts. Three other variables characterized the increased air pollution in settlements recorded in recent years, as well as the level of radiation pollution of the regions territory and the population health estimated for 10 classes of diseases (for the circulatory system, endocrine system, etc.). The values of such dummy variables were obtained from open data from the Federal State Statistics Service (Rosstat) etc. The model parameters were estimated by the least squares method using the training table, which included 40 Russias regions, the t parameter for variable Y t was assessed starting from November, 1, 2021. As a result, a statistical model was built with an approximation error equal to 3%. For regions of the regions examined this error was 1.94 (1.5)% for the value Y t that has been fixed on the 1st Nov. The plots show daily prediction for mortality rate due to COVID-19 in the first half of November for seven Russian regions compared with actual data. The model can be useful in development of medical and demographic policy in geographic regions, as well as generating adjusted compartment models that based on systems of differential equations (SEIRF, SIRD, etc.). |
| first_indexed | 2024-04-11T07:40:46Z |
| format | Article |
| id | doaj.art-7dbebe6869f54066a9565c6463aaf871 |
| institution | Directory Open Access Journal |
| issn | 2220-7619 2313-7398 |
| language | Russian |
| last_indexed | 2024-04-11T07:40:46Z |
| publishDate | 2022-11-01 |
| publisher | Sankt-Peterburg : NIIÈM imeni Pastera |
| record_format | Article |
| series | Инфекция и иммунитет |
| spelling | doaj.art-7dbebe6869f54066a9565c6463aaf8712022-12-22T04:36:35ZrusSankt-Peterburg : NIIÈM imeni PasteraИнфекция и иммунитет2220-76192313-73982022-11-0112478378910.15789/2220-7619-ASR-18461192Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric modelVladimir S. Stepanov0https://orcid.org/0000-0002-4478-376XThe Central Economics and Mathematics Institute of the Russian Academy of SciencesThe objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronavirus (SARS-CoV-2). The mathematical methods consist of correlation and regression analysis, methods of testing statistical hypotheses. First, a multiple Variable Structure Regression should be specified. The intercept in the model differs from region to region, depending on the combination of values for dummy variables. The role of the dependent variable Y t was chosen as the cumulative mortality published by the operational headquarters for the regions that has been linked to day t, so that COVID-19 was considered the main cause of death. The complex of explanatory variables included two factorial variables that changed daily, and had a lag relative to t value. Also, this complex included a number of variables that did not change with the growth of t: the explanatory variable with the regions availability with doctors of certain specialties; and four dummy variables. One of them coded the regions belonging to the two southern Russian Federal Districts. Three other variables characterized the increased air pollution in settlements recorded in recent years, as well as the level of radiation pollution of the regions territory and the population health estimated for 10 classes of diseases (for the circulatory system, endocrine system, etc.). The values of such dummy variables were obtained from open data from the Federal State Statistics Service (Rosstat) etc. The model parameters were estimated by the least squares method using the training table, which included 40 Russias regions, the t parameter for variable Y t was assessed starting from November, 1, 2021. As a result, a statistical model was built with an approximation error equal to 3%. For regions of the regions examined this error was 1.94 (1.5)% for the value Y t that has been fixed on the 1st Nov. The plots show daily prediction for mortality rate due to COVID-19 in the first half of November for seven Russian regions compared with actual data. The model can be useful in development of medical and demographic policy in geographic regions, as well as generating adjusted compartment models that based on systems of differential equations (SEIRF, SIRD, etc.).https://iimmun.ru/iimm/article/viewFile/1846/1489regression modelair pollutionsars-cov-2mortality modelingmorbiditypublic healthmortality forecastrussia’s regions |
| spellingShingle | Vladimir S. Stepanov Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model Инфекция и иммунитет regression model air pollution sars-cov-2 mortality modeling morbidity public health mortality forecast russia’s regions |
| title | Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model |
| title_full | Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model |
| title_fullStr | Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model |
| title_full_unstemmed | Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model |
| title_short | Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model |
| title_sort | assessing sars cov 2 related mortality rate in russian regions based on the econometric model |
| topic | regression model air pollution sars-cov-2 mortality modeling morbidity public health mortality forecast russia’s regions |
| url | https://iimmun.ru/iimm/article/viewFile/1846/1489 |
| work_keys_str_mv | AT vladimirsstepanov assessingsarscov2relatedmortalityrateinrussianregionsbasedontheeconometricmodel |