Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality
The paper identifies major factors associated with the pandemic spread in the Russian regions, using econometric models and nonlinear «Random Forest» models to assess their significance. The study is based on data of the Russian regions for March-December 2020, a balanced panel sample included 780 o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Moscow State University, Faculty of Economics
2022-12-01
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| Series: | Население и экономика |
| Online Access: | https://populationandeconomics.pensoft.net/article/87739/download/pdf/ |
| _version_ | 1811300736074514432 |
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| author | Marina G. Kolosnitsyna Mikhail Yu. Chubarov |
| author_facet | Marina G. Kolosnitsyna Mikhail Yu. Chubarov |
| author_sort | Marina G. Kolosnitsyna |
| collection | DOAJ |
| description | The paper identifies major factors associated with the pandemic spread in the Russian regions, using econometric models and nonlinear «Random Forest» models to assess their significance. The study is based on data of the Russian regions for March-December 2020, a balanced panel sample included 780 observations. Prevalence of the pandemic was estimated based on the excess mortality rate. The study has identified a positive relationship between excess mortality and the share of migrants and a negative relationship between excess mortality and the share of pensioners in the region. Importance of climatic factors has been confirmed: high temperatures, other things being equal, reduce excess mortality, while high humidity, on the contrary, increases it. Excess mortality is higher in the regions with lower population mobility. Mortality is higher in the regions with high per capita incomes and regions with significant unemployment. Vice versa, excess mortality is lower in the regions with better doctor and nurse staffing levels. The study results show that in case of repeated waves of the epidemic or emergence of new viruses, public health policy should be geographically differentiated. Priority should be given to epidemiological situation in the regions with humid climate and low temperatures, high incomes, intensive migration, and high unemployment rates. Significant investments in medical education, higher number of medical specialists and their more even distribution across regions are required. This approach turns out to be more effective in terms of reducing mortality rather than restrictions on population mobility. |
| first_indexed | 2024-04-13T06:55:54Z |
| format | Article |
| id | doaj.art-381c07cbba2b4130a8541105bd803a6a |
| institution | Directory Open Access Journal |
| issn | 2658-3798 |
| language | English |
| last_indexed | 2024-04-13T06:55:54Z |
| publishDate | 2022-12-01 |
| publisher | Moscow State University, Faculty of Economics |
| record_format | Article |
| series | Население и экономика |
| spelling | doaj.art-381c07cbba2b4130a8541105bd803a6a2022-12-22T02:57:15ZengMoscow State University, Faculty of EconomicsНаселение и экономика2658-37982022-12-016412010.3897/popecon.6.e8773987739Spread of COVID-19 in the Russian regions in 2020: factors of excess mortalityMarina G. Kolosnitsyna0Mikhail Yu. Chubarov1HSE UniversityHSE UniversityThe paper identifies major factors associated with the pandemic spread in the Russian regions, using econometric models and nonlinear «Random Forest» models to assess their significance. The study is based on data of the Russian regions for March-December 2020, a balanced panel sample included 780 observations. Prevalence of the pandemic was estimated based on the excess mortality rate. The study has identified a positive relationship between excess mortality and the share of migrants and a negative relationship between excess mortality and the share of pensioners in the region. Importance of climatic factors has been confirmed: high temperatures, other things being equal, reduce excess mortality, while high humidity, on the contrary, increases it. Excess mortality is higher in the regions with lower population mobility. Mortality is higher in the regions with high per capita incomes and regions with significant unemployment. Vice versa, excess mortality is lower in the regions with better doctor and nurse staffing levels. The study results show that in case of repeated waves of the epidemic or emergence of new viruses, public health policy should be geographically differentiated. Priority should be given to epidemiological situation in the regions with humid climate and low temperatures, high incomes, intensive migration, and high unemployment rates. Significant investments in medical education, higher number of medical specialists and their more even distribution across regions are required. This approach turns out to be more effective in terms of reducing mortality rather than restrictions on population mobility.https://populationandeconomics.pensoft.net/article/87739/download/pdf/ |
| spellingShingle | Marina G. Kolosnitsyna Mikhail Yu. Chubarov Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality Население и экономика |
| title | Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality |
| title_full | Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality |
| title_fullStr | Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality |
| title_full_unstemmed | Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality |
| title_short | Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality |
| title_sort | spread of covid 19 in the russian regions in 2020 factors of excess mortality |
| url | https://populationandeconomics.pensoft.net/article/87739/download/pdf/ |
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