| Autor: |
Sonya O. Vysochanskaya, Artem A. Basov, Yury V. Zhernov, Tatiana R. Belova, Alexander M. Zatevalov, Oleg V. Mitrokhin, Inna A. Fadeeva, Svetlana Y. Kombarova |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Informatics in Medicine Unlocked, Vol 42, Iss , Pp 101389- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2352-9148 |
| DOI: |
10.1016/j.imu.2023.101389 |
| Popis: |
The aim of the study was to determine the impact of the novel coronavirus disease 2019 (COVID-19) mitigation measures on the spread of pertussis and identify which measures were most effective in preventing the spread of this disease. In order to analyze pertussis incidence dynamics in Moscow (Russian Federation), the quasiexperimental interrupted time series (ITS) approach was used. The mathematical modeling of the incidence time series was conducted with regression with autoregressive integrated moving average (ARIMA) errors. COVID-19 mitigation measures reduced the incidence of pertussis infection compared with the predicted incidence without restrictive measures of 42.7 %. Our analysis has shown that the most efficient COVID-19 mitigation measures influencing pertussis incidence were «restriction of mass events», «self-isolation regime for the elderly persons over 65 years of age and persons with chronic diseases» and «transfer to remote work of at least 30 % of the total number of employees». The obtained results of this research can be used for the selection of the most efficient mitigation measures to reduce the incidence and limit the spread of pertussis outbreaks. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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