Characterisation of the COVID-19 epidemic process in Moscow and search for possible determinants of the trends of the observed changes

Q3 Medicine
Vladimir A. Gushchin, Andrei A. Pochtovyi, Daria D. Kustova, Darya A. Ogarkova, Denis A. Kleymenov, Tatyana A. Semenenko, Denis Yu. Logunov, Vladimir I. Zlobin, Alexander L. Gintsburg
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 The purpose of the study is to identify factors that potentially determine the trends of observed changes using a molecular epidemiological analysis of the main characteristics of the epidemic process of a new coronavirus infection (COVID-19).
 Materials and methods. For the analysis, the data of Russian national genome sequence database of SARS-CoV-2 virus (VGARus) were combined with information on morbidity and mortality presented at the official internet resources стопкоронавирус.рф and Yandex DataLens, the dynamics of vaccination, COVID-19 disease incidence and hospitalization from the portal Gogov.ru. A multicentre retrospective observational epidemiological study was conducted to examine the sex and age structure of hospitalised patients. Anonymized case histories of patients with COVID-19 collected at different follow-up periods in the institutions of Moscow (41,561 cases) served as a source of data for the sex and age structure analysis.
 Results. We identified 11 periods with significantly different complex epidemiological characteristics. A decrease in the incidence among young people of working age during the period of restrictive measures was revealed. In 3 out of 11 worsening of the epidemic situation coincided with the beginning of the circulation of a new genetic variant of the pathogen COVID-19 (variants Wuhan, Delta, Omicron). A decrease in the incidence in the summer period was noted, regardless of the circulating genetic variants.
 Conclusion. A significant part of the observed dynamics of the characteristics of the epidemic process in Moscow can be explained by the properties of the pathogen, seasonality and dynamics of magnitude of the herd immunity. The influence of the dynamics of the herd immunity indicators on the course of the epidemic process is to be studied further.","PeriodicalId":24020,"journal":{"name":"Zhurnal mikrobiologii, epidemiologii, i immunobiologii","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Zhurnal mikrobiologii, epidemiologii, i immunobiologii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36233/0372-9311-375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
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Abstract

Background. Constant assessment of the dynamics of the main characteristics of the epidemic process is the basic function of epidemiological surveillance of infectious diseases. The search for factors that determine changes in the characteristics of the epidemic process makes it possible to develop timely management decisions and reduce the risk of an increase in the scale of the pandemic. Moscow is the main centre of attraction for the population of other Russian regions with the most complex structure of social links and the highest population density. The purpose of the study is to identify factors that potentially determine the trends of observed changes using a molecular epidemiological analysis of the main characteristics of the epidemic process of a new coronavirus infection (COVID-19). Materials and methods. For the analysis, the data of Russian national genome sequence database of SARS-CoV-2 virus (VGARus) were combined with information on morbidity and mortality presented at the official internet resources стопкоронавирус.рф and Yandex DataLens, the dynamics of vaccination, COVID-19 disease incidence and hospitalization from the portal Gogov.ru. A multicentre retrospective observational epidemiological study was conducted to examine the sex and age structure of hospitalised patients. Anonymized case histories of patients with COVID-19 collected at different follow-up periods in the institutions of Moscow (41,561 cases) served as a source of data for the sex and age structure analysis. Results. We identified 11 periods with significantly different complex epidemiological characteristics. A decrease in the incidence among young people of working age during the period of restrictive measures was revealed. In 3 out of 11 worsening of the epidemic situation coincided with the beginning of the circulation of a new genetic variant of the pathogen COVID-19 (variants Wuhan, Delta, Omicron). A decrease in the incidence in the summer period was noted, regardless of the circulating genetic variants. Conclusion. A significant part of the observed dynamics of the characteristics of the epidemic process in Moscow can be explained by the properties of the pathogen, seasonality and dynamics of magnitude of the herd immunity. The influence of the dynamics of the herd immunity indicators on the course of the epidemic process is to be studied further.
描述莫斯科COVID-19流行过程并寻找观察到的变化趋势的可能决定因素
背景。不断评估流行过程主要特征的动态是传染病流行病学监测的基本功能。寻找决定流行病进程特征变化的因素,就有可能制定及时的管理决策,并减少流行病规模扩大的风险。莫斯科是吸引俄罗斯其他地区人口的主要中心,拥有最复杂的社会联系结构和最高的人口密度。本研究的目的是通过对新型冠状病毒感染(COVID-19)流行过程的主要特征进行分子流行病学分析,确定可能决定观察到的变化趋势的因素。材料和方法。为了进行分析,将俄罗斯国家SARS-CoV-2病毒基因组序列数据库(VGARus)数据与官方互联网资源стопкоронавирус提供的发病率和死亡率信息相结合。来自门户网站Gogov.ru的疫苗接种动态、COVID-19疾病发病率和住院率。对住院患者的性别和年龄结构进行了多中心回顾性观察性流行病学研究。在莫斯科各机构收集的不同随访时期的COVID-19患者的匿名病史(41,561例)作为性别和年龄结构分析的数据来源。 结果。我们确定了11个具有显著不同复杂流行病学特征的时期。在采取限制措施期间,工作年龄青年的发病率有所下降。在疫情恶化的11个国家中,有3个国家恰逢病原体COVID-19新的遗传变异(武汉、德尔塔、欧米克隆变异)开始传播。注意到,与流行的遗传变异无关,夏季发病率有所下降。 结论。观察到的莫斯科流行过程特征的很大一部分动态可以用病原体的特性、季节性和群体免疫幅度的动态来解释。群体免疫指标动态对疫情进程的影响有待进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Zhurnal mikrobiologii, epidemiologii, i immunobiologii
Zhurnal mikrobiologii, epidemiologii, i immunobiologii Immunology and Microbiology-Immunology and Microbiology (miscellaneous)
CiteScore
1.40
自引率
0.00%
发文量
51
审稿时长
8 weeks
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