俄罗斯南部蜱传感染:现代流行病学形势,建立“预测”和“解释”发病率模型的新方法(阿斯特拉罕立克次体热和克里米亚-刚果出血热)

Darya A. Prislegina, O. V. Maletskaya, V. Dubyanskiy, Tatiana V. Taran, A. E. Platonov
{"title":"俄罗斯南部蜱传感染:现代流行病学形势,建立“预测”和“解释”发病率模型的新方法(阿斯特拉罕立克次体热和克里米亚-刚果出血热)","authors":"Darya A. Prislegina, O. V. Maletskaya, V. Dubyanskiy, Tatiana V. Taran, A. E. Platonov","doi":"10.15789/2220-7619-tbi-2036","DOIUrl":null,"url":null,"abstract":"The article presents a description of the current tick-borne infection epidemiological situation in the south of Russia from the years 2013 to 2022, proposes a new approach to develop forecasting models for morbidity dynamics of Astrakhan rickettsial fever (ARF) and Crimean hemorrhagic fever (СCHF) in the Astrakhan region and presents data assessing 2022 explaining models for the Stavropol Territory and Astrakhan Region. Materials and methods. A comprehensive research was performed using epidemiological analysis and non-parametric statistical methods. The data assessing tick-borne infections epidemic process manifestations were retrieved from ARF and CCHF morbidity databases (developed as a project) and documents of infectious disease focus epidemiological examination provided by the departments of Rospotrebnadzor in the subjects of the Southern and North Caucasian Federal Districts. Morbidity models were developed using the Bayes theorem and Walds sequential statistical analysis, with a preliminary calculation of indicators informativeness by the Kullback method. The values of climatic factors from the database of the Center for Collective Use IKI-monitoring of the Space Research Institute of the Russian Academy of Sciences were used. Results. The results of the study indicate persistence of serious epidemiological situation regarding rickettsiosis of the tick-borne spotted fever group, Q fever, tick-borne borreliosis and CCHF in the south of Russia. Almost all tick-borne infections nosological forms in children under 14 years (including young children and infants) were widely involved in the epidemic process, which belong to patients at risk for a complicated disease course due to complicated diagnostics and treatment. The annual registration of tick-borne infections cases in the resort areas, with the subsequent occurrence of imported cases in other, including non-endemic regions poses a serious problem. The proposed forecasting models allow to predict the CСHF and ARF morbidity for each administrative district of the Astrakhan region with up to 91.7% accuracy. The explaining models CСHF accuracy for the Stavropol Territory and Astrakhan Region, when tested in 2022, was 88.5 and 83.3%, respectively, for ARF 91.7%. Conclusions. The further continuation of forecasting and explaining models verification for planning preventive measures and propose similar steps for tick-borne borreliosis and Q fever to epidemiological tick-borne infections to stabilize situation in the south of Russia.","PeriodicalId":21412,"journal":{"name":"Russian Journal of Infection and Immunity","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tick-borne infections in the south of Russia: modern epidemiological situation, new approach to create “forecasting” and “explaining” morbidity models (in astrakhan rickettsiosis fever and crimean-congo hemorrhagic fever)\",\"authors\":\"Darya A. Prislegina, O. V. Maletskaya, V. Dubyanskiy, Tatiana V. Taran, A. E. Platonov\",\"doi\":\"10.15789/2220-7619-tbi-2036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents a description of the current tick-borne infection epidemiological situation in the south of Russia from the years 2013 to 2022, proposes a new approach to develop forecasting models for morbidity dynamics of Astrakhan rickettsial fever (ARF) and Crimean hemorrhagic fever (СCHF) in the Astrakhan region and presents data assessing 2022 explaining models for the Stavropol Territory and Astrakhan Region. Materials and methods. A comprehensive research was performed using epidemiological analysis and non-parametric statistical methods. The data assessing tick-borne infections epidemic process manifestations were retrieved from ARF and CCHF morbidity databases (developed as a project) and documents of infectious disease focus epidemiological examination provided by the departments of Rospotrebnadzor in the subjects of the Southern and North Caucasian Federal Districts. Morbidity models were developed using the Bayes theorem and Walds sequential statistical analysis, with a preliminary calculation of indicators informativeness by the Kullback method. The values of climatic factors from the database of the Center for Collective Use IKI-monitoring of the Space Research Institute of the Russian Academy of Sciences were used. Results. The results of the study indicate persistence of serious epidemiological situation regarding rickettsiosis of the tick-borne spotted fever group, Q fever, tick-borne borreliosis and CCHF in the south of Russia. Almost all tick-borne infections nosological forms in children under 14 years (including young children and infants) were widely involved in the epidemic process, which belong to patients at risk for a complicated disease course due to complicated diagnostics and treatment. The annual registration of tick-borne infections cases in the resort areas, with the subsequent occurrence of imported cases in other, including non-endemic regions poses a serious problem. The proposed forecasting models allow to predict the CСHF and ARF morbidity for each administrative district of the Astrakhan region with up to 91.7% accuracy. The explaining models CСHF accuracy for the Stavropol Territory and Astrakhan Region, when tested in 2022, was 88.5 and 83.3%, respectively, for ARF 91.7%. Conclusions. The further continuation of forecasting and explaining models verification for planning preventive measures and propose similar steps for tick-borne borreliosis and Q fever to epidemiological tick-borne infections to stabilize situation in the south of Russia.\",\"PeriodicalId\":21412,\"journal\":{\"name\":\"Russian Journal of Infection and Immunity\",\"volume\":\"27 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Journal of Infection and Immunity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15789/2220-7619-tbi-2036\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Infection and Immunity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15789/2220-7619-tbi-2036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了2013年至2022年俄罗斯南部蜱传感染流行病学现状,提出了一种开发阿斯特拉罕地区阿斯特拉罕立克次体热(ARF)和克里米亚出血热(СCHF)发病率动态预测模型的新方法,并提供了评估2022年斯塔夫罗波尔地区和阿斯特拉罕地区解释模型的数据。材料和方法。采用流行病学分析和非参数统计方法进行综合研究。评估蜱传感染流行过程表现的数据来自ARF和CCHF发病率数据库(作为一个项目开发的)和Rospotrebnadzor部门在南高加索和北高加索联邦区的受试者中提供的传染病焦点流行病学检查文件。采用贝叶斯定理和Walds序列统计分析建立发病率模型,并采用Kullback方法初步计算指标信息量。使用了俄罗斯科学院空间研究所集体使用iki监测中心数据库中的气候因子值。结果。研究结果表明,在俄罗斯南部,蜱传斑点热组立克次体病、Q热、蜱传伯氏螺旋体病和CCHF持续存在严重的流行病学情况。14岁以下儿童(包括幼儿和婴儿)中几乎所有蜱传感染的病原学形式都广泛参与流行过程,由于诊断和治疗复杂,属于病程复杂的患者。度假区每年登记的蜱传感染病例,随后在其他地区(包括非流行地区)出现输入性病例,构成一个严重问题。所提出的预测模型可以预测阿斯特拉罕地区每个行政区域的CСHF和ARF发病率,准确率高达91.7%。在2022年测试时,斯塔夫罗波尔领土和阿斯特拉罕地区的解释模型CСHF的准确性分别为88.5和83.3%,ARF为91.7%。结论。进一步继续预测和解释模型验证,以规划预防措施,并就蜱传borreliosis和Q热提出与流行病学蜱传感染类似的步骤,以稳定俄罗斯南部的局势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Tick-borne infections in the south of Russia: modern epidemiological situation, new approach to create “forecasting” and “explaining” morbidity models (in astrakhan rickettsiosis fever and crimean-congo hemorrhagic fever)
The article presents a description of the current tick-borne infection epidemiological situation in the south of Russia from the years 2013 to 2022, proposes a new approach to develop forecasting models for morbidity dynamics of Astrakhan rickettsial fever (ARF) and Crimean hemorrhagic fever (СCHF) in the Astrakhan region and presents data assessing 2022 explaining models for the Stavropol Territory and Astrakhan Region. Materials and methods. A comprehensive research was performed using epidemiological analysis and non-parametric statistical methods. The data assessing tick-borne infections epidemic process manifestations were retrieved from ARF and CCHF morbidity databases (developed as a project) and documents of infectious disease focus epidemiological examination provided by the departments of Rospotrebnadzor in the subjects of the Southern and North Caucasian Federal Districts. Morbidity models were developed using the Bayes theorem and Walds sequential statistical analysis, with a preliminary calculation of indicators informativeness by the Kullback method. The values of climatic factors from the database of the Center for Collective Use IKI-monitoring of the Space Research Institute of the Russian Academy of Sciences were used. Results. The results of the study indicate persistence of serious epidemiological situation regarding rickettsiosis of the tick-borne spotted fever group, Q fever, tick-borne borreliosis and CCHF in the south of Russia. Almost all tick-borne infections nosological forms in children under 14 years (including young children and infants) were widely involved in the epidemic process, which belong to patients at risk for a complicated disease course due to complicated diagnostics and treatment. The annual registration of tick-borne infections cases in the resort areas, with the subsequent occurrence of imported cases in other, including non-endemic regions poses a serious problem. The proposed forecasting models allow to predict the CСHF and ARF morbidity for each administrative district of the Astrakhan region with up to 91.7% accuracy. The explaining models CСHF accuracy for the Stavropol Territory and Astrakhan Region, when tested in 2022, was 88.5 and 83.3%, respectively, for ARF 91.7%. Conclusions. The further continuation of forecasting and explaining models verification for planning preventive measures and propose similar steps for tick-borne borreliosis and Q fever to epidemiological tick-borne infections to stabilize situation in the south of Russia.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Mice microglia cytokine profile changes under the influence of HSV-1 Synthetic thymic hexapeptide in the correction of alterations of antibacterial immune defense and normalization of the profile of proinflammatory cytokines in immunocompromized Children with local unlimited acute peritonitis Balance of pro- and anti-inflammatory cytokines in young patients who passed active Immunization against SARS-CoV-2 during the COVID-19 Pandemic Conserved linear B-cell peptides among the influenza A viral neuraminidases enhance the cross-protective potential of inactivated whole-virion influenza vaccine Characteristics of virus-specific immunological reactions following COVID-19 vaccination in heart transplant recipients
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1