地理信息系统软件综合体“俄罗斯流行病学地图集”分析模块的开发。“联邦区领土”,用于进一步分析流行病学过程。

Sovremennye tekhnologii v meditsine Pub Date : 2024-01-01 Epub Date: 2024-12-27 DOI:10.17691/stm2024.16.6.02
S A Sarskov, M V Vyushkov, S L Slavin, N N Zaitseva
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引用次数: 0

摘要

这项研究的目的是开发关于当前传染病和寄生虫病的地理信息软件综合体的附加分析模块,以提高流行病学监测的质量,并建立一个关于俄罗斯联邦各主题流行病进程发展趋势的数据库。材料和方法:使用符合软件复合体一般概念的软件(JavaScript、PHP等)开发了对病种组发病率进行比较和动态分析的附加分析块,并将其集成到新版Web应用程序“俄罗斯流行病学地图集”中。联邦区领土”。在免费的关系型MySQL数据库管理系统的控制下,将包括疾病组信息在内的初始数据转换成一组相互关联的表,并进一步整合到新版Atlas数据库中。结果:分析了现有病种分类和寻找可能形成病种分组的附加特征,优化了现有流行病学地图集数据库。设计了以病理性分组估算累积发病率的新分析块中流行病学指标的获取和评价算法。为Web应用程序“俄罗斯流行病学地图集”创建了原始的分析模块“病种分组发病率比较分析”和“病种分组发病率动态分析”。“联邦区领土”,根据行政领土主体单位、地区主体和整个地区的疾病分组进行比较和动态发病率分析,并提供详细信息的可能性。基于数据库查询的材料包含时间(日历月)和空间细节(俄罗斯联邦主题的行政领土单位)。所有材料都可以导出为各种格式(.xls、。pdf、。csv、。png、。jpeg、。svg)的表格、图形或地图。由于伏尔加河联邦区和俄罗斯当前流行病学地图集的数据库是通用的,因此处理表格和查询的机制是相同的,因此在复制新的Web应用程序版本时,可以使用俄罗斯流行病学地图集或其他联邦区地图集中采用的开发方法。新的分析单元可以扩展关于当前传染病发病率的概念,揭示区域特征,促进行政当局提出更准确、有科学根据的决策建议,并及时采取预防和抗流行病措施。结论:开发的分析模块集成到新版“俄罗斯联邦区领土流行病学地图集”中,旨在扩展地理信息软件综合体的分析能力。它们的特点是,在优化和提高流行病学监测、在一个单独的主题、联邦区和整个俄罗斯联邦对当前传染病和寄生虫病的操作和回顾性流行病学分析和质量方面具有重要意义,并具有进一步改进分析方法和技术的重要潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Development of Analytical Modules of the Geographic Information System Software Complex "Epidemiological Atlas of Russia. Territory of the Federal District" for Additional Analysis of Epidemiological Processes.

Development of Analytical Modules of the Geographic Information System Software Complex "Epidemiological Atlas of Russia. Territory of the Federal District" for Additional Analysis of Epidemiological Processes.

Development of Analytical Modules of the Geographic Information System Software Complex "Epidemiological Atlas of Russia. Territory of the Federal District" for Additional Analysis of Epidemiological Processes.

The aim of the study is to develop additional analytical modules of geoinformation software complex on current infectious and parasitic diseases aimed to improve the quality of epidemiological monitoring and to generate a database on the trends of epidemical process development in the subjects of the Russian Federation.

Materials and methods: Additional analytical blocks on comparative and dynamic analysis of morbidity by the groups of nosologies were developed using the software meeting the general concept of the software complex (JavaScript, PHP, and others) and integrated into a new version of the Web application "Epidemiological Atlas of Russia. Territory of the Federal District". The initial data including information by the groups of diseases were converted into a set of interrelated tables with their further integration into the database of a new version of the Atlas under the control of a free relational MySQL database management system.

Results: The existing classifications of nosologic forms and the search for additional characteristics, potentially forming the groups of nosologies, have been analyzed and the current database of the Epidemiological Atlas has been optimized. The algorithms for obtaining and evaluating epidemiological indicators in the new analytical blocks for estimating cumulative morbidity by the nosologic groups were designed. There were created original analytical modules "Comparative analysis of morbidity by the groups of nosologies" and "Dynamic analysis of morbidity by the groups of nosologies" for the Web application "Epidemiological Atlas of Russia. Territory of Federal District" for the comparative and dynamic morbidity analysis based on the groups of nosologies in the administrative-territorial subject units, in the district subjects, and in the district as a whole, with the possibility of information detailing. The materials based on the database queries contain temporal (calendar month) and spatial detailing (administrative-territory unit of the Russian Federation subject). All materials may be exported as tables, graphs, or maps in various formats (.xls, .pdf, .csv, .png, .jpeg, .svg). Since the databases of the current epidemiological atlases of the Volga Federal District and Russia are universal, the mechanisms of processing tables and queries are identical providing the possibility of using the developed approaches employed in the Epidemiological Atlas of Russia or atlases of other federal districts in case of replicating a new Web application version. New analytical blocks may extend notions on the incidence of current infectious diseases and reveal characteristic regional features, facilitate more exact scientifically grounded proposals for decision-making by the executive authorities and timely taking preventive and anti-epidemic measures.

Conclusion: The developed analytical modules integrated into the new version of the "Epidemiological Atlas of Russia, Territory of the Federal District" were designed to extend the analytical capabilities of the geoinformation software complex. They are characterized by a high significance in optimization and quality improvement of epidemiological monitoring, operative and retrospective epidemiological analysis of current infectious and parasitic diseases in a separate subject, a federal district, and the Russian Federation as a whole, and represent an essential potential for further improvement of analytical methods and technologies.

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