The Internet search engines as an additional tool in public health research in the context of disease outbreaks

被引:2
|
作者
Batrimenko, Andrey Valerievich [1 ]
Denisova, Svetlana [2 ]
Lisovskii, Dmitrii [3 ]
Orlov, Sergey [3 ]
Soshnikov, Sergey [3 ,4 ]
机构
[1] Natl Res Univ, Moscow Inst Phys & Technol, Dolgoprudnyj, Russia
[2] AI Yevdokimov Moscow State Univ Med & Dent, Minist Healthcare Russian Federat, Moscow, Russia
[3] IM Sechenov First Moscow State Med Univ, Sechenov Univ, Inst Leadership & Hlth Management, Moscow, Russia
[4] Moscow Inst Phys & Technol, Lab Anal Populat Hlth Indicators & Digitalizat Hl, Dolgoprudnyj, Russia
关键词
Public health; Statistics; INFECTION; IMMUNITY;
D O I
10.1108/IJHG-09-2021-0094
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Purpose The study aims to help epidemiologists identify new patterns and trends in spreading infections on the example of the current coronavirus disease 2019 (COVID-19) pandemic using data from search engines. The study identified the types of thematic search of Russian Internet users and queries that have a mathematically confirmed correlation with public health indicators: mortality and morbidity from COVID-19. The study aims to determine digital epidemiology search trends to the current COVID-19 pandemic. The study identified the types of thematic search of RuNet users and queries that have a mathematically confirmed correlation with public health indicators: mortality and morbidity from COVID-19. Design/methodology/approach The authors explored two types of data: (1) the monthly datasets of keywords relevant to COVID-19 extracted from the Yandex search engine and (2) officially published statistics data. Alongside, the authors searched for associations between all variables in this dataset. The Benjamin-Hochberg correction for multiple hypothesis testing was applied to the obtained results to improve the reliability of the results. The authors built a unique website with opportunities to update datasets and designed dashboards to visualize the research outcomes using PHP and Python. Findings The research results show the number of significant relationships that the authors interpreted in epidemiology as a new instrument in Public Health research. There are 132 data combinations with a correlation higher than 75%, making it possible to determine a mathematically reliable relationship between search statistics trends and mortality/morbidity indicators. The most statistically significant effects identified in bundles "query" - "query", "query" - "morbidity", "query" - "mortality". Originality/value The authors developed a new approach in analyzing outbreaks of infections and their consequences based on a comprehensive analysis of epidemiological and infodemic data. The research results are relevant to public health as other decision-making and situational analysis tools for citizens and specialists who want to receive additional confirmation for the indicators of the official statistics of the headquarters for control and monitoring of the situation with coronavirus and others infections.
引用
收藏
页码:194 / 207
页数:14
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