دورية أكاديمية

Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States

التفاصيل البيبلوغرافية
العنوان: Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States
المؤلفون: Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu
المصدر: Geospatial Health, Vol 18, Iss 1 (2023)
بيانات النشر: PAGEPress Publications, 2023.
سنة النشر: 2023
المجموعة: LCC:Geography (General)
مصطلحات موضوعية: COVID-19, spatio-temporal feature analysis, IDW, spatiotemporal scan statistics, Bayesian spatio-temporal model, USA, Geography (General), G1-922
الوصف: This article examines three spatiotemporal methods used for analyzing of infectious diseases, with a focus on COVID-19 in the United States. The methods considered include inverse distance weighting (IDW) interpolation, retrospective spatiotemporal scan statistics and Bayesian spatiotemporal models. The study covers a 12-month period from May 2020 to April 2021, including monthly data from 49 states or regions in the United States. The results show that the spread of COVID-19 pandemic increased rapidly to a high value in winter of 2020, followed by a brief decline that later reverted into another increase. Spatially, the COVID-19 epidemic in the United States exhibited a multi-centre, rapid spread character, with clustering areas represented by states such as New York, North Dakota, Texas and California. By demonstrating the applicability and limitations of different analytical tools in investigating the spatiotemporal dynamics of disease outbreaks, this study contributes to the broader field of epidemiology and helps improve strategies for responding to future major public health events.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1827-1987
1970-7096
العلاقة: https://geospatialhealth.net/index.php/gh/article/view/1200Test; https://doaj.org/toc/1827-1987Test; https://doaj.org/toc/1970-7096Test
DOI: 10.4081/gh.2023.1200
الوصول الحر: https://doaj.org/article/79be83c3c08a4bfeb034cc332425ce33Test
رقم الانضمام: edsdoj.79be83c3c08a4bfeb034cc332425ce33
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:18271987
19707096
DOI:10.4081/gh.2023.1200