Fine-Scale Space-Time Cluster Detection of COVID-19 in Mainland China Using Retrospective Analysis
Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a diff...
Main Authors: | Min Xu, Chunxiang Cao, Xin Zhang, Hui Lin, Zhong Yao, Shaobo Zhong, Zhibin Huang, Duerler Robert Shea |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
|
Series: | International Journal of Environmental Research and Public Health |
Subjects: | |
Online Access: | https://www.mdpi.com/1660-4601/18/7/3583 |
Similar Items
-
Cluster Initiative in Fine Chemicals as a Case of Practical Implementation of Triple Helix Collaboration for Regional Economic Growth and Innovation-Driven Development
by: Liana KOBZEVA, et al.
Published: (2017-03-01) -
Mapping Fine-Scale Urban Spatial Population Distribution Based on High-Resolution Stereo Pair Images, Points of Interest, and Land Cover Data
by: Min Xu, et al.
Published: (2020-02-01) -
Built Environment Typologies Prone to Risk: A Cluster Analysis of Open Spaces in Italian Cities
by: Alessandro D’Amico, et al.
Published: (2021-08-01) -
Determining endemic values of cutaneous leishmaniasis in Iranian Fars province by retrospectively detected clusters and receiver operating characteristic curve analysis
by: Marjan Zare, et al.
Published: (2019-01-01) -
New Constraints on Spatial Variations of the Fine Structure Constant from Clusters of Galaxies
by: Ivan De Martino, et al.
Published: (2016-12-01)