Bayesian space-time SIR modeling of Covid-19 in two US states during the 2020-2021 pandemic

被引：6
|
作者：
Lawson, Andrew B. [1 ]
Kim, Joanne [1 ]
机构：
[1] Med Univ South Carolina, Dept Publ Hlth Sci, Charleston, SC 29425 USA
来源：
PLOS ONE | 2022年 / 17卷 / 12期
关键词：
D O I：
10.1371/journal.pone.0278515
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in two contrasting US states during 2020-2021. A variety of models are evaluated at the county level for goodness-of-fit and an assessment of confounding predictors is also made. It is found that models with three deprivation predictors and neighborhood effects are important. In addition, the work index from Google mobility was also found to provide an increased explanation of the transmission dynamics.
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页数：20
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