Spatio-temporal small area surveillance of the COVID-19 pandemic

被引:3
作者
Martinez-Beneito, Miguel A. [1 ,2 ]
Mateu, Jorge [3 ]
Botella-Rocamora, Paloma [2 ,4 ]
机构
[1] Univ Valencia, Dept Stat & Operat Res, Burjassot, Valencia, Spain
[2] UV FISABIO, Unitat Mixta recerca metodes estadist dades Biome, Valencia, Spain
[3] Univ Jaume I Castellon, Dept Math, Castellon de La Plana, Spain
[4] Conselleria Sanitat & Universal Salut Publ, Subdirecc Gen Epidemiol Vigilancia Salud & Sanidad, Valencia, Spain
关键词
COVID-19; Disease mapping; Instantaneous reproduction number; Spatio-temporal modelling;
D O I
10.1016/j.spasta.2021.100551
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The emergence of COVID-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with small units of analysis, are a priority in this context. These models provide geographically detailed and temporally updated overviews of the current state of the pandemic, making public health interventions more effective. These models also allow estimating epidemiological indicators highly demanded for COVID-19 surveillance, such as the instantaneous reproduction number R-t, even for small areas. In this paper, we propose a new spatio-temporal spline model particularly suited for COVID-19 surveillance, which allows estimating and monitoring R-t for small areas. We illustrate our proposal on the study of the disease pandemic in two Spanish regions. As a result, we show how tourism flows have shaped the spatial distribution of the disease in these regions. In these case studies, we also develop new epidemiological tools to be used by regional public health services for small area surveillance. (c) 2021 The Author(s). Published by Elsevier B.V.
引用
收藏
页数:13
相关论文
共 23 条
[1]  
[Anonymous], Centro Nacional de Epidemiologia
[2]   BAYESIAN IMAGE-RESTORATION, WITH 2 APPLICATIONS IN SPATIAL STATISTICS [J].
BESAG, J ;
YORK, J ;
MOLLIE, A .
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1991, 43 (01) :1-20
[3]  
Consejo Interterritorial Sistema Nacional de Salud, COORDINATED RESPONSE
[4]  
Cori Anne, 2021, CRAN
[5]   A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics [J].
Cori, Anne ;
Ferguson, Neil M. ;
Fraser, Christophe ;
Cauchemez, Simon .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2013, 178 (09) :1505-1512
[6]  
Cressie N, 2011, WILEY SERIES PROBABI
[7]   Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: A data-driven analysis [J].
Fang, Yaqing ;
Nie, Yiting ;
Penny, Marshare .
JOURNAL OF MEDICAL VIROLOGY, 2020, 92 (06) :645-659
[8]   Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe [J].
Han, Emeline ;
Tan, Melisa Mei Jin ;
Turk, Eva ;
Sridhar, Devi ;
Leung, Gabriel M. ;
Shibuya, Kenji ;
Asgari, Nima ;
Oh, Juhwan ;
Garcia-Basteiro, Alberto L. ;
Hanefeld, Johanna ;
Cook, Alex R. ;
Hsu, Li Yang ;
Teo, Yik Ying ;
Heymann, David ;
Clark, Helen ;
McKee, Martin ;
Legido-Quigley, Helena .
LANCET, 2020, 396 (10261) :1525-1534
[9]   Assessment of basic reproduction number (R0), spatial and temporal epidemiological determinants, and genetic characterization of SARS-CoV-2 in Bangladesh [J].
Islam, Ariful ;
Abu Sayeed, Md ;
Rahman, Md Kaisar ;
Zamil, Shafayat ;
Abedin, Josefina ;
Saha, Otun ;
Hassan, Mohammad Mahmudul .
INFECTION GENETICS AND EVOLUTION, 2021, 92
[10]  
Leroux B.G., 1999, Statistical models in epidemiology, the environment and clinical trials