Endemic-epidemic models to understand COVID-19 spatio-temporal evolution

被引：14
作者：
Celani, Alessandro [1 ]
Giudici, Paolo [2 ]
机构：
[1] Polytech Univ Marche, Dipartimento Sci Econ & Sociali, Piazzale Raffaele Martelli 8, I-60121 Ancona, Italy
[2] Univ Pavia, Dipartimento Sci Econ & Aziendali, Via San Felice Al Monastero 5, I-27100 Pavia, Italy
来源：
SPATIAL STATISTICS | 2022年 / 49卷
关键词：
Contagion models; Multivariate statistics; COVID-19; Poisson processes; Spatio-temporal models;
D O I：
10.1016/j.spasta.2021.100528
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
We propose an endemic-epidemic model: a negative binomial space-time autoregression, which can be employed to monitor the contagion dynamics of the COVID-19 pandemic, both in time and in space. The model is exemplified through an empirical analysis of the provinces of northern Italy, heavily affected by the pandemic and characterized by similar non-pharmaceutical policy interventions. (C) 2021 Elsevier B.V. All rights reserved.
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页数：15
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共 32 条
  • [11] Predictive Model Assessment for Count Data
    Czado, Claudia
    Gneiting, Tilmann
    Held, Leonhard
    [J]. BIOMETRICS, 2009, 65 (04) : 1254 - 1261
  • [12] An interactive web-based dashboard to track COVID-19 in real time
    Dong, Ensheng
    Du, Hongru
    Gardner, Lauren
    [J]. LANCET INFECTIOUS DISEASES, 2020, 20 (05) : 533 - 534
  • [13] An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian regions
    Farcomeni, Alessio
    Maruotti, Antonello
    Divino, Fabio
    Jona-Lasinio, Giovanna
    Lovison, Gianfranco
    [J]. BIOMETRICAL JOURNAL, 2021, 63 (03) : 503 - 513
  • [14] Integer-valued GARCH process
    Ferland, Rene
    Latour, Alain
    Oraichi, Driss
    [J]. JOURNAL OF TIME SERIES ANALYSIS, 2006, 27 (06) : 923 - 942
  • [15] Fronterre C, 2020, MEDRXIV
  • [16] Girardi P, 2020, Arxiv, DOI arXiv:2004.03187
  • [17] Mixtures of products of Dirichlet processes for variable selection in survival analysis
    Giudici, P
    Mezzetti, M
    Muliere, P
    [J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2003, 111 (1-2) : 101 - 115
  • [18] Giudici P, 2000, STAT MED, V19, P2579, DOI 10.1002/1097-0258(20000915/30)19:17/18<2579::AID-SIM589>3.0.CO
  • [19] 2-G
  • [20] Modelling and predicting the spatio-temporal spread of cOVID-19 in Italy
    Giuliani, Diego
    Dickson, Maria Michela
    Espa, Giuseppe
    Santi, Flavio
    [J]. BMC INFECTIOUS DISEASES, 2020, 20 (01)
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