Modeling the spread of COVID-19 in New York City

被引：9

作者：

Olmo, Jose ^{[1
,2
]}

Sanso-Navarro, Marcos ^{[1
]}

机构：

[1] Univ Zaragoza, Dept Anal Econ, Zaragoza, Spain

[2] Univ Southampton, Dept Econ, Southampton, England

来源：

PAPERS IN REGIONAL SCIENCE | 2021年 / 100卷 / 05期

关键词：

Bayesian model averaging; COVID-19; Poisson regression; prediction models; spatial effects; MATHEMATICAL-THEORY; G-PRIORS; SELECTION; EPIDEMICS; UNCERTAINTY; FORECASTS; MIXTURES;

D O I：

10.1111/pirs.12615

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper proposes an ensemble predictor for the weekly increase in the number of confirmed COVID-19 cases in the city of New York at zip code level. Within a Bayesian model averaging framework, the baseline is a Poisson regression for count data. The set of covariates includes autoregressive terms, spatial effects, and demographic and socioeconomic variables. Our results for the second wave of the coronavirus pandemic show that these regressors are more significant to predict the number of new confirmed cases as the pandemic unfolds. Both pointwise and interval forecasts exhibit strong predictive ability in-sample and out-of-sample.

引用

页码：1209 / +

页数：22

共 39 条

[1] Almagro M., 2021, 37 OPP INCL GROWTH I
[2] JUE Insight: The determinants of the differential exposure to COVID-19 in New York city and their evolution over time
Almagro, Milena
Orane-Hutchinson, Angelo
[J]. JOURNAL OF URBAN ECONOMICS, 2022, 127
[3] Anselin L., 2003, COMPANION THEORETICA
[4] Borjas G.J., 2020, W26952 NAT BUR EC RE
[5] Cheshire PaulC., 2014, URBAN EC URBAN POLIC
[6] Choi Y., 2020, ARXIV200704743
[7] Clyde M., 2020, BAS: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
[8] Bayesian Adaptive Sampling for Variable Selection and Model Averaging
Clyde, Merlise A.
Ghosh, Joyee
Littman, Michael L.
[J]. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2011, 20 (01) : 80 - 101
[9] Spatial analysis of COVID-19 clusters and contextual factors in New York City
Cordes, Jack
Castro, Marcia C.
[J]. SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY, 2020, 34
[10] Black/African American Communities are at highest risk of COVID-19: spatial modeling of New York City ZIP Code-level testing results
DiMaggio, Charles
Klein, Michael
Berry, Cherisse
Frangos, Spiros
[J]. ANNALS OF EPIDEMIOLOGY, 2020, 51 : 7 - 13

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