Estimation of COVID-19 mortality in the United States using Spatio-temporal Conway Maxwell Poisson model.
Spat Stat
; 49: 100542, 2022 Jun.
Article
in English
| MEDLINE | ID: covidwho-1458685
ABSTRACT
Spatio-temporal Poisson models are commonly used for disease mapping. However, after incorporating the spatial and temporal variation, the data do not necessarily have equal mean and variance, suggesting either over- or under-dispersion. In this paper, we propose the Spatio-temporal Conway Maxwell Poisson model. The advantage of Conway Maxwell Poisson distribution is its ability to handle both under- and over-dispersion through controlling one special parameter in the distribution, which makes it more flexible than Poisson distribution. We consider data from the pandemic caused by the SARS-CoV-2 virus in 2019 (COVID-19) that has threatened people all over the world. Understanding the spatio-temporal pattern of the disease is of great importance. We apply a spatio-temporal Conway Maxwell Poisson model to data on the COVID-19 deaths and find that this model achieves better performance than commonly used spatio-temporal Poisson model.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal:
Spat Stat
Year:
2022
Document Type:
Article
Affiliation country:
J.spasta.2021.100542
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