ArticleStochastic environmental research and risk assessment : research journal2022
A comparison of multiple neighborhood matrix specifications for spatio-temporal model fitting: a case study on COVID-19 data.
Article in Stochastic environmental research and risk assessment : research journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04581096 (Evaluation of the Response of COVID-19 Spread With a Spatiotemporal Analysis in a Tertiary Hospital), which is not on this map. Cited by 7 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Evaluation of the Response of COVID-19 Spread With a Spatiotemporal Analysis in a Tertiary Hospital
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- A Mixture of Distributed Lag Non-Linear Models to Account for Spatially Heterogeneous Exposure-Lag-Response Associations.Statistics in medicine · 2026Article
- Wildfires and climate justice: future wildfire events predicted to disproportionally impact socioeconomically vulnerable communities in North Carolina.Frontiers in public health · 2024Article
- Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study.The Lancet regional health. Southeast Asia · 2023Article
- Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia.BMC public health · 2023Article
- Multivariate Kalman filtering for spatio-temporal processes.Stochastic environmental research and risk assessment : research journal · 2022Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Establishing proper neighbor relations between a set of spatial units under analysis is essential when carrying out a spatial or spatio-temporal analysis. However, it is usual that researchers choose some of the most typical (and simple) neighborhood structures, such as the first-order contiguity matrix, without exploring other options. In this paper, we compare the performance of different neighborhood matrices in the context of modeling the weekly relative risk of COVID-19 over small areas located in or near Valencia, Spain. Specifically, we construct contiguity-based, distance-based, covariate-based (considering mobility flows and sociodemographic characteristics), and hybrid neighborhood matrices. We evaluate the goodness of fit, the overall predictive quality, the ability to detect high-risk spatio-temporal units, the capability to capture the spatio-temporal autocorrelation in the data, and the goodness of smoothing for a set of spatio-temporal models based on each of the neighborhood matrices. The results show that contiguity-based matrices, some of the distance-based matrices, and those based on sociodemographic characteristics perform better than the matrices based on
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