Background: Nutrition is not a treatment for COVID-19, but it is a modifiable contributor to the
development of chronic disease, which is highly associated with COVID-19 severe illness …

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from
the basics of disease mapping to the most advanced topics in this field. A multidimensional …

消除贫困是人类社会的共同目标. 贫困分布具有明显的空间特征, 同时呈现出空间异质性和空间
相关性. 时空统计学以时空分析为优势, 在贫困的时空分布及形成机制研究中发挥了重要作用 …

In this paper, our aim is to analyze geographical and temporal variability of disease
incidence when spatio‐temporal count data have excess zeros. To that end, we consider …

Zero excess in the study of geographically referenced mortality data sets has been the focus
of considerable attention in the literature, with zero‐inflation being the most common …

Disease mapping models have been popularly used to model disease incidence with spatial
correlation. In disease mapping models, zero inflation is an important issue, which often …

Spatial epidemiology often involves the analysis of spatial count data with an unusually high
proportion of zero observations. While Bayesian hierarchical models perform very well for …

In this work we introduce a spatio-temporal process with pareto marginal distributions.
Dependence in space and time is introduced through the use of latent variables in a …

To study the impact of climate variables on morbidity of some diseases in Mexico, we
propose a spatiotemporal varying coefficients regression model. For that we introduce a new …

We describe a procedure to introduce general dependence structures on a set of random
variables. These include order-q moving average-type structures, as well as seasonal …