Figure 6
From: Spatiotemporal Analysis of Influenza in China, 2005–2018
Map of the posterior probabilities of convolutional spatial relative risk (\({e}^{{\upsilon }_{i}+{\nu }_{i}}\)) > 1.0, spatiotemporal model of influenza incidence risk with covariates, China Prefectures, 2005–2018. Note: The linear terms in the model of spatiotemporal model of influenza incidence risk with covariates were \(\log ({\theta }_{ij})={\rm{\alpha }}+{\sum }_{k=1}^{n}{\beta }_{k}{x}_{k}+\)\({\nu }_{i}+{\upsilon }_{i}+{\gamma }_{1j}+{\delta }_{ij}\), which included all variables in the univariate analysis models; an intercept (α); a spatially unstructured random effect term (νi); a spatially structured conditional autoregression term (υi); a first-order random walk-correlated time variable (γ1j); and an interaction term for time and place (δij).
