Since the publication of the second edition, many new Bayesian tools and methods have
been developed for space-time data analysis, the predictive modeling of health outcomes …

It has long been known that air pollution is harmful to human health, as many
epidemiological studies have been conducted into its effects. Collectively, these studies …

Spatiotemporal visualization and analytical tools (SATs) are increasingly being applied to
risk-based surveillance/monitoring of adverse health events affecting humans, animals, and …

The health impact of long‐term exposure to air pollution is now routinely estimated using
spatial ecological studies, owing to the recent widespread availability of spatial referenced …

Statistical models used to estimate the spatiotemporal pattern in disease risk from areal unit
data represent the risk surface for each time period with known covariates and a set of …

Dengue disease has become a major public health problem. Accurate and precise
identification, prediction and mapping of high-risk areas are crucial elements of an effective …

Background Estimating the long-term health impact of air pollution in a spatio-temporal
ecological study requires representative concentrations of air pollutants to be constructed for …

Progressively more and more attention has been paid to how location affects health
outcomes. The area of disease mapping focusses on these problems, and the Bayesian …

Exposure to high levels of air pollutant concentration is known to be associated with
respiratory problems which can translate into higher morbidity and mortality rates. The link …

The field of spatio-temporal modelling has witnessed a recent surge as a result of
developments in computational power and increased data collection. These developments …