Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space-time variations in disease incidences. These analyses can provide important information that leads to better decision making in public health. The first part of the book addresses general issues related to epidemiology, GIS, environmental studies, clustering, and ecological analysis. The second part presents basic statistical methods used in spatial epidemiology, including fundamental likelihood principles, Bayesian methods, and testing and nonparametric approaches. With a focus on special methods, the third part describes geostatistical models, splines, quantile regression, focused clustering, mixtures, multivariate methods, and much more. The final part examines special problems and application areas, such as residential history analysis, segregation, health services research, health surveys, infectious disease, veterinary topics, and health surveillance and clustering. Spatial epidemiology, also known as disease mapping, studies the geographical or spatial distribution of health outcomes. This handbook offers a wide-ranging overview of state-of-the-art approaches to determine the relationships between health and various risk factors, empowering researchers and policy makers to tackle public health problems.
Berchuck, S., M. Janko, F. Medeiros, W. Pan, and S. Mukherjee (2019). Bayesian non-parametric factor analysis for longitudinal spatial surfaces. arxiv:1911.04337v1. prepub. Berman, M. and T. R. Turner (1992).
This book brings together contributions from an international group of practitioners from a wide spectrum of disciplinesincluding epidemiologists, statisticians, geographers, demographers and pollution modellers, providing a comprehensive ...
Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.
Vinten-Johansen, P., Brody, H., Paneth, N., Rachman, S., Rip, M., 2003. Cholera, Chloroform, and the Science ... Walter, S., Martin Taylor, S., Marrett, L., 1999. An analysis of determinants of ... Wartenberg, D., Greenberg, M., 1990.
This book provides a practical, comprehensive and up-to-date overview of the use of spatial statistics in epidemiology - the study of the incidence and distribution of diseases.
Aßheuer, T., Thiele-Eich, I., and Braun, B., 2013. Coping with the impacts of severe flood events in Dhaka's slums—the role of social capital. Erdkunde, 67(1): 21–35. Awata, S. Bech, P. Yoshida, S. Suzuki, S. Yamashita, M. Ohara, A., ...
Spatial Epidemiology
The theoretical upper bound is 2 l/Z N Z Z wij(Yi — 7) Ills N if' "=1 N N 221147 ZZ i;éjj=1 i=1 (cf. Cliff and Ord 1981, p. 21; Haining 1990, p. 234; Bailey and Gatrell 1995, p. 270). Moran's I is very similar to Pearson's ...
Addressing this gap, Handbook of Spatial Point-Pattern Analysis in Ecology shows how the t
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, and other spatial biostatistical areas.