State-of-the-art methods in model-based geostatistics (MBG) and its application to problems in global public health. Scientific objective is to describe the pattern of spatial variation in a health outcome using explicit probability models and established principles of statistical inference.

"This is an excellent source for public health professionals so far as the needed state-of-the-art concepts and methods that are needed to analyse and interpret geostatistical data. Basic knowledge of mathematical statistics is necessary to read through this well-written book... Focus has been made on disease mapping, environmental epidemiology, generalized linear models, variogram, and R-codes. The references are thorough and up-to-date. The examples are real-life oriented and interesting... Some unique features of this well-written book are the illustrations and they include river blindness in Liberia, heavy metal monitoring in Galicia, malnutrition in Ghana, rolling malaria in Malawi, ozone concentration in Eastern United States, prevalence and intensity of infection among others.This book is quite suitable to be a textbook for a graduate level course in global public health or geo-statistics. Researchers and doctoral graduate students seeking thesis topic ought to read this book. I enjoyed reading this book. I recommend this book to statistics and computing professionals."
- Ramalingam Shanmugam, in the Journal of Statistical Computation and Simulation, April 2020