Environmental Epidemiology Statistics

Applied Spatial Data Analysis with R is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS.

by Michael J. Panik (Author)

The novel viral pandemic coronavirus disease 2019 (COVID-19) has sparked uncertainties and controversies as to its origin, epidemiology, and natural course. In this situation, the medical disciplines have strived to contribute to a better understanding of the disease with the best available evidence gained from the scientific method of observation and statistics. The study of the cutaneous manifestations of COVID-19 has evolved with the hope that they may be useful as markers for the disease, for prognostication, and further insights into the pathogenesis of the disease manifestations. In the wake of COVID-19, we have decided to take a more general look at the hair and scalp in infectious disease. Specifically, we must recognize that infectious diseases have wider preconditions besides the infectious agents, to include environmental and societal factors. Unless we also take account of the ecological, immunological, and behavioral circumstances that affect the emergence and spread of infectious diseases, including those of the hair and scalp, our knowledge of the pathogens and their connection to clinical disease presentation remain only partial and incomplete.