The development of powerful computing environment and the geographical information system (GIS) in recent decades has thrust the analysis of geo-referenced disease incidence data into the mainstream of spatial epidemiology. This book offers a modern perspective on statistical methods for detecting disease clustering, an indispensable procedure to find a statistical evidence on aetiology of the disease under study.
With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Furthermore, the research area of statistical methods for disease clustering now attracts a wide audience due to the perceived need to implement wide-ranging monitoring systems to detect possible health-related events such as the occurrence of the severe acute respiratory syndrome (SARS), pandemic influenza and bioterrorism

@book{tango2010statistical, author = {Tango, Toshiro}, title = {Statistical Methods for Disease Clustering}, series = {Statistics for Biology and Health}, publisher = {Springer New York}, address = {New York, NY}, year = {2010}, edition = {1}, url = {http://scans.hebis.de/HEBCGI/show.pl?22114256_aub.html}, isbn = {1441915729 (Sekundärausgabe)}, keywords = {bachelor, clustering, disease, kursarbeit, literaturliste}, abstract = {The development of powerful computing environment and the geographical information system (GIS) in recent decades has thrust the analysis of geo-referenced disease incidence data into the mainstream of spatial epidemiology. This book offers a modern perspective on statistical methods for detecting disease clustering, an indispensable procedure to find a statistical evidence on aetiology of the disease under study.
With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Furthermore, the research area of statistical methods for disease clustering now attracts a wide audience due to the perceived need to implement wide-ranging monitoring systems to detect possible health-related events such as the occurrence of the severe acute respiratory syndrome (SARS), pandemic influenza and bioterrorism} }

%0 = book %A = Tango, Toshiro %C = New York, NY %D = 2010 %I = Springer New York %T = Statistical Methods for Disease Clustering %U = http://scans.hebis.de/HEBCGI/show.pl?22114256_aub.html