id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-281177-2eycqf8o	Robertson, Colin	Review of methods for space–time disease surveillance	2010-02-20		.txt	text/plain	8860	449	44	Surveillance systems serve a variety of public health functions (e.g., outbreak detection, control planning) by integrating data representing human and/or animal health with statistical methods (Diggle, 2003) , visualization tools (Moore et al., 2008) , and increasingly, linkage with other geographic datasets within a GIS (Odiit et al., 2006) . Space-time scan statistics are able to detect and locate clusters of disease, and can condition expected counts for individual sub-regions on population data or on previous case data, making these methods suitable for implementation where data volume is large. At the root of the problem is a conceptual discrepancy between the definition of a disease outbreak (which disease surveillance systems are often interested in detecting) and a disease cluster (defined by spatial proximity) which is common to all statistical testing methods for space-time surveillance (Lawson, 2005) .	./cache/cord-281177-2eycqf8o.txt	./txt/cord-281177-2eycqf8o.txt