Using infectious intestinal disease surveillance data to explore illness aetiology; a cryptosporidiosis case study.
Infectious intestinal disease (IID) surveillance data are an under-utilised information source on illness geography. This paper uses a case study of cryptosporidiosis in England and Wales to demonstrate how these data can be converted into area-based rates and the factors underlying illness geography investigated. Ascertainment bias is common in surveillance datasets, and we develop techniques to investigate and control this. Rural areas, locations with many livestock and localities with poor water treatment had elevated levels of cryptosporidiosis. These findings accord with previous research validating the techniques developed. Their use in future studies investigating IID geography is therefore recommended.
Lake
Iain R
IR
School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK. i.lake@uea.ac.uk
Nichols
Gordon
G
Harrison
Florence C D
FC
Bentham
Graham
G
Sari Kovats
R
R
Grundy
Chris
C
Hunter
Paul R
PR
D016000:Cluster Analysis; D003457:Cryptosporidiosis / Q000453:epidemiology / Q000209:etiology*; D004403:Dysentery / Q000209:etiology*; D004739:England / Q000453:epidemiology; D006801:Humans; D011159:Population Surveillance; D014852:Wales / Q000453:epidemiology; D014881:Water Supply