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Kriging the Local Risk of a Rare Disease from a Register of Diagnoses
Author(s) -
Webster R.,
Oliver M. A.,
Muir K. R.,
Mann J. R.
Publication year - 1994
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/j.1538-4632.1994.tb00318.x
Subject(s) - variogram , statistics , covariate , mathematics , binomial distribution , negative binomial distribution , epidemiology , kriging , econometrics , demography , medicine , poisson distribution , sociology
A substantial problem in studying the geographical epidemiology of rare noncontagious diseases is to estimate the risks of their development within populations. A geostatistical solution is described and illustrated by a case study of cancer among children in the West Midlands of England for the years 1980 to 1984 inclusive. Data consist of the numbers of diagnosed cases of cancer and of healthy children in each of 838 electoral wards, the centroids of which are known accurately. The rate of incidence or frequency, equal to the number of cases divided by the number of children, is a binomial variable and is treated as a realization of the underlying risk of a child's developing the disease that varies from place to place. The experimental variogram of the frequency was computed using the standard formulation. The variogram of the risk was obtained from it taking into account the numbers of children at risk and the error associated with each observed frequency. The variogram of the risk increased monotonically from 0 at zero lag to about 50 kilometers, and it was modeled as Whittle's two‐dimensional elementary correlation function. The covariances of frequency and cross‐covariances between the frequency and the risk were derived from it, and these were then used together with the data to krige the risk and map it. The risk of developing the disease is shown to have a patchy distribution, strongly autocorrelated at the regional scale of the investigation.