Spatial Disease Surveillance: Methods and Applications

Chapter
Part of the Computational Biology book series (COBO, volume 15)

Keywords

Markov Chain Monte Carlo Spatial Cluster Spatial Weight Matrix Cluster Detection Disease Mapping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    A. Agresti. Categorical Data Analysis. Wiley, New York, 2002. MATHCrossRefGoogle Scholar
  2. 2.
    L. Anselin. Local indicators of spatial association-LISA. Geogr Anal, 27:93–115, 1995. CrossRefGoogle Scholar
  3. 3.
    R. Assuncao and E. Reis. A new proposal to adjust Moran’s I for population density. Stat Med, 18:2147–2162, 1999. CrossRefGoogle Scholar
  4. 4.
    R. Assuncao, M. Costa, A. Tavares, and S. Ferreira. Fast detection of arbitrarily shaped disease clusters. Stat Med, 25:723–745, 2006. MathSciNetCrossRefGoogle Scholar
  5. 5.
    J. Besag and J. Newell. The detection of clusters in rare diseases. J R Stat Soc A, 154:143–155, 1991. CrossRefGoogle Scholar
  6. 6.
    D.G. Clayton and J. Kaldor. Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics, 43:671–681, 1987. CrossRefGoogle Scholar
  7. 7.
    A.D. Cliff and J.K. Ord. Spatial Processes: Models And Applications. Pion, London, 1981. MATHGoogle Scholar
  8. 8.
    N. Cressie and N. Chen. Spatial modeling of regional variables. J Am Stat Assoc, 84:393–401, 1989. MATHCrossRefGoogle Scholar
  9. 9.
    A.C. Davison and D.V. Hinkley. Bootstrap Methods and Their Application. Cambridge University Press, Cambridge, 1997. MATHGoogle Scholar
  10. 10.
    P.J. Diggle. Overview of statistical methods for disease mapping and its relationship to cluster detection. In P. Elliott, J.C. Wakefield, N.G. Best, and D.J. Briggs, editors, Spatial Epidemiology: Methods and Applications, pages 87–103. Oxford University Press, London, 2000. Google Scholar
  11. 11.
    P. Diggle, J.A. Tawn, and R.A. Moyeed. Model-based Geostatistics with discussion. Appl Stat, 47:299–350, 1998. MathSciNetMATHGoogle Scholar
  12. 12.
    M. Dwass. Modified randomization tests for nonparametric hypothesis. Ann Math Stat, 28:181–187, 1957. MathSciNetMATHCrossRefGoogle Scholar
  13. 13.
    J. Faraway. Extending the Linear Model with R. Chapman & Hall, Boca Raton, 2006. MATHGoogle Scholar
  14. 14.
    R.E. Gangnon and M.K. Clayton. Cluster modeling for disease rate mapping. In A.B. Lawson and G.T. Denison, editors, Spatial Cluster Modelling, pages 147–162. Chapman & Hall/CRC, London, 2002. Google Scholar
  15. 15.
    R.C. Geary. The contiguity ratio and statistical mapping. Inc Stat, 5:115–145, 1954. Google Scholar
  16. 16.
    A. Getis and J. Ord. The analysis of spatial association by use of distance statistics. Geogr Anal, 24:189–206, 1992. CrossRefGoogle Scholar
  17. 17.
    P. Good. Permutation Tests. Springer, New York, 2000. MATHCrossRefGoogle Scholar
  18. 18.
    P. Green and S. Richardson. Hidden Markov models and disease mapping. J Am Stat Assoc, 96:1055–1070, 2002. MathSciNetCrossRefGoogle Scholar
  19. 19.
    R. Haining. Spatial Data Analysis in the Social and Environmental Sciences. Cambridge University Press, Cambridge, 1990. CrossRefGoogle Scholar
  20. 20.
    R. Haining, J. Law, and D. Griffith. Modelling small area counts in the presence of overdispersion and spatial autocorrelation. Comput Stat Data Anal, 53:2923–2947, 2009. MathSciNetMATHCrossRefGoogle Scholar
  21. 21.
    M. Kulldorff. A spatial scan statistic. Commun Stat Theory Methods, 26:1481–1496, 1997. MathSciNetMATHCrossRefGoogle Scholar
  22. 22.
    M. Kulldorff. SaTScan v7.0.1: Software for the Spatial and Space-time Scan Statistic. Information Management Services Inc., 2006, http://www.satscan.org/.
  23. 23.
    M. Kulldorff and N. Nagarwalla. Spatial disease clusters: detection and inference. Stat Med, 14:799–810, 1995. CrossRefGoogle Scholar
  24. 24.
    M. Kulldorff, T. Tango, and P. Park. Power comparisons for disease clustering tests. Comput Stat Data Anal, 42:665–684, 2003. MathSciNetMATHCrossRefGoogle Scholar
  25. 25.
    A.B. Lawson. Statistical Methods in Spatial Epidemiology. Wiley, New York, 2001. MATHGoogle Scholar
  26. 26.
    A.B. Lawson and A. Clark. Spatial mixture relative risk models applied to disease mapping. Stat Med, 21:359–370, 2002. CrossRefGoogle Scholar
  27. 27.
    A.B. Lawson and D.G.T. Denison. Spatial Clustering Modeling. CRC Press, New York, 2002. CrossRefGoogle Scholar
  28. 28.
    G. Lin and T. Zhang. Loglinear residual tests of Moran’s I autocorrelation and their applications to Kentucky Breast Cancer Data. Geogr Anal, 38:209–225, 2006. CrossRefGoogle Scholar
  29. 29.
    G. Lin and T. Zhang. Loglinear residual tests of Moran’s I autocorrelation and their applications to Kentucky Breast Cancer Data. Geogr Anal, 39:293–310, 2007. CrossRefGoogle Scholar
  30. 30.
    P. McCullagh. Quasi-likelihood functions. Ann Stat, 11:59–67, 1983. MathSciNetMATHCrossRefGoogle Scholar
  31. 31.
    P.A.P. Moran. The interpretation of statistical maps. J R Stat Soc Ser B, 10:243–251, 1948. MATHGoogle Scholar
  32. 32.
    J.I. Naus. The distribution of the size of the maximum cluster of points on the line. J Am Stat Assoc, 60:532–538, 1965. MathSciNetCrossRefGoogle Scholar
  33. 33.
    S. Openshaw, M. Charlton, C. Wymer, and A.W. Craft. A mark I geographical analysis machine for the automated analysis of point data sets. Int J GIS, 1:335–358, 1987. Google Scholar
  34. 34.
    K. Ord. Estimation methods for models of spatial interaction. J Am Stat Assoc, 70:120–126, 1975. MathSciNetMATHCrossRefGoogle Scholar
  35. 35.
    S.C. Richardson and C. Monfort. Ecological correlation studies. In P. Elliott, J.C. Wakefield, N.G. Best, and D.J. Briggs, editors, Spatial Epidemiology, pages 205–220. Oxford University Press, London, 2000. Google Scholar
  36. 36.
    P.A. Rogerson. The detection of clusters using a spatial version of the chi-square goodness-of-fit statistics. Geogr Anal, 31:130–147, 1999. CrossRefGoogle Scholar
  37. 37.
    T. Tango. A class of tests for detecting general and focused clustering of rare diseases. Stat Med, 14:2323–2334, 1995. CrossRefGoogle Scholar
  38. 38.
    T. Tango and K. Takahashi. A flexibly shaped spatial scan statistic for detecting clusters. Int J Health Geogr, 2005. doi: 10.1186/1476-072X-4-11.
  39. 39.
    J.C. Wakefield, J.E. Kelsall, and S.E. Morris. Clustering cluster detection, and spatial variation in risk. In P. Elliott, J.C. Wakefield, N.G. Best, and D.J. Briggs, editors, Spatial Epidemiology: Methods and Applications, pages 205–220. Oxford University Press, London, 2000. Google Scholar
  40. 40.
    T. Waldhor. The spatial autocorrelation coefficient Moran’s I under heteroscedasticity. Stat Med, 15:887–892, 1996. CrossRefGoogle Scholar
  41. 41.
    S.D. Walter. The analysis of regional patterns in health data. Am J Epidemiol, 136:730–741, 1992. Google Scholar
  42. 42.
    A. Whittemore, N. Friend, B. Brown, and E. Holly. A test to detect clusters of disease. Biometrika, 74:631–635, 1987. MathSciNetMATHCrossRefGoogle Scholar
  43. 43.
    T. Zhang and G. Lin. A supplemental indicator of high-value or low-value spatial clustering. Geogr Anal, 38:209–225, 2006. CrossRefGoogle Scholar
  44. 44.
    T. Zhang and G. Lin. A Decomposition of Moran’s I for clustering detection. Comput Stat Data Anal, 51:6123–6137, 2007. MathSciNetMATHCrossRefGoogle Scholar
  45. 45.
    T. Zhang and G. Lin. Scan statistics in loglinear models. Comput Stat Data Anal, 53:2851–2858, 2009. MathSciNetMATHCrossRefGoogle Scholar
  46. 46.
    T. Zhang and G. Lin. Cluster detection based on spatial associations and iterated residuals in generalized linear mixed models. Biometrics, 65:353–360, 2009. MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Department of StatisticsPurdue UniversityWest LafayetteUSA

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