Advanced Modeling for Surveillance: Clustering of Relative Risk Changes

Spatial and Syndromic Surveillance for Public Health

Volumn , Issue , 2005, Pages 223-243

  Lawson, Andrew B ^a  

^a UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

Advanced modeling; Cluster concepts; Computational speed ups; Mobile recording unit (MRU); Optimal surveillance methodology; Public health surveillance; Spatial modeling of count data; Spatio temporal (ST) modeling; Syndromic cluster assessment; Syndromic surveillance

Indexed keywords

EID: 84889366666     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/0470092505.ch13     Document Type: Chapter

References (462)

1. Aerne, L.A., Champ, C.W. and Rigdon, S.E. (1991) Evaluation of control charts under linear trend. Communications in Statistics. Theory and Methods, 20, 3341-3349.
2. Aitkin, M. (1996a) Empirical Bayes shrinkage using posterior random effect means from nonparametric maximum likelihood estimation in general random effect models. In A. Forcina, G.M. Marchetti, R. Hatzinger, and G. Galmacci (eds), Statistical Modelling: Proceedings of the 11th International Workshop, pp. 87-92. Cittá di Castello: Graphos.
3. Aitkin, M. (1996b) A general maximum likelihood analysis of overdispersion in generalised linear models. Statistics and Computing, 6, 251-262.
4. Alexander, F.E. and Boyle, P. (eds) (1996) Methods for Investigating Localized Clustering of Disease. Lyon: International Agency for Research on Cancer.
5. Alm, S.E. (1997) On the distribution of the scan statistic of a two dimensional Poisson process. Advances in Applied Probability, 29, 1-16.
6. Alm, S.E. (1998) Approximations and simulations of the distribution of scan statistics for Poisson processes in higher dimensions. Extremes, 1, 111-126.
7. Al-Osh, M.A. and Alzaid, A.A. (1987) First-order integer-valued autoregressive (INAR(1)) process. Journal of Times Series Analysis, 8, 261-275.
8. Alt, F.B. (1985) Multivariate quality control. In N.L. Johnson and S. Kotz (eds) Encyclopedia of Statistical Science 6, pp. 110-122. New York: John Wiley & Sons, Inc.
9. Alt, K.W. and Vach, W. (1991) The reconstruction of 'genetic kinship' in prehistoric burial complexes-problems and statistics. In H.H. Bock and P. Ihm (eds), Classification, Data Analysis and Knowledge Organization. Berlin: Springer-Verlag.
10. Alwan, L.C. (2000) Designing an effective exponential cusum chart without the use of nomographs. Communications in Statistics, 29, 2879-2893.
11. American Public Health Association (2000) Control of Communicable Diseases Manual (J.E. Chin, ed.). Washington, DC: American Public Health Association.
12. Anderson, N.H. and Titterington, D.M. (1997) Some methods for investigating spatial clustering, with epidemiological applications. Journal of the Royal Statistical Society, Series A, 160, 87-105.
13. Andersson, E. (2002) Monitoring cyclical processes-a nonparametric approach. Journal of Applied Statistics, 29, 973-990.
14. Arteaga, C. and Ledolter, J. (1997) Control charts based on order-restricted tests. Statistics & Probability Letters, 32, 1-10.
15. Aylin, P., Best, N., Bottle, A. and Marshall, C. (2003) Following Shipman: a pilot system for monitoring mortality rates in primary care. The Lancet, 362, 485-491.
16. Baddeley, A. and Turner, R. (2000) Practical maximum pseudolikelihood for spatial point patterns. Australia and New Zealand Journal of Statistics, 42, 283-322.
17. Banerjee, S., Wall, M.M. and Carlin, B.P. (2003) Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota. Biostatistics, 4, 123-142.
18. Barbujani, G. (1987) A review of statistical methods for continuous monitoring of malformation frequencies. European Journal of Epidemiology, 3, 67-77.
19. Bartlett, M.S. (1964) The spectral analysis of two-dimensional point processes. Biometrika, 51, 299-311.
20. Basseville, M. and Nikiforov, I. (1993) Detection of Abrupt Changes: Theory and Application. Englewood Cliffs, NJ: Prentice Hall.
21. Bate, A., Lindquist, M., Edwards, I.R., Olsson, S., Orre, R., Lansner, A. and Freitas, R.M.D. (1998) A Bayesian neural network method for adverse drug reaction signal generation. European Journal of Clinical Pharmacology, 54, 315-321.
22. Bay, S.D. and Pazzani, M.J. (1999) Detecting change in categorical data: mining contrast sets. In S. Chaudhuri and D. Madigan (eds), Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 302-306. New York: Association for Computing Machinery.
23. Beato Filho, C.C., Assuno, R.M., Silva, B.F., Marinho, F.C., Reis, I.A. and Almeida M.C. (2001) Homicide clusters and drug traffic in Belo Horizonte, Minas Gerais, Brazil from 1995 to 1999. Cadernos de Saúde Pública, 17, 1163-1171. Available at http://www.scielo.br/pdf/csp/v17n5/6324.pdf.
24. Beibel, M. (2000) A note on sequential detection with exponential penalty for the delay. Annals of Statistics, 28, 1696-1701.
25. Beitel, A.J., Olson, K.L., Reis, B.Y. and Mandl, K.D. (2004) Use of emergency department chief complaint and diagnostic codes for identifying respiratory illness in a pediatric population. Pediatric Emergency Care, 20, 355-360.
26. Bell, C., Gordon, L. and Pollak, M. (1994) An efficient nonparametric detection scheme and its application to surveillance of a Bernoulli process with unknown baseline. In E. Carlstein, H.-G. Müller and D. Siegmund (eds), Change-Point Problems IMS Lecture Notes-Monograph Series, vol. 23, pp. 7-27. Hayward, CA: Institute of Mathematical Statistics.
27. Benjamini, Y. and Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B, 57, 289-300.
28. Berke, O. and Grosse Beilage, E. (2003) Spatial relative risk mapping of pseudorabiesseropositive pig herds in an animal-dense region. Journal of Veterinary Medicine, Series B, 50, 322-325.
29. Berke, O., von Keyserlingk, M., Broll, S. and Kreienbrock, L. (2002) On the distribution of Echinococcus multilocularis in red foxes in Lower Saxony: identification of a high risk area by spatial epidemiological cluster analysis. Berliner und Münchener Tierarztliche Wochenschrift, 115, 428-434.
30. Berman, M. and Turner, T.R. (1992) Approximating point process likelihoods with GLIM. Applied Statistics, 41, 31-38.
31. Bernardinelli, L., Clayton, D.G., Pascutto, C., Montomoli, C., Ghislandi, M. and Songini, M. (1995) Bayesian analysis of space-time variation in disease risk. Statistics in Medicine, 14, 2433-2443.
32. Bernardo, J.M. and Smith, A.F.M. (1994) Bayesian Theory. Chichester: John Wiley & Sons, Ltd.
33. Besag, J. and Newell, J. (1991) The detection of clusters in rare diseases. Journal of the Royal Statistical Society, Series A, 154, 143-155.
34. Besag, J., York, J. and Mollié, A. (1991) Bayesian image restoration with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43, 1-59.
35. Bhattacharya, R. and Waymire, E. (1990) Stochastic Processes with Applications. New York: John Wiley and Sons, Inc.
36. Birnbaum, D. (1984) Analysis of hospital infection surveillance data. Infection Control, 5, 332-338.
37. Bithell, J. (1990) An application of density estimation to geographical epidemiology. Statistics in Medicine, 9, 691-701.
38. Bithell, J.F. (1995) The choice of test for detecting raised disease risk near a point source. Statistics in Medicine, 14, 2309-2322.
39. Bock, R.D. and Aitkin, M. (1981) Marginal maximum likelihood estimation of item parameters: an application of an EM algorithm. Psychometrika, 46, 443-459.
40. Bodden, K.M. and Rigdon, S.E. (1999) A program for approximating the in-control ARL for the MEWMA chart. Journal of Quality Technology, 31, 120-123.
41. Böhning, D., Dietz, E. and Schlattmann, P. (2000) Space-time mixture modelling of public health data. Statistics in Medicine, 19, 2333-2344.
42. Bonetti, M and Pagano, M. (2004a) The interpoint distance distribution as a descriptor of point patterns, with an application to cluster detection. Statistics in Medicine. In press.
43. Bonetti, M and Pagano, M. (2004b) Parametric estimation of interpoint distance distributions, with an application to biosurveillance data. Unpublished.
44. Bonferroni, C.E. (1936) Teoria statistica delle classi e calcolo delle probabilità. Pubblicazioni del R. Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 3-62.
45. Borror, C.M., Champ, C.W. and Rigdon, S.E. (1998) Poisson EWMA control charts. Journal of Quality Technology, 30, 352-361.
46. Borror, C.M., Keats, J.B. and Montgomery, D.C. (2003) Robustness of the time between events CUSUM. International Journal of Production Research, 41, 3435-3444.
47. Boscoe, F.P., McLaughlin, C., Schymura, M.J. and Kielb, C.L. (2003) Visualization of the spatial scan statistic using nested circles. Health and Place, 9, 273-277.
48. Box, G.E.P. and Jenkins, G.M. (1970). Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day.
49. Boyle, E., Johnson, H., Kelly, A. and McDonnell, R. (2004) Congenital anomalies and proximity to landfill sites. Irish Medical Journal, 97, 16-18.
50. Breslow, N. and Clayton, D.G. (1993) Approximate inference in generalized linear mixed models. Journal of the American Statistical Association, 88, 9-25.
51. Breslow, N. and Day, N. (1987) Statistical Methods in Cancer Research, Volume 2: The Design and Analysis of Cohort Studies. Lyon: International Agency for Research on Cancer.
52. Brookmeier, R. and Stroup, D. (eds) (2004) Monitoring the Health of Populations: Statistical Principles and Methods for Public Health. Oxford: Oxford University Press.
53. Brookmeyer, R. and Gail, M.H. (1994) AIDS Epidemiology: A Quantitative Approach. New York: Oxford University Press.
54. Brown, S.M., Benneyan, J.C., Theobald, D.A., Sands, K., Hahn, M.T., Potter-Bynoe, G.A., Stelling, J.M., O'Brien, T.F. and Goldmann, D.A. (2002) Binary cumulative sums and moving averages in nosocomial infection cluster detection. Emerging Infectious Diseases, 8, 1426-1432.
55. Bryant, G. and Monk, P. (2001) Final Report of the Investigations into the North Leicestershire Cluster of Variant Creutzfeldt-Jakob Disease. Leicester: Leicestershire NHS Health Authority.
56. Buehler, J.W. (1998) Surveillance. In K.J. Rothman and S. Greenland (eds), Modern Epidemiology, pp. 435-457. Philadelphia: Lippincott Williams and Wilkins Publishers.
57. Buehler, J.W., Berkelman, R., Hartley, D. and Peters, C. (2003) Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases, 9, 1197-1204.
58. Buntinx, F., Geys, H., Lousbergh, D., Broeders, G., Cloes, E., Dhollander, D., Op De Beeck, L., Vanden Brande, J., Van Waes, A. and Molenberghs, G. (2003) Geographical differences in cancer incidence in the Belgian province of Limburg. European Journal of Cancer, 39, 2058-2072.
59. Burkom, H.S. (2003) Biosurveillance applying scan statistics with multiple, disparate data sources. Journal of Urban Health, 80, i57-i65.
60. Cardinal, M., Roy, R. and Lambert, J. (1999). On the application of integer-valued time series models for the analysis of disease incidence. Statistics in Medicine, 18, 2025-2039.
61. Carlin, B.P. and Banerjee, S. (2003) Hierarchical multivariate CAR models for spatiotemporally correlated survival data. In J.M. Bernardo, M.J. Bayarri, A.P. Dawid, J.O. Berger, D. Heckerman, A.F.M. Smith, and M. West (eds), Bayesian Statistics, 7. Oxford: Oxford University Press.
62. Carlin, B.P. and Louis, T.A. (1996) Bayes and Empirical Bayes Methods for Data Analysis. London: Chapman & Hall.
63. Carstairs, V. (1981) Small area analysis and health service research. Community Medicine, 3, 131-139.
64. Celeux, G., Forbes, F., Robert, C. and Titterington, D. (2003) Deviance information criteria for missing data models. Cahiers de mathématiqués de Ceremade 0325, INRIA Rhône-Alpes.
65. Centers for Disease Control and Prevention (1988) Update: Graphic method for presentation of notifiable disease data-United States 1990. Morbidity and Mortality Weekly Report, 40, 124-125.
66. Centers for Disease Control and Prevention (2001) Updated guidelines for evaluating public health surveillance systems. Morbidity and Mortality Weekly Report, 50, 1-35.
67. Centers for Disease Control and Prevention (2004) Emergency preparedness & response: Biological agents/diseases. http://www.bt.cdc.gov/Agent/agentlistcategory. asp (accessed August 17, 2004).
68. Chan, L.K. and Zhang, J. (2001) Cumulative sum control charts for the covariance matrix. Statistica Sinica, 11, 767-790.
69. Chaput, E.K., Meek, J.I. and Heimer, R. (2002) Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. Emerging Infectious Diseases, 8, 943-948.
70. Chen, R. (1978) A surveillance system for congenital abnormalities. Journal of the American Statistical Association, 73, 323-327.
71. Chen, J. and Glaz, J. (1996) Two dimensional discrete scan statistics. Statistics and Probability Letters, 31, 59-68.
72. Chen, R., Mantel, N., Connelly, R.R. and Isacson, P. (1982) A monitoring system for chronic diseases. Methods of Information in Medicine, 21, 86-90.
73. Chen, R., Connelly, R.R. and Mantel, N. (1993) Analysing post-alarm data in a monitoring system, in order to accept or reject the alarm. Statistics in Medicine, 12, 1807-1812.
74. Chen, R., Iscovich, J. and Goldbourt, U. (1997) Clustering of leukaemia cases in a city in Israel. Statistics in Medicine, 16, 1873-1887.
75. Chib, S. and Jeliazkov, I. (2001) Marginal likelihood from the Metropolis-Hastings output. Journal of the American Statistical Association, 96, 270-281.
76. Choi, K. and Thacker, S.B. (1981) An evaluation of influenza mortality surveillance, 1962-1979. 1: Time series forecasts of expected pneumonia and influenza deaths. American Journal of Epidemiology, 113, 215-226.
77. Chu, C.-S.J. (1995) Detecting a shift in GARCH models. Econometric Reviews, 14, 241-266.
78. Clark, A.B. and Lawson, A.B. (2002) Spatio-temporal cluster modelling of small area health data. In A.B. Lawson and D. Denison (eds), Spatial Cluster Modelling, Chapter 14. Boca Raton, FL: CRC Press.
79. Clark, A.B. and Lawson, A.B. (2005) Surveillance of individual level disease maps. Submitted.
80. Clayton, D.G. and Bernardinelli, L. (1992) Bayesian methods for mapping disease risk. In P. Elliott, J. Cuzick, D. English and R. Stern (eds), Geographical and Environmental Epidemiology: Methods for Small-Area Studies. Oxford: Oxford University Press.
81. Clayton, D.G. and Kaldor, J. (1987) Empirical Bayes estimates of age-standardised relative risks for use in disease mapping. Biometrics, 43, 671-691.
82. Cliff, A.D. and Ord, J.K. (1981) Spatial Processes: Models and Applications. London: Pion.
83. Colorado Department of Public Health and Environment (2002) Analysis of birth defect data in the vicinity of the Redfield plume area in southeastern Denver county: 1989-1999. Colorado Department of Public Health and the Environment (http://www.cdphe.state.co.us/hm/redfield_birthdefects_study.pdf).
84. Cooper, B. and Lipsitch, M. (2004) The analysis of hospital infection data using hidden Markov models. Biostatistics, 5, 223-237.
85. Cooper, G. and Herskovits, E. (1992) A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9, 309-347.
86. Costagliola, D., Flahault, A., Galinec, D., Garnerin, P., Menares, J. and Valleron, A.-J. (1991) A routine tool for detection and assessment of epidemics of influenza-like syndromes in France. American Journal of Public Health, 81, 97-99.
87. Coulston, J.W. and Riitters, K.H. (2003) Geographic analysis of forest health indicators using spatial scan statistics. Environmental Management, 31, 764-773.
88. Cousens, S., Smith, P.G., Ward, H., Everington, D., Knight, R.S.G., Zeidler, M., Stewart, G., Smith-Bathgate, E.A.B., Macleod, M.A., Mackenzie, J. and Will R.G. (2001) Geographical distribution of variant Creutzfeldt-Jakob disease in Great Britain, 1994-2000. Lancet, 357, 1002-1007.
89. Couteron, P. and Kokou, K. (1997) Woody vegetation spatial patterns in a semi-arid savanna of Burkina Faso, West Africa. Plant Ecology, 132, 211-227.
90. Crosier, R.B. (1988) Multivariate generalizations of cumulative sum quality-control schemes. Technometrics, 30, 291-303.
91. Crowder, S.V. (1989) Design of exponentially weighted moving average schemes. Journal of Quality Technology, 21, 155-162.
92. Cuzick, J. and Edwards, R. (1990) Spatial clustering for inhomogeneous populations. Journal of the Royal Statistical Society, Series B, 52, 73-104.
93. Cuzick, J. and Hills, M. (1991) Clustering and clusters-summary. In G. Draper (ed.), The Geographical Epidemiology of Childhood Leukaemia and Non-Hodgkin Lymphomas in Great Britain, 1966-1983, pp. 123-125. London: HMSO.
94. Daley, D. and Vere-Jones, D. (1988) An Introduction to the Theory of Point Processes. New York: Springer-Verlag.
95. Daniel, W.W. (1995) Biostatistics: A Foundation for Analysis in the Health Sciences. New York: John Wiley & Sons, Inc.
96. Davison, A.C. and Snell, E.J. (1991) Residuals and diagnostics. In D.V. Hinkley, N. Reid and E.J. Snell (eds), Statistical Theory and Modelling. London: Chapman & Hall.
97. Dawid, A. (1992) Applications of a general propagation algorithm for probabilistic expert systems. Statistics and Computing, 2, 25-36.
98. Deng, K. and Moore, A.W. (1995) Multiresolution instance-based learning. In Proceedings of the 14th International Joint Conference on Artifical Intelligence, pp. 1233-1239. San Mateo, CA: Morgan Kanfmann.
99. Devine, O. and Louis, T. (1994) A constrained empirical Bayes estimator for incidence rates in areas with small populations. Statistics in Medicine, 13, 1119-1133.
100. Diggle, P.J. (1990) A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point. Journal of the Royal Statistical Society, Series A, 153, 349-362.
101. Diggle, P. and Rowlingson, B. (1994) A conditional approach to point process modelling of elevated risk. Journal of the Royal Statistical Society, Series A, 157, 433-440.
102. Diggle, P.J. and Chetwynd, A.G. (1991) Second-order analysis of spatial clustering for inhomogeneous populations. Biometrics, 47, 1155-1163.
103. Diggle, P.J., Tawn, J. and Moyeed, R. (1998) Model-based geostatistics. Applied Statistics, 47, 299-350.
104. Diggle, P.J., Morris, S. and Wakefield, J.C. (2000) Point-source modelling using matched case-control data. Biostatistics, 1, 1-17.
105. Diggle, P., Knorr-Held, L., Rowlingson, B., Su, T., Hawtin, P. and Bryant, T. (2004) On-line monitoring of public health surveillance data. In R. Brookmeyer and D. Stroup (eds), Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance, Chapter 9. Oxford: Oxford University Press.
106. Dobbertin, M., Baltensweiler, A. and Rigling, D. (2001) Tree mortality in an unmanaged mountain pine (Pinus mugo var. uncinata) stand in the Swiss National Park impacted by root rot fungi. Forest Ecology and Management, 145, 79-89.
107. Doherr, M.G., Hett, A.R., Rufenacht, J., Zurbriggen, A. and Heim, D. (2002) Geographical clustering of cases of bovine spongiform encephalopathy (BSE) born in Switzerland after the feed ban. Veterinary Record, 151, 467-472.
108. Domangue, R. and Patch, S.C. (1991) Some omnibus exponentially weighted moving average statistical process monitoring schemes. Technometrics, 33, 299-313.
109. Doucet, A., de Freitas, N. and Gordon, N. (eds) (2001) Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag.
110. Du, J.G. and Li, Y. (1991) The integer-valued autoregressive (INAR(p)) model. Journal of Times Series Analysis, 12, 129-142.
111. Duczmal, L. and Assunçião, R.M. (2004) A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters. Computational Statistics and Data Analysis, 45, 269-286.
112. DuMouchel, W. (1999) Bayesian data mining in large frequency tables, with an application to the FDA spontaneous reporting system. American Statistician, 53, 177-202.
113. Dwass, M. (1957) Modified randomization tests for nonparametric hypotheses. Annals of Mathematical Statistics, 28, 181-187.
114. Elliott, P., Wakefield, J.C., Best, N.G. and Briggs, D.J. (eds) (2000) Spatial Epidemiology: Methods and Applications. Oxford: Oxford University Press.
115. Enemark, H.L., Ahrens, P., Juel, C.D., Petersen, E., Petersen, R.F., Andersen, J.S., Lind, P. and Thamsborg, S.M. (2002) Molecular characterization of Danish Cryptosporidium parvum isolates. Parasitology, 125, 331-341.
116. Ewan, W.D. and Kemp, K.W. (1960) Sampling inspection of continous processes with no autocorrelation between successive results. Biometrika, 47, 363-380.
117. Falconi, F., Ochs, H. and Deplazes, P. (2002) Serological cross-sectional survey of psoroptic sheep scab in Switzerland. Veterinary Parasitology, 109, 119-127.
118. Fang, Z., Kulldorff, M. and Gregorio, D.I. (2004) Brain cancer in the United States, 1986-95: a geographic analysis. Neuro-oncology, 6, 179-187.
119. Farrington, P. and Andrews, N. (2004) Outbreak detection: application to infectious disease surveillance. In R. Brookmeyer and D. Stroup (eds), Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance, Chapter 8. Oxford: Oxford University Press.
120. Farrington, P., and Beale, A.D. (1998) The detection of outbreaks of infectious disease. In L. Lierl, A.D. Cliff, A. Valleron, P. Farrington, and M. Bull (eds), Geomed '97. Stuttgart: B.G. Teubner.
121. Farrington, C.P. and Andrews, N.J. (2004) Statistical aspects of detecting infectious disease outbreaks. In R. Brookmeyer and D.F. Stroup (eds), Monitoring the Health of Populations. Oxford: Oxford University Press.
122. Farrington, C.P., Andrews, N.J., Beale, A.D. and Catchpole, M.A. (1996) A statistical algorithm for the early detection of outbreaks of infectious disease. Journal of the Royal Statistical Society, Series A, 159, 547-563.
123. Fawcett, T. and Provost, F. (1999) Activity monitoring: noticing interesting changes in behavior. In S. Chaudhuri and D. Madigan (eds), Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 53-62. New York: Association for Computing Machinery.
124. Fernàndez, C. and Green, P.J. (2002) Modelling spatially corelated data via mixtures: a Bayesian approach. Journal of the Royal Statitsical Society, Series B, 64, 805-826.
125. Fevre, E.M., Coleman, P.G., Odiit, M., Magona, J.W., Welburn, S.C. and Woolhouse, M.E.J. (2001) The origins of a new Trypanosoma brucei rhodesiense sleeping sickness outbreak in eastern Uganda. Lancet, 358, 625-628.
126. Flahault, A., Garnerin, P., Chauvin, P., Farran, N., Saidi, Y., Diaz, C. and Toubiana, L. (1995) Sentinelle traces of an epidemic of acute gastroenteritis in France. Lancet, 346, 162-163.
127. Forand, S.P., Talbot, T.O., Druschel, C. and Cross, P.K. (2002) Data quality and the spatial analysis of disease rates: congenital malformations in New York State. Health and Place, 8, 191-199.
128. Frisén, M. (1986) Unimodal regression. The Statistician, 35, 479-485.
129. Frisén, M. (1992) Evaluations of methods for statistical surveillance. Statistics in Medicine, 11, 1489-1502.
130. Frisén, M. (2000) Statistical surveillance of business cycles. Research Report, Department of Statistics, Göteborg University.
131. Frisén, M. (2003) Statistical surveillance: optimality and methods. International Statistical Review, 71, 403-434.
132. Frisén, M. and de Maré, J. (1991) Optimal surveillance. Biometrika, 78, 271-280.
133. Frisén, M. and Gottlow, M. (2003) Graphical evaluation of statistical surveillance. Research Report 2003:10, Statistical Research Unit, Göteborg University.
134. Frisén, M. and Wessman, P. (1999) Evaluations of likelihood ratio methods for surveillance. Differences and robustness. Communications in Statistics. Simulation and Computation, 28, 597-622.
135. Fuchs, C. and Benjamini, Y. (1994) Multivariate profile charts for statistical process control. Technometrics, 36, 182-195.
136. Gallus, G., Radaelli, G. and Marchi, M. (1991) Poisson approximation to a negative binomial process in the surveillance of rare health events. Methods of Information in Medicine, 30, 206-209.
137. Gallus, G., Mandelli, C., Marchi, M. and Radaelli, G. (1986) On surveillance methods for congenital malformations. Statistics in Medicine, 5, 565-571.
138. Gan, F.F. (1991) Monitoring observations generated from a binomial distribution using modified exponentially weighted moving average control charts. Journal of Statistical Computation and Simulation, 37, 45-60.
139. Gan, F.F. (1992a) Cusum control charts under linear drift. The Statistician, 41, 71-84.
140. Gan, F.F. (1992b) Exact run length distributions for one-sided exponential CUSUM schemes. Statistica Sinica, 2, 297-312.
141. Gan, F.F. (1993) An optimal design of EWMA control charts based on median run-length. Journal of Statistical Computation and Simulation, 45, 169-184.
142. Gan, F.F. (1994) Design of optimal exponential CUSUM control charts. Journal of Quality Technology, 26, 109-124.
143. Gangnon, R. and Clayton, M. (2000) Bayesian detection and modeling of spatial disease clustering. Biometrics, 56, 922-935.
144. Gelman, A., Carlin, J., Stern, H. and Rubin, D. (2003). Bayesian Data Analysis (2nd edn). London: Chapman & Hall.
145. George, M., Wiklund, L., Aastrup, M., Pousette, J., Thunholm, B., Saldeen, T., Wernroth, L., Zaren, B. and Holmberg, L. (2001) Incidence and geographical distribution of sudden infant death syndrome in relation to content of nitrate in drinking water and groundwater levels. European Journal of Clinical Investigation, 31, 1083-1094.
146. German, R.R. (2000) Sensitivity and predictive value positive measurements for public health surveillance systems. Epidemiology, 11, 720-727.
147. Glaz, J. and Balakrishnan, N. (eds) (1999) Scan Statistics and Applications. Boston: Birkhäuser.
148. Glaz, J., Naus, J. and Wallenstein, S. (2001). Scan Statistics. New York: Springer-Verlag.
149. Glick, B.J. (1979) The spatial autocorrelation of cancer mortality. Social Science and Medicine, 13D, 123-130.
150. Goldenberg, A., G. Shmueli, R.A. Caruana, and S.E. Fienberg, (2002) Early statistical detection of anthrax outbreaks by tracking over-the-couner medication sales. Proceedings of the National Academy of Sciences, 99, 5237-5249.
151. Good, P. (2000) Permutation Tests-A Practical Guide to Resampling Methods for Testing Hypotheses (2nd edn). New York: Springer-Verlag.
152. Gordon, L. and Pollak, M. (1997) Average run length to false alarm for surveillance schemes designed with partially specified pre-change distribution. Annals of Statistics, 25, 1284-1310.
153. Green, P.J. and Richardson, S. (2002) Hidden Markov models and disease mapping. Journal of the American Statitsical Association, 97, 1055-1070.
154. Green, C., Hoppa, R.D., Young, T.K. and Blanchard, J.F. (2003) Geographic analysis of diabetes prevalence in an urban area. Social Science and Medicine, 57, 551-560.
155. Gregorio, D.I., Kulldorff, M., Barry, L., Samociuk, H. and Zarfos, K. (2001) Geographic differences in primary therapy for early stage breast cancer. Annals of Surgical Oncology, 8, 844-849.
156. Gregorio, D.I., Kulldorff, M., Barry, L. and Samociuk, H. (2002) Geographic differences in invasive and in situ breast cancer incidence according to precise geographic coordinates, Connecticut, 1991-1995. International Journal of Cancer, 100, 194-198.
157. Grimson, R.C. (1991) A versatile test for clustering and a proximity analysis of neurons. Methods of Information in Medicine, 30, 299-303.
158. Gustavsson, F. (2000) Adaptive Filtering and Change Detection. Chichester: John Wiley & Sons, Ltd.
159. Hamilton, J.D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357-384.
160. Hand, D., Mannila, H. and Smyth, P. (2001) Principles of Data Mining. Cambridge, MA: MIT Press.
161. Hanson, C.E. and Wieczorek, W.F. (2002) Alcohol mortality: a comparison of spatial clustering methods. Social Science and Medicine, 55, 791-802.
162. Härdle, W. (1991) Smoothing Techniques: with Implementation in S. New York: Springer- Verlag.
163. Harrison, P.J. and Stevens, C.F. (1976) Bayesian forecasting (with discussion). Journal of the Royal Statistical Society, Series B, 38, 205-247.
164. Hauck, D.J., Runger, G.C. and Montgomery, D.C. (1999) Multivariate statistical process monitoring and diagnosis with grouped regression-adjusted variables. Communications in Statistics. Simulation and Computation, 28, 309-328.
165. Hawkins, D.M. (1991) Multivariate quality control based on regression-adjusted variables. Technometrics, 33, 61-75.
166. Hawkins, D.M. and Olwell, D.H. (1998) Cumulative Sum Charts and Charting for Quality Improvement. New York: Springer-Verlag.
167. Healy, J.D. (1987) A note on multivariate CUSUM procedures. Technometrics, 29, 409-412.
168. Heffernan, R., Mostashari, F., Das, D., Karpati, A., Kulldorff, M. and Weiss, D. (2004) Syndromic surveillance in public health practice: the New York City emergency department system. Emerging Infectious Diseases, 10, 858-864.
169. Helfenstein, U. (1986) Box-Jenkins modelling of some viral infectious diseases. Statistics in Medicine, 5, 37-47.
170. Hill, G.B., Spicer, C.C. and Weatherall, J.A.C. (1968) The computer surveillance of congenital malformations. British Medical Journal, 24, 215-218.
171. Hjalmars, U., Kulldorff, M., Gustafsson, G. and Nagarwalla, N. (1996) Childhood leukemia in Sweden: using GIS and a spatial scan statistic for cluster detection. Statistics in Medicine, 15, 707-715.
172. Hjalmars, U., Kulldorff, M., Wahlquist, Y. and Lannering, B. (1999) Increased incidence rates but no space-time clustering of childhood malignant brain tumors in Sweden. Cancer, 85, 2077-2090.
173. Hoar, B.R., Chomel, B.B., Rolfe, D.L., Chang, C.C., Fritz, C.L., Sacks, B.N. and Carpenter, T.E. (2003) Spatial analysis of Yersinia pestis and Bartonella vinsonii subsp. berkhoffii seroprevalence in California coyotes (Canis latrans). Preventive Veterinary Medicine, 56, 299-311.
174. Hossain, M. and Lawson, A.B. (2005) Local likelihood disease clustering: development and evaluation. Environmental and Ecological statistics (to appear)
175. Hotelling, H. (1947) Multivariate quality control. In C. Eisenhart, M.W. Hastay and W.A. Wallis (eds), Techniques of Statistical Analysis. New York: McGraw-Hill.
176. Hsu, C.E., Jacobson, H.E. and Soto Mas, F. (2004) Evaluating the disparity of female breast cancer mortality among racial groups-a spatiotemporal analysis. International Journal of Health Geographics, 3:4.
177. Huang, L., Kulldorff, M. and Gregorio, D. (2004) A spatial scan statistic for survival data. Manuscript.
178. Huillard d'Aignaux, J., Cousens, S.N., Delasnerie-Laupretre, N., Brandel, J.P., Salomon, D., Laplanche, J.L., Hauw, J.J. and Alperovitch, A. (2002) Analysis of the geographical distribution of sporadic Creutzfeldt-Jakob disease in France between 1992 and 1998. International Journal of Epidemiology, 31, 490-495.
179. Hunter, J.S. (1986) The exponentially weighted moving average. Journal of Quality Technology, 18, 203-210.
180. Hutwagner, L.C., Maloney, E.K., Bean, N.H., Slusker, L. and Martin, S.M. (1997) Using laboratory-based surveillance data for prevention: an algorithm for detecting salmonella outbreaks. Emerging Infectious Diseases, 3, 395-400.
181. Hutwagner, L., Thompson, W., Seeman, G.M. and Treadwell, T. (2003) The bioterrorism preparedness and response Early Aberration Reporting System (EARS). Journal of Urban Health-Bulletin of the New York Academy of Medicine, 80, i89-i96.
182. Inskip, H., Beral, V., Fraser, P. and Haskey, P. (1983) Methods for age-adjustment of rates. Statistics in Medicine, 2, 483-493.
183. Jackson, J.E. (1985) Multivariate quality control. Communications in Statistics. Theory and Methods, 14, 2657-2688.
184. Järpe, E. (1999) Surveillance of the interaction parameter of the Ising model. Communications in Statistics. Theory and Methods, 28, 3009-3027.
185. Järpe, E. (2000) On univariate and spatial surveillance. Ph.D thesis, Department of Statistics, Göteborg University.
186. Järpe, E. (2001) Surveillance, environmental. In A.El-Shaarawi and W.W. Piegorsh (eds), Encyclopedia of Environmetrics. Chichester: John Wiley & Sons, Ltd.
187. Jemal, A., Kulldorff, M., Devesa, S.S., Hayes, R.B. and Fraumeni, J.F. (2002) A geographic analysis of prostate cancer mortality in the United States. International Journal of Cancer, 101, 168-174.
188. Johnson, R.A. and Wichern, D.W. (2002) Applied Multivariate Statistical Analysis (5th edn). Upper Saddle River, NJ: Prentice Hall.
189. Joly, D.O., Ribic, C.A., Langenberg, J.A., Beheler, K., Batha, C.A., Dhuey, B.J., Rolley, R.E., Bartelt, G., Van Deelen, T.R. and Samual, M.D. (2003) Chronic wasting disease in free-ranging Wisconsin white-tailed deer. Emerging Infectious Diseases, 9, 599-601.
190. Kafadar, K. and Stroup, D.F. (1992) Analysis of aberrations in public health surveillance data: estimating variances on correlated samples. Statistics in Medicine, 11, 1551-1568.
191. Källén, B. and Winberg, J. (1969) Multiple malformations studied with a national register of malformations. Pediatrics, 44, 410-417.
192. Kalman, R.E. (1960). A new approach to linear filtering and prediction problems. Transactions of the ASME, Journal of Basic Engineering, 82, 35-45.
193. Kaminski, R.J., Jefferis, E.S. and Chanhatasilpa, C. (2000) A spatial analysis of American police killed in the line of duty. In L.S. Turnbull, E.H. Hendrix and B.D. Dent (eds), Atlas of Crime: Mapping the Criminal Landscape. Phoenix, AZ: Oryx Press.
194. Kang, L. and Albin, S.L. (2000) On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32, 418-426.
195. Karlin, S. and Taylor, H. (1975) First Course in Stochastic Processes (2nd edn). New York: Academic Press.
196. Kaufmann, A.F., Meltzer, M.I. and Schmid, G.P. (1997) The economic impact of a bioterrorist attack: Are prevention and postattack intervention programs justifiable? Emerging Infectious Diseases, 3, 83-94.
197. Kelsall, J. and Diggle, P. (1995) Non-parametric estimation of spatial variation in relative risk. Statistics in Medicine, 14, 2335-2342.
198. Kelsall, J. and Diggle, P. (1998) Spatial variation in risk of disease: a nonparametric binary regression approach. Applied Statistics, 47, 559-573.
199. Kenett, R. and Pollak, M. (1996) Data-analytic aspects of the Shiryaev-Roberts control chart: surveillance of a non-homogeneous Poisson process. Journal of Applied Statistics, 23, 125-137.
200. Kharrazi, M., et al. (1998) Pregnancy outcomes around the B.K.K. landfill, West Covina, California: Ananalysis by address. California Department of Health Services.
201. Klassen, A.C., Curriero, F.C., Hong, J.H., Williams, C., Kulldorff, M., Meissner, H.I., Alberg, A. and Ensminger, M. (2004) The role of area-level influences on prostate cancer grade and stage at diagnosis. Preventive Medicine, 39, 441-448.
202. Kleinman, K., Abrams, A., Kulldorff, M. and Platt, R. (2005) Choosing a denominator for the space-time scan statistic approach to spatial surveillance. Epidemiology and Infection (to appear).
203. Kleinman, K., Lazarus, R. and Platt, R. (2004a) A generalized linear mixed models approach for detecting incident clusters of disease in small areas, with an application to biological terrorism. American Journal of Epidemiology, 159, 217-224.
204. Kleinman, K., Lazarus, R. and Platt, R. (2004b) Kleinman et al. Respond to 'Surveilling Surveillance'. American Journal of Epidomiology, 159, 228.
205. Knorr-Held, L. (2000) Bayesian modelling of inseparable space-time variation in disease risk. Statistics in Medicine, 19, 2555-2567.
206. Knorr-Held, L. and Besag, J. (1998) Modelling risk from disease in time and space. Statistics in Medicine, 17, 2045-2060.
207. Knoth, S. and Schmid, W. (2002) Monitoring the mean and the variance of a stationary process. Statistica Neerlandica, 56, 77-100.
208. Knox, E.G. (1964) The detection of space-time interactions. Applied Statistics, 13, 25-29.
209. Knox, E.G. (1989) Detection of clusters. In P. Elliott (ed.), Methodology of Enquiries into Disease Clustering, pp. 17-20. London: Small Area Health Statistics Unit.
210. Knuesel, R., Segner, H. and Wahli, T. (2003) A survey of viral diseases in farmed and feral salmonids in Switzerland. Journal of Fish Diseases, 26, 167-182.
211. Kourti, T. and MacGregor, J.F. (1996) Multivariate SPC methods for process and product monitoring. Journal of Quality Technology, 28, 409-428.
212. Krieger, A.M., Pollak, M. and Yakir, B. (2003) Surveillance of a simple linear regression. Journal of the American Statistical Association, 98, 456-469.
213. Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics: Theory and Methods, 26, 1481-1496.
214. Kulldorff, M. (1998) Statistical methods for spatial epidemiology: tests for randomness. In M. Löytönen and A. Gatrell (eds), GIS and Health. London: Taylor & Francis, 49-62.
215. Kulldorff, M. (1999) Spatial scan statistics: models, calculations and applications. In J. Glaz and N. Balakrishnan (eds), Scan Statistics and Applications, pp. 303-322. Boston: Birkhäuser.
216. Kulldorff, M. (2001) Prospective time-periodic geographical disease surveillance using a scan statistic. Journal of the Royal Statistical Society, Series A, 164, 61-72.
217. Kulldorff, M. and Nagarwalla, N. (1995) Spatial disease clusters: detection and inference. Statistics in Medicine, 14, 799-810.
218. Kulldorff, M., Feuer, E.J., Miller, B.A. and Freedman, L.S. (1997) Breast cancer in northeastern United States: a geographical analysis. American Journal of Epidemiology, 146, 161-170.
219. Kulldorff, M., Athas, W., Feuer, E., Miller, B. and Key, C. (1998) Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos. American Journal of Public Health, 88, 1377-1380.
220. Kulldorff, M., Fang, Z. and Walsh, S.J. (2003) A tree-based scan statistic for database disease surveillance. Biometrics, 59, 323-331.
221. Kulldorff, M., Tango, T. and Park, P. (2003) Power comparisons for disease clustering tests. Computational Statistics and Data Analyis, 42, 665-684.
222. Kulldorff, M., Zhang, Z., Hartman, J., Heffernan, R., Huang, L. and Mostashari, F. (2004a) Evaluating disease outbreak detection methods: Benchmark data and power calculations. Morbidity and Mortality Weekly Report, 53 (supplement), 144-151.
223. Kulldorff, M., Huang, L., Pickle, L. and Duczmal, L. (2004b) An elliptic spatial scan statistic. Manuscript.
224. Lai, T.L. (1995) Sequential changepoint detection in quality-control and dynamical systems. Journal of the Royal Statistical Society, Series B, 57, 613-658.
225. Lai, T.L. (1998) Information bounds and quick detection of parameter in stochastic systems. IEEE Transactions on Information Theory, 44, 2917-2929.
226. Lai, T.L. and Shan, Z. (1999) Efficient recursive algorithms for detection of abrupt changes in signals and control systems. IEEE Transactions on Automatic Control, 44, 952-966.
227. Latour, A. (1997) The multivariate GINAR(p) process. Advances in Applied Probability, 29, 228-248.
228. Latour, A. (1998) Existence and stochastic structure of a non-negative integer-valued autoregressive processes. Journal of Times Series Analysis, 19, 439-455.
229. Lauritzen, S., Dawid, A., Larsen, B. and Leimer, H.-G. (1990) Independence properties of directed Markov fields. Networks, 20, 491-505.
230. Lawson, A.B. (1992) GLIM and normalising constant models in spatial and directional data analysis. Computational Statistics and Data Analysis, 13, 331-348.
231. Lawson, A.B. (1993a) A deviance residual for heterogeneous spatial Poisson processes. Biometrics, 49, 889-897.
232. Lawson, A.B. (1993b) On the analysis of mortality events associated with a pre-specified fixed point. Journal of the Royal Statistical Society, Series A, 156, 363-377.
233. Lawson, A.B. (1995) Markov chain Monte Carlo methods for putative pollution source problems in environmental epidemiology. Statistics in Medicine, 14, 2473-2486.
234. Lawson, A.B. (1996) Markov chain Monte Carlo methods for spatial cluster processes. In M.M. Meyer and J.L. Rosenberger (eds), Computing Science and Statistics: Proceedings of the Interface, Volume 27, pp. 314-319. Fairfax Station, VA: Interface Foundation of North America.
235. Lawson, A.B. (2001) Statistical Methods in Spatial Epidemiology. New York: John Wiley & Sons, Inc.
236. Lawson, A.B. (2005) Local likelihood Bayesian cluster modelling for small area health data. Submitted.
237. Lawson, A.B. (2004) Some issues in the spatio-temporal analysis of public health surveillance data. In R. Brookmeyer and D. Stroup (eds), Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance, Chapter 11. Oxford: Oxford University Press.
238. Lawson, A.B., Biggeri, A. and Lagazio, C. (1996) Modelling heterogeneity in discrete spatial data models via MAP and MCMC methods. In A. Forcina, G. Marchetti, R. Hatzinger, and G. Galmacci (eds), Proceedings of the 11th International Workshop on Statistical Modelling, pp. 240-250. Graphos, Citta di Castello.
239. Lawson, A.B., Biggeri, A. and Dreassi, E. (1999) Edge effects in disease mapping. In A.B. Lawson, D. Böhning, E. Lesaffre, A. Biggeri, J.-F. Viel, and R. Bertollini (eds), Disease Mapping and Risk assessment for Public Health, Chapter 6, pp. 85-97. Wiley.
240. Lawson, A.B. Böhning, D., Lesaffre, E., Biggeri, A., Viel, J.-F. and Bertollini, R. (1999) Disease Mapping and Risk Assessment for Public Health. Chichester: John Wiley & Sons, Ltd.
241. Lawson, A.B., Browne, W.J. and Vidal-Rodeiro, C.L. (2003) Disease Mapping with WinBUGS and MLwiN. Chichester: John Wiley & Sons, Ltd.
242. Lawson, A.B. and Clark, A. (1999). Markov chain Monte Carlo methods for clustering in case event and count data in spatial epidemiology. In M.E. Halloran and D. Berry (eds), Statistics and Epidemiology: Environment and Clinical Trials, pp. 193-218. New York: Springer-Verlag.
243. Lawson, A.B., Clark, A.B. and Vidal-Rodeiro, C.L. (2004) Developments in general and syndromic surveillance for small area health data. Journal of Applied Statistics, 31, 963-978.
244. Lawson, A.B. and Cressie, N. (2000) Spatial statistical methods for environmental epidemiology. In C.R. Rao and P.K. Sen (eds), Bioenvironmental and Public Health Statistics, Handbook of Statistics Vol. 18, pp. 357-396. Amsterdam: Elsevier.
245. Lawson, A.B. and Denison, D. (2002) Spatial Cluster Modelling. Boca Raton, FL: Chapman & Hall/CRC.
246. Lawson, A.B. and Waller, L. (1996) A review of point pattern methods for spatial modelling of events around sources of pollution. Environmetrics, 7, 471-488.
247. Lawson, A.B. and Williams, F. (1993) Applications of extraction mapping in environmental epidemiology. Statistics in Medicine, 12, 1249-1258.
248. Lawson, A.B. and Williams, F. (1994) Armadale: a case study in environmental epidemiology. Journal of the Royal Statistical Society, Series A, 157, 285-298.
249. Lawson, A.B. and Williams, F. (2000) Spatial competing risk models in disease mapping. Statistics in Medicine, 19, 2451-2468.
250. Lazarus, R., Kleinman, K., Dashevsky, I., DeMaria Jr, A., and Platt, R. (2001) Using automated records for rapid detection of illness syndromes: the example of lower respiratory disease. BMC Public Health, 1, 1-9.
251. Lazarus, R., K. Kleinman, I. Dashevsky, C. Adams, P. Kludt, J. Alfred DeMaria, and R. Platt (2002) Use of automated ambulatory-care encounter records for detection of acute illness clusters, including potential bioterrorism events. Emerging Infectious Diseases, 8, 753-760.
252. Le Strat, Y. and Carrat, F. (1999) Monitoring epidemiologic surveillance data using hidden Markov models. Statistics in Medicine, 18, 3463-3478.
253. Liu, R.Y. (1995) Control charts for multivariate processes. Journal of the American Statistical Association, 90, 1380-1387.
254. Ljung, G.M. and Box, G.E.P. (1978) On a measure of lack of fit in time series models. Biometrika, 65, 297-303.
255. Loader, C.R. (1991) Large-deviation approximations to the distribution of scan statistics. Advances in Applied Probability, 23, 751-771.
256. Lober, W.B., Karras, B.T., Wagner, M.M., Overhage, J.M., Davidson, A.J., Fraser, H., Trigg, L.J., Mandl, K.D., Espino, J.U. and Tsui, F.C. (2002) Roundtable on bioterrorism detection: information system-based surveillance. Journal of the American Medical Informatics Association, 9, 105-115.
257. Lober, W.B., Trigg, L.J., Karras, B.T., Bliss, D., Ciliberti, J., Stewart, L. and Duchin, J.S. (2003) Syndromic surveillance using automated collection of computerized discharge diagnoses. Journal of Urban Health, 80, i97-i106.
258. Lombardo, J., Burkom, H., Elbert, E., Magruder, S., Lewis, S.H., Loschen, W., Sari, J., Sniegoski, C., Wojcik, R. and Pavlin, J. (2003)A systems overview of the Electronic Surviellence System for the Early Notification of Community-Based Epidemics (ESSENCE II). Journal of Urban Health-Bulletin of the New York Academy of Medicine, 80, i32-i42.
259. López-Abente, G., Morales-Piga, A., Bachiller-Corral, F.J., Illera-Martín, O., Martín- Domenech, R. and Abraira, V. (2003) Identification of possible areas of high prevalence of Paget's disease of bone in Spain. Clinical and Experimental Rheumatology, 21, 635-638.
260. Lowry, C.A. and Montgomery, D.C. (1995) A review of multivariate control charts. IIE Transactions, 27, 800-810.
261. Lowry, C.A., Woodall, W.H., Champ, C.W. and Rigdon, S.E. (1992) A multivariate exponentially weighted moving average control chart. Technometrics, 34, 46-53.
262. Lu, X.S., Xie, M., Goh, T.N. and Lai, C.D. (1998) Control chart for multivariate attribute processes. International Journal of Production Research, 36, 3477-3489.
263. Lucas, J.M. (1985) Counted data CUSUM's. Technometrics, 27, 129-144.
264. Lucas, J.M. and Crosier, R.B. (1982) Fast initial response for CUSUM quality control schemes: give your CUSUM a head start. Technometrics, 24, 199-205.
265. Lucas, J.M. and Saccucci, M.S. (1990) Exponentially weighted moving average control schemes: properties and enhancements. Technometrics, 32, 1-12.
266. Lui, K.-J. and Rudy, R.K. (1989) An application of a mathematical model to adjust for time lag in case reporting. Statistics in Medicine, 8, 259-262.
267. MacDonald, L. and Zucchini, W. (1997) Hidden Markov and Other Models for Discrete- Valued Time Series. London: Chapman & Hall.
268. MacEachren, A.M. (1995) How Maps Work: Representation, Visualisation and Design. New York: Guilford Press.
269. Mandl, K.D., Overhage, J.M., Wagner, M.M., Lober, W.B., Sebastiani, P., Mostashari, F., Pavlin, J.A., Gesteland, P.H., Treadwell, T., Koski, E., Hutwagner, L., Buckeridge, D.L., Aller, R.D. and Grannis, S. (2004) Implementing syndromic surveillance: a practical guide informed by the early experience. Journal of the American Medical Informatics Association, 11, 141-150.
270. Manton, K., Woodbury, M. and Stallard, E. (1981) A variance components approach to categorical data models with heterogeneous mortality rates in North Carolina counties. Biometrics, 37, 259-269.
271. Maravelakis, P.E., Bersimis, S., Panaretos, J. and Psarakis, S. (2002) Identifying the out of control variable in a multivariate control chart. Communications in Statistics. Theory and Methods, 31, 2391-2408.
272. Margai, F. and Henry, N. (2003) A community-based assessment of learning disabilities using environmental and contextual risk factors. Social Science and Medicine, 56, 1073-1085.
273. Marshall, R. (1991) Mapping disease and mortality rates using empirical Bayes estimators. Applied Statistics, 40, 283-294.
274. Marshall, C., Best, N., Bottle, A. and Aylin, P. (2004) Statistical issues in the prospective monitoring of health outcomes across multiple units. Journal of the Royal Statistical Society, Series A, 167, 541-559.
275. Mason, R.L., Tracy, N.D. and Young, J.C. (1995) Decomposition of T2 for multivariate control chart interpretation. Journal of Quality Technology, 27, 99-108.
276. Mastrangelo, C.M., Runger, G.C. and Montgomery, D.C. (1996) Statistical process monitoring with principal components. Quality and Reliability Engineering International, 12, 203-210.
277. Mathers, C., Harris, R. and Lancaster, P. (1994) A CUSUM scheme based on the exponential distribution for surveillance of rare congenital malformations. Australian Journal of Statistics, 36, 21-30.
278. McCulloch, C. and Searle, S. (2001) Generalized, Linear, and Mixed Models, New York: John Wiley & Sons, Inc.
279. Michelozzi, P., Capon, A., Kirchmayer, U., Forastiere, F., Biggeri, A., Barca, A. and Perucci, C.A. (2002) Adult and childhood leukemia near a high-power radio station in Rome, Italy. American Journal of Epidemiology, 155, 1096-1103.
280. Miller, C.J., C. Genovese, R.C. Nichol, L. Wasserman, A. Connolly, D. Reichart, A. Hopkins, J. Schneider, and A. Moore (2001) Controlling the false discovery rate in astrophysical data analysis. Technical report, Carnegie Mellon University.
281. Miller, M.A., Gardner, I.A., Kreuder, C., Paradies, D.M., Worcester, K.R., Jessup, D.A., Dodd, E., Harris, M.D., Ames, J.A., Packham, A.E. and Conrad, P.A. (2002) Coastal freshwater runoff is a risk factor for Toxoplasma gondii infection of southern sea otters (Enhydra lutris nereis). International Journal for Parasitology, 32, 997-1006.
282. Miller, M.A., Grigg, M.E., Kreuder, C., James, E.R., Melli, A.C., Crosbie, P.R., Jessup, D.A., Boothroyd, J.C., Brownstein, D. and Conrad, P.A. (2004) An unusual genotype of Toxoplasma gondii is common in California sea otters (Enhydra lutris nereis) and is a cause of mortality. International Journal for Parasitology, 34, 275-284.
283. MMWR (2001) Recognition of illness associated with the intentional release of a biologic agent. Morbidity and Mortality Weekly Report, 50, 893-897.
284. Mohebbi, C. and Havre, L. (1989) Multivariate control charts: a loss function approach. Sequential Analysis, 8, 253-268.
285. Møller, J. and Waagepetersen, R.P. (2002) Statitsical inference for Cox processes. In A.B. Lawson and D. Denison (eds), Spatial Cluster Modelling, Chapter 3. Boca Raton, FL: CRC Press.
286. Monmonier, M. (1996) How to Lie with Maps (2nd edn). Chicago: University of Chicago Press.
287. Montgomery, D. (1996) Introduction to Statistical Quality Control. New York: John Wiley & Sons, Inc.
288. Moore, A.W. (1999) Very fast mixture-model-based clustering using multiresolution kd-trees. In M. Kearns and D. Cohn (eds), Advances in Neural Information Processing Systems, Volume 10, pp. 543-549. San Francisco: Morgan Kaufmann.
289. Moore, A. and M.S. Lee (1998) Cached sufficient statistics for efficient machine learning with large datasets. Journal of Artificial Intelligence Research, 8, 67-91.
290. Moore, A. and Wong, W.-K. (2003) Optimal reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learning. In T. Fawcett and N. Mishra (eds), Proceedings of the Twentieth International Conference on Machine Learning, pp. 552-559. Menlo Park, CA: AAAI Press.
291. Moore, M., Katona, P., Kaplan, J.E., Schonberger, L.B. and Hatch, M.H. (1982) Poliomyelitis in the United States, 1969-1981. Journal of Infectious Diseases, 4, 558-563.
292. Mostashari, F. and Hartman, J. (2003) Syndromic surveillance: a local perspective. Journal of Urban Health, 80, i1-i7.
293. Mostashari, F., Kulldorff, M., Hartman, J.J., Miller, J.R. and Kulasekera, V. (2003) Dead bird clustering: a potential early warning system for West Nile virus activity. Emerging Infectious Diseases, 9, 641-646.
294. Moustakides, G.V. (1986) Optimal stopping-times for detecting changes in distributions. Annals of Statistics, 14, 1379-1387.
295. Naus, J. (1965a) The distribution of the size of maximum cluster of points on the line. Journal of the American Statistical Association, 60, 532-538.
296. Naus, J. (1965b) Clustering of random points in two dimensions. Biometrika, 52, 263-267.
297. Neill, D.B. and Moore, A.W. (2004a) A fast multi-resolution method for detection of significant spatial disease clusters. In S. Thrun, L. Saul, and B. Schölkopf (eds), Advances in Neural Information Processing Systems 16. Cambridge, MA: MIT Press.
298. Neill, D.B. and Moore, A.W. (2004b) Rapid detection of significant spatial clusters. In R. Kolhavi, J. Gehrke, W. DuMouchel and J. Ghosh (eds), Proceedings of the 10th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York: Association for Computing Machinery.
299. New York State Department of Health (2001) Cancer Surveillance Improvement Initiative. (http://www.health.state.ny.us/nysdoh/cancer/csii/nyscsii2.htm).
300. Ngai, H.M. and Zhang, J. (2001) Multivariate cumulative sum control charts based on projection pursuit. Statistica Sinica, 11, 747-766.
301. Nobre, F.F., Monteiro, A.B.S., Telles, P.R. and Williamson, G.D. (2001) Dynamic linear model and SARIMA: a comparison of their forecasting performance in epidemiology. Statistics in Medicine, 20, 3051-3069.
302. Norström, M., Pfeiffer, D.U. and Jarp, J. (2000) A space-time cluster investigation of an outbreak of acute respiratory disease in Norwegian cattle herds. Preventive Veterinary Medicine, 47, 107-119.
303. Olea-Popelka, F.J., Griffin, J.M., Collins, J.D., McGrath, G. and Martin, S.W. (2003) Bovine tuberculosis in badgers in four areas in Ireland: does tuberculosis cluster? Preventive Veterinary Medicine, 59, 103-111.
304. Openshaw, S., Charlton, M., Craft, A. and Birch, J. (1988) Investigation of leukemia clusters by use of a geographical analysis machine. Lancet, 1, 272-273.
305. Orre, R., Lansner, A., Bate, A. and Lindquist, M. (2000) Bayesian neural networks with confidence estimations applied to data mining. Computational Statistics & Data Analysis, 34, 473-493.
306. Ozonoff, A., Bonetti, M., Forsberg, L. and Pagano, M. (2004) Power comparisons for an improved disease clustering test. Computational Statistics and Data Analyis, 48, 679-684
307. Pagano, M. (1978) On periodic and multiple autoregressions. Annals of Statistics, 6, 1310-1317.
308. Page, E.S. (1954) Continuous inspection schemes. Biometrika, 41, 100-115.
309. Patil, G.P. and Taillie, C. (2003) Geographic and network surveillance via scan statistics for critical area detection. Statistical Science, 18, 457-465.
310. Patil, G.P. and Taillie, C. (2004) Upper level set scan statistic for detecting arbitrarily shaped hotspots. Environmental and Ecological Statistics, 11, 183-197.
311. Pavlin, J.A. (2003) Investigation of disease outbreaks detected by 'syndromic' surveillance systems. Journal of Urban Health, 80, i107-i114.
312. Perez, A.M., Ward, M.P., Torres, P. and Ritacco, V. (2002) Use of spatial statistics and monitoring data to identify clustering of bovine tuberculosis in Argentina. Preventive Veterinary Medicine, 56, 63-74.
313. Petzold, M., Sonesson, C., Bergman, E. and Kieler, H. (2004) Surveillance in longitudinal models. Detection of intrauterine growth restriction. Biometrics, 60, 1025-1033
314. Pickle, L.W. and Hermann, D.J. (1995) Cognitive aspects of statistical mapping. Technical Report 18, NCHS Office of Research and Methodology, Washington, DC.
315. Pignatiello, Jr, J.J. and Runger, G.C. (1990) Comparisons of multivariate CUSUM charts. Journal of Quality Technology, 22, 173-186.
316. Platt, R., Bocchino, C., Caldwell, B., Harmon, R., Kleinman, K., Lazarus, R., Nelson, A.F., Nordin, J.D. and Ritzwoller, D.P. (2003) Syndromic surveillance using minimum transfer of identifiable data: the example of the National Bioterrorism Syndromic Surveillance Demonstration Program. Journal of Urban Health, 80, i25-i31.
317. Pollak, M. and Siegmund, D. (1975) Approximations to the expected sample size of certain sequential tests. Annals of Statistics, 3, 1267-1282.
318. Pollak, M. and Siegmund, D. (1985) A diffusion process and its applications to detecting a change in the drift of Brownian motion. Biometrika, 72, 267-280.
319. Poor, V.H. (1998) Quickest detection with exponential penalty for delay. Annals of Statistics, 26, 2179-2205.
320. Preparata, F.P. and Shamos, M.I. (1985) Computational Geometry: An Introduction. New York: Springer-Verlag.
321. Qiu, P.H. and Hawkins, D. (2001) A rank-based multivariate CUSUM procedure. Technometrics, 43, 120-132.
322. Qiu, P.H. and Hawkins, D. (2003) A nonparametric multivariate cumulative sum procedure for detecting shifts in all directions. The Statistician, 52, 151-164.
323. Radaelli, G. (1992) Using the Cuscore technique in the surveillance of rare health events. Journal of Applied Statistics, 19, 75-81.
324. Radaelli, G. (1994) Poisson and negative binomial dynamics for counted data under CUSUM-type chart. Journal of Applied Statistics, 21, 347-356.
325. Radaelli, G. (1996) Detection of an unknown increase in the rate of a rare event. Journal of Applied Statistics, 23, 105-113.
326. Rao, C.R. and Mitra, S.K. (1971) Generalized Inverse of Matrices and its Applications. Wiley.
327. Rath, T.M., Carreras, M. and Sebastiani, P. (2003) Automated detection of influenza epidemics with hidden Markov models. In M.R. Berthold, H.-J. Lenz, E. Bradley, R. Kruse, C. Borgelt and F. Pfenning (eds), Advances in Intelligent Data Analysis V, pp. 521-531. Berlin: Springer-Verlag.
328. Raubertas, R.F. (1989) An analysis of disease surveillance data that uses geographic locations of the reporting units. Statistics in Medicine, 8, 267-271.
329. Reis, B.Y. and Mandl, K.D. (2003) Time series modeling for syndromic surveillance. BMC Medical Informatics and Decision Making, 3, 1-11.
330. Reis, B.Y., Pagano, M. and Mandl, K.D. (2003) Using temporal context to improve biosurveillance. Proceedings of the National Academy of Sciences of the USA, 100, 1961-1965.
331. Rigau-Perez, J.G., Millard, P.S., Walker, D.R., Deseda, C.C. and Casta-Velez, A. (1999) A deviation bar chart for detecting dengue outbreaks in Puerto Rico. American Journal of Public Health, 89, 374-378.
332. Ripley, B. (1988) Statistical Inference for Spatial Processes. Cambridge: Cambridge University Press.
333. Ripley, B.D. (1976) The second-order analysis of a stationary point process. Journal of Applied Probability, 13, 255-266.
334. Ripley, B.D. (1981) Spatial Statistics. New York: Wiley.
335. Robert, C., Celeux, G. and Diebolt, J. (1993). Bayesian estimation of hidden Markov chains: A stochastic implementation. Statistics and Probability Letters, 16, 77-83.
336. Robert, C., Rydén, T. and Titterington, D. (2000). Bayesian inference in hidden Markov models through reversible jump Markov chain Monte Carlo. Journal of the Royal Statistical Society, Series B, 62, 57-75.
337. Robert, C.P. and Casella, G. (1999) Monte Carlo Statistical Methods. New York: Springer- Verlag.
338. Roberts, S.W. (1959) Control chart tests based on geometric moving averages. Technometrics, 1, 239-250.
339. Roberts, S.W. (1966) A comparison of some control chart procedures. Technometrics, 8, 411-430.
340. Robertson, T., Wright, F.T. and Dykstra, R.L. (1988) Order Restricted Inference. Chichester: John Wiley & Sons, Ltd.
341. Roche, L.M., Skinner, R. and Weinstein, R.B. (2002) Use of a geographic information system to identify and characterize areas with high proportions of distant stage breast cancer. Journal of Public Health Management and Practice, 8(2), 26-32.
342. Rogerson, P. (1997) Surveillance methods for monitoring the development of spatial patterns. Statistics in Medicine, 16, 2081-2093.
343. Rogerson, P. (2001a) A statistical method for the detection of geographic clustering. Geographical Analysis, 33, 215-227.
344. Rogerson, P. (2001b) Monitoring point patterns for the development of space-time clusters. Journal of the Royal Statistical Society, Series A, 164, 87-96.
345. Rogerson, P. (2004) Formulas for the design of cusum quality control charts. Submitted for publication.
346. Rogerson, P. and Sun, Y. (2001) Spatial monitoring of geographic patterns: an application to crime analysis. Computers, Environment, and Urban Systems, 25, 539-556.
347. Rogerson, P. and Yamada, I. (2004a) Approaches to syndromic surveillance when data consist of small regional counts. Morbidity and Mortality Weekly Report, 53 (supplement), 79-85.
348. Rogerson, P. and Yamada, I. (2004b) Monitoring change in spatial patterns of disease: comparing univariate and multivariate cumulative sum approaches. Statistics in Medicine, 23, 2195-2214.
349. Rosolowski, M. and Schmid, W. (2003) EWMA charts for monitoring the mean and the autocovariances of stationary Gaussian processes. Sequential Analysis, 22, 257-285.
350. Ross, S. (1989) Introduction to Probability Models (4th edn). San Diego, CA: Academic Press.
351. Ross, A. and Davis, S. (1990) Point pattern analysis of the spatial proximity of residences prior to diagnosis of persons with Hodgkin's disease. American Journal of Epidemiology, 132, 53-62.
352. Rossi, G., Lampugnani, L. and Marchi, M. (1999) An approximate CUSUM procedure for surveillance of health events. Statistics in Medicine, 18, 2111-2122.
353. Runger, G.C. (1996) Projections and the U2 chart for multivariate statistical process control. Journal of Quality Technology, 28, 313-319.
354. Runger, G.C. and Prabhu, S.S. (1996) A Markov chain model for the multivariate exponentially weighted moving averages control chart. Journal of the American Statistical Association, 91, 1701-1706.
355. Runger, G.C., Keats, J.B., Montgomery, D.C. and Scranton, R.D. (1999) Improving the performance of the multivariate exponentially weighted moving average control chart. Quality and Reliability Engineering International, 15, 161-166.
356. Ryan, T.P. (2000) Statistical Methods for Quality Improvement. New York: John Wiley & Sons, Inc.
357. Sabel, C.E., Boyle, P.J., Löytönen, M., Gatrell, A.C., Jokelainen, M., Flowerdew, R. and Maasilta P. (2003) Spatial clustering of amyotrophic lateral sclerosis in Finland at place of birth and place of death. American Journal of Epidemiology, 157, 898-905.
358. Samet, H. (1990) The Design and Analysis of Spatial Data Structures. Reading, MA: Addison- Wesley.
359. Sankoh, O.A., Ye, Y., Sauerborn, R., Muller, O. and Becher, H. (2001) Clustering of childhood mortality in rural Burkina Faso. International Journal of Epidemiology, 30, 485-492.
360. Sauders, B.D., Fortes, E.D., Morse, D.L., Dumas, N., Kiehlbauch, J.A., Schukken, Y., Hibbs, J.R. and Wiedmann, M. (2003) Molecular subtyping to detect human listeriosis clusters. Emerging Infectious Diseases, 9, 672-680.
361. Schmid, W. and Schöne, A. (1997) Some properties of the EWMA control chart in the presence of autocorrelation. Annals of Statistics, 25, 1277-1283.
362. Schnell, D., Zaidi, A. and Reynolds, G. (1989) A time series analysis of gonorrhea surveillance data. Statistics in Medicine, 8, 343-352.
363. Scott, S. (2002) Bayesian methods for hidden Markov models: Recursive computing in the 21st century. Journal of the American Statistical Association, 97, 337-351.
364. Scott, S., James, G. and Sugar, C. (2004) Hidden Markov models for longitudinal comparisons. Technical report (http://www-rcf.usc.edu/~ sls/hmm_hs_v2.pdf).
365. Scranton, R.D., Runger, G.C., Keats, J.B. and Montgomery, D.C. (1996) Efficient shift detection using multivariate exponentially-weighted moving average control charts and principal components. Quality and Reliability Engineering International, 12, 165-171.
366. Serfling, R.E. (1963) Methods for current statistical analysis of excess pneumonia- influenza deaths. Public Health Reports, 78, 494-506.
367. Sheehan, T.J., Gershman, S.T., MacDougal, L., Danley, R., Mroszczyk, M., Sorensen, A.M. and Kulldorff, M. (2000) Geographical surveillance of breast cancer screening by tracts, towns and zip codes. Journal of Public Health Management and Practice, 6, 48-57.
368. Sheehan, T.J., DeChello, L.M., Kulldorff, M., Gregorio, D.I., Gershman, S. and Mroszczyk, M. (2004) The geographic distribution of breast cancer incidence in Massachusetts 1988-1997, adjusted for covariates. International Journal of Health Geographics, 3:17.
369. Shewhart, W.A. (1931) Economic Control of Quality of Manufactured Product. London: Macmillan.
370. Shiryaev, A.N. (1963) On optimum methods in quickest detection problems. Theory of Probability and its Applications, 8, 22-46.
371. Siegmund, D. (1985) Sequential Analysis: Tests and Confidence Intervals. New York: Springer-Verlag.
372. Siegmund, D. and Venkatraman, E.S. (1995) Using the generalized likelihood ratio statistic for sequential detection of a change-point. Annals of Statistics, 23, 255-271.
373. Siegmund, D.O. and Worsley, K.J. (1995) Testing for a signal with unknown location and scale in a stationary Gaussian random field. Annals of Statistics, 23, 608-639.
374. Silverman, B.W. (1976) Limit theorems for dissociated random variables. Advances in Applied Probability, 8, 806-819.
375. Skinner, K.R., Montgomery, D.C. and Runger, G.C. (2003) Process monitoring for multiple count data using generalized linear model-based control charts. International Journal of Production Research, 41, 1167-1180.
376. Smith, A.F. and West, M. (1983) Monitoring renal transplants: an application of the multiprocess Kalman filter. Biometrics, 39, 867-878.
377. Smith, K.L., DeVos, V., Bryden, H., Price, L.B., Hugh-Jones, M.E. and Keim, P. (2000) Bacillus anthracis diversity in Kruger National Park. Journal of Clinical Microbiology, 38, 3780-3784.
378. Snow, J. (1854) On the Mode of Communication of Cholera (2nd edn). London: Churchill Livingstone.
379. Sonesson, C. (2003) Evaluations of some exponentially weighted moving average methods. Journal of Applied Statistics, 30, 1115-1133.
380. Sonesson, C. and Bock, D. (2003) A review and discussion of prospective statistical surveillance in public health. Journal of the Royal Statistical Society, Series A, 166, 5-21.
381. Song, C. and Kulldorff, M. (2003) Power evaluation of disease clustering tests. International Journal of Health Geographics, 2:9.
382. Sosin, D.M. (2003) Draft framework for evaluating syndromic surveillance systems. Journal of Urban Health, 80, i8-i13.
383. Spiegelhalter, D. and Lauritzen, S. (1990) Sequential updating of conditional probabilities on directed graphical structures. Networks, 20, 579-605.
384. Spiegelhalter, D.J., Best, N.G., Gilks, W.R. and Inskip, H. (1996) Hepatitis B: a case study in MCMC methods. In W.R. Gilks, S. Richardson, and D.J. Spiegelhalter (eds), Markov Chain Monte Carlo in Practice. London: Chapman & Hall.
385. Spiegelhalter, D., Thomas, A. and Best, N. (1999) WinBUGS version 1.2 user manual. Technical report, MRC Biostatistics Unit.
386. Spiegelhalter, D., Best, N., Carlin, B. and van der Linde, A. (2002) Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society, Series B, 64, 583-640.
387. Srivastava, M.S. and Wu, Y. (1993) Comparison of EWMA, CUSUM and Shiryaev- Roberts procedures for detecting a shift in the mean. Annals of Statistics, 21, 645-670.
388. Steiner, S.H., Cook, R.J. and Farewell, V.T. (1999) Monitoring paired binary surgical outcomes using cumulative sum charts. Statistics in Medicine, 18, 69-86.
389. Stern, H.S. and Cressie, N.A.C. (2000) Posterior predictive model checks for disease mapping models. Statistics in Medicine, 19, 2377-2397.
390. Stern, L. and Lightfoot, D. (1999) Automated outbreak detection: a quantitative retrospective analysis. Epidemiology and Infection, 122, 103-110.
391. Steutel, F.W. and van Harn, K. (1979) Discrete analogues of self-decomposability and stability. Annals of Probability, 7, 893-899.
392. Stone, R.A. (1998) Investigation of excess environmental risk around putative sources: statistical problems and a proposed test. Statistics in Medicine, 7, 649-660.
393. Stoumbos, Z.G., Reynolds Jr, M.R., Ryan, T.P. and Woodall, W.H. (2000) The state of statistical process control as we proceed into the 21st century. Journal of the American Statistical Association, 95, 992-998.
394. Stroup, D.F. and Thacker, S.B. (1993) A Bayesian approach to the detection of aberrations in public-health surveillance data. Epidemiology, 4, 435-443.
395. Stroup, D.F., Thacker, S.B. and Herndon, J.L. (1988) Application of multiple time-series analysis to the estimation of pneumonia and influenza mortality by age 1962-1983. Statistics in Medicine, 7, 1045-1059.
396. Stroup, D.F., Williamson, G.D., Herndon, J.L. and Karon, J.M. (1989) Detection of aberrations in the occurrence of notifiable diseases surveillance data. Statistics in Medicine, 8, 323-329.
397. Stroup, D.F., Wharton, M., Kafadar, K. and Dean, A.G. (1993). Evaluation of a method for detecting aberrations in public health surveillance data. American Journal of Epidemiology, 137, 373-380.
398. Stroup, D.F., Williamson, D.F., Dean, A.D., Haddad, S., Basha, M. and Rapose, W. (1994) Statistical Software for Public Health Surveillance. Atlanta, GA: Centers for Disease Control and Prevention.
399. Stroup, D.F., Brookmeyer, R. and Kalsbeek, W.D. (2004) Public health surveillance in action: a framework. In R. Brookmeyer and D.F. Stroup (eds), Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance, pp. 1-35. Oxford: Oxford University Press.
400. Sudakin, D.L., Horowitz, Z. and Giffin, S. (2002) Regional variation in the incidence of symptomatic pesticide exposures: applications of geographic information systems. Journal of Toxicology-Clinical Toxicology, 40, 767-773.
401. Sullivan, J.H. and Jones, L.A. (2002) A self-starting control chart for multivariate individual observations. Technometrics, 44, 24-33.
402. Sun, D., Tsutakawa, R. and Kim, H. (2000) Spatio-temporal interaction with disease mapping. Statistics in Medicine, 19, 2015-2035.
403. Tango, T. (1995) A class of tests for detecting 'general' and 'focused' clustering of rare diseases. Statistics in Medicine, 14, 2323-2334.
404. Tango, T. (2000) A test for spatial disease clustering adjusted for multiple testing. Statistics in Medicine, 19, 191-204.
405. Teutsch, S.M. and Churchill, R.E. (2000) Principles and Practice of Public Health Surveillance, (2nd edition). Oxford: Oxford University Press.
406. Thacker, S. (1994) 'Historical development', in S. Teutsch and R. Churchill (eds), Principles and Practice of Public Health Surveillance. Oxford: Oxford University Press.
407. Thacker, S.B. (2000) Historical Development. In S.M. Teutsch and R.E. Churchill (eds), Principles and Practice of Public Health Surveillance (2nd edn), pp. 1-16. New York: Oxford University Press.
408. Thacker, S.B. and Berkelman, R.L. (1988) Public health surveillance in the United States. Epidemiol Reviews, 10, 164-190.
409. Thacker, S.B., Choi, K. and Brachman, P.S. (1983) The surveillance of infectious diseases. Journal of the American Medical Association, 249, 1181-1185.
410. Thomas, A.J. and Carlin, B.P. (2003) Late detection of breast and colorectal cancer in Minnesota counties: an application of spatial smoothing and clustering. Statistics in Medicine, 22, 113-127.
411. Timm, N.H. (1996) Multivariate quality control using finite intersection tests. Journal of Quality Technology, 28, 233-243.
412. Tsui, K.L. and Woodall, W.H. (1993) Multivariate control charts based on loss functions. Sequential Analysis, 12, 79-92.
413. Tsui, F.C., Espino, J.U., Dato, V.M., Gesteland, P.H., Hutman, J. and Wagner, M.M. (2003) Technical description of RODS: a real-time public health surveillance system. Journal of the American Medical Informatics Association, 10, 399-408.
414. Tsutakawa, R. (1988) Mixed model for analysing geographic variability in mortality rates. Journal of the American Statistical Association, 83, 37-42.
415. Turnbull, B., Iwano, E.J., Burnett, W.S., Howe, H.L. and Clark, L.C. (1990) Monitoring for clusters of disease: Application to leukemia incidence in Upstate New York. American Journal of Epidemiology, 132, S136-S143.
416. United States Department of Agriculture (2001) West Nile virus in equids in the Northeastern United States in 2000. USDA, APHIS, Veterinary Services (http://www.aphis.usda.gov/vs/ceah/wnvreport.pdf).
417. VanBrackle, L. and Williamson, G.D. (1999) A study of the average run length characteristics of the National Notifiable Diseases Surveillance System. Statistics in Medicine, 18, 3309-3319.
418. VanEenwyk, J., Bensley, L., McBride, D., Hoskins, R., Solet, D., McKeeman Brown, A., Topiwala, H., Richter, A. and Clark, R. (1999) Addressing community health concerns around SeaTac Airport: Second Report. Washington State Department of Health (http://www.doh.wa.gov/EHSPHL/Epidemiology/NICE/publications/ Seatac_Report2.pdf).
419. Vardeman, S. and Ray, D. (1985) Average run lengths for CUSUM schemes when observations are exponentially distributed. Technometrics, 27, 145-150.
420. Vidal-Rodeiro, C.L. and Lawson, A.B. (2005) An evaluation of the edge effects in disease map modelling. Computational Statistics and Data Analysis. To appear.
421. Viel, J.F., Arveux, P., Baverel, J. and Cahn, J.Y. (2000) Soft-tissue sarcoma and non- Hodgkin's lymphoma clusters around a municipal solid waste incinerator with high dioxin emission levels. American Journal of Epidemiology, 152, 13-19.
422. Wagner, M., Tsui, F.C., Espino, J.U., Dato, V.M., Sittig, D.F., Caruana, R.A., McGinnis, L.F., Deerfield, D.W., Druzdzel, M.J. and Friedsma, D.B. (2001) The emerging science of very early detection of disease outbreaks. Journal of Public Health Management Practice, 7, 51-59.
423. Wallenstein, S. (1980) A test for detection of clustering over time. American Journal of Epidemiology, 111, 367-72.
424. Waller, L.A., Turnbull, B.W., Clark, L.C. and Nasca, P. (1992) Chronic disease surveillance and testing of clustering of disease and exposure. Environmetrics, 3, 281-300.
425. Waller, L., Turnbull, B., Clark, L. and Nasca, P. (1994) Spatial pattern analyses to detect rare disease clusters. In N. Lange, L. Ryan, L. Billiard, D. Brillinger, L. Conquest, and J. Greenhouse (eds), Case Studies in Biometry, pp. 3-24. New York: John Wiley & Sons, Inc.
426. Waller, L.A., Carlin, B.P., Xia, H. and Gelfand, A.E. (1997) Hierarchical spatio-temporal mapping of disease rates. Journal of the American Statistical Association, 92, 607-617.
427. Walsh, S.J. and DeChello, L.M. (2001) Geographical variation in mortality from systemic lupus erythematosus in the United States. Lupus, 10, 637-646.
428. Walsh, S.J. and Fenster, J.R. (1997) Geographical clustering of mortality from systemic sclerosis in the southeastern United States, 1981-90. Journal of Rheumatology, 24, 2348-2352.
429. Walter, S.D. (1993) Visual and statistical assessment of spatial clustering in mapped data. Statistics in Medicine, 12, 1275-1291.
430. Walter, S.D. (1994) A simple test for spatial pattern in regional health data. Statistics in Medicine, 13, 1037-1044.
431. Ward, M.P. (2001) Blowfly strike in sheep flocks as an example of the use of a time-space scan statistic to control confounding. Preventive Veterinary Medicine, 49, 61-69.
432. Ward, M.P. (2002) Clustering of reported cases of leptospirosis among dogs in the United States and Canada. Preventive Veterinary Medicine, 56, 215-226.
433. Watier, L., Richardson, S. and Hubert, B. (1991) A time series construction of an alert threshold with application to S. bovismorbificans in France. Statistics in Medicine, 10, 1493-1509.
434. Weatherall, J.A.C. and Haskey, J.C. (1976) Surveillance of malformations. British Medical Journal, 32, 39-44.
435. Weinstock, M.A. (1981) A generalized scan statistic test for the detection of clusters. International Journal of Epidemiology, 10, 289-293.
436. Wessman, P. (1998) Some principles for surveillance adopted for multivariate processes with a common change point. Communications in Statistics. Theory and Methods, 27, 1143-1161.
437. Wessman, P. (1999) Studies on the surveillance of univariate and multivariate processes. Ph.D. thesis, Department of Statistics, Göteborg University.
438. West, M. and Harrison, J. (1989) Bayesian Forecasting and Dynamic Models. New York: Springer-Verlag.
439. Wetherill, G.B. and Brown, D.W. (1991) Statistical Process Control: Theory and Practice London: Chapman & Hall.
440. Wharton, M., Price, W., Hoesly, F., Woolard, D., White, K., Greene, C. and McNabb, S. (1993) Evaluation of a method for detecting outbreaks of diseases in 6 states. American Journal of Preventive Medicine, 9, 45-49.
441. White, C.H. and Keats, J.B. (1996) ARLs and higher order run length moments for Poisson CUSUM. Journal of Quality Technology, 28, 363-369.
442. Whittemore, A.S., Friend, N., Brown, B.W. and Holly, E.A. (1987) A test to detect clusters of disease. Biometrika, 74, 631-635.
443. Wierda, S.J. (1994) Multivariate statistical process control: recent results and directions for future research. Statistica Neerlandica, 48, 147-168.
444. Wikle, C.K. (2002) Spatial modelling of count data: A case study in modelling breeding bird survey data on large spatial domains. In A.B. Lawson and D.G.T. Denison (eds), Spatial Cluster Modelling, Chapter 11. Boca Raton, FL: CRC Press.
445. Williamson, G.D. and Hudson, G.W. (1999) A monitoring system for detecting aberrations in public health surveillance reports. Statistics in Medicine, 18, 3283-3298.
446. Wolter, C. (1987) Monitoring intervals between rare events: a cumulative score procedure compared with Rina Chen's sets technique. Methods of Information in Medicine, 26, 215-219.
447. Wong, W.-K. (2004) Data mining for early disease outbreak detection. Ph.D. thesis, Carnegie Mellon University.
448. Wong, W.-K., A.W. Moore, G. Cooper, and M. Wagner (2002) Rule-based anomaly pattern detection for detecting disease outbreaks. In K. Ford (ed.), Proceedings of the Eighteenth National Conference on Artificial Intelligence, pp. 217-223. Menlo Park, CA: AAAI Press.
449. Wong, W.-K., A. Moore, G. Cooper, and M. Wagner (2003) Bayesian network anomaly pattern detection for disease outbreaks. In T. Fawcett and N. Mishra (eds), Proceedings of the Twentieth International Conference on Machine Learning, pp. 808-815. Menlo Park, CA: AAAI Press.
450. Wong, W.K., Moore, A., Cooper, G. and Wagner, M. (2003) WSARE: What's strange about recent events? Journal of Urban Health, 80, i66-i75.
451. Woodall, W.H. (1997) Control charts based on attribute data: bibliography and review. Journal of Quality Technology, 29, 172-183.
452. Woodall, W.H. and Montgomery, D.C. (1999) Research issues and ideas in statistical process control. Journal of Quality Technology, 31, 376-386.
453. Woodall, W.H. and Ncube, M.M. (1985) Multivariate CUSUM quality-control procedures. Technometrics, 27, 285-292.
454. Wright, S. (1921) Correlation and causation. Journal of Agricultural Research, 20, 557-585.
455. Xia, H. and Carlin, B.P. (1998) Spatio-temporal models with errors in co-variates: Mapping ohio lung cancer mortality. Statistics in Medicine, 17, 2025-2043.
456. Yashchin, E. (1993) Statistical control schemes-methods, applications and generalizations. International Statistical Review, 61, 41-66.
457. Yashchin, E. (1994) Monitoring variance components. Technometrics, 36, 379-393.
458. Yeh, A.B., Lin, D.K.J., Zhou, H.H. and Venkataramani, C. (2003) A multivariate exponentially weighted moving average control chart for monitoring process variability. Journal of Applied Statistics, 30, 507-536.
459. Yiannakoulias, N., Rowe, B.H., Svenson, L.W., Schopflocher, D.P., Kelly, K., Voaklander, D.C. (2003) Zones of prevention: the geography of fall injuries in the elderly. Social Science and Medicine, 57, 2065-2073.
460. Zaidi, A., Schnell, D. and Reynolds, G. (1989) Time series analysis of syphillis surveillance data. Statistics in Medicine, 8, 353-362.
461. Zeger, S.L. (1988) A regression model for time series of counts. Biometrika, 75, 621-629.
462. Zhu, L. and Carlin, B.P. (2000) Comparing hierarchical models for spatio-temporally misaligned data using the deviance information criterion. Statistics in Medicine, 19, 2265-2278.