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Generalized Scan Statistics for Disease Surveillance

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  • Pei-Sheng Lin

Abstract

type="main" xml:id="sjos12063-abs-0001"> In applying scan statistics for disease surveillance, it would be valuable to have an integrated model that simultaneously includes environmental covariates and spatial correlation. In this paper, a generalized scan statistics under quasi-likelihood functions is proposed to address this issue. We use a two-step estimation process to obtain estimates of coefficients and adapt a bootstrapping method for the minimal p-value to address the multiple-testing problem. Under suitable conditions, the proposed method is consistent and can control the type I error rate. Simulations and applications to real data sets are used to evaluate the method.

Suggested Citation

  • Pei-Sheng Lin, 2014. "Generalized Scan Statistics for Disease Surveillance," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 791-808, September.
    • Handle: RePEc:bla:scjsta:v:41:y:2014:i:3:p:791-808
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    File URL: http://hdl.handle.net/10.1111/sjos.12063
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    References listed on IDEAS

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    1. Pei-Sheng Lin, 2008. "Estimating equations for spatially correlated data in multi-dimensional space," Biometrika, Biometrika Trust, vol. 95(4), pages 847-858.
    2. Tonglin Zhang & Ge Lin, 2009. "Cluster Detection Based on Spatial Associations and Iterated Residuals in Generalized Linear Mixed Models," Biometrics, The International Biometric Society, vol. 65(2), pages 353-360, June.
    3. J. Law, 2009. "Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology by LAWSON, A. B," Biometrics, The International Biometric Society, vol. 65(2), pages 661-662, June.
    4. Ozonoff, Al & Bonetti, Marco & Forsberg, Laura & Pagano, Marcello, 2005. "Power comparisons for an improved disease clustering test," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 679-684, April.
    5. Kulldorff, Martin & Tango, Toshiro & Park, Peter J., 2003. "Power comparisons for disease clustering tests," Computational Statistics & Data Analysis, Elsevier, vol. 42(4), pages 665-684, April.
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    1. Pei‐Sheng Lin & Jun Zhu, 2020. "A heterogeneity measure for cluster identification with application to disease mapping," Biometrics, The International Biometric Society, vol. 76(2), pages 403-413, June.
    2. Malinga, G.A. & Niedzwecki, J.M., 2016. "Lightning field behavior around grounded airborne systems," Renewable Energy, Elsevier, vol. 87(P1), pages 572-584.
    3. Goel, Varun & Kumar, Naresh & Singh, Paramvir, 2018. "Impact of modified parameters on diesel engine characteristics using biodiesel: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2716-2729.
    4. Mohamed-Salem Ahmed & Lionel Cucala & Michaël Genin, 2021. "Spatial autoregressive models for scan statistic," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-20, December.
    5. Pei‐Sheng Lin & Yi‐Hung Kung & Murray Clayton, 2016. "Spatial scan statistics for detection of multiple clusters with arbitrary shapes," Biometrics, The International Biometric Society, vol. 72(4), pages 1226-1234, December.
    6. Riechers, Maraja & Barkmann, Jan & Tscharntke, Teja, 2016. "Perceptions of cultural ecosystem services from urban green," Ecosystem Services, Elsevier, vol. 17(C), pages 33-39.

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