59ª RBras – Ouro Preto - MG
Sessão Temática I: Adaptive Likelihood Ratio Strategies for the Detection of Space-Time
Disease Clusters
Max Sousa de Lima - Statistics Department, Universidade Federal do Amazonas
Luiz Henrique Duczmal - Statistics Department, Universidade Federal de Minas Gerais
Abstract: A method based on adaptive likelihood ratios (ALRs) for the detection of emerging
disease clusters is presented. The martingale structure of the regular likelihood ratio is
preserved by the ALR. The upper limit for the false alarm rate of the proposed method
depends only on the quantity of evaluated cluster candidates. Thus Monte Carlo simulations
are not required to validate the procedures statistical significance, allowing the construction of
a fast computational algorithm to detect clusters. The number of evaluated clusters is also
significantly reduced, through the use of an adaptive approach to prune many unpromising
clusters. This further increases the computational speed. Performance is evaluated through
simulations to measure the average detection delay and the probability of correct cluster
detection. We present applications for thyroid cancer in New Mexico and hanseniasis in
children in the Brazilian Amazon.
Keywords: Spatial Analysis, Space-time clusters, Sequential Analysis, Adaptive Likelihood
Ratio, Simulation
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