We propose a review of spatial scan statistics approaches in the context of survival data. After presenting the general principle of spatial scan statistics, we review the literature and find that few approaches exist. We distinguish between the first parametric approaches, based on a specific distribution model and therefore not very flexible, and a semi-parametric method. However, these approaches do not allow taking into account the spatial dependence frequently observed in the data. We then present a more recent approach allowing us to take them into account. Finally, we describe the adjustment of cluster detection on covariates before illustrating the methods on the detection of abnormal survival time clusters following the diagnosis of leukemia.
Citation: Camille Frévent. A review of spatial scan statistics for survival data[J]. AIMS Mathematics, 2025, 10(6): 14088-14101. doi: 10.3934/math.2025634
We propose a review of spatial scan statistics approaches in the context of survival data. After presenting the general principle of spatial scan statistics, we review the literature and find that few approaches exist. We distinguish between the first parametric approaches, based on a specific distribution model and therefore not very flexible, and a semi-parametric method. However, these approaches do not allow taking into account the spatial dependence frequently observed in the data. We then present a more recent approach allowing us to take them into account. Finally, we describe the adjustment of cluster detection on covariates before illustrating the methods on the detection of abnormal survival time clusters following the diagnosis of leukemia.
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Camille Frévent. A review of spatial scan statistics for survival data[J]. AIMS Mathematics, 2025, 10(6): 14088-14101. doi: 10.3934/math.2025634
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