Prospective time periodic geographical disease surveillance using a scan statistic

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The structure of optimal private tests for simple hypotheses (2018, background): “Change-point detection has a long history in statistics and information theory (e.g. [She31, Pag54, Pag55, Shi63, Lor71, Pol85, Mou86, Pol87, Lai95, Kul01, Mei06, VB14]).”
Is Average Run Length to False Alarm Always an Informative Criterion? (2008, neutral): “See, for example, Shewhart (1931), Page (1954), Roberts (1966), Shiryayev (1963, 1978), Lorden (1971), Moustakides (1986), Pollak (1985, 1987), Ritov (1990), Lai (1995) and Kulldorff (2001).”
A review and discussion of prospective statistical surveillance in public health (2003, methodology): “In a comment (Lawson, 2001b) on Kulldorff (2001) and Rogerson (2001) it was pointed out that the surveillance methodology in this area must be developed to reduce the expected delay in the detection.”
Spatio-Temporal Data Mining (2017, methodology): “Generalization of the scan statistic for ST data, termed as space-time scan statistics, have been explored for studying disease outbreaks, crime hot-spots, and events in twitter data [Cheng and Wicks 2014; Kulldorff 2001; Kulldorff et al. 2005].”