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This paper is centered around the focused cluster detection methods.
The CSS, FSS, BYM, and MLE spatial focused cluster detection methods are outlined in the Appendix.
The CSS, FSS, BYM, and MLE spatial focused cluster detection methods are outlined below.
Focused cluster detection methods include the circular spatial scan statistic (CSS) [ 18], flexible spatial scan statistic (FSS) [ 19], and Bayesian disease mapping (BYM) [ 15].
Focused cluster detection methods identify regions with a high number of disease occurrences in an area around a potential cause (i.e., a toxic waste site) [ 13, 14].
Such comparisons will need to include formal health economic assessments that account for the capital expense of establishing benchtop NGS equipment and expertise in a laboratory, as well as the potential cost-savings associated with more focused cluster investigation, and infection control interventions.
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We also might wish to ask whether exposure traces for the cases exhibit focused clustering.
The first evaluated focused clustering of residential histories using k = 5 nearest neighbors.
If not readjusted, the maximum focus range will be exceeded during sequencing and incorrectly focused clusters will result.
A frequentist approach based on maximum likelihood estimation (MLE) has been recently used to identify potential focused clusters as well.
We then develop a suite of novel tests for evaluating local, global and focused clustering in residential histories using case-control data.
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