Conference is now cancelled
A (corrected) graphical hypothesis test of spatiotemporal clustering and clustering range estimation for the tau statistic.
Timothy M Pollington (MathSys, University of Warwick; visiting Big Data Institute, University of Oxford.)
The tau statistic τ uses geolocation and symptom onset time to assess global spatiotemporal clustering and estimate its extent, for epidemiological studies [1,2]. We explore how implementation could bias τ estimates . Graphical hypothesis tests or parameter estimation for τ have been applied incorrectly in the past ; I explain how Diggle highlighted this error and suggested the correction. Using the Hagelloch open-access measles dataset, we compare a previous analysis as the baseline  vs. our modified implementation of a graphical hypothesis test, and estimated clustering range by i) bootstrap sampling method; ii) number of bootstrap samples N; iii) CI type (bias-corrected & accelerated (BCa) vs percentile); and iv) distance band sets.
 Salje et al. PNAS. 2012  Lessler et al. PLoS One. 2016  Pollington et al. arXiv/stat.AP. 2019  ibid. arXiv/stat.ME. 2019