Some dissimilarity measures of branching processes and optimal decision making in the presence of potential pandemics

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Abstract

We compute exact values respectively bounds of dissimilarity/distinguishabilitymeasures-in the sense of the Kullback-Leibler information distance (relative entropy) and some transforms of more general power divergences and Renyi divergences-between two competing discrete-time Galton-Watson branching processes with immigration GWI for which the offspring as well as the immigration (importation) is arbitrarily Poisson-distributed; especially, we allow for arbitrary type of extinction-concerning criticality and thus for non-stationarity. We apply this to optimal decision making in the context of the spread of potentially pandemic infectious diseases (such as e.g., the current COVID-19 pandemic), e.g., covering different levels of dangerousness and different kinds of intervention/mitigation strategies. Asymptotic distinguishability behaviour and diffusion limits are investigated, too.

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Kammerer, N. B., & Stummer, W. (2020). Some dissimilarity measures of branching processes and optimal decision making in the presence of potential pandemics. Entropy, 22(8). https://doi.org/10.3390/E22080874

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