ACHTERBOSCH, Thom J. and DOPFER, Dorte DV, 2006. Cattle trade and the risk of importing animal diseases into the Netherlands. Online. Available from: https://ageconsearch.umn.edu/record/29089/ [Accessed 31 January 2024]. BASU, Srinka and SEN, Sugata, 2023. COVID 19 Pandemic, Socio-Economic Behaviour and Infection Characteristics: An Inter-Country Predictive Study Using Deep Learning. Computational Economics. February 2023. Vol. 61, no. 2, p. 645–676. DOI 10.1007/s10614-021-10223-5. HARPER, Robert and TEE, Philip, 2021. Balancing capacity and epidemic spread in the global airline network. Applied Network Science. December 2021. Vol. 6, no. 1, p. 94. DOI 10.1007/s41109-021-00432-0. Abstract The structure of complex networks has long been understood to play a role in transmission and spreading phenomena on a graph. Such networks form an important part of the structure of society, including transportation networks. As society fights to control the COVID-19 pandemic, an important question is how to choose the optimum balance between the full opening of transport networks and the control of epidemic spread. In this work we investigate the interplay between network dismantling and epidemic spread rate as a proxy for the imposition of travel restrictions to control disease spread. For network dismantling we focus on the weighted and unweighted forms of metrics that capture the topological and informational structure of the network. Our results indicate that there is benefit to a directed approach to imposing travel restrictions, but we identify that more detailed models of the transport network are necessary for definitive results. RODRÍGUEZ‐ITURBE, Ignacio, 1986. Scale of fluctuation of rainfall models. Water Resources Research. Online. August 1986. Vol. 22, no. 9S. DOI 10.1029/WR022i09Sp0015S. [Accessed 31 January 2024]. The role of scale in the rainfall characterizations resulting from different rainfall models is the main issue under study. Three different types of models are analyzed: temporal rainfall models at a point, areal storm rainfall models, and space‐time rainfall representations. The perspective is taken that precipitation models need mainly to incorporate those features of the process which lead to an adequate representation under some amount of local averaging either in time or in space or in space and time. Thus the characteristics of the averaged rainfall process resulting from the different models are analyzed with a special emphasis on the role of the scale of fluctuation of the process in these characteristics. RODRIGUEZ‐ITURBE, Ignacio and EAGLESON, Peter S., 1987. Mathematical models of rainstorm events in space and time. Water Resources Research. January 1987. Vol. 23, no. 1, p. 181–190. DOI 10.1029/WR023i001p00181. The spatial and temporal structure of rainfall from storm events is investigated using point process techniques. Cells are assumed to be distributed in space either independently according to a Poisson process, or with clustering according to a Neyman‐Scott scheme. Cells are born randomly through the storm and their rain is spread in time and space according to functions which may include random parameters. Two processes are studied: the rainfall intensity process which in reality is never measured and the cumulative rainfall process through the life of the storm. The mean, variance, and covariance structure are obtained for both processes under the different assumed models. YUVAL, Janni, NITZAN, Mor, TANNENBAUM, Neta Ravid and BARAK, Boaz, 2021. Optimizing testing policies for detecting COVID-19 outbreaks.. Online. 1 January 2021. arXiv. arXiv:2007.04827. Available from: http://arxiv.org/abs/2007.04827 [Accessed 31 January 2024]. The COVID-19 pandemic poses challenges for continuing economic activity while reducing health risks. While these challenges can be mitigated through testing, testing budget is often limited. Here we study how institutions, such as nursing homes, should utilize a fixed test budget for early detection of an outbreak. Using an extended network-SEIR model, we show that given a certain budget of tests, it is generally better to test smaller subgroups of the population frequently than to test larger groups but less frequently. The numerical results are consistent with an analytical expression we derive for the size of the outbreak at detection in an exponential spread model. Our work provides a simple guideline for institutions: distribute your total tests over several batches instead of using them all at once. We expect that in the appropriate scenarios, this easy-to-implement policy recommendation will lead to earlier detection and better mitigation of local COVID-19 outbreaks. arXiv:2007.04827 [physics, q-bio]