Abstract
The scenario presented in this chapter is investigating the potential effects of different testing policies in combination with isolating households. In particular we will explore the effect of isolating the household of an infected member and giving priority in testing for healthcare and education workers. Assuming that we have more tests available than necessary for the healthcare and education workers, the effect of different strategies for the leftover tests, don’t test youth, test only elderly with leftover tests, and test everyone with leftover tests are investigated. The results show that the combination of no priority in testing + testing everyone with leftover tests + isolation of the household of an infected member is the best combination to “flatten the curve”. Furthermore, the amount of deaths, the impact on hospitals, and the effects on people in isolation are explored. This scenario has been developed on request of regional Italian authorities.
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Acknowledgements
We would like to acknowledge the members of the ASSOCC team for their valuable contributions to this chapter. Furthermore, we would like to thank Annet Onnes for creating the basic R code that has been used in the OFAT analysis. Additionally, we would like thank Loïs Vanhée, Harko Verhagen for initial support with the OFAT analysis, and Mijke van den Hurk for proof reading and her valuable feedback for this chapter. The simulations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Umeå partially funded by the Swedish Research Council through grant agreement no. 2018-05973. This research was conducted using the resources of High Performance Computing Center North (HPC2N). This research was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) and WASP - Humanities and Society (WASP-HS) funded by the Knut and Alice Wallenberg Foundation.
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Kammler, C., Mellema, R. (2021). Testing and Adaptive Testing During the COVID-19 Crisis. In: Dignum, F. (eds) Social Simulation for a Crisis. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-76397-8_6
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DOI: https://doi.org/10.1007/978-3-030-76397-8_6
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