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ABSTRACT
Several spatiotemporal epidemic models have described how contact and mobility restrictions have a dynamic effect on morbidity and mortality of fast transmitting pathogens in epidemics. Despite this, there have been rather limited contributions looking at policy optimization. This work combines a new spatiotemporal epidemic model of a heterogeneous mixed population located at different places with an optimal control approach to show the effects of contact and mobility restrictions under policy optimization. The objective of optimization not only includes epidemiological but also socio-economic implications of the restrictions. Several scenarios are numerically investigated, and the dependence of the optimal policy on some basic epidemiological parameters is analysed. The results illustrate the strong impact of spatial heterogeneity on optimal policy measures. An analysis of the stability of the disease-free equilibrium of the model is also presented.
Acknowledgments
The authors are thankful to one of the reviewers of the paper for a remark about the non-symmetricity of , and to Alberto Corella and Robert Israel for suggesting to us the proof of Lemma 3.1. This work was supported by the Austrian Science Fund (FWF) under grant No I-4571-N.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
All data supporting the findings of this study are available within the paper.
Disclaimer
Te views expressed in this article are purely those of the authors and may not, under any circumstances, be regarded as an official position of the European Commission.
Notes
1. More compartments can be involved in the model for more detailed description of the disease dynamics, similarly as in the single location models.