
Mathematical Biosciences and Engineering, 2019, 16(2): 813830. doi: 10.3934/mbe.2019038.
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The change of susceptibility following infection can induce failure to predict outbreak potential by $\mathcal{R}_{0}$
1 Department of Mathematical Sciences, Shimane University, 1060 Nishikawatsucho, Matsue, Japan
2 Division of Bioinformatics, Research Center for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido, Japan, JST, PRESTO, 418 Honcho, Kawaguchi, Saitama, 332–0012, Japan
Received: , Accepted: , Published:
Keywords: epidemic model; shortterm disease transmission dynamics; boosting of immunity; final epidemic size
Citation: Yukihiko Nakata, Ryosuke Omori. The change of susceptibility following infection can induce failure to predict outbreak potential by $\mathcal{R}_{0}$. Mathematical Biosciences and Engineering, 2019, 16(2): 813830. doi: 10.3934/mbe.2019038
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This article has been cited by:
 1. Yukihiko Nakata, Ryosuke Omori, Epidemic dynamics with a timevarying susceptibility due to repeated infections, Journal of Biological Dynamics, 2019, 13, 1, 567, 10.1080/17513758.2019.1643043
 2. Bruno Buonomo, Effects of informationdependent vaccination behavior on coronavirus outbreak: insights from a SIRI model, Ricerche di Matematica, 2020, 10.1007/s11587020005068
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