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For a recently derived pairwise model of network epidemics with non-Markovian recovery, we prove that under some mild technical conditions on the distribution of the infectious periods, smaller variance in the recovery time leads to higher reproduction number, and consequently to a larger epidemic outbreak, when the mean infectious period is fixed.
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Röst, G., Vizi, Zs., and Kiss, I. Z.: Impact of non-Markovian recovery on network epidemics, in: Mondaini RP (ed.) BIOMAT 2015, World Scientific, 40–53 (2016)
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Janson, S. , Luczak, M., and Windridge, P.: Law of large numbers for the SIR epidemic on a random graph with given degrees. Random Struct. Alg., 45
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Miller, J. C., and Kiss, I. Z.: Epidemic spread in networks: Existing methods and current challenges. Mathematical Modelling of Natural Phenomena 9(2)
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Barbarossa MV, Dénes A, Kiss G, Nakata Y, Röst G, Vizi Z: Transmission Dynamics and Final Epidemic Size of Ebola Virus Disease Outbreaks with Varying Interventions. PLoS ONE 10(7)
2015
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Kiss, I.Z., Miller, J.C., and Simon, L.P.: Mathematics of Epidemics on Networks – From Exact to Approximate Models. Springer (2017)
2017
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Sherborne, N., Miller, J. C., Blyuss, K. B., and Kiss, I. Z.: Mean-field models for non-Markovian epidemics on networks. Journal of Mathematical Biology, 1–24 (2017)
2017
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Wilkinson, R.R., Ball, F.G., and Sharkey, K.J.: The relationships between message passing, pairwise, Kermack-McKendrick and stochastic SIR epidemic models. J. Math. Biol. 75(6-–7)
2017
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