On the Convexity of the Effective Reproduction Number

Jhonatan Tavori*, Hanoch Levy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In this study, we analyze the evolution of the effective reproduction number, R, through a Susceptible-Infective-Recovered spreading process in heterogeneous populations; Characterizing its decay process allows to analytically study the effects of countermeasures on the progress of the virus under heterogeneity, and to optimize their policies. A striking result of recent studies has shown that heterogeneity across individuals (or superspreading) may have a drastic effect on the spreading process progression, which may cause a nonlinear decrease of R in the number of infected individuals. We account for heterogeneity and analyze the stochastic progression of the spreading process. We show that the decrease of R is, in fact, convex in the number of infected individuals, where this convexity stems from heterogeneity. The analysis is based on establishing stochastic monotonic relations between the susceptible populations in varying times of the spread. We demonstrate that the convex behavior of the effective reproduction number affects the performance of countermeasures used to fight the spread of a virus. The results are applicable to the control of virus and malware spreading in computer networks as well. We examine numerically the sensitivity of the herd immunity threshold to the heterogeneity level and to the chosen countermeasures policy.

Original languageEnglish
Pages (from-to)783-795
Number of pages13
JournalJournal of Computational Biology
Issue number7
StatePublished - 1 Jul 2023


FundersFunder number
Blavatnik Family Foundation
Israel Science Foundation2482/21


    • convex optimization
    • heterogeneity
    • spreading processes


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