TY - JOUR
T1 - On the Convexity of the Effective Reproduction Number
AU - Tavori, Jhonatan
AU - Levy, Hanoch
N1 - Publisher Copyright:
© Copyright 2023, Mary Ann Liebert, Inc., publishers 2023.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - convex optimization
KW - heterogeneity
KW - spreading processes
UR - http://www.scopus.com/inward/record.url?scp=85162161523&partnerID=8YFLogxK
U2 - 10.1089/cmb.2022.0371
DO - 10.1089/cmb.2022.0371
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C2 - 37130305
AN - SCOPUS:85162161523
SN - 1066-5277
VL - 30
SP - 783
EP - 795
JO - Journal of Computational Biology
JF - Journal of Computational Biology
IS - 7
ER -