Abstract
The basic reproduction number R 0—the number of individuals directly infected by an infectious person in an otherwise susceptible population—is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R 0 and Ω. However, if one considers disease spreading on a temporal contact network—where one knows when contacts happen, not only between whom—then larger R 0 does not necessarily imply larger Ω. In this paper, we numerically investigate the relationship between R 0 and Ω for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R 0 an imperfect predictor of Ω. We find that descriptors related to both temporal and topological aspects affect the relationship between R 0 and Ω, but in different ways.
Highlights
The interaction between medical and theoretical epidemiology of infectious diseases is probably not as strong as it should
We have shown that temporal network structure of human contacts can change the interpretation of the basic reproduction number R0
It is hard to give a succinct explanation for this phenomenon, and we do not attempt that in the present paper
Summary
The interaction between medical and theoretical epidemiology of infectious diseases is probably not as strong as it should. Perhaps the most important are the ideas of epidemic thresholds and the parameter R0—the basic reproduction number—as a key predictor of the epidemiological severity of a disease [1,2]. R0 is defined as the expected number of other individuals that an infected individual will infect if he or she enters a population entirely composed of susceptible individuals. It is a combined property of the process of contagion and the contact patterns of the population. In classic mathematical models of infectious disease spreading, R0 = 1 marks an epidemic threshold. In the limit of large populations, a finite
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