Perspectives on the basic reproductive ratio

By Jane Marie Heffernan, R. Smith, Lindi M. Wahl. Journal of the Royal Society Interface, 2005

1,257 citations recorded by the source corpus.

The basic reproductive ratio, R0, is defined as the expected number of secondary infections arising from a single individual during his or her entire infectious period, in a population of susceptibles. This concept is fundamental to the study of epidemiology and within-host pathogen dynamics. Most importantly, R0 often serves as a threshold parameter that predicts whether an infection will spread. Related parameters which share this threshold behaviour, however, may or may not give the true value of R0. In this paper we give a brief overview of common methods of formulating R0 and surrogate threshold parameters from deterministic, non-structured models. We also review common means of estimating R0 from epidemiological data. Finally, we survey the recent use of R0 in assessing emerging diseases, such as severe acute respiratory syndrome and avian influenza, a number of recent livestock diseases, and vector-borne diseases malaria, dengue and West Nile virus.

Subfields: Epidemiology, Modeling and Simulation, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/3032c4d6b3743e7d1d1442ff5c9d77ec0c8f5f96

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Citations in the corpus

Thermal biology of mosquito-borne disease (2019, methodology): “Reproduction numbers can be calculated using multiple methods, with differing interpretations (Heesterbeek 2002; Heffernan et al. 2005; Diekmann et al. 2009), although their direct application is limited in realistically variable environments (Baca€er & Guernaoui 2006; Baca€er & Ait Dads 2012).”
Dynamics of information diffusion and its applications on complex networks (2016, background): “Therefore, λ = 1 is a threshold value of the SIS model, which is also known as the basic reproduction number [217].”
How generation intervals shape the relationship between growth rates and reproductive numbers (2007, background): “The reproductive number has often been named as a key concept in epidemic theory (Anderson & May 1991; Roberts & Heesterbeek 2003; Heffernan et al. 2005).”
Coupled disease–behavior dynamics on complex networks: A review (2015, background): “In simple terms, R0 is the mean number of secondary infections caused by a single infectious individual, during its entire infectious period, in an otherwise susceptible population [4].”
Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees (2011, methodology): “Several methods can be used to compute R0 [40,41], possibly yielding different estimates [42] for the same epidemiological parameters.”
Networks and the Epidemiology of Infectious Disease (2010, methodology): “[151] summarise various methods for estimating R0 from epidemiological data based on endemic equilibrium, average age at infection, epidemic final size, and intrinsic growth rate [114, 152, 153].”
Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model (2010, methodology): “For the compartmentalization used here, R0 can be obtained in each subpopulation by evaluating the largest eigenvalue of the Jacobian or next generation matrix of the infection dynamics in a disease-free state [15,28], yielding”
Complexity of the Basic Reproduction Number (R0) (2019, background): “Data-driven approaches include the use of the number of susceptible persons at endemic equilibrium, average age at infection, final size equation, and intrinsic growth rate (10).”
Epidemiological modeling of invasion in heterogeneous landscapes: spread of sudden oak death in California (1990–2030) (2011, background): “This measure of local outbreak potential, an operational surrogate of the basic reproductive number (R0) (Heffernan et al. 2005), is designed to quantify the potential for spread conditioned on an isolated introduction at any location.”
Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models (2010, methodology): “[30] Heffernan JM, Smith RJ, Wahl LM: Perspectives on the basic reproductive ratio.”