Infectious diseases of humans: Dynamics and control

By P. Kaye. 1993

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Citations in the corpus

Network theory and SARS: predicting outbreak diversity (2004, background): “It is relatively straightforward to derive based on routinely collected epidemiologic data and can be predictive in homogeneous settings; it also has historically informed effective vaccination strategies (Anderson and May, 1991; Hethcote, 2000).”
Habitat fragmentation and species richness (2015, background): “The landscape-level extinction threshold has enormous practical importance for conservation and habitat restoration, as much as the analogous concept of eradication threshold in epidemiology (Anderson & May, 1991), which explains why vaccination works although not every individual can be vaccinated.”
Seasonality and the dynamics of infectious diseases. (2006, background): “2006 Blackwell Publishing Ltd/CNRS pathogens such as measles virus, the value of R0 depends on the product of the transmission coefficient (b) and the duration of the infectious period (Anderson & May 1991).”
Viral Phylodynamics (2013, background): “The two may be linked by the following equation [27]:”
Body size, diet and sociality influence the species richness of parasitic worms in anthropoid primates (2004, background): “Social interactions generate a network of contacts through which many parasites spread within populations (Anderson and May, 1979, 1991), and host behavioural contacts should have overriding importance for parasite community diversity (Morand, 2000; Altizer et al., 2003b).”
Graph theory and networks in Biology. (2006, background): “However, while this strategy can work for homogeneous populations, it is known to be ineffective in the heterogeneous case [234].”
The role of infectious diseases in biological conservation (2009, background): “Mathematical models and epidemiological theory have been increasingly used to understand the population impact of infectious diseases (Anderson & May, 1992).”
The Allee effect, stochastic dynamics and the eradication of alien species (2003, background): “…rate, critical fraction of hosts vaccinated, or habitat loss thresholds) have been widely explored as part of efforts to devise more effective approaches to prevent species extinctions and in efforts to eradicate pathogens (Lande 1987; Anderson & May 1991; Bascompte & RodriguezTrelles 1998).”
Multi-compartment models (2007, background): “Models with variation in infectiousness have been considered since a long time in the literature [28, 1, 26, 42, 43].”
Limiting the spread of misinformation in social networks (2011, background): “tial people in a social network [28] uses SIS (susceptible-infectedsusceptible), SIR (susceptible-infected-recovered) models [2, 11, 21] and concludes that the influence of a node is more dependent on its location in the network than the number of connections it has.”
Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees (2011, background): “The starting point of most modeling approaches is the assumption of homogeneous mixing, which assumes that every individual has an equal probability of contacting other individuals in the population [1].”
Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium (2009, unknown): “Such assumptions, in combination with the age-specific cumulative incidence of infection (for instance based on seroprevalence data [14]), enable estimating the so-called "Who Acquires Infection From Whom" (WAIFW) matrix [1].”
Perspectives on the basic reproductive ratio (2005, methodology): “A derivation for this simple relation is also provided by Mollison (1995a) and Hethcote (2000); for further discussion, see Anderson & May (1991) and Brauer (2002).”