Elasticity analysis in epidemiology: an application to tick-borne infections

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Amy Matser, Nienke Hartemink, Hans Heesterbeek, Alison Galvani and Stephen Davis

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Ecology Letters, (2009) 12: 1298–1305 doi: 10.1111/j.1461-0248.2009.01378.x



Data description: 

Next Generation Matrices (NGMs) for seven tick-borne zoonoses


Anaplasma phagocytophila, Borrelia burgdorferi, Crimean-Congo haemorrhagic fever virus, elasticities, Kyasanur forest disease virus, next-generation matrix, Rickettsia rickettsii, Thogoto virus, tick-borne encephalitis virus


The application of projection matrices in population biology to plant and animal populations has a parallel in infectious disease ecology when next-generation matrices (NGMs) are used to characterize growth in numbers of infected hosts (R0). The NGM is appropriate for multi-host pathogens, where each matrix element represents the number of cases of one type of host arising from a single infected individual of another type. For projection matrices, calculations of the sensitivity and elasticity of the population growth rate to changes in the matrix elements has generated insight into plant and animal populations. These same perturbation analyses can be used for infectious disease systems. To illustrate this in detail we parameterized an NGM for seven tick-borne zoonoses and compared them in terms of the contributions to R0 from three different routes of transmission between ticks, and between ticks and vertebrate hosts. The definition of host type may be the species of the host or the route of infection, or, as was the case for the set of tick-borne pathogens, a combination of species and the life stage at infection. This freedom means that there is a broad range of disease systems and questions for which the methodology is appropriate.