Network epidemiology and plant trade networks.

Models of epidemics in complex networks are improving our predictive understanding of infectious disease outbreaks. Nonetheless, applying network theory to plant pathology is still a challenge. This overview summarizes some key developments in network epidemiology that are likely to facilitate its application in the study and management of plant diseases.

SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.

Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.

Plant health and global change--some implications for landscape management.

Global change (climate change together with other worldwide anthropogenic processes such as increasing trade, air pollution and urbanization) will affect plant health at the genetic, individual, population and landscape level. Direct effects include ecosystem stress due to natural resources shortage or imbalance. Indirect effects include (i) an increased frequency of natural detrimental phenomena, (ii) an increased pressure due to already present pests and diseases, (iii) the introduction of new invasive species either as a result of an improved suitability of the climatic conditions or as a result of increased trade, and (iv) the human response to global change.

Disease spread in small-size directed networks: epidemic threshold, correlation between links to and from nodes, and clustering.

Network epidemiology has mainly focused on large-scale complex networks. It is unclear whether findings of these investigations also apply to networks of small size. This knowledge gap is of relevance for many biological applications, including meta-communities, plant-pollinator interactions and the spread of the oomycete pathogen Phytophthora ramorum in networks of plant nurseries.

Modelling disease spread and control in networks: implications for plant sciences.

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.