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J A P Heesterbeek - One of the best experts on this subject based on the ideXlab platform.

  • Characterizing the next-Generation Matrix and basic reproduction number in ecological epidemiology.
    Journal of mathematical biology, 2012
    Co-Authors: M G Roberts, J A P Heesterbeek
    Abstract:

    We address the interaction of ecological processes, such as consumer-resource relationships and competition, and the epidemiology of infectious diseases spreading in ecosystems. Modelling such interactions seems essential to understand the dynamics of infectious agents in communities consisting of interacting host and non-host species. We show how the usual epidemiological next-Generation Matrix approach to characterize invasion into multi-host communities can be extended to calculate R₀, and how this relates to the ecological community Matrix. We then present two simple examples to illustrate this approach. The first of these is a model of the rinderpest, wildebeest, grass interaction, where our inferred dynamics qualitatively matches the observed phenomena that occurred after the eradication of rinderpest from the Serengeti ecosystem in the 1980s. The second example is a prey-predator system, where both species are hosts of the same pathogen. It is shown that regions for the parameter values exist where the two host species are only able to coexist when the pathogen is present to mediate the ecological interaction.

  • The construction of next-Generation matrices for compartmental epidemic models.
    Journal of the Royal Society Interface, 2009
    Co-Authors: Odo Diekmann, J A P Heesterbeek, Mick G. Roberts
    Abstract:

    The basic reproduction number ℛ0 is arguably the most important quantity in infectious disease epidemiology. The next-Generation Matrix (NGM) is the natural basis for the definition and calculation...

  • the basic reproduction number for complex disease systems defining r0 for tick borne infections
    The American Naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

  • The Basic Reproduction Number for Complex Disease Systems: Defining R0 for Tick‐Borne Infections
    The American naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

Nienke Hartemink - One of the best experts on this subject based on the ideXlab platform.

  • the basic reproduction number for complex disease systems defining r0 for tick borne infections
    The American Naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

  • The Basic Reproduction Number for Complex Disease Systems: Defining R0 for Tick‐Borne Infections
    The American naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

Irit Sagi - One of the best experts on this subject based on the ideXlab platform.

  • Next Generation Matrix metalloproteinase inhibitors - Novel strategies bring new prospects.
    Biochimica et biophysica acta. Molecular cell research, 2017
    Co-Authors: Maxim Levin, Yael Udi, Inna Solomonov, Irit Sagi
    Abstract:

    Enzymatic proteolysis of cell surface proteins and extracellular Matrix (ECM) is critical for tissue homeostasis and cell signaling. These proteolytic activities are mediated predominantly by a family of proteases termed Matrix metalloproteinases (MMPs). The growing evidence in recent years that ECM and non-ECM bioactive molecules (e.g., growth factors, cytokines, chemokines, on top of matrikines and matricryptins) have versatile functions redefines our view on the roles Matrix remodeling enzymes play in many physiological and pathological processes, and underscores the notion that ECM proteolytic reaction mechanisms represent master switches in the regulation of critical biological processes and govern cell behavior. Accordingly, MMPs are not only responsible for direct degradation of ECM molecules but are also key modulators of cardinal bioactive factors. Many attempts were made to manipulate ECM degradation by targeting MMPs using small peptidic and organic inhibitors. However, due to the high structural homology shared by these enzymes, the majority of the developed compounds are broad-spectrum inhibitors affecting the proteolytic activity of various MMPs and other zinc-related proteases. These inhibitors, in many cases, failed as therapeutic agents, mainly due to the bilateral role of MMPs in pathological conditions such as cancer, in which MMPs have both pro- and anti-tumorigenic effects. Despite the important role of MMPs in many human diseases, none of the broad-range synthetic MMP inhibitors that were designed have successfully passed clinical trials. It appears that, designing highly selective MMP inhibitors that are also effective in vivo, is not trivial. The challenges related to designing selective and effective metalloprotease inhibitors, are associated in part with the aforesaid high structural homology and the dynamic nature of their protein scaffolds. Great progress was achieved in the last decade in understanding the biochemistry and biology of MMPs activity. This knowledge, combined with lessons from the past has drawn new "boundaries" for the development of the next-Generation MMP inhibitors. These novel agents are currently designed to be highly specific, capable to discriminate between the homologous MMPs and ideally administered as a short-term topical treatment. In this review we discuss the latest progress in the fields of MMP inhibitors in terms of structure, function and their specific activity. The development of novel highly specific inhibitors targeting MMPs paves the path to study complex biological processes associated with ECM proteolysis in health and disease. This article is part of a Special Issue entitled: Matrix Metalloproteinases edited by Rafael Fridman.

  • Next Generation Matrix Metalloproteinase Inhibitors – Novel Strategies Bring New Prospects
    Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 2017
    Co-Authors: Maxim Levin, Yael Udi, Inna Solomonov, Irit Sagi
    Abstract:

    Enzymatic proteolysis of cell surface proteins and extracellular Matrix (ECM) is critical for tissue homeostasis and cell signaling. These proteolytic activities are mediated predominantly by a family of proteases termed Matrix metalloproteinases (MMPs). The growing evidence in recent years that ECM and non-ECM bioactive molecules (e.g., growth factors, cytokines, chemokines, on top of matrikines and matricryptins) have versatile functions redefines our view on the roles Matrix remodeling enzymes play in many physiological and pathological processes, and underscores the notion that ECM proteolytic reaction mechanisms represent master switches in the regulation of critical biological processes and govern cell behavior. Accordingly, MMPs are not only responsible for direct degradation of ECM molecules but are also key modulators of cardinal bioactive factors. Many attempts were made to manipulate ECM degradation by targeting MMPs using small peptidic and organic inhibitors. However, due to the high structural homology shared by these enzymes, the majority of the developed compounds are broad-spectrum inhibitors affecting the proteolytic activity of various MMPs and other zinc-related proteases. These inhibitors, in many cases, failed as therapeutic agents, mainly due to the bilateral role of MMPs in pathological conditions such as cancer, in which MMPs have both pro- and anti-tumorigenic effects. Despite the important role of MMPs in many human diseases, none of the broad-range synthetic MMP inhibitors that were designed have successfully passed clinical trials. It appears that, designing highly selective MMP inhibitors that are also effective in vivo, is not trivial. The challenges related to designing selective and effective metalloprotease inhibitors, are associated in part with the aforesaid high structural homology and the dynamic nature of their protein scaffolds. Great progress was achieved in the last decade in understanding the biochemistry and biology of MMPs activity. This knowledge, combined with lessons from the past has drawn new "boundaries" for the development of the next-Generation MMP inhibitors. These novel agents are currently designed to be highly specific, capable to discriminate between the homologous MMPs and ideally administered as a short-term topical treatment. In this review we discuss the latest progress in the fields of MMP inhibitors in terms of structure, function and their specific activity. The development of novel highly specific inhibitors targeting MMPs paves the path to study complex biological processes associated with ECM proteolysis in health and disease. This article is part of a Special Issue entitled: Matrix Metalloproteinases edited by Rafael Fridman.

Stephen Davis - One of the best experts on this subject based on the ideXlab platform.

  • the basic reproduction number for complex disease systems defining r0 for tick borne infections
    The American Naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

  • The Basic Reproduction Number for Complex Disease Systems: Defining R0 for Tick‐Borne Infections
    The American naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

Sarah E Randolph - One of the best experts on this subject based on the ideXlab platform.

  • the basic reproduction number for complex disease systems defining r0 for tick borne infections
    The American Naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support

  • The Basic Reproduction Number for Complex Disease Systems: Defining R0 for Tick‐Borne Infections
    The American naturalist, 2008
    Co-Authors: Nienke Hartemink, Sarah E Randolph, Stephen Davis, J A P Heesterbeek
    Abstract:

    Characterizing the basic reproduction number, , for R 0 many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemio- logical reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne dis- eases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host popu- lation into epidemiologically different types of individuals and constructing a Matrix of reproduction numbers, the so-called next- Generation Matrix. Each Matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the Matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the in- fection cannot establish. The biological interpretation closely matches that of for disease systems with only one type of individual and R 0 where infection is directly transmitted. The parameters defining each Matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-Generation Matrix for Lyme disease and tick- borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct com- parison of the two etiological agents. This provides further support