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Modéliser les dynamiques épidémiques dans des réseaux d'échanges avec interactions contraintes et comportements adaptatifs.
No full textExchanges among agents, typically individuals or companies, fulfil various needs such as reproduction and economic profit, but can also support infectious disease transmission, impacting biological populations and potentially altering the disease-conducive exchanges. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, behavioural responses in exchange dynamics are not limited to risk-aversion; they are driven by different motivation and are constrained because resources are limited and exchanges are costly. Adaptive behaviour refers to change in agent behaviour, and potentially in exposure to risk, in response to disruption such as disease outbreak; the change may be through adaptation of social or economic mechanisms. Interaction constraints limit in different ways the capacity of agents to interact. They can limit the interaction of a given agent with everybody else (sparseness constraint), the rate and direction of exchanges (weighting and directional constraints), or the rate of encounter between agents (frictional constraint). While the sparseness constraint has been exhaustively studied, the epidemiological consequences of the three other constraints are poorly understood. Here, we use a combination of empirical analyses and mathematical modelling approaches to explore the influence of interaction constraints and adaptive behaviour on the combined dynamics of exchanges and infection. We can hence suggest relevant policies to prevent and mitigate exchange-driven epidemics. The examples investigated are sexually transmitted infection dynamics in sexual-contact networks, and epidemics in markets of animal livestock or ornamental plants. First, we show that differing patterns in agent contact structures and in epidemic dynamics arise when the networks are subject to combinations of interaction constraints. We identify analytical conditions when weighting and directional constraints limit the occurrence and severity of epidemic outbreaks, and translate these threshold conditions into disease-control strategies. These results hold in the case when agents are passive. Second, we account for adaptive behaviour encountered in markets that propagate infections and propose that the joint dynamics of markets and disease spread are limited by trade friction. This specific constraint creates a trade-off between the frequency and intensity of market transactions that can influence epidemics more strongly than risk-aversion. We finally suggest policy for limiting disease contagion in markets and minimise its adverse impact on trade. Our work demonstrates that the integration of differing standpoints at the crossroad of natural and social sciences is important in tackling the challenges posed by the emergence of exchange-driven epidemics. We believe our general approach can be transposed to other systems where agents exhibit adaptive behaviour and face interaction constraints, e.g. in ecology or in economics.Les échanges entre agents tels que les individus ou les entreprises couvrent de nombreux besoins tels que la reproduction et la recherche de profits, mais peuvent dans le même temps faciliter la transmission des maladies infectieuses. En conséquence, les épidémies sont susceptibles de causer des dommages au sein des populations biologiques et d’altérer ces mêmes échanges qui véhiculent les infections. Les modèles épidémiologiques intègrent de plus en plus les comportements d’aversion au risque en réaction aux épidémies. Ces comportements induisent une réduction des contacts infectieux entre agents. Toutefois, les comportements qui sous-tendent les échanges ne se réduisent pas à l’aversion au risque. Les échanges sont conditionnés par des motivations différentes et sont contraints en raison de leurs coûts et du caractère limité des ressources. Face à une émergence épidémique, les comportements adaptatifs se traduisent par des ajustements dans les actions des agents qui peuvent augmenter ou réduire leur exposition au risque d’infection. De multiples mécanismes adaptatifs liés à des processus sociaux et économiques contribuent à expliquer ces ajustements. Les contraintes d’interaction limitent la capacité des agents à échanger de diverses manières. Elles peuvent réduire la capacité d’un agent à interagir avec ses alter ego (contrainte de creux), le taux d’échange (contrainte de pondération), la direction des échanges (contrainte de direction) ou la fréquence de rencontre entre agents (contrainte de friction). Si la contrainte de creux a été largement étudiée, les implications épidémiologiques des trois autres contraintes restent mal comprises. Dans cette recherche, nous combinons analyses empiriques et explorations de modèles mathématiques pour étudier l’influence des contraintes d’interaction et des comportements adaptatifs sur la dynamique conjointe des échanges et de l’infection. Nous pouvons ainsi proposer des politiques de prévention et de maîtrise des épidémies véhiculées par les échanges. Nos études de cas incluent la dynamique des infections sexuellement transmissibles dans des réseaux de contacts sexuels et les épidémies propagées dans des marchés d’échanges d’animaux ou de plantes. Dans un premier temps, nous montrons que la superposition de contraintes d’interaction engendre une grande diversité de structures d’échanges et de dynamiques épidémiques. Nous identifions des conditions analytiques pour lesquelles les contraintes de pondération et de direction limitent la probabilité d’émergence et la sévérité des maladies infectieuses, et traduisons ces conditions théoriques en matière de politiques de santé. Ces résultats sont obtenus en supposant que les agents sont passifs. Dans un second temps, nous prenons également en considération les comportements adaptatifs rencontrés dans les marchés qui véhiculent des infections, et suggérons que la dynamique conjointe de l’infection et des échanges est limitée par la friction marchande. La contrainte de friction engendre un compromis entre fréquence et intensité des transactions commerciales, et peut amoindrir les épidémies de manière plus importante que l’aversion au risque. Nous évoquons finalement des mesures pratiques pour limiter la transmission des maladies infectieuses dans les marchés tout en minimisant les effets délétères sur le commerce. Notre thèse démontre l’importance d’adopter des approches interdisciplinaires pour relever les défis des émergences épidémiques imputables aux échanges. Les idées et outils développés peuvent être transposés à d’autres systèmes, par exemple en écologie ou en économie
Modéliser les dynamiques épidémiques dans des réseaux d'échanges avec interactions contraintes et comportements adaptatifs.
No full textExchanges among agents, typically individuals or companies, fulfil various needs such as reproduction and economic profit, but can also support infectious disease transmission, impacting biological populations and potentially altering the disease-conducive exchanges. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, behavioural responses in exchange dynamics are not limited to risk-aversion; they are driven by different motivation and are constrained because resources are limited and exchanges are costly. Adaptive behaviour refers to change in agent behaviour, and potentially in exposure to risk, in response to disruption such as disease outbreak; the change may be through adaptation of social or economic mechanisms. Interaction constraints limit in different ways the capacity of agents to interact. They can limit the interaction of a given agent with everybody else (sparseness constraint), the rate and direction of exchanges (weighting and directional constraints), or the rate of encounter between agents (frictional constraint). While the sparseness constraint has been exhaustively studied, the epidemiological consequences of the three other constraints are poorly understood. Here, we use a combination of empirical analyses and mathematical modelling approaches to explore the influence of interaction constraints and adaptive behaviour on the combined dynamics of exchanges and infection. We can hence suggest relevant policies to prevent and mitigate exchange-driven epidemics. The examples investigated are sexually transmitted infection dynamics in sexual-contact networks, and epidemics in markets of animal livestock or ornamental plants. First, we show that differing patterns in agent contact structures and in epidemic dynamics arise when the networks are subject to combinations of interaction constraints. We identify analytical conditions when weighting and directional constraints limit the occurrence and severity of epidemic outbreaks, and translate these threshold conditions into disease-control strategies. These results hold in the case when agents are passive. Second, we account for adaptive behaviour encountered in markets that propagate infections and propose that the joint dynamics of markets and disease spread are limited by trade friction. This specific constraint creates a trade-off between the frequency and intensity of market transactions that can influence epidemics more strongly than risk-aversion. We finally suggest policy for limiting disease contagion in markets and minimise its adverse impact on trade. Our work demonstrates that the integration of differing standpoints at the crossroad of natural and social sciences is important in tackling the challenges posed by the emergence of exchange-driven epidemics. We believe our general approach can be transposed to other systems where agents exhibit adaptive behaviour and face interaction constraints, e.g. in ecology or in economics.Les échanges entre agents tels que les individus ou les entreprises couvrent de nombreux besoins tels que la reproduction et la recherche de profits, mais peuvent dans le même temps faciliter la transmission des maladies infectieuses. En conséquence, les épidémies sont susceptibles de causer des dommages au sein des populations biologiques et d’altérer ces mêmes échanges qui véhiculent les infections. Les modèles épidémiologiques intègrent de plus en plus les comportements d’aversion au risque en réaction aux épidémies. Ces comportements induisent une réduction des contacts infectieux entre agents. Toutefois, les comportements qui sous-tendent les échanges ne se réduisent pas à l’aversion au risque. Les échanges sont conditionnés par des motivations différentes et sont contraints en raison de leurs coûts et du caractère limité des ressources. Face à une émergence épidémique, les comportements adaptatifs se traduisent par des ajustements dans les actions des agents qui peuvent augmenter ou réduire leur exposition au risque d’infection. De multiples mécanismes adaptatifs liés à des processus sociaux et économiques contribuent à expliquer ces ajustements. Les contraintes d’interaction limitent la capacité des agents à échanger de diverses manières. Elles peuvent réduire la capacité d’un agent à interagir avec ses alter ego (contrainte de creux), le taux d’échange (contrainte de pondération), la direction des échanges (contrainte de direction) ou la fréquence de rencontre entre agents (contrainte de friction). Si la contrainte de creux a été largement étudiée, les implications épidémiologiques des trois autres contraintes restent mal comprises. Dans cette recherche, nous combinons analyses empiriques et explorations de modèles mathématiques pour étudier l’influence des contraintes d’interaction et des comportements adaptatifs sur la dynamique conjointe des échanges et de l’infection. Nous pouvons ainsi proposer des politiques de prévention et de maîtrise des épidémies véhiculées par les échanges. Nos études de cas incluent la dynamique des infections sexuellement transmissibles dans des réseaux de contacts sexuels et les épidémies propagées dans des marchés d’échanges d’animaux ou de plantes. Dans un premier temps, nous montrons que la superposition de contraintes d’interaction engendre une grande diversité de structures d’échanges et de dynamiques épidémiques. Nous identifions des conditions analytiques pour lesquelles les contraintes de pondération et de direction limitent la probabilité d’émergence et la sévérité des maladies infectieuses, et traduisons ces conditions théoriques en matière de politiques de santé. Ces résultats sont obtenus en supposant que les agents sont passifs. Dans un second temps, nous prenons également en considération les comportements adaptatifs rencontrés dans les marchés qui véhiculent des infections, et suggérons que la dynamique conjointe de l’infection et des échanges est limitée par la friction marchande. La contrainte de friction engendre un compromis entre fréquence et intensité des transactions commerciales, et peut amoindrir les épidémies de manière plus importante que l’aversion au risque. Nous évoquons finalement des mesures pratiques pour limiter la transmission des maladies infectieuses dans les marchés tout en minimisant les effets délétères sur le commerce. Notre thèse démontre l’importance d’adopter des approches interdisciplinaires pour relever les défis des émergences épidémiques imputables aux échanges. Les idées et outils développés peuvent être transposés à d’autres systèmes, par exemple en écologie ou en économie
Epidemic spread on weighted networks.
No full textThe contact structure between hosts shapes disease spread. Most network-based models used in epidemiology tend to ignore heterogeneity in the weighting of contacts between two individuals. However, this assumption is known to be at odds with the data for many networks (e.g. sexual contact networks) and to have a critical influence on epidemics' behavior. One of the reasons why models usually ignore heterogeneity in transmission is that we currently lack tools to analyze weighted networks, such that most studies rely on numerical simulations. Here, we present a novel framework to estimate key epidemiological variables, such as the rate of early epidemic expansion (r0) and the basic reproductive ratio (R0), from joint probability distributions of number of partners (contacts) and number of interaction events through which contacts are weighted. These distributions are much easier to infer than the exact shape of the network, which makes the approach widely applicable. The framework also allows for a derivation of the full time course of epidemic prevalence and contact behaviour, which we validate with numerical simulations on networks. Overall, incorporating more realistic contact networks into epidemiological models can improve our understanding of the emergence and spread of infectious diseases
Weighting for sex acts to understand the spread of STI on networks
No full textposter + abstract 3 pagesInternational audienceHuman sexual networks exhibit a heterogeneous structure where few individuals have many partners and many individuals have few partners. Network theory predicts that the spread of sexually transmitted infections (STI) on such networks should exhibit striking properties (e.g. rapid spread). However, these properties cannot be found in epidemiological data. Current network models typically assume a constant STI transmission risk per partnership, which is unrealistic because it implies that sexual activity is proportional to the number of partners and that individuals have the same activity with each partner. We develop a framework that allows us to weight any sexual network based on biological assumptions. Our results indicate that STI spreading on the resulting weighted networks do not have heterogeneous-related properties, which is consistent with data and earlier studies
Weighting for sex acts to understand the spread of STI on networks.
No full textHuman sexual networks exhibit a heterogeneous structure where few individuals have many partners and many individuals have few partners. Network theory predicts that the spread of sexually transmitted infections (STI) on such networks should exhibit striking properties (e.g. rapid spread). However, these properties cannot be found in epidemiological data. Current network models typically assume a constant STI transmission risk per partnership, which is unrealistic because it implies that sexual activity is proportional to the number of partners and that individuals have the same activity with each partner. We develop a framework that allows us to weight any sexual network based on biological assumptions. Our results indicate that STI spreading on the resulting weighted networks do not have heterogeneous-related properties, which is consistent with data and earlier studies
Weighting for sex acts to understand the spread of STI on networks
No full textInternational audienceHuman sexual networks exhibit a heterogeneous structure where few individuals have many partners and many individuals have few partners. Network theory predicts that the spread of sexually transmitted infections (STI) on such networks should exhibit striking properties (e.g. rapid spread). However, these properties cannot be found in epidemiological data. Current network models typically assume a constant STI transmission risk per partnership, which is unrealistic because it implies that sexual activity is proportional to the number of partners and that individuals have the same activity with each partner. We develop a framework that allows us to weight any sexual network based on biological assumptions. Our results indicate that STI spreading on the resulting weighted networks do not have heterogeneous-related properties, which is consistent with data and earlier studies
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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