Publications by authors named "Mathieu Moslonka-Lefebvre"

BackgroundMany countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity.AimWe aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours.MethodsWe conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020.

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Conventional epidemiological studies of infections spreading through trade networks, e.g., via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread.

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Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting trade that conduces the disease. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, responses in market dynamics clearly differ from simple risk aversion, as are driven by other motivation and conditioned by "friction" constraints (a term we borrow from labour economics).

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The 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.

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Human 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.

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Article Synopsis
  • The paper explores a new model (SIS(c)) for understanding disease spread in networks, especially in situations where infection status isn't just binary (sick or healthy).
  • It derives key relationships analytically, such as the epidemic threshold based on two important factors: infection persistence and transmission probability.
  • The study not only introduces an algorithm for calculating these thresholds but also suggests control strategies targeting specific market categories in the horticultural trade, with broader implications for other networks like food trade and idea dissemination.
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There is increasing use of networks in ecology and epidemiology, but still relatively little application in phytopathology. Networks are sets of elements (nodes) connected in various ways by links (edges). Network analysis aims to understand system dynamics and outcomes in relation to network characteristics.

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Post-translational modification of protein cysteine residues is emerging as an important regulatory and signaling mechanism. We have identified numerous putative targets of redox regulation in the unicellular green alga Chlamydomonas reinhardtii. One enzyme, isocitrate lyase (ICL), was identified both as a putative thioredoxin target and as an S-thiolated protein in vivo.

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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.

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