Metaecoepidemic models generalize metapopulation systems, combining local population dynamics with inter-patch migration coupled with an epidemic proliferation. A resource-consumer model is introduced with an ecosystem composed by two patches, in which consumers can freely move. A disease affects resources of the second patch. This situation corresponds to a grassland-herbivore environment, where one patch, managed in an extensive way, has a wider plant diversity, while the other one is highly fertilized leading to an important forage production. The latter is also subject to a fungal disease. Herbivores both feed on healthy or infected crop and can freely migrate between the two patches. A preliminary investigation focuses on behaviors emerging from some parts of the model, respectively, formed by uncoupled patches and by the purely demographic coupled model. Equilibria of the whole system are assessed and characterized. Results are then compared with the purely demographic model to highlight the role of the disease in this dynamics. A thorough numerical investigation of the model completes this analysis to assess the system behavior near each equilibrium. System bifurcations have also been explored as well as the response of the system equilibria to parameter perturbations. The disease eradication is possible under suitable circumstances. Coexistence of the five populations through persistent oscillations is also possible, but it is not at a stable level.
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http://dx.doi.org/10.1007/s11538-020-00764-5 | DOI Listing |
J Neurol
January 2025
Neuromuscular Diseases Unit, Neurology Department, Hospital Universitari I Politècnic La Fe, Neuromuscular Reference Centre, ERN-EURO-NMD, Avenida de Fernando Abril Martorell 106, 46026, Valencia, Spain.
Background: Distal myopathies (MPDs) are heterogeneous diseases of complex diagnosis whose prevalence and distribution in specific populations are unknown.
Methods: Demographic, clinical, genetic, neurophysiological, histopathological and muscle imaging characteristics of a MPDs cohort from a neuromuscular reference center were analyzed to study their epidemiology, features, genetic distribution and factors related to diagnosis.
Results: The series included 219 patients (61% were men, 94% Spanish and 41% sporadic cases).
Diagn Progn Res
January 2025
Department of Clinical Medicine, Hammel Neurorehabilitation Centre-University Research Clinic, Aarhus University, Voldbyvej 15, 8450, Hammel, Denmark.
Background: The initial theme of the PROGRESS framework for prognosis research is termed overall prognosis research. Its aim is to describe the most likely course of health conditions in the context of current care. These average group-level prognoses may be used to inform patients, health policies, trial designs, or further prognosis research.
View Article and Find Full Text PDFBMC Geriatr
January 2025
University of Southampton, Southampton, UK.
Background: To our knowledge capture-recapture techniques have not been used to estimate dementia prevalence using routinely collected data in England, nor have they been used to estimate changes in undiagnosed dementia over time. In this study we aimed to use routinely collected electronic health records to estimate the number of undiagnosed dementia cases there are in England and how this has changed over time. We also aimed to assess whether proportion of undiagnosed cases differed by age group, ethnicity, socioeconomic deprivation and sex.
View Article and Find Full Text PDFBMC Infect Dis
December 2024
Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Background: Worldwide, tuberculosis (TB) is among the most common causes of death. To our knowledge, there has been no study showing the prevalence of EPTB in Khuzestan province. Therefore, the objective of this research was to investigate the prevalence of EPTB in patients with or without pulmonary TB in different cities of Khuzestan province from 2002 to 2023.
View Article and Find Full Text PDFFront Artif Intell
December 2024
Robert Bosch Center for Data Science and Artificial Intelligence, Indian Institute of Technology Madras, Chennai, India.
We study a contextual bandit setting where the agent has access to causal side information, in addition to the ability to perform multiple targeted experiments corresponding to potentially different context-action pairs-simultaneously in one-shot within a budget. This new formalism provides a natural model for several real-world scenarios where parallel targeted experiments can be conducted and where some domain knowledge of causal relationships is available. We propose a new algorithm that utilizes a novel entropy-like measure that we introduce.
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