2,723 research outputs found
Particle velocity controls phase transitions in contagion dynamics
Interactions often require the proximity between particles. The movement of
particles, thus, drives the change of the neighbors which are located in their
proximity, leading to a sequence of interactions. In pathogenic contagion,
infections occur through proximal interactions, but at the same time the
movement facilitates the co-location of different strains. We analyze how the
particle velocity impacts on the phase transitions on the contagion process of
both a single infection and two cooperative infections. First, we identify an
optimal velocity (close to half of the interaction range normalized by the
recovery time) associated with the largest epidemic threshold, such that
decreasing the velocity below the optimal value leads to larger outbreaks.
Second, in the cooperative case, the system displays a continuous transition
for low velocities, which becomes discontinuous for velocities of the order of
three times the optimal velocity. Finally, we describe these characteristic
regimes and explain the mechanisms driving the dynamics.Comment: 9 pages, 5 figures, 12 supplementary figure
Coupling between COVID-19 and seasonal influenza leads to synchronization of their dynamics
Interactions between COVID-19 and other pathogens may change their dynamics.
Specifically, this may hinder the modelling of empirical data when the symptoms
of both infections are hard to distinguish. We introduce a model coupling the
dynamics of COVID-19 and seasonal influenza, simulating cooperation,
competition and asymmetric interactions. We find that the coupling synchronizes
both infections, with a strong influence on the dynamics of influenza, reducing
its time extent to a half
Digital cities and the spread of COVID-19: characterizing the impact of non-pharmaceutical interventions in five cities in Spain
Mathematical modeling has been fundamental to achieving near real-time
accurate forecasts of the spread of COVID-19. Similarly, the design of
non-pharmaceutical interventions has played a key role in the application of
policies to contain the spread. However, there is less work done regarding
quantitative approaches to characterize the impact of each intervention, which
can greatly vary depending on the culture, region, and specific circumstances
of the population under consideration. In this work, we develop a
high-resolution, data-driven agent-based model of the spread of COVID-19 among
the population in five Spanish cities. These populations synthesize multiple
data sources that summarize the main interaction environments leading to
potential contacts. We simulate the spreading of COVID-19 in these cities and
study the effect of several non-pharmaceutical interventions. We illustrate the
potential of our approach through a case study and derive the impact of the
most relevant interventions through scenarios where they are suppressed. Our
framework constitutes a first tool to simulate different intervention scenarios
for decision-making.Comment: Main text with 5 figures and 1 table, and Supplementary Materia
Risk of Coinfection Outbreaks in Temporal Networks: A Case Study of a Hospital Contact Network
We study the spreading of cooperative infections in an empirical temporal network of contacts between people, including health care workers and patients, in a hospital. The system exhibits a phase transition leading to one or several endemic branches, depending on the connectivity pattern and the temporal correlations. There are two endemic branches in the original setting and the non-cooperative case. However, the cooperative interaction between infections reinforces the upper branch, leading to a smaller epidemic threshold and a higher probability for having a big outbreak. We show the microscopic mechanisms leading to these differences, characterize three different risks, and use the influenza features as an example for this dynamics.DFG, 345463468, Interacting Dynamics on Networks, Applications to Epidemiology (idonate
Identification of suspicious behaviour through anomalies in the tracking data of fishing vessels
Automated positioning devices can generate large datasets with information on
the movement of humans, animals and objects, revealing patterns of movement,
hot spots and overlaps among others. This information is obtained after
cleaning the data from errors of different natures. However, in the case of
Automated Information Systems (AIS), attached to vessels, these errors can come
from intentional manipulation of the electronic device. Thus, the analysis of
anomalies can provide valuable information on suspicious behaviour. Here, we
analyse anomalies of fishing vessel trajectories obtained with the Automatic
Identification System. The map of silence anomalies, those occurring when
positioning data is absent for more than 24 h, shows that they occur more
likely closer to land, observing 94.9% of the anomalies at less than 100 km
from the shore. This behaviour suggests the potential of identifying silence
anomalies as a proxy for illegal activities. With the increasing availability
of high-resolution positioning of vessels and the development of powerful
statistical analytical tools, we provide hints on the automatic detection of
illegal activities that may help optimise monitoring, control and surveillance
measures
Foraging density for squirrel monkey Saimiri sciureus in two forests in Puerto Lopez - Colombia
ABSTRACT
Objective. Forest remnants were analyzed to determine the density of squirrel monkeys (Saimiri sciureus) and the degree of alteration of the forest, by selecting areas for the conservation and maintenance of the species in natural environments. Materials and methods. Linear transects were conducted on two wooden fragments, “La Reforma” and “Campo Hermoso” farms (Puerto Lopez, Meta, Colombia), recording sightings of squirrel monkeys and identifying the tree species used by the primates. Results. The fragments studied correspond to trails at the edge of water bodies with low connectivity. Highest density values were observed on the second transect of La Reforma, a possible consequence of an overcrowding phenomenon due to the high degree of isolation of the fragment. The species preferentially used as refuge and food source were: Bellucia grossularioides, Eugenia jambos, Inga alba, Mauritia flexuosa, Pseudolmedia laevis and Rollinia edulis. Conclusions. The phenology of the plant species allows for a dynamic food supply, considering the constant availability of food for the primates. Therefore, despite the evident ecological problem of these forests, it is possible to use active restoration programs to strengthen the existing dynamics and balance the biogeochemical dynamics of the ecosystem, so that socioeconomic human activities are not in conflict with conservation efforts and vice versa
Foraging density for squirrel monkey Saimiri sciureus in two forests in Puerto Lopez - Colombia
ABSTRACTObjective. Forest remnants were analyzed to determine the density of squirrel monkeys (Saimiri sciureus) and the degree of alteration of the forest, by selecting areas for the conservation and maintenance of the species in natural environments. Materials and methods. Linear transects were conducted on two wooden fragments, “La Reforma” and “Campo Hermoso” farms (Puerto Lopez, Meta, Colombia), recording sightings of squirrel monkeys and identifying the tree species used by the primates. Results. The fragments studied correspond to trails at the edge of water bodies with low connectivity. Highest density values were observed on the second transect of La Reforma, a possible consequence of an overcrowding phenomenon due to the high degree of isolation of the fragment. The species preferentially used as refuge and food source were: Bellucia grossularioides, Eugenia jambos, Inga alba, Mauritia flexuosa, Pseudolmedia laevis and Rollinia edulis. Conclusions. The phenology of the plant species allows for a dynamic food supply, considering the constant availability of food for the primates. Therefore, despite the evident ecological problem of these forests, it is possible to use active restoration programs to strengthen the existing dynamics and balance the biogeochemical dynamics of the ecosystem, so that socioeconomic human activities are not in conflict with conservation efforts and vice versa
Big data analyses reveal patterns and drivers of the movements of southern elephant seals
The growing number of large databases of animal tracking provides an
opportunity for analyses of movement patterns at the scales of populations and
even species. We used analytical approaches, developed to cope with big data,
that require no a priori assumptions about the behaviour of the target agents,
to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina)
in the Southern Ocean, that was comprised of >500,000 location estimates
collected over more than a decade. Our analyses showed that the displacements
of these seals were described by a truncated power law distribution across
several spatial and temporal scales, with a clear signature of directed
movement. This pattern was evident when analysing the aggregated tracks despite
a wide diversity of individual trajectories. We also identified marine
provinces that described the migratory and foraging habitats of these seals.
Our analysis provides evidence for the presence of intrinsic drivers of
movement, such as memory, that cannot be detected using common models of
movement behaviour. These results highlight the potential for big data
techniques to provide new insights into movement behaviour when applied to
large datasets of animal tracking.Comment: 18 pages, 5 figures, 6 supplementary figure
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