Non-systemic transmission of tick-borne diseases: a network approach

Tick-Borne diseases can be transmitted via non-systemic (NS) transmission. This occurs when tick gets the infection by co-feeding with infected ticks on the same host resulting in a direct pathogen transmission between the vectors, without infecting the host. This transmission is peculiar, as it does not require any systemic infection of the host. The NS transmission is the main efficient transmission for the persistence of the Tick-Borne Encephalitis virus in nature. By describing the heterogeneous ticks aggregation on hosts through a \hyphenation{dynamical} bipartite graphs representation, we are able to mathematically define the NS transmission and to depict the epidemiological conditions for the pathogen persistence. Despite the fact that the underlying network is largely fragmented, analytical and computational results show that the larger is the variability of the aggregation, and the easier is for the pathogen to persist in the population.Comment: 15 pages, 4 figures, to be published in Communications in Nonlinear Science and Numerical Simulatio

Firsthand Opiates Abuse on Social Media: Monitoring Geospatial Patterns of Interest Through a Digital Cohort

In the last decade drug overdose deaths reached staggering proportions in the US. Besides the raw yearly deaths count that is worrisome per se, an alarming picture comes from the steep acceleration of such rate that increased by 21% from 2015 to 2016. While traditional public health surveillance suffers from its own biases and limitations, digital epidemiology offers a new lens to extract signals from Web and Social Media that might be complementary to official statistics. In this paper we present a computational approach to identify a digital cohort that might provide an updated and complementary view on the opioid crisis. We introduce an information retrieval algorithm suitable to identify relevant subspaces of discussion on social media, for mining data from users showing explicit interest in discussions about opioid consumption in Reddit. Moreover, despite the pseudonymous nature of the user base, almost 1.5 million users were geolocated at the US state level, resembling the census population distribution with a good agreement. A measure of prevalence of interest in opiate consumption has been estimated at the state level, producing a novel indicator with information that is not entirely encoded in the standard surveillance. Finally, we further provide a domain specific vocabulary containing informal lexicon and street nomenclature extracted by user-generated content that can be used by researchers and practitioners to implement novel digital public health surveillance methodologies for supporting policy makers in fighting the opioid epidemic.Comment: Proceedings of the 2019 World Wide Web Conference (WWW '19

Optimizing surveillance for livestock disease spreading through animal movements

The spatial propagation of many livestock infectious diseases critically depends on the animal movements among premises; so the knowledge of movement data may help us to detect, manage and control an outbreak. The identification of robust spreading features of the system is however hampered by the temporal dimension characterizing population interactions through movements. Traditional centrality measures do not provide relevant information as results strongly fluctuate in time and outbreak properties heavily depend on geotemporal initial conditions. By focusing on the case study of cattle displacements in Italy, we aim at characterizing livestock epidemics in terms of robust features useful for planning and control, to deal with temporal fluctuations, sensitivity to initial conditions and missing information during an outbreak. Through spatial disease simulations, we detect spreading paths that are stable across different initial conditions, allowing the clustering of the seeds and reducing the epidemic variability. Paths also allow us to identify premises, called sentinels, having a large probability of being infected and providing critical information on the outbreak origin, as encoded in the clusters. This novel procedure provides a general framework that can be applied to specific diseases, for aiding risk assessment analysis and informing the design of optimal surveillance systems.Comment: Supplementary Information at https://sites.google.com/site/paolobajardi/Home/archive/optimizing_surveillance_ESM_l.pdf?attredirects=

The Topological Invariant Approach: From Cosmology to Complex Biological Systems

This thesis addresses applications of topological invariants in the context of gravity, electromagnetism and complex systems. Specifically, in Chapters 3-8, different theories of gravity involving the Gauss–Bonnet term are discussed, as well as f(G) gravity, scalar-tensor theories and non-local theories. In all cases, after selecting viable models by symmetry considerations, field equation solutions are provided in cosmological and spherically symmetric backgrounds. In Chapter 9, basic foundations of Chern-Simons theory are reviewed, as in Chapters 10-13 the theory is then applied to the gravitational interaction, electromagnetism and complex biological systems. This latter application mainly aims to predict the effect of the induced mutations occurring in DNA/RNA sequences

Interplay of network dynamics and ties heterogeneity on spreading dynamics

The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent works showed a strong influence of temporal network dynamics on disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about the conditions for infected stable state in weighted networks. In particular, we reveal the role of heterogeneity of edge weights and of the dynamic assignment of weights on the ties in the network in driving the spread of the epidemic. In this context we show that when weights are dynamically assigned to ties in the network an heterogeneous distribution is able to hamper the diffusion of the disease, contrary to what happens when weights are fixed in time.Comment: 10 pages, 10 figure

Equivalence of non-minimally coupled cosmologies by Noether symmetries

We discuss non-minimally coupled cosmologies involving different geometric invariants. Specifically, actions containing a non-minimally coupled scalar field to gravity described, in turn, by curvature, torsion and Gauss--Bonnet scalars are considered. We show that couplings, potentials and kinetic terms are determined by the existence of Noether symmetries which, moreover, allows to reduce and solve dynamics. The main finding of the paper is that different non-minimally coupled theories, presenting the same Noether symmetries, are dynamically equivalent. In other words, Noether symmetries are a selection criterion to compare different theories of gravity.Comment: 16 pages. Accepted for publication in "International Journal of Modern Physics D

Late-time constraints on modified Gauss-Bonnet cosmology

In this paper, we consider a gravitational action containing a combination of the Ricci scalar, $R$, and the topological Gauss--Bonnet term, $G$. Specifically, we study the cosmological features of a particular class of modified gravity theories selected by symmetry considerations, namely the $f(R,G)= R^n G^{1-n}$ model. In the context of a spatially flat, homogeneous and isotropic background, we show that the currently observed acceleration of the Universe can be addressed through geometry, hence avoiding \emph{de facto} the shortcomings of the cosmological constant. We thus present a strategy to numerically solve the Friedmann equations in presence of pressureless matter and obtain the redshift behavior of the Hubble expansion rate. Then, to check the viability of the model, we place constraints on the free parameters of the theory by means of a Bayesian Monte Carlo method applied to late-time cosmic observations. Our results show that the $f(R,G)$ model is capable of mimicking the low-redshift behavior of the standard $\Lambda$CDM model, though substantial differences emerge when going toward high redshifts, leading to the absence of a standard matter-dominated epoch. Finally, we investigate the energy conditions and show that, under suitable choices for the values of the cosmographic parameters, they are all violated when considering the mean value of $n$ obtained from our analysis, as occurs in the case of a dark fluid.Comment: 10 pages, 3 figures, 1 tabl

Noether Symmetries and Quantum Cosmology in Extended Teleparallel Gravity

We apply the Noether Symmetry Approach to point-like teleparallel Lagrangians in view to derive minisuperspaces suitable for Quantum Cosmology. Adopting the Arnowitt-Deser-Misner formalism, we find out related Wave Functions of the Universe. Specifically, by means of appropriate changes of variables suggested by the existence of Noether symmetries, it is possible to obtain the cosmological Hamiltonians whose solutions are classical trajectories interpretable as observable universes.Comment: 15 Pages, 1 figur

Minisuperspace quantum cosmology in f(Q)f(Q) gravity

$f(Q)$ symmetric-teleparallel gravity is considered in view of Quantum Cosmology. Specifically, we derive cosmological equations for $f(Q)$ models and then investigate the related energy conditions. In the minisuperspace formalism, the point-like $f(Q)$ Hamiltonian is taken into account. In this framework, we obtain and solve the Wheeler-De Witt equation, thus finding the Wave Function of the Universe in different cases. We show that the Hartle Criterion can be applied and classical observable universes occur.Comment: 17 pages, 2 Figures. Accepted for publication in EPJ

Contribuciones de la educación artística a la construcción de la identidad profesional docente: competencias básicas y comunicativas.

This article deals with theprofessional identityof teachersand howthe artscancontributetoits development.We analyze theprofessional competencesof teachersand the importance of communication, emphasizing therelevance ofreflective practice andsignificant learningina collaborative environmentthat take into accountsocial interactionand negotiationofknowledge.The arts disciplines promote social tools that allow people to build their identities, such as verbal and nonverbal communication, critical thinking and the exchange of experiences.Este artículo trata la identidad profesional docente y como las disciplinas artísticas contribuyena su desarrollo. Se analizan las competencias profesionales y la importancia de la comunicación, enfatizando la relevancia de la práctica reflexiva y del aprendizaje significativo en un entorno colaborativo que pone en valor las interacciones sociales y la negociación de los conocimientos. Las disciplinas artísticas favorecenherramientas sociales que permiten al individuo construir su propia identidad, como la comunicación verbal y no verbal, el espíritu crítico y el intercambio de experiencias