The effect of competition between health opinions on epidemic dynamics

Past major epidemic events showed that when an infectious disease is perceived to cause severe health outcomes, individuals modify health behavior affecting epidemic dynamics. To investigate the effect of this feedback relationship on epidemic dynamics, we developed a compartmental model that couples a disease spread framework with competition of two mutually exclusive health opinions (health-positive and health-neutral) associated with different health behaviors. The model is based on the assumption that individuals switch health opinions as a result of exposure to opinions of others through interpersonal communications. To model opinion switch rates, we considered a family of functions and identified the ones that allow health opinions to coexist. Finally, the model includes assortative mixing by opinions. In the disease-free population, either the opinions cannot coexist and one of them is always dominating (mono-opinion equilibrium) or there is at least one stable coexistence of opinions equilibrium. In the latter case, there is multistability between the coexistence equilibrium and the two mono-opinion equilibria. When two opinions coexist, it depends on their distribution whether the infection can invade. If presence of the infection leads to increased switching to a health-positive opinion, the epidemic burden becomes smaller than indicated by the basic reproduction number. Additionally, a feedback between epidemic dynamics and health opinion dynamics may result in (sustained) oscillatory dynamics and a switch to a different stable opinion distribution. Our model captures feedback between spread of awareness through social interactions and infection dynamics and can serve as a basis for more elaborate individual-based models

Epidemic processes in complex networks

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

Statistical physics of vaccination

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination–one of the most important preventive measures of modern times–is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research

Adaptive dynamical networks

It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields, in particular, for the models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In this review, we provide a detailed description of adaptive dynamical networks, show their applications in various areas of research, highlight their dynamical features and describe the arising dynamical phenomena, and give an overview of the available mathematical methods developed for understanding adaptive dynamical networks

The structure and dynamics of multilayer networks

In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.Comment: In Press, Accepted Manuscript, Physics Reports 201

Zoonoses

Animals are all around us. We overlap with them in environments across the globe, which leads to myriad interactions, including shared infectious and parasitic diseases. Such diseases, known as zoonoses, are the focus of this book. Within its pages, the authors describe the nature and transmission of zoonoses, discuss the diseases of greatest concern, detail different protective measures, and examine the factors responsible for zoonosis emergence and evolution. This work encourages readers to delve deeper into the world of animals and microbes that surrounds us. It presents knowledge we must possess to better protect ourselves and, more importantly, to adopt a more holistic approach to our relationships with animals and the living world

Mosquitopia

This edited volume brings together natural scientists, social scientists and humanists to assess if (or how) we may begin to coexist harmoniously with the mosquito. The mosquito is humanity’s deadliest animal, killing over a million people each year by transmitting malaria, yellow fever, Zika and several other diseases. Yet of the 3,500 species of mosquito on Earth, only a few dozen of them are really dangerous—so that the question arises as to whether humans and their mosquito foe can learn to live peacefully with one another. Chapters assess polarizing arguments for conserving and preserving mosquitoes, as well as for controlling and killing them, elaborating on possible consequences of both strategies. This book provides informed answers to the dual question: could we eliminate mosquitoes, and should we? Offering insights spanning the technical to the philosophical, this is the “go to” book for exploring humanity’s many relationships with the mosquito—which becomes a journey to finding better ways to inhabit the natural world. Mosquitopia will be of interest to anyone wanting to explore dependencies between human health and natural systems, while offering novel perspectives to health planners, medical experts, environmentalists and animal rights advocates

Preventing the next pandemic: Zoonotic diseases and how to break the chain of transmission

In the spirit of the UN Framework for the Immediate Socio-economic Response to COVID-19, the United Nations Environment Programme (UNEP) has teamed up with the renowned International Livestock Research Institute (ILRI) and other key partners to develop an evidence-based assessment report on the risk of future zoonotic outbreaks. This report focuses specifically on the environmental side of the zoonotic dimension of disease outbreaks during the COVID-19 pandemic. It tries to fill a critical knowledge gap and provide policymakers with a better understanding of the context and nature of potential future zoonotic disease outbreaks. It examines the root causes of the COVID-19 pandemic and other zoonoses. The report also looks at where zoonoses come from and how we can reduce the likelihood of their occurrence. The report explores the role of animals, and in particular non-domestic animals, in emerging infectious human diseases. This is essential for our global efforts to improve our response preparedness because the frequency of spillover of pathogenic organisms jumping from animals to humans has been increasing considerably, due to the growing magnitude of our unsustainable natural resource use in today’s world

Zoonoses (Project 1): Wildlife/domestic livestock interactions

The objective of this study was to synthesise the best available scientific knowledge about zoonotic disease transmission through livestock and wildlife interaction (direct or indirect), with emphasis on risk factors, drivers and trajectories of transmission, as well as promising interventions for controlling important zoonoses, based on managing the interaction between domestic livestock and wildlife. A multi-disciplinary team from the International Livestock Research Institute, Kenya, and the Royal Veterinary College, United Kingdom, with expertise in zoonoses, epidemiology, socio-economics, and wildlife, undertook the review. A database of important zoonoses was compiled and used to develop a list of priority zoonoses with a livestock-wildlife interface for developing countries. Spatial relationships between important zoonoses and land use and human population density were explored. A systematic review was carried out focussing on: disease transmission routes, risk factors for disease transmission, drivers of wildlife-livestock interactions, pathogens of wildlife capable of recombining with organisms in livestock, wildlife species that are potential sources of zoonotic pathogens, production and socio-economic factors influencing the risk of transmission, and risk management and control interventions