Cost-efficient vaccination protocols for network epidemiology

We investigate methods to vaccinate contact networks -- i.e. removing nodes in such a way that disease spreading is hindered as much as possible -- with respect to their cost-efficiency. Any real implementation of such protocols would come with costs related both to the vaccination itself, and gathering of information about the network. Disregarding this, we argue, would lead to erroneous evaluation of vaccination protocols. We use the susceptible-infected-recovered model -- the generic model for diseases making patients immune upon recovery -- as our disease-spreading scenario, and analyze outbreaks on both empirical and model networks. For different relative costs, different protocols dominate. For high vaccination costs and low costs of gathering information, the so-called acquaintance vaccination is the most cost efficient. For other parameter values, protocols designed for query-efficient identification of the network's largest degrees are most efficient

Layer-switching cost and optimality in information spreading on multiplex networks

We study a model of information spreading on multiplex networks, in which agents interact through multiple interaction channels (layers), say online vs.\ offline communication layers, subject to layer-switching cost for transmissions across different interaction layers. The model is characterized by the layer-wise path-dependent transmissibility over a contact, that is dynamically determined dependently on both incoming and outgoing transmission layers. We formulate an analytical framework to deal with such path-dependent transmissibility and demonstrate the nontrivial interplay between the multiplexity and spreading dynamics, including optimality. It is shown that the epidemic threshold and prevalence respond to the layer-switching cost non-monotonically and that the optimal conditions can change in abrupt non-analytic ways, depending also on the densities of network layers and the type of seed infections. Our results elucidate the essential role of multiplexity that its explicit consideration should be crucial for realistic modeling and prediction of spreading phenomena on multiplex social networks in an era of ever-diversifying social interaction layers.Comment: 15 pages, 7 figure

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme --- a simple, but universal strategy requiring only local information --- and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.Comment: 4 figure

One Health proof of concept: Bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface.

As the world continues to react and respond inefficiently to emerging infectious diseases, such as Middle Eastern Respiratory Syndrome and the Ebola and Zika viruses, a growing transdisciplinary community has called for a more proactive and holistic approach to prevention and preparedness - One Health. Such an approach presents important opportunities to reduce the impact of disease emergence events and also to mitigate future emergence through improved cross-sectoral coordination. In an attempt to provide proof of concept of the utility of the One Health approach, the US Agency for International Development's PREDICT project consortium designed and implemented a targeted, risk-based surveillance strategy based not on humans as sentinels of disease but on detecting viruses early, at their source, where intervention strategies can be implemented before there is opportunity for spillover and spread in people or food animals. Here, we share One Health approaches used by consortium members to illustrate the potential for successful One Health outcomes that can be achieved through collaborative, transdisciplinary partnerships. PREDICT's collaboration with partners around the world on strengthening local capacity to detect hundreds of viruses in wild animals, coupled with a series of cutting-edge virological and analytical activities, have significantly improved our baseline knowledge on the zoonotic pool of viruses and the risk of exposure to people. Further testament to the success of the project's One Health approach and the work of its team of dedicated One Health professionals are the resulting 90 peer-reviewed, scientific publications in under 5 years that improve our understanding of zoonoses and the factors influencing their emergence. The findings are assisting in global health improvements, including surveillance science, diagnostic technologies, understanding of viral evolution, and ecological driver identification. Through its One Health leadership and multi-disciplinary partnerships, PREDICT has forged new networks of professionals from the human, animal, and environmental health sectors to promote global health, improving our understanding of viral disease spillover from wildlife and implementing strategies for preventing and controlling emerging disease threats

Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution

Early detection of disease outbreaks in human and animal populations is crucial to the effective surveillance of emerging infectious diseases. However, there are marked geographical disparities in capacity for early detection of outbreaks, which limit the effectiveness of global surveillance strategies. Linking surveillance approaches for emerging and neglected endemic zoonoses, with a renewed focus on existing disease problems in developing countries, has the potential to overcome several limitations and to achieve additional health benefits. Poor reporting is a major constraint to the surveillance of both emerging and endemic zoonoses, and several important barriers to reporting can be identified: (i) a lack of tangible benefits when reports are made; (ii) a lack of capacity to enforce regulations; (iii) poor communication among communities, institutions and sectors; and (iv) complexities of the international regulatory environment. Redirecting surveillance efforts to focus on endemic zoonoses in developing countries offers a pragmatic approach that overcomes some of these barriers and provides support in regions where surveillance capacity is currently weakest. In addition, this approach addresses immediate health and development problems, and provides an equitable and sustainable mechanism for building the culture of surveillance and the core capacities that are needed for all zoonotic pathogens, including emerging disease threats

Spreading processes in Multilayer Networks

Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of an online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.Comment: 21 pages, 3 figures, 4 table

Disease Surveillance Networks Initiative Africa: Final Evaluation

The overall objective of the Foundation's Disease Surveillance Networks (DSN) Initiative is to strengthen technical capacity at the country level for disease surveillance and to bolster response to outbreaks through the sharing of technical information and expertise. It supports formalizing collaboration, information sharing and best practices among established networks as well as trans-national, interdisciplinary and multi-sectoral efforts, and is experienced in developing and fostering innovative partnerships. In order to more effectively address disease threats, the DSN has four key outcome areas:(1) forming and sustaining trans-boundary DSN;(2) strengthening and applying technical and communication skills by local experts and institutions;(3) increasing access and use of improved tools and methods on information sharing, reporting and monitoring; and(4) emphasizing One Health and transdisciplinary approaches to policy and practice at global, regional and local levels