Social encounter networks: collective properties and disease transmission

A fundamental challenge of modern infectious disease epidemiology is to quantify the networks of social and physical contacts through which transmission can occur. Understanding the collective properties of these interactions is critical for both accurate prediction of the spread of infection and determining optimal control measures. However, even the basic properties of such networks are poorly quantified, forcing predictions to be made based on strong assumptions concerning network structure. Here, we report on the results of a large-scale survey of social encounters mainly conducted in Great Britain. First, we characterize the distribution of contacts, which possesses a lognormal body and a power-law tail with an exponent of −2.45; we provide a plausible mechanistic model that captures this form. Analysis of the high level of local clustering of contacts reveals additional structure within the network, implying that social contacts are degree assortative. Finally, we describe the epidemiological implications of this local network structure: these contradict the usual predictions from networks with heavy-tailed degree distributions and contain public-health messages about control. Our findings help us to determine the types of realistic network structure that should be assumed in future population level studies of infection transmission, leading to better interpretations of epidemiological data and more appropriate policy decisions.     

Sushi in the United States, 1945–1970

Sushi first achieved widespread popularity in the United States in the mid-1960s. Many accounts of sushi's US establishment foreground the role of a small number of key actors, yet underplay the role of a complex web of large-scale factors that provided the context in which sushi was able to flourish. This article critically reviews existing literature, arguing that sushi's US popularity arose from contingent, long-term, and gradual processes. It examines US newspaper accounts of sushi during 1945–1970, which suggest the discursive context for US acceptance of sushi was considerably more propitious than generally acknowledged. Using California as a case study, the analysis also explains conducive social and material factors, and directs attention to the interplay of supply- and demand-side forces in the favorable positioning of this “new” food. The article argues that the US establishment of sushi can be understood as part of broader public acceptance of Japanese cuisine.     

Adaptive particles for incompressible fluid simulation

We propose a particle-based technique for simulating incompressible fluid that includes adaptive refinement of particle sampling. Each particle represents a mass of fluid in its local region. Particles are split into several particles for finer sampling in regions of complex flow. In regions of smooth flow, neighboring particles can be merged. Depth below the surface and Reynolds number are exploited as our criteria for determining whether splitting or merging should take place. For the fluid dynamics calculations, we use the hybrid FLIP method, which is computationally simple and efficient. Since the fluid is incompressible, each particle has a volume proportional to its mass. A kernel function, whose effective range is based on this volume, is used for transferring and updating the particle’s physical properties such as mass and velocity. Our adaptive particle-based simulation is demonstrated in several scenarios that show its effectiveness in capturing fine detail of the flow, where needed, while efficiently sampling regions where less detail is required.