In general, different countries and communities respond to epidemics in accordance with their own control plans and protocols. However, owing to global human migration and mobility, strategic planning for epidemic control measures through the collaboration of relevant public health administrations is gaining importance for mitigating and containing large-scale epidemics. Here, we present a framework to evaluate the effectiveness of random (non-strategic) and targeted (strategic) epidemic interventions for spatially separated patches in metapopulation models. For a random intervention, we analytically derive the critical fraction of patches that receive epidemic interventions, above which epidemics are successfully contained. The analysis shows that the heterogeneity of patch connectivity makes it difficult to contain epidemics under the random intervention. We demonstrate that, particularly in such heterogeneously connected networks, targeted interventions are considerably effective compared to the random intervention. Our framework is useful for identifying the target areas where epidemic control measures should be focused.

SUMMARY: Although Kawasaki disease (KD), which was first reported in the 1960s, is assumed to be infectious, its aetiological agent(s) remains unknown. We compared the geographical distribution of the force of infection and the super-annual periodicity of KD and seven other paediatric infectious diseases in Japan. The geographical distribution of the force of infection, which was estimated as the inverse of the mean patient age, was similar in KD and other paediatric viral infections. This similarity was due to the fact that the force of infection was determined largely by the total fertility rate. This finding suggests that KD shares a transmission route, i.e. sibling-to-sibling infection, with other paediatric infections. The super-annual periodicity, which is positively associated with the sum of an infectious disease's incubation period and infectious period, was much longer for KD and exanthema subitum than other paediatric infectious diseases. The virus for exanthema subitum is known to persist across the host's lifespan, which suggests that the aetiological agent for KD may also be capable of persistent infection. Taken together, these findings suggest that the aetiological agent for KD is transmitted through close contact and persists asymptomatically in most hosts.

We model the disorder-induced increase in fracture strength by applying a two-dimensional elastic network with an initial crack. The model has all the nearest neighbors, except those on the initial crack, connected by springs, which are randomly chosen as either hard or soft. All the springs are cut at the same force threshold. Our calculations show that the maximum stress in the disordered system is increased if the initial crack length is sufficiently large, and we discuss the relationship between the crack length and the force distribution or the work done on the system. We also derive the enhancement of the stress intensity factor and fracture toughness by analyzing the generation of the fracture process zone.

In some species, one of the roles of pheromones is to influence aggregation behavior. We first propose a macroscopic cross-diffusion model for the self-organized aggregation of German cockroaches that includes directed movement due to an aggregation pheromone. We then propose a microscopic particle model which is set into context with the macroscopic model. Our goal is to link the macroscopic and microscopic descriptions by using the singular and the hydrodynamic limit procedures. A hybrid model related to the macroscopic and microscopic models is also proposed as a cockroach aggregation model. This hybrid model assumes that each individual responds to pheromone concentration and moves by two-mode simple symmetric random walks. It shows that even though the movement of individuals is not directed, two-mode simple symmetric random walks and effect of the pheromone result in self-organized aggregation.

In recent years, serious infectious diseases tend to transcend national borders and widely spread in a global scale. The incidence and prevalence of epidemics are highly influenced not only by pathogen-dependent disease characteristics such as the force of infection, the latent period, and the infectious period, but also by human mobility and contact patterns. However, the effect of heterogeneous mobility of individuals on epidemic outcomes is not fully understood. Here, we aim to elucidate how spatial mobility of individuals contributes to the final epidemic size in a spatial susceptible-exposed-infectious-recovered (SEIR) model with mobile individuals in a square lattice. After illustrating the interplay between the mobility parameters and the other parameters on the spatial epidemic spreading, we propose an index as a function of system parameters, which largely governs the final epidemic size. The main contribution of this study is to show that the proposed index is useful for estimating how parameter scaling affects the final epidemic size. To demonstrate the effectiveness of the proposed index, we show that there is a positive correlation between the proposed index computed with the real data of human airline travels and the actual number of positive incident cases of influenza B in the entire world, implying that the growing incidence of influenza B is attributed to increased human mobility.