School's Out: Seasonal Variation in the Movement Patterns of School Children.

School children are core groups in the transmission of many common infectious diseases, and are likely to play a key role in the spatial dispersal of disease across multiple scales. However, there is currently little detailed information about the spatial movements of this epidemiologically important age group. To address this knowledge gap, we collaborated with eight secondary schools to conduct a survey of movement patterns of school pupils in primary and secondary schools in the United Kingdom. We found evidence of a significant change in behaviour between term time and holidays, with term time weekdays characterised by predominately local movements, and holidays seeing much broader variation in travel patterns. Studies that use mathematical models to examine epidemic transmission and control often use adult commuting data as a proxy for population movements. We show that while these data share some features with the movement patterns reported by school children, there are some crucial differences between the movements of children and adult commuters during both term-time and holidays.AJK was supported by the Medical Research Council (fellowship MR/K021524/1, http://www.mrc.ac.uk/) and the RAPIDD program of the Science & Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health (http://www.fic.nih.gov/about/staff/pages​/epidemiology-population.aspx#rapidd). AJKC was supported by the Alborada Trust (http://www.alboradatrust.com/). KTDE was supported by the NIHR (CDF-2011-04- 019, http://www.nihr.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version. It was first published by PLOS at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128070#

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza

Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys

Epidemics on contact networks: a general stochastic approach

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our systematic framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible (SIS) and susceptible-infectious-removed (SIR) dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.Comment: Main document: 16 pages, 7 figures. Electronic Supplementary Material (included): 6 pages, 1 tabl

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics

Mutations in fam20b and xylt1 Reveal That Cartilage Matrix Controls Timing of Endochondral Ossification by Inhibiting Chondrocyte Maturation

Differentiating cells interact with their extracellular environment over time. Chondrocytes embed themselves in a proteoglycan (PG)-rich matrix, then undergo a developmental transition, termed “maturation,” when they express ihh to induce bone in the overlying tissue, the perichondrium. Here, we ask whether PGs regulate interactions between chondrocytes and perichondrium, using zebrafish mutants to reveal that cartilage PGs inhibit chondrocyte maturation, which ultimately dictates the timing of perichondral bone development. In a mutagenesis screen, we isolated a class of mutants with decreased cartilage matrix and increased perichondral bone. Positional cloning identified lesions in two genes, fam20b and xylosyltransferase1 (xylt1), both of which encode PG synthesis enzymes. Mutants failed to produce wild-type levels of chondroitin sulfate PGs, which are normally abundant in cartilage matrix, and initiated perichondral bone formation earlier than their wild-type siblings. Primary chondrocyte defects might induce the bone phenotype secondarily, because mutant chondrocytes precociously initiated maturation, showing increased and early expression of such markers as runx2b, collagen type 10a1, and ihh co-orthologs, and ihha mutation suppressed early perichondral bone in PG mutants. Ultrastructural analyses demonstrated aberrant matrix organization and also early cellular features of chondrocyte hypertrophy in mutants. Refining previous in vitro reports, which demonstrated that fam20b and xylt1 were involved in PG synthesis, our in vivo analyses reveal that these genes function in cartilage matrix production and ultimately regulate the timing of skeletal development

Heterogeneities in leishmania infantum infection : using skin parasite burdens to identify highly infectious dogs

Background: The relationships between heterogeneities in host infection and infectiousness (transmission to arthropod vectors) can provide important insights for disease management. Here, we quantify heterogeneities in Leishmania infantum parasite numbers in reservoir and non-reservoir host populations, and relate this to their infectiousness during natural infection. Tissue parasite number was evaluated as a potential surrogate marker of host transmission potential. Methods: Parasite numbers were measured by qPCR in bone marrow and ear skin biopsies of 82 dogs and 34 crab-eating foxes collected during a longitudinal study in Amazon Brazil, for which previous data was available on infectiousness (by xenodiagnosis) and severity of infection. Results: Parasite numbers were highly aggregated both between samples and between individuals. In dogs, total parasite abundance and relative numbers in ear skin compared to bone marrow increased with the duration and severity of infection. Infectiousness to the sandfly vector was associated with high parasite numbers; parasite number in skin was the best predictor of being infectious. Crab-eating foxes, which typically present asymptomatic infection and are non-infectious, had parasite numbers comparable to those of non-infectious dogs. Conclusions: Skin parasite number provides an indirect marker of infectiousness, and could allow targeted control particularly of highly infectious dogs

Understanding the identity of lived experience researchers and providers: a conceptual framework and systematic narrative review

Background: Identity is how we understand ourselves and others through the roles or social groups we occupy. This review focuses on lived experience researchers and providers and the impact of these roles on identity. Lived experience researchers and providers use their lived experience of mental or physical disability either as experts by experience, researchers, peer workers, or mental health professionals with lived experience. They must navigate both professional and personal aspects to their roles which can be complex. Performing roles simultaneously embodying professional and lived experiences contribute towards a lack of clarity to identity. This is not adequately explained by the theoretical evidence base for identity. Main body: This systematic review and narrative synthesis aimed to provide a conceptual framework to understand how identity of lived experience researchers and providers is conceptualised. A search strategy was entered into EBSCO to access Academic search complete, CINAHL, MEDLINE, PsycINFO, Psych Articles, and Connected papers. Out of the 2049 yielded papers, thirteen qualitative papers were eligible and synthesised, resulting in a conceptual framework. Five themes explained identity positions: Professional, Service user, Integrated, Unintegrated and Liminal. The EMERGES framework, an original conception of this review, found themes of: Enablers and Empowerment, Motivation, Empathy of the self and others, Recovery model and medical model, Growth and transformation, Exclusion and Survivor roots contributed to lived experience researcher and provider identities. Conclusions: The EMERGES framework offers a novel way to understand the identities of lived experience researchers and providers, helping support effective team working in mental health, education, and research settings