The application of statistical network models in disease research

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Host social structure is fundamental to how infections spread and persist, and so the statistical modelling of static and dynamic social networks provides an invaluable tool to parameterise realistic epidemiological models. We present a practical guide to the application of network modelling frameworks for hypothesis testing related to social interactions and epidemiology, illustrating some approaches with worked examples using data from a population of wild European badgers Meles meles naturally infected with bovine tuberculosis. Different empirical network datasets generate particular statistical issues related to non-independence and sampling constraints. We therefore discuss the strengths and weaknesses of modelling approaches for different types of network data and for answering different questions relating to disease transmission. We argue that statistical modelling frameworks designed specifically for network analysis offer great potential in directly relating network structure to infection. They have the potential to be powerful tools in analysing empirical contact data used in epidemiological studies, but remain untested for use in networks of spatio-temporal associations. As a result, we argue that developments in the statistical analysis of empirical contact data are critical given the ready availability of dynamic network data from bio-logging studies. Furthermore, we encourage improved integration of statistical network approaches into epidemiological research to facilitate the generation of novel modelling frameworks and help extend our understanding of disease transmission in natural populations.M.J.S. is funded by a NERC standard grant (NE/M004546/1) awarded to R.A.M., D.P.C., D.J.H. and M.B., with the APHA team at Woodchester Park, UK (lead scientist is R.J.D.) as project partners

Seasonal variation in daily patterns of social contacts in the European badger Meles meles

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Social interactions among hosts influence the persistence and spread of infectious pathogens. Daily 20 and seasonal variation in the frequency and type of social interactions will play an important role in 21 disease epidemiology, and alongside other factors may have an influence on wider disease dynamics 22 by causing seasonal forcing of infection, especially if the seasonal variation experienced by a 23 population is considerable. We explored temporal variation in within-group contacts in a high-24 density population of European badgers Meles meles naturally-infected with bovine tuberculosis. 25 Summer contacts were more likely and of longer duration during the daytime, while the frequency 26 and duration of winter contacts did not differ between day and night. In spring and autumn within-27 group contacts peaked at dawn and dusk, corresponding with when they were of shortest duration 28 with reduced potential for aerosol transmission of pathogens. Summer and winter could be critical 29 for bovine tuberculosis transmission in badgers, due to the high frequency and duration of contacts 30 during resting periods, and we discuss the links between this result and empirical data. This study 31 reveals clear seasonality in daily patterns of contact frequency and duration in species living in stable 32 social groups, suggesting that changes in social contacts could drive seasonal forcing of infection in 33 wildlife populations even when the number of individuals interacting remains similar.MJS is funded by NERC grant NE/M004546/1 awarded to RAM, DPC, DJH and MB, with RJD and the 386 APHA team at Woodchester Park, UK as project partners. Data were collected for NW’s PhD, funded 387 by Defra. We thank Jared Wilson-Aggarwal and two anonymous reviewers for useful comments and 388 Keith Silk for providing the photograph for Figure 1

Social structure contains epidemics and regulates individual roles in disease transmission in a group-living mammal

This is the final version. Available from Wiley via the DOI in this record. Data accessibility: The original weighted adjacency matrix for the high‐density population of European badgers, as well as code used for simulating networks and disease simulations can be found online https://doi.org/10.5061/dryad.49n3878.Population structure is critical to infectious disease transmission. As a result, theoretical and empirical contact network models of infectious disease spread are increasingly providing valuable insights into wildlife epidemiology. Analyzing an exceptionally detailed dataset on contact structure within a high-density population of European badgers Meles meles, we show that a modular contact network produced by spatially structured stable social groups, lead to smaller epidemics, particularly for infections with intermediate transmissibility. The key advance is that we identify considerable variation among individuals in their role in disease spread, with these new insights made possible by the detail in the badger dataset. Furthermore, the important impacts on epidemiology are found even though the modularity of the Badger network is much lower than the threshold that previous work suggested was necessary. These findings reveal the importance of stable social group structure for disease dynamics with important management implications for socially structured populations.Natural Environment Research Council (NERC

Factors affecting the intention of providers to deliver more effective continuing medical education to general practitioners: a pilot study

BACKGROUND: Despite the importance of continuing medical education (CME) for GPs, there has been little research into how providers decide what types of CME to deliver to GPs. This study aimed to identify factors affecting the intention of providers to provide more effective types of CME; and to design a survey instrument which can be used to test the applicability of Triandis' model of social behaviour to the provision of CME to general practitioners. METHODS: This was a cross-sectional study on a convenience sample of 11 Australian providers of CME for interviews and a random sample of 25 providers for the pilot test. Open-ended interviews structured on Triandis' theory were performed with key informants who provide CME to GPs. These were used to develop a pilot survey instrument to measure the factors affecting intention, resulting in a revised instrument for use in further research. RESULTS: There was a broad range of factors affecting providers' intention to deliver more effective forms of CME identified, and these were classifiable in a manner which was consistent with Triandis' model. Key factors affecting providers' intention were the attitude toward CME within organisations and the time and extra work involved. CONCLUSIONS: We identified a range of potential factors influencing the intention of providers to provide more effective forms of CME, in all categories of Triandis model. Those interested in increasing the choice of more effective CME activities available to GPs may need to broaden the methods used in working with providers to influence them to use more effective CME techniques. The interview material and questionnaire analysis of the pilot survey support the use of Triandis model. Further research is needed to validate Triandis'model for the intention to deliver more effective forms of CME. Such research will inform future strategies aimed at increasing the amount and choice of effective CME activities available for GPs

Intraaortic Balloon Pump Counterpulsation and Cerebral Autoregulation: an observational study

The use of Intra-aortic counterpulsation is a well established supportive therapy for patients in cardiac failure or after cardiac surgery. Blood pressure variations induced by counterpulsation are transmitted to the cerebral arteries, challenging cerebral autoregulatory mechanisms in order to maintain a stable cerebral blood flow. This study aims to assess the effects on cerebral autoregulation and variability of cerebral blood flow due to intra-aortic balloon pump and inflation ratio weaning

A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology

Changing scale, for example the ability to move seamlessly from an individual-based model to a population-based model, is an important problem in many fields. In this paper we introduce process algebra as a novel solution to this problem in the context of models of infectious disease spread. Process algebra allows us to describe a system in terms of the stochastic behaviour of individuals, and is a technique from computer science. We review the use of process algebra in biological systems, and the variety of quantitative and qualitative analysis techniques available. The analysis illustrated here solves the changing scale problem: from the individual behaviour we can rigorously derive equations to describe the mean behaviour of the system at the level of the population. The biological problem investigated is the transmission of infection, and how this relates to individual interaction

The trauma of ongoing conflict and displacement in Chechnya: quantitative assessment of living conditions, and psychosocial and general health status among war displaced in Chechnya and Ingushetia

BACKGROUND: Conflict in Chechnya has resulted in over a decade of violence, human rights abuses, criminality and poverty, and a steady flow of displaced seeking refuge throughout the region. At the beginning of 2004 MSF undertook quantitative surveys among the displaced populations in Chechnya and neighbouring Ingushetia. METHODS: Surveys were carried out in Ingushetia (January 2004) and Chechnya (February 2004) through systematic sampling. Various conflict-related factors contributing to ill health were researched to obtain information on displacement history, living conditions, and psychosocial and general health status. RESULTS: The average length of displacement was five years. Conditions in both locations were poor, and people in both locations indicated food shortages (Chechnya (C): 13.3%, Ingushetia (I): 11.3%), and there was a high degree of dependency on outside help (C: 95.4%, I: 94.3%). Most people (C: 94%, I: 98%) were confronted with violence in the past. Many respondents had witnessed the killing of people (C: 22.7%, I: 24.1%) and nearly half of people interviewed witnessed arrests (C: 53.1%, I: 48.4%) and maltreatment (C: 56.2%, I: 44.5%). Approximately one third of those interviewed had directly experienced war-related violence. A substantial number of people interviewed – one third in Ingushetia (37.5%) and two-thirds in Chechnya (66.8%) – rarely felt safe. The violence was ongoing, with respondents reporting violence in the month before the survey (C: 12.5%, I: 4.6%). Results of the general health questionnaire (GHQ 28) showed that nearly all internally displaced persons interviewed were suffering from health complaints such as somatic complaints, anxiety/insomnia, depressive feelings or social dysfunction (C: 201, 78.5%, CI: 73.0% – 83.4%; I: 230, 81.3%, CI: 76.2% – 85.6%). Poor health status was reflected in other survey questions, but health services were difficult to access for around half the population (C: 54.3%, I: 46.6%). DISCUSSION: The study demonstrates that the health needs of internally displaced in both locations are similarly high and equally unaddressed. The high levels of past confrontation with violence and ongoing exposure in both locations is likely to contribute to a further deterioration of the health status of internally displaced. As of March 2007, concerns remain about how the return process is being managed by the authorities

Biodiversity modelling in practice - predicting bird and woody plant species richness on farmlands

In light of decreasing species richness on farmland and an increasing awareness of biodiversity issues among customers and food companies, concepts and models to evaluate and enhance farmland biodiversity are greatly needed. It is important that the models are easy to apply as they have to be utilized by practitioners such as farmers and their consultants. In this study, simple but valid predictors were identified to rapidly assess the species richness of birds and woody plants in hedgerows, an important farmland landscape element. Hedgerows were sampled in seven agricultural landscapes throughout Germany. By means of automatic model selection procedures, linear regression models were estimated to predict bird and woody plant species richness. Cross validation procedures were carried out in order to visualize model selection uncertainty and estimate the prediction error. Due to a rather high prediction error, the model for plants can only be recommended for use when field work is not feasible. The model for birds, however, explained 70.8% of the variance in species numbers. It may help farmers, food companies and nature conservation agencies to rapidly evaluate bird species richness in hedgerows on farmland and to identify potentials and appropriate measures for enhancing it

Heat and moisture exchangers (HMEs) and heated humidifiers (HHs) in adult critically ill patients: a systematic review, meta-analysis and meta-regression of randomized controlled trials

The aims of this systematic review and meta-analysis of randomized controlled trials are to evaluate the effects of active heated humidifiers (HHs) and moisture exchangers (HMEs) in preventing artificial airway occlusion and pneumonia, and on mortality in adult critically ill patients. In addition, we planned to perform a meta-regression analysis to evaluate the relationship between the incidence of artificial airway occlusion, pneumonia and mortality and clinical features of adult critically ill patients