4 research outputs found

    Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models

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    <p>Abstract</p> <p>Background</p> <p>In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used.</p> <p>Methods</p> <p>We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels.</p> <p>Results</p> <p>The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, <it>R</it><sub>0</sub>, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes.</p> <p>Conclusions</p> <p>The good agreement between the two modeling approaches is very important for defining the tradeoff between data availability and the information provided by the models. The results we present define the possibility of hybrid models combining the agent-based and the metapopulation approaches according to the available data and computational resources.</p

    Psychometric properties of the Scale for Quality Evaluation of the Bachelor Degree in Nursing Version 2 (QBN 2)

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    To evaluate all the variables that affect nursing education is important for nursing educators to have valid and reliable instruments that can measure the perceived quality of the Bachelor Degree in Nursing. This study testing the Scale for Quality Evaluation of the Bachelor Degree in Nursing instrument and its psychometric properties with a descriptive design. Participant were first, second and third year students of the Bachelor Degree in Nursing Science from three Italian universities. The Scale for Quality Evaluation of Bachelor Degree in Nursing consists of 65 items that use a 4 point Likert scale ranging from “strongly disagree” to “strongly agree”. The instrument comes from a prior version with 41 items that were modified and integrated with 24 items to improve reliability. Six hundred and fifty questionnaires were completed and considered for the present study. The mean age of the students was 24.63 years, 65.5% were females. Reliability of the scale resulted in a very high Cronbach's alpha (0.96). The construct validity was tested with factor analysis that showed 7 factors. The Scale for Quality Evaluation of the Bachelor Degree in Nursing, although requiring further studies, represents a useful instrument to measure the quality of the Bachelor Nursing Degree
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