27 citations · 31 across the 4 of their papers we have counts for
7 papers
Interoperability of statistical models in pandemic preparedness: principles and reality
George Nicholson, Marta Blangiardo, Mark Briers +12
We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving p…
School neighbourhood and compliance with WHO-recommended annual NO2 guideline: a case study of Greater London
Niloofar Shoari, Shahram Heydari, Marta Blangiardo
Despite several national and local policies towards cleaner air in England, many schools in London breach the WHO-recommended concentrations of air pollutants such as NO2 and PM2.5…
A joint bayesian space-time model to integrate spatially misaligned air pollution data in R-INLA
Chiara Forlani, Samir Bhatt, Michela Cameletti +2
In air pollution studies, dispersion models provide estimates of concentration at grid level covering the entire spatial domain, and are then calibrated against measurements from m…
A spatio-temporal model to understand forest fires causality in Europe
Oscar Rodriguez de Rivera, Antonio López-Quílez, Marta Blangiardo +1
Forest fires are the outcome of a complex interaction between environmental factors, topography and socioeconomic factors (Bedia et al, 2014). Therefore, understand causality and e…
Missing data analysis and imputation via latent Gaussian Markov random fields
Virgilio Gómez-Rubio, Michela Cameletti, Marta Blangiardo
In this paper we recast the problem of missing values in the covariates of a regression model as a latent Gaussian Markov random field (GMRF) model in a fully Bayesian framework. O…
A hierarchical modelling approach to assess multi pollutant effects in time-series studies
Marta Blangiardo, Monica Pirani, Lauren Kanapka +2
When assessing the short term effect of air pollution on health outcomes, it is common practice to consider one pollutant at a time, due to their high correlation. Multi pollutant…