Modelling spatio-temporal data with multiple seasonalities: the NO2 portuguese case

This study aims at characterizing the spatial and temporal dynamics of spatio-temporal data sets, characterized by high resolution in the temporal dimension which are becoming the norm rather than the exception in many application areas, namely environmental modelling. In particular, air pollution data, such as NO2 concentration levels, often incorporate also multiple recurring patterns in time imposed by social habits, anthropogenic activities and meteorological conditions. A two-stage modelling approach is proposed which combined with a block bootstrap procedure correctly assesses uncertainty in parameters estimates and produces reliable confidence regions for the space-time phenomenon under study. The methodology provides a model that is satisfactory in terms of goodness of fit, interpretability, parsimony, prediction and forecasting capability and computational costs. The proposed framework is potentially useful for scenario drawing in many areas, including assessment of environmental impact and environmental policies, and in a myriad applications to other research fields. (C) 2017 Elsevier B.V. All rights reserved.- The authors acknowledge Foundation FCT (Fundacao para a Ciencia e Tecnologia) for funding through Individual Scholarship Ph.D. PD/BD/105743/2014, Centre of Mathematics of Minho University within project UID/MAT/00013/2013 and Center for Research & Development in Mathematics and Applications of Aveiro University within project UID/MAT/04106/2013.info:eu-repo/semantics/publishedVersio

Making the Most of Clinical Data: Reviewing the Role of Pharmacokinetic-Pharmacodynamic Models of Anti-malarial Drugs

Mechanistic within-host models integrating blood anti-malarial drug concentrations with the parasite-time profile provide a valuable decision tool for determining dosing regimens for anti-malarial treatments, as well as a formative component of population-level drug resistance models. We reviewed published anti-malarial pharmacokinetic-pharmacodynamic models to identify the challenges for these complex models where parameter estimation from clinical field data is limited. The inclusion of key pharmacodynamic processes in the mechanistic structure adopted varies considerably. These include the life cycle of the parasite within the red blood cell, the action of the anti-malarial on a specific stage of the life cycle, and the reduction in parasite growth associated with immunity. With regard to estimation of the pharmacodynamic parameters, the majority of studies simply compared descriptive summaries of the simulated outputs to published observations of host and parasite responses from clinical studies. Few studies formally estimated the pharmacodynamic parameters within a rigorous statistical framework using observed individual patient data. We recommend three steps in the development and evaluation of these models. Firstly, exploration through simulation to assess how the different parameters influence the parasite dynamics. Secondly, application of a simulation-estimation approach to determine whether the model parameters can be estimated with reasonable precision based on sampling designs that mimic clinical efficacy studies. Thirdly, fitting the mechanistic model to the clinical data within a Bayesian framework. We propose that authors present the model both schematically and in equation form and give a detailed description of each parameter, including a biological interpretation of the parameter estimates

Making the most of clinical data: reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs.

Mechanistic within-host models integrating blood anti-malarial drug concentrations with the parasite-time profile provide a valuable decision tool for determining dosing regimens for anti-malarial treatments, as well as a formative component of population-level drug resistance models. We reviewed published anti-malarial pharmacokinetic-pharmacodynamic models to identify the challenges for these complex models where parameter estimation from clinical field data is limited. The inclusion of key pharmacodynamic processes in the mechanistic structure adopted varies considerably. These include the life cycle of the parasite within the red blood cell, the action of the anti-malarial on a specific stage of the life cycle, and the reduction in parasite growth associated with immunity. With regard to estimation of the pharmacodynamic parameters, the majority of studies simply compared descriptive summaries of the simulated outputs to published observations of host and parasite responses from clinical studies. Few studies formally estimated the pharmacodynamic parameters within a rigorous statistical framework using observed individual patient data. We recommend three steps in the development and evaluation of these models. Firstly, exploration through simulation to assess how the different parameters influence the parasite dynamics. Secondly, application of a simulation-estimation approach to determine whether the model parameters can be estimated with reasonable precision based on sampling designs that mimic clinical efficacy studies. Thirdly, fitting the mechanistic model to the clinical data within a Bayesian framework. We propose that authors present the model both schematically and in equation form and give a detailed description of each parameter, including a biological interpretation of the parameter estimates

Making the most of clinical data: Reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs

Mechanistic within-host models integrating blood anti-malarial drug concentrations with the parasite-time profile provide a valuable decision tool for determining dosing regimens for anti-malarial treatments, as well as a formative component of population-level drug resistance models. We reviewed published anti-malarial pharmacokinetic-pharmacodynamic models to identify the challenges for these complex models where parameter estimation from clinical field data is limited. The inclusion of key pharmacodynamic processes in the mechanistic structure adopted varies considerably. These include the life cycle of the parasite within the red blood cell, the action of the anti-malarial on a specific stage of the life cycle, and the reduction in parasite growth associated with immunity. With regard to estimation of the pharmacodynamic parameters, the majority of studies simply compared descriptive summaries of the simulated outputs to published observations of host and parasite responses from clinical studies. Few studies formally estimated the pharmacodynamic parameters within a rigorous statistical framework using observed individual patient data. We recommend three steps in the development and evaluation of these models. Firstly, exploration through simulation to assess how the different parameters influence the parasite dynamics. Secondly, application of a simulation- estimation approach to determine whether the model parameters can be estimated with reasonable precision based on sampling designs that mimic clinical efficacy studies. Thirdly, fitting the mechanistic model to the clinical data within a Bayesian framework. We propose that authors present the model both schematically and in equation form and give a detailed description of each parameter, including a biological interpretation of the parameter estimates. © 2014 American Association of Pharmaceutical Scientists