Objectives: We study partial unlock or reopening interaction with seasonal effects in a managed epidemic to quantify overshoot effects on small and large unlock steps and discover robust strategies for reducing overshoot. Methods: We simulate partial unlock of social distancing for epidemics...

In this paper we introduce a parameter dependent class of Krylov-based methods, namely CD, for the solution of symmetric linear systems. We give evidence that in our proposal we generate sequences of conjugate directions, extending some properties of the standard Conjugate Gradient (CG) method,...

We develop an integrated epidemiological-macroeconomic model to analyze the interplay between the COVID-19 outbreak and economic activity, as a tool for capacity building purposes. We illustrate a workhorse framework that combines a rich epidemiological model with an economic block to shed light...

Epidemic analysis by dynamical modelling is a reliable and insightful way to analyse epidemiological data in order to extract key indicators about the outbreak and to make predictions on its future course. We develop a generalised SEIR model based on Peng et al. 2020 and estimate it on a...

COVID-19 has caused an immense worldwide impact, indicating the unpreparedness of several governments in handling contagious virus outbreaks. This research uses a time-dependent model analysing the sum of the epidemiological cost, relating to the direct cost from the loss of lives, ICU...

Medicare Part D provides prescription drug coverage through Medicare approved plans offered by private insurance companies and HMOs. In this paper, we study the role of current prescription drug use and health risks, related expectations, and subjective factors in the demand for prescription...

We devise a theoretical model for the optimal dynamical control of an infectious disease whose diffusion is described by the SVIR compartmental model. The control is realized through implementing social rules to reduce the disease’s spread, which often implies substantial economic and social...

This paper studies the computational complexity of Bayesian and quasi-Bayesian estimation in large samples carried out using a basic Metropolis random walk. The framework covers cases where the underlying likelihood or extremum criterion function is possibly non-concave, discontinuous, and of...