OBJECTIVE To assess the degree to which the Chinese people are protected from catastrophic household expenditure and impoverishment from medical expenses and to explore the health system and structural factors influencing the first of these outcomes. METHODS Data were derived from the Fourth National Health Service Survey. An analysis of catastrophic health expenditure and impoverishment from...

BACKGROUND The catastrophic health expenditure and impoverishment indices offer guidance for developing appropriate health policies and intervention programs to decrease financial inequity. This study assesses socioeconomic inequalities in catastrophic health expenditure and impoverishment in relation to self-reported non-communicable diseases (NCD) in urban Hanoi, Vietnam. METHODS A cross-se...

Observational errors of Particle Filtering are studied over the case a state-space model with linear observation equation. In this study, observational estimated prior to upcoming observations. This action is added basic algorithm filter as new step for acquisition state estimations. intervention useful in presence missing data problems mainly, well sample tracking impoverishment issues. It app...

Condensation is a widely-used tracking algorithm based on particle filters. Although some results have been achieved, it has several unpleasant behaviours. In this paper, we highlight these misbehaviours and propose two improvements. A new weight assignment, which avoids sample impoverishment, is presented. Subsequently, the prediction process is enhanced. The proposal has been successfully tes...

BACKGROUND Out-of-pocket (OOP) medical expenses often lead to catastrophic expenditure and impoverishment in low- and middle-income countries. Yet, there has been no systematic examination of which specific diseases and conditions (e.g., tuberculosis, cardiovascular disease) drive medical impoverishment, defined as OOP direct medical costs pushing households into poverty. METHODS We used a co...

Particle filter is a probability estimation method based on Bayesian framework and it has unique advantage to describe the target tracking non-linear and non-Gaussian. In this study, firstly, analyses the particle degeneracy and sample impoverishment in particle filter multi-target tracking algorithm and secondly, it applies Markov Chain Monte Carlo (MCMC) method to improve re-sampling process ...

during the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degeneracy and impoverishment. We are investigating methods that are particularly efficient at Particle Distribution Optimization (PDO) to fight sample degeneracy and impoverishment, with an emphasis on intelligence choices....

This paper examines the impact of impoverishment on patients' preferences with respect to improving the quality of health care, by focusing on the sudden impoverishment experience that affected the Occupied Palestinian Territory (OPT) since the beginning of the second Palestinian Uprising of September 2000. Two random samples of patients (352 and 353 individuals, respectively) were interviewed ...

BACKGROUND Health expenditure for tuberculosis (TB) care often pushes households into catastrophe and poverty. New Cooperative Medical Scheme (NCMS) aims to protect households from catastrophic health expenditure (CHE) and impoverishment in rural China. This article assesses the effect of NCMS on relieving CHE and impoverishment from TB care in rural China. METHODS Three hundred fourty-seven ...

A novel resampling algorithm (called Deterministic Resampling) is proposed, which avoids uncensored discarding of low weighted particles thereby avoiding sample impoverishment. The diversity of particles is maintained by deterministically sampling support particles to improve the residual resampling. A proof is given that our approach can be strictly unbiased and maintains the original state de...