Poor knowledge, scarce resources, and lack of or misaligned incentives have been widely documented as drivers of the irrational use of medicine (IUM), which significantly challenges the efficiency of health systems across the globe. However, there is limited understanding of the influence of each factor on IUM. We used detailed data on provider treatment of presumptive asthma cases in rural China to assess the contributions of provider knowledge, resource constraints, and provider behavior on IUM. This study enrolled 370 village providers from southwest China. All providers responded to a clinical vignette to test their knowledge of how to treat presumptive asthma. Resource constraints (“capacity”) were defined as the availability of the prescribed medicines in vignette. To measure provider behavior (“performance”), a subset of providers (104 of 370) were randomly selected to receive unannounced visits by standardized patients (SPs) who performed of presumptive asthma symptoms described in the vignette. We found that, 54% (201/370) of providers provided the vignette-based patients with prescriptions. Moreover, 67% (70/104) provided prescriptions for the SPs. For the vignette, only 10% of the providers prescribed the correct medicines; 38% prescribed only unnecessary medicines (and did not provide correct medicine); 65% prescribed antibiotics (although antibiotics were not required); and 55% prescribed polypharmacy prescriptions (that is, they prescribed five or more different types of drugs). For the SP visits, the numbers were 12%, 51%, 63%, and 0%, respectively. The lower number of medicines in the SP visits was due, in part, to the injections’ not being allowed based on ethical considerations (in response to the vignette, however, 65% of providers prescribed injections). The difference between provider knowledge and capacity is insignificant, while a significant large gap exists between provider performance and knowledge/capacity (for 11 of 17 indicators). Our analysis indicated that capacity constraints play a minor role in driving IUM compared to provider performance in the treatment of asthma cases in rural China. If similar findings hold for other disease cases, this suggests that policies to reduce the IUM in rural China have largely been unsuccessful, and alternatives for improving aligning provider incentives with appropriate drug use should be explored.
Disseminating data is a core mission of international organizations (IOs). IO lending and conditionality may incentivize governments to collect and disclose aggregate economic data. We explore the association between loans from the Bretton Woods Institutions (BWIs) and an index of economic transparency derived from the data-reporting practices of governments to the World Bank. Using a matching method for causal inference complemented by a multilevel regression analysis, we find consistent evidence of a positive and statistically significant effect of BWI loans on the improvement of the level of economic transparency in developing countries.
Despite growing attention to job satisfaction as a social determinant of alcohol-related behaviors, few studies focus on its diverse impacts on alcohol consumption. Using data from the China Family Panel Study in 2018, this study uses logistic regression analysis to examine how job satisfaction affects alcohol consumption in China, finding that people who were satisfied with their jobs were more likely to be regularly drinking. Employed people who were satisfied with their working environment and working hours were more likely to regularly drink, but those who were satisfied with their wages and working security were less likely to be regularly drinking. Findings suggest that the link between job satisfaction and alcohol consumption is dynamic. Employment policies, working wellbeing improvement programs, and alcohol policy improvement should, therefore, be designed on the basis of a comprehensive account of entire job-related attitudes.
International trade separates consumption of goods from related environmental impacts, including greenhouse gas emissions from agriculture and land-use change (together referred to as “land-use emissions”). Through use of new emissions estimates and a multiregional input-output model, we evaluated land-use emissions embodied in global trade from 2004 to 2017. Annually, 27% of land-use emissions and 22% of agricultural land are related to agricultural products ultimately consumed in a different region from where they were produced. Roughly three-quarters of embodied emissions are from land-use change, with the largest transfers from lower-income countries such as Brazil, Indonesia, and Argentina to more industrialized regions such as Europe, the United States, and China. Mitigation of global land-use emissions and sustainable development may thus depend on improving the transparency of supply chains.
This paper presents a CFD modeling of deNOx process in a coal-fired power plant selective catalytic reduction (SCR) system, with focus on the transient hydrodynamics of multi-species flow and the influence of vortex on the deNOx process. For this purpose, a comprehensive CFD model is established, parameter study and model validation are performed, and the hydrodynamics, vortex evolution and species concentration distribution are numerically investigated. Simulation results indicate that many vortices with various scale/intensity/shape exist in the SCR system, causing apparent pressure pulsations and velocity fluctuations. High-intensity eddies are mainly distributed in the deflector group Ι, the NH3 nozzles, the static mixer, and the right part of the rectifying grille. The number of eddies decreases significantly with reducing the unit loads. Affected by vortex evolution, the NH3 concentration fluctuates in the SCR system, especially in the vertical flue. The deNOx process completes within 6 s, and the ammonia slip is less than 1.0 ppm, which well meets the requirement of industrial standards. In addition, the static mixer severely destroys the velocity uniformity but favors the mixing of NH3 and NOx. The rectifying grille improves the uniformity of flow field and species concentration field significantly.
Phosphate addition is commonly applied as an effective method to remediate lead contaminated sites via formation of low solubility lead phosphate solids. However, subsequent transport of the lead phosphate particles may impact the effectiveness of this remediation strategy. Hence, this study investigates the mechanisms involved in the aggregation of lead phosphate particles and their deposition in sand columns as a function of typical water chemistry parameters. Clean bed filtration theory was evaluated to predict the particle deposition behavior, using Derjaguin–Landau–Verwey–Overbeek (DLVO) theory to estimate particle-substrate interactions. The observed particle deposition was not predictable from the primary energy barrier in clean bed filtration models, even in simple monovalent background electrolyte (NaNO3), because weak deposition in a secondary energy minimum prevailed even at low ionic strength, and ripening occurred at ionic strengths of 12.5 mM or higher. For aged (aggregated) suspensions, straining also occurred at 12.5 mM or higher. Aggregation and deposition were further enhanced at low total P/Pb ratios (i.e., P/Pb = 1) and in the presence of divalent cations, such as Ca2+ (≥ 0.2 mM), which resulted in less negative particle surface potentials and weaker electrostatic repulsion forces. However, the presence of 5 mg C/L of humic acid induced strong steric or electrosteric repulsion, which hindered particle aggregation and deposition even in the presence of Ca2+. This study demonstrates the importance of myriad mechanisms in lead phosphate deposition and provides useful information for controlling water chemistry in phosphate applications for lead remediation.
This paper identifies and estimates the causal effect of an intervention on repeatedly measured units that co-exist and interact with one another in a social network, when the dichotomous intervention is not randomly assigned and the network evolution may be driven by choices of social agents. We adopt the potential outcome framework and develop identification assumptions to define and identify three estimands, namely, the direct treatment effect, the spillover effect, and the general treatment effect. Our framework incorporates social network ties as part of the joint treatment and treats longitudinal networks as variables rather than constants. It also considers complicated causal paths generated by interdependent outcomes. We propose a model-based estimation strategy and use a factor analysis to correct for biases caused by latent homophily. By imputing potential outcomes based on simultaneous equations, we disentangle spillover effects from direct treatment effects and explicitly estimate first-order and higher-order causal effects. The proposed method is easy to implement and flexible to accommodate a wide variety of networks.
