Interventions for an Artemisinin‐based Malaria Medicine Supply Chain

Artemisinin combination therapy, the most effective malaria treatment today, is manufactured from an agriculturally derived starting material Artemisia annua. Artemisinin, the main ingredient in malaria medicines, is extracted from Artemisia leaves and used in the production of medicine for treating malaria. The artemisinin market has witnessed high volatility in the supply and price of artemisinin extract. A large fraction of malaria medicines for endemic countries in sub‐Saharan Africa is financed by the Global Fund to Fight AIDS, TB, and Malaria and the US President's Malaria Initiative. These agencies together with the World Health Organization, UNITAID, the United Kingdom Department for International Development and the Bill and Melinda Gates Foundation are exploring ways to increase the level of artemisinin production, reduce volatility of artemisinin prices, and improve overall access to malaria medicines for the population. We develop a model of the supply chain, calibrate the model using field data, and investigate the impact of various interventions. Our model shows that initiatives aimed at improving average yield, creating a support‐price for agricultural artemisinin, and a larger and carefully managed supply of semi‐synthetic artemisinin have the greatest potential for improving supply and reducing price volatility of artemisinin‐based malaria medicine.     

A looser cointegration concept using fractional integration parameters and quantification of market responsiveness

Many economic variables are fractionally integrated of order d, FI(d) with unequal d's. For modeling their long-run equilibria, we explain why the usual cointegration fails to exist and the unit root type tests have low power. Hence, we propose a looser concept called “tie integration”. A new numerical minimization problem reveals the value of d in the absence of tie integration, denoted by d_null. We use the d from residuals of a regression, as well as, d_null to devise a new index called strength of tie (SOT). An application quantifies market responsiveness.     

Supply Chains and Global Health: An Imperative for Bringing Operations Management Scholarship into Action

Many people in developing countries do not have access to effective vaccines, medicines, and other life‐saving health technologies. Shortage of health care workers, severe financial constraints, and lack of awareness are some of the major obstacles that prevent higher access. However, ineffective and poorly designed supply chains for purchasing and distributing the medicines, vaccines, and health technologies are one of the most important barriers to increasing access. We argue that the ineffectiveness of the global health supply chain can be attributed largely to: coordination problems across multiple stakeholders with widely divergent objectives, lack of careful supply chain design, and use of myopic operational objectives and metrics. The operations management research community can contribute to improving this by applying existing knowledge to the field of global health delivery and by researching new frameworks of analysis which would then become the cornerstones for policy advice to those who design, operate, or finance these supply chains.     

The propagation of lean thinking in SMEs

Abstract

Small and Medium-sized Enterprises (SMEs) play a pivotal role in economic growth, industrial output, and employment creation. However, SMEs are often ignored by researchers as far as the adoption of lean is concerned in comparison to Large Enterprises (LEs). Therefore, the literature regarding lean implementation in SMEs is not conspicuous, and many SMEs have only a limited understanding and awareness of lean. This paper offers a comprehensive literature review with a focus on the implementation of lean in SMEs and explores the applicability of lean thinking in such environments. An attempt is made to provide an analysis of lean practices that have been applied in SMEs and critical success factors for lean transformation in SMEs. It also contributes to the field of lean implementation research by proposing a framework for lean in SMEs and identifies the scope of future research.     

Health status and health care services among older persons in India

India is characterized by significant rural-based living, population heterogeneity, financial constraints, and reverse sex ratio. Traditions of joint families, life-long physical activity, vegetarianism, and social and spiritual enrichment, all known to promote healthy aging, are widely prevalent. With the increasing pace of population aging, the health of older persons in India has been the focus of recent attention. Existing data indicate a significant morbidity among the aged, much of which may remain subclinical. Considerable variations in morbidity exist with respect to gender, place of residence (rural vs. urban), and socioeconomic status. Rapid demographic transition without a concomitant epidemiological transition is responsible for the dual load of infections and degenerative diseases in older persons, these being common causes of death. Most age-related morbidity is preventable. Health promotion and cost-effective interventions based on the primary health care approach over a lifelong course, especially at the village level, will greatly help towards achieving the goal of healthy aging. The rapidly changing socioeconomic scenario in India also calls for appropriate policy actions to achieve this goal.     

Optimal allocation of subjects in a matched pair cluster-randomized trial with fixed number of heterogeneous clusters

In cluster-randomized trials, investigators randomize clusters of individuals such as households, medical practices, schools or classrooms despite the unit of interest are the individuals. It results in the loss of efficiency in terms of the estimation of the unknown parameters as well as the power of the test for testing the treatment effects. To recoup this efficiency loss, some studies pair similar clusters and randomize treatment within pairs. However, the clusters within a treatment arm might be heterogeneous in nature. In this article, we propose a locally optimal design that accounts the clusters heterogeneity and optimally allocates the subjects within each cluster. To address the dependency of design on the unknown parameters, we also discuss Bayesian optimal designs. Performances of proposed designs are investigated numerically through some data examples.     

Estimating standard error of intra-class correlation coefficients up to three level unbalanced nested clinical trials

ABSTRACT

Very often researchers plan a balanced design for cluster randomization clinical trials in conducting medical research, but unavoidable circumstances lead to unbalanced data. By adopting three or more levels of nested designs, they usually ignore the higher level of nesting and consider only two levels, this situation leads to underestimation of variance at higher levels. While calculating the sample size for three-level nested designs, in order to achieve desired power, intra-class correlation coefficients (ICCs) at individual level as well as higher levels need to be considered and must be provided along with respective standard errors. In the present paper, the standard errors of analysis of variance (ANOVA) estimates of ICCs for three-level unbalanced nested design are derived. To conquer the strong appeal of distributional assumptions, balanced design, equality of variances between clusters and large sample, general expressions for standard errors of ICCs which can be deployed in unbalanced cluster randomization trials are postulated. The expressions are evaluated on real data as well as highly unbalanced simulated data.     

Factors affecting mosquito populations in created wetlands in urban landscapes

Constructed, created and restored wetlands are gaining popularity in urban areas due to many ecosystem services they provide. However, there is a concern over mosquito breeding in such wetlands. We studied factors affecting mosquito populations in two experimental flow-through created wetlands, a stormwater wetland, a pond and 40 mono-specific and mixed plant mesocosms (1?m²) at the Olentangy River Wetland Research Park (ORWRP) in Columbus, Ohio. The flow-through created wetlands had less mosquito larval density (2 to 4/dip) compared to the pond (36.2?±?8.4/dip) (p?<?0.00001) and stormwater wetland (24.9?±?10.2/dip) (p?=?0.002). Sites with higher larval density in the flow-through wetlands were outflow regions (p?=?0.009) and emergent vegetation sites (p?=?0.023). Mixed vegetation communities consisting of Sparganium eurycarpum, Juncus effusus, and Schoenoplectus tabernaemontani rather than mono specific Typha communities provided most conducive environment for mosquito breeding (p?<?0.0001). Mesocosm plots with steady inflow (10?cm depth) and deep water (20?cm) in summer and shallow water (5?cm) in spring had higher mosquito densities than mesocosm plots with other hydrological conditions. Among water quality parameters, conductivity (p?=?0.004) positively and dissolved oxygen (p?=?0.052) negatively correlated with mosquito larval density. Six mosquito species identified in all water bodies were Culex pipiens, Culex salinarius, Culex restuans, Uranotaenia sapphirina, Anopheles quadrimaculatus, and Anopheles punctipennis some of which may transmit deadly human pathogens. This information will be useful for targeting mosquito populations in specific sections of urban created wetlands and to develop improved designs for urban wetlands.