Search

Several studies have shown that the performance of a supply chain is heavily influenced by the pattern of relationships among firms. This paper analyzes the structure of relationships (network topology) that leads to the highest agility of a food supply chain when sudden demand changes occur. To do this, a simulation model that represents a supply chain and specific rules to allocate orders is built. The supply chain in the model follows the specific characteristics of trade in the primary sector. The model is fitted to the conditions of a real seafood supply chain in Mexico. Agility is measured through the effect on the order fulfillment of a sudden demand shock and the recovery time of this rate to previous values. The simulation results show that the most suitable structure depends on how product is distributed among suppliers. If product is evenly shared, supply chains with homogeneous topologies are more agile than supply chains with heterogeneous topologies, but the result is the opposite if product is unevenly shared among suppliers. Other previous recommendations, such as having multiple suppliers and horizontal links, are confirmed by the simulations. These findings contribute to the general debate on which is the optimal topology for an agile supply chain. [ABSTRACT FROM AUTHOR]

Introduction: Verbal autopsy (VA) is a useful tool for evaluating causes of death, especially in places with limited or no vital registration systems. The Population Health Metrics Research Consortium (PHMRC) developed a validated questionnaire and a set of automated methods to determine the cause of death from a VA. However, the application of these methods needs to be tested in a community environment. Objective: To estimate cause-specific mortality fractions (CSMFs) using VAs and compare them against those obtained in the vital statistics of the state of Hidalgo, Mexico. Methods: A random sample of deaths occurred in 2009 was selected from vital statistics in the state of Hidalgo. The full PHMRC validated VA instrument was applied to the relatives of the deceased, and the cause of death was determined using Tariff's automated method. The causes of death were grouped into 34 causes for adults, 21 for children and 6 for newborns. Results were compared with cause of death on death certificates for all deaths. Results: A total of 1,198 VAs were analyzed. The Tariff method was not able to assign a cause of death in only 9% of adults, 2% of children and 7% of neonatal deaths. The CSMFs obtained from the Tariff method were similar in some cases to those of vital statistics (e.g. cirrhosis), but different in others (e.g. sepsis). Conclusion: The application of VAs in a community sample, analyzed with the Tariff method, allowed assigning a cause of death to most of the cases, with results similar to those of vital statistics for most conditions. This tool can be useful to strengthen the quality of vital statistics. [ABSTRACT FROM AUTHOR]