Search results

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

Grounded in dynamic capability view, this research develops a decision support model, which enables determining consistent and sufficient configurations of resilience strategies to mitigate vaccine operations and distributions (O&D) challenges and thus improve O&D performance (i.e. O&DP).

Through qualitative in-depth interviews, the authors first identified challenges and resilience strategies related to vaccine O&D. Next, using the quality function deployment technique, three quantitative case studies were performed to determine the most important challenges and resilience strategies. Finally, utilising fuzzy set qualitative comparative analysis, the authors determine sufficient conditions of challenges and strategies leading to improve vaccine O&DP.

The findings reveal that strategies alone are not effective instead a combination of strategies and nullification of challenges is needed to enhance vaccine O&DP. Further, the findings revealed that not only the presence of challenges, but also the lack of strategies reduces the vaccine O&DP.

The authors' findings will assist the health service decision-makers for strategizing an effective and efficient vaccination program by selecting the right combination of challenges and resilience strategies.

The authors' study develops a novel decision support model and offers significant learning for the future vaccine O&DP.

The already-strained vaccine supply chain (VSC) of the expanded program for immunization (EPI) require a more robust and structured distribution network for pandemic/outbreak vaccination due to huge volume demand and time constraint. In this paper, a lean-agile-green (LAG) practices approach is proposed to improve the operational, economic and environmental efficiency of the VSC.

A fuzzy decision framework of importance performance analysis (IPA)–analytical hierarchy process (AHP)–technique for order for preference by similarity in ideal solution (TOPSIS) has been presented in this paper to prioritize the LAG practices on the basis of the influence on performance indicators. Sensitivity analysis is carried out to check the robustness of the presented model.

The derived result indicates that sustainable packaging, coordination among supply chain stakeholders and cold chain technology improvement are among the top practices affecting most of the performance parameters of VSC. The sensitivity analysis reveals that the priority of practices is highly dependent on the weightage of performance indicators.

This study's finding will help policymakers reframe strategies for sustainable VSC (SVSC) by including new management practices that can handle regular immunization programs as well as emergency mass vaccination.

To the best of the authors' knowledge, this is the first study that proposes the LAG framework for SVSC. The IPA–Fuzzy AHP (FAHP)–Fuzyy TOPSIS (FTOPSIS) is also a novel combination in decision-making.

The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.

Despite rapid success in bringing SARS-CoV-2 vaccines to distribution by multiple pharmaceutical corporations, supply chain failures in production and distribution can plague pandemic recovery. This review analyzes and addresses gaps in modeling supply chain resilience in general and specifically for vaccines in order to guide researchers and practitioners alike to improve critical function of vaccine supply chains in the face of inevitable disruptions.

Systematic review of the literature on modeling supply chain resilience from 2007 to 2020 is analyzed in tandem with the vaccine supply chain manufacturing literature. These trends are then used to apply a novel matrix analysis to seven Securities and Exchange Commission (SEC) annual filings of pharmaceutical corporations involved in COVID-19 vaccine manufacture and distribution.

Pharmaceutical corporations favor efficiency as they navigate regulatory, economic and other threats to their vaccine supply chains, neglecting resilience – absorption, adaptation and recovery from inevitable and unexpected disruptions. However, explicitly applying resilience analytics to the vaccine supply chain and further leveraging emerging network science tools found in the academic literature, such as artificial intelligence (AI), stress tests and digital twins, will help supply chain managers to better quantify efficiency/resilience tradeoffs across all associated networks/domains and support optimal system performance post disruption.

This is the first review addressing resilience analytics in vaccine supply chains and subsequent extension to operational management through novel matrix analyses of SEC Filings. The authors provide analyses and recommendations that facilitate resilience quantification capabilities for vaccine supply chain managers, regulatory agencies and corporate stakeholders and are especially relevant for pandemic response, including application to the SARS-CoV-2 vaccines.

The purpose of this paper is to identify the key performance indicators (KPIs) of vaccine supply chain of Universal Immunization Program (UIP) India, and measure their impact on vaccine supply chain performance improvement, so that results of this study can help the decision makers manage the activity and effectiveness of their resources in order to improve vaccine delivery performance and child immunization coverage.

The 41 KPIs in terms of four dimension of the balanced scorecard (BSC), i.e. financial, customer, internal process and learning and growth have been identified and validated from the literature and expert’s opinions. Further, the impact of internal process and learning and growth performance indicators on the vaccine supply chain performance improvement have been evaluated using two-way assessment. The rankings obtained using two-way assessment are then compared to DEMATEL approach to validate the results.

The results from the analysis reveal that “Enhancement in employee work satisfaction” (LG3=10.08 percent), “Enhancement in professional vaccine supply chain managers and leaders” (LG2 = 6.70 percent) “Improvement in planning and coordination in the supply chain” (LG9 = 6.57 percent) are the three critical performance indicators having maximum impact on vaccine supply chain performance improvement. The decision makers should give priority to these performance indicators to improve delivery performance and immunization coverage.

This study focuses on the improvement in vaccine delivery performance, therefore, analysis and findings can be useful to government immunization programs of India to other developing nations to improve child immunization coverage.

To our knowledge, this paper is first to attempt to provide a direction to improve immunization coverage through vaccine supply chain performance indicators.

This paper aims to provide an integrated production-routing model in a three-echelon supply chain containing a two-layer transportation system to minimize the total costs of production, transportation, inventory holding and expired drugs treatment. In the proposed problem, some specifications such as multisite manufacturing, simultaneous pickup and delivery and uncertainty in parameters are considered.

At first, a mathematical model has been proposed for the problem. Then, one possibilistic model and one robust possibilistic model equivalent to the initial model are provided regarding the uncertain nature of the model parameters and the inaccessibility of their probability function. Finally, the performance of the proposed model is evaluated using the real data collected from a pharmaceutical production center in Iran. The results reveal the proper performance of the proposed models.

The results obtained from applying the proposed model to a real-life production center indicated that the number of expired drugs has decreased because of using this model, also the costs of the system were reduced owing to integrating simultaneous drug pickup and delivery operations. Moreover, regarding the results of simulations, the robust possibilistic model had the best performance among the proposed models.

This research considers a two-layer vehicle routing in a production-routing problem with inventory planning. Moreover, multisite manufacturing, simultaneous pickup of the expired drugs and delivery of the drugs to the distribution centers are considered. Providing a robust possibilistic model for tackling the uncertainty in demand, costs, production capacity and drug expiration costs is considered as another remarkable feature of the proposed model.

The recent Childhood Immunization Initiative of the Clinton Administration was a dramatic and ambitious policy response to what we will show is a case of significant management and implementation failure. Interpreted by the Administration as a policy failure, low rates of early childhood immunization met with an aggressive and targeted policy response which ultimately diverted attention away from significant evidence of fundamental problems of service delivery, infrastructure, and parental knowledge and behavior. Analyzes and seeks to evaluate the reasons for the poor fit between the diagnosis of the problem of existing childhood immunization policy and the ultimate policy prescription of the Clinton Administration which relies almost exclusively on reducing the price of vaccines.

The study aims to develop an integrated quantitative approach and suggest a framework to assess the impact of a technological intervention on the internal process dimension of the vaccine supply chain (VSC) system for multiple administered regions.

An evaluation index system is developed by selecting suitable performance indicators (PIs) that define the objectives of a VSC. Then multicriteria decision-making (MCDM) methods are applied to obtain pre and post-intervention relative ranks for the regions and performance scores of the objectives. A bilateral data envelopment analysis (DEA) compares significant efficiency differences between improvement and deterioration groups.

This study demonstrates that technological intervention improves the internal process dimension of a VSC for the regions under consideration. The empirical study delivers two groups of regions showing improvement or deterioration in relative performance ranking due to the technological intervention. However, the efficiency-based bilateral comparison may reveal an insignificant difference between the two groups.

Decision-makers associated with VSC will find the suggested model helpful in assessing the impact of technological intervention. They can easily identify specific objectives of VSC's internal process dimension, whether a particular region has observed an improvement or deterioration in its relative performance and maximize the outcome by focusing on the areas of concern for a specific region.

This study is the first to provide a quantitative approach that empirically determines relative performance improvement or deterioration of different regions for a set of identified VSC objectives in the context of the Indian states.