Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19

Single-walled carbon nanotube-protein complex: A strategy to improve the immune response to protein in mice

Vaccines represent an effective tool for controlling disease infection. As a key component of vaccines, many types of adjuvants have been developed and used today. This study is designed to investigate the efficacy of single-walled carbon nanotubes (SWCNTs) as a new adjuvant. The results showed that SWCNT could adsorb the antigen by intermolecular action, and the adsorption rate was significantly higher after dispersion of the SWCNTs in a sonic bath. The titer of specific antibody of mice in the SWCNTs group was higher than that of the mice in the antigen control group, confirming the adjuvant efficacy of SWCNTs. During immunisation, the specific antibody was detected earlier in the mice of the SWCNTs group, especially when the amount of antigen was reduced. And it was proved that the titer of antibodies was higher after subcutaneous and intraperitoneal injection compared to intramuscular injection. Most importantly, the mice immunised with SWCNTs showed almost the same level of immunity as the mice in the FCA (Freund's complete adjuvant) group, indicating that the SWCNTs were an effective adjuvant. In addition, the mice in the SWCNT group maintained antibody levels for 90 days after the last booster vaccination and showed a good state of health during the observed period. We also found that the SWCNTs were able to induce macrophages activation and enhance antigen uptake by mouse peritoneal macrophages.

Confirmation of a measurement model for hospital supply chain resilience

Background

The hospital supply chain has revealed increasing vulnerabilities and disruptions in the wake of the COVID-19 pandemic, threatening the healthcare services and patient safety. The resilience of hospital supply chains has emerged as a paramount concern within the healthcare system. However, there is a lack of systematic research to develop an instrument tailored to the healthcare industry that is both valid and reliable for measuring hospital supply chain resilience. Therefore, this study aims to construct and validate a comprehensive scale for assessing hospital supply chain resilience, based on dynamic capability theory.

Methods

This study followed rigorous scale development steps, starting with a literature review and 15 semi-structured interviews to generate initial items. These items were then refined through expert panel feedback and three rounds of Delphi studies. Using data from 387 hospitals in Province S, mainland China, the scale underwent rigorous testing and validation using structural equation modeling. To ensure the most effective model, five alternative models were examined to determine the most suitable parsimonious model.

Results

The study produced a 26-item scale that captures five dimensions of resilience in line with dynamic capability theory: anticipation, adaptation, response, recovery, and learning, all showing satisfactory consistency, reliability and validity.

Conclusion

The multi-dimensional scale offers hospital managers a valuable tool to identify areas needing attention and improvement, benchmark resilience against their counterparts, and ultimately strengthen their supply chains against unexpected risks.

Modeling Supply and Demand Dynamics of Vaccines against Epidemic-Prone Pathogens: Case Study of Ebola Virus Disease

Health emergencies caused by epidemic-prone pathogens (EPPs) have increased exponentially in recent decades. Although vaccines have proven beneficial, they are unavailable for many pathogens. Furthermore, achieving timely and equitable access to vaccines against EPPs is not trivial. It requires decision-makers to capture numerous interrelated factors across temporal and spatial scales, with significant uncertainties, variability, delays, and feedback loops that give rise to dynamic and unexpected behavior. Therefore, despite progress in filling R&D gaps, the path to licensure and the long-term viability of vaccines against EPPs continues to be unclear. This paper presents a quantitative system dynamics modeling framework to evaluate the long-term sustainability of vaccine supply under different vaccination strategies. Data from both literature and 50 expert interviews are used to model the supply and demand of a prototypical Ebolavirus Zaire (EBOV) vaccine. Specifically, the case study evaluates dynamics associated with proactive vaccination ahead of an outbreak of similar magnitude as the 2018-2020 epidemic in North Kivu, Democratic Republic of the Congo. The scenarios presented demonstrate how uncertainties (e.g., duration of vaccine-induced protection) and design criteria (e.g., priority geographies and groups, target coverage, frequency of boosters) lead to important tradeoffs across policy aims, public health outcomes, and feasibility (e.g., technical, operational, financial). With sufficient context and data, the framework provides a foundation to apply the model to a broad range of additional geographies and priority pathogens. Furthermore, the ability to identify leverage points for long-term preparedness offers directions for further research.