Analyzing Vaccine Manufacturing Supply Chain Disruptions for Pandemic Preparedness using Discrete-Event Simulation

The COVID-19 pandemic exposed critical vulnerabilities in vaccine supply chains, highlighting the need for robust manufacturing for rapid pandemic response to support CEPI’s 100 Days Mission. We develop a discrete-event simulation model to analyze supply chain disruptions and enables policymakers and vaccine manufacturers to quantify disruptions and assess mitigation strategies. Unlike prior studies examining components in isolation, our approach integrates production processes, quality assurance and control (QA/QC) activities, and raw material procurement to capture system-wide dynamics. A detailed mRNA case study analyzes disruption scenarios for a facility targeting 50 million doses: facility shutdowns, workforce reductions, raw material shortages, infrastructure failures, extended procurement lead times, and increased QA/QC capacity. Three main insights emerge. First, QA/QC personnel are the primary bottleneck, with utilization reaching 84.5% under normal conditions while machine utilization remains below 33%. Doubling QA/QC capacity increases annual output by 79.1%, offering greater returns than equipment investments. Second, raw material disruptions are highly detrimental, with extended lead times reducing three-year output by 19.6% and causing stockouts during 51.8% of production time. Third, the model shows differential resilience: acute disruptions (workforce shortages, shutdowns, power outages) allow recovery within 6 to 9 weeks, whereas chronic disruptions (supply delays) cause prolonged performance degradation.

💡 Research Summary

The paper addresses the critical vulnerabilities exposed by the COVID‑19 pandemic in vaccine manufacturing supply chains and proposes a comprehensive solution to support CEPI’s “100‑Day Mission.” Recognizing that traditional supply‑chain models (e.g., multi‑echelon inventory optimization) assume stationary demand and deterministic lead times, the authors argue that these approaches are inadequate for pandemic scenarios characterized by sudden demand spikes and frequent disruptions. To capture the complex, stochastic interactions among production processes, quality‑assurance/quality‑control (QA/QC) activities, and raw‑material procurement, they develop the first discrete‑event simulation (DES) model that integrates all three subsystems within a single framework.

The methodology section justifies DES as the most appropriate tool because vaccine manufacturing is inherently event‑driven: batch completions, material arrivals, and test approvals occur at discrete points and trigger state changes throughout the system. The model represents a hypothetical mRNA vaccine facility targeting 50 million doses per year. It includes detailed process steps (cell culture, formulation, fill‑finish), QA/QC testing stages (raw‑material release, in‑process testing, final release), and a procurement network for critical inputs such as specialized lipids and single‑use bioreactor bags. Stochastic distributions are assigned to lead times, equipment breakdowns, and personnel availability, allowing the simulation to generate realistic variability.

Six disruption scenarios are examined over a three‑year horizon: (1) facility shutdowns/power outages, (2) workforce reductions of 30 % and 50 %, (3) raw‑material shortages, (4) infrastructure failures, (5) extended procurement lead times, and (6) a mitigation scenario where QA/QC capacity is doubled. Performance metrics include annual output, inventory stock‑outs, resource utilization, and time to recovery.

Key findings are striking. Under baseline conditions, QA/QC personnel operate at 84.5 % utilization, making them the primary bottleneck, while equipment utilization remains below 33 %. Doubling QA/QC capacity yields a 79.1 % increase in annual output, indicating that investment in skilled personnel delivers far higher returns than additional equipment. Raw‑material disruptions are even more damaging: a 20 % increase in lead time reduces three‑year cumulative output by 19.6 % and causes stock‑outs for 51.8 % of production time. Acute disruptions (shutdowns, workforce cuts, power loss) recover within 6–9 weeks, whereas chronic supply‑chain delays lead to prolonged performance degradation with no quick rebound.

The authors synthesize three major contributions: (1) the integrated DES model fills a gap in the literature where previous studies examined production, QA/QC, or procurement in isolation; (2) a decision‑support system that enables policymakers and manufacturers to quantitatively assess the impact of disruptions and evaluate mitigation strategies before a crisis hits; (3) an applied mRNA case study that validates the model and uncovers actionable insights. Limitations are acknowledged, including the difficulty of modeling regulatory approval timelines and the omission of global logistics networks. Future work is suggested on linking the DES to digital‑twin platforms, extending the model to multi‑facility, multi‑region settings, and incorporating cost‑benefit analyses of resilience investments.

Overall, the paper demonstrates that strengthening QA/QC workforce capacity and securing diversified, strategically stocked raw‑material supplies are the most effective levers for enhancing vaccine manufacturing resilience, thereby advancing the goal of delivering safe, effective vaccines within 100 days of a pandemic declaration.