Analyzing Vaccine Manufacturing Supply Chain Disruptions for Pandemic Preparedness using Discrete-Event Simulation
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866915786887528448 |
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| author | Kelchtermans, Robin Stienen, Valentijn Dietrich, Guido Bernuzzi, Mauro Vandaele, Nico |
| author_facet | Kelchtermans, Robin Stienen, Valentijn Dietrich, Guido Bernuzzi, Mauro Vandaele, Nico |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_08988 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Analyzing Vaccine Manufacturing Supply Chain Disruptions for Pandemic Preparedness using Discrete-Event Simulation Kelchtermans, Robin Stienen, Valentijn Dietrich, Guido Bernuzzi, Mauro Vandaele, Nico General Economics Economics 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. |
| title | Analyzing Vaccine Manufacturing Supply Chain Disruptions for Pandemic Preparedness using Discrete-Event Simulation |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2602.08988 |