ArticlePloS one2016
Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19.European journal of operational research · 2023Article
- Comparative performance of between-population vaccine allocation strategies with applications for emerging pandemics.Vaccine · 2023Article
- Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic.European journal of operational research · 2023Article
- Timing the race of vaccination, new variants, and relaxing restrictions during COVID-19 pandemic.Journal of computational science · 2022Article
- Characterisation of Omicron Variant during COVID-19 Pandemic and the Impact of Vaccination, Transmission Rate, Mortality, and Reinfection in South Africa, Germany, and Brazil.Biotech (Basel (Switzerland)) · 2022Article
- Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?Physica D. Nonlinear phenomena · 2021Article
- A hybrid simulation model to study the impact of combined interventions on Ebola epidemic.PloS one · 2021Article
- A theoretical single-parameter model for urbanisation to study infectious disease spread and interventions.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.