ArticleMathematical biosciences2021
Optimal allocation of limited vaccine to control an infectious disease: Simple analytical conditions.
Article in Mathematical biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.Systematic reviews · 2024Pooled it
- Optimizing vaccine site locations while considering travel inconvenience and public health outcomes.Health care management science · 2026Article
- Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models.Infectious Disease Modelling · 2024Review
- Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.Naval research logistics · 2024Article
- Incorporating social determinants of health into transmission modeling of COVID-19 vaccine in the US: a scoping review.Lancet regional health. Americas · 2024Article
- Vaccination for communicable endemic diseases: optimal allocation of initial and booster vaccine doses.Journal of mathematical biology · 2024Article
- Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models.medRxiv : the preprint server for health sciences · 2024Article
- The hammer and the jab: Are COVID-19 lockdowns and vaccinations complements or substitutes?European journal of operational research · 2023Article
- Risk of Testing Positive for COVID-19 among Healthcare and Healthcare-Related Workers.Vaccines · 2023Article
- Understanding the impact of disease and vaccine mechanisms on the importance of optimal vaccine allocation.Infectious Disease Modelling · 2023Article
- Asymptotic Analysis of Optimal Vaccination Policies.Bulletin of mathematical biology · 2023Article
- Article
- Optimal vaccination in a SIRS epidemic model.Economic theory · 2022Article
- Sequential allocation of vaccine to control an infectious disease.Mathematical biosciences · 2022Article
- Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia.Transportation research. Part E, Logistics and transportation review · 2022Article
- Vaccine and inclusion.Journal of public economic theory · 2022Article
- Dynamic resource allocation for controlling pathogen spread on a large metapopulation network.Journal of the Royal Society, Interface · 2022Article
- Article
- Optimal allocation of limited vaccine to minimize the effective reproduction number.Mathematical biosciences · 2021Article
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2 authors.
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Abstract
When allocating limited vaccines to control an infectious disease, policy makers frequently have goals relating to individual health benefits (e.g., reduced morbidity and mortality) as well as population-level health benefits (e.g., reduced transmission and possible disease eradication). We consider the optimal allocation of a limited supply of a preventive vaccine to control an infectious disease, and four different allocation objectives: minimize new infections, deaths, life years lost, or quality-adjusted life years (QALYs) lost due to death. We consider an SIR model with n interacting populations, and a single allocation of vaccine at time 0. We approximate the model dynamics to develop simple analytical conditions characterizing the optimal vaccine allocation for each objective. We instantiate the model for an epidemic similar to COVID-19 and consider n=2 population groups: one group (individuals under age 65) with high transmission but low mortality and the other group (individuals age 65 or older) with low transmission but high mortality. We find that it is optimal to vaccinate younger individuals to minimize new infections, whereas it is optimal to vaccinate older individuals to minimize deaths, life years lost, or QALYs lost due to death. Numerical simulations show that the allocations resulting from our conditions match those found using much more computationally expensive algorithms such as exhaustive search. Sensitivity analysis on key parameters indicates that the optimal allocation is robust to changes in parameter values. The simple conditions we develop provide a useful means of informing vaccine allocation decisions for communicable diseases.
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