ArticleScientific reports2020
Strategic spatiotemporal vaccine distribution increases the survival rate in an infectious disease like Covid-19.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed, 8 citations in OpenAlex.
- Understanding Nash epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models.Infectious Disease Modelling · 2024Review
- How mathematical modelling can inform outbreak response vaccination.BMC infectious diseases · 2024Review
- Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models.medRxiv : the preprint server for health sciences · 2024Article
- Modeling geographic vaccination strategies for COVID-19 in Norway.PLoS computational biology · 2024Article
- Rational social distancing policy during epidemics with limited healthcare capacity.PLoS computational biology · 2023Article
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- Projecting the COVID-19 immune landscape in Japan in the presence of waning immunity and booster vaccination.Journal of theoretical biology · 2023Article
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- Seasonal Variation Analysis for Weekly Cases, Deaths, and Hospitalizations of COVID-19 in the United States.Advances in experimental medicine and biology · 2023Article
- Optimal allocation strategies for prioritized geographical vaccination for Covid-19.Physica A · 2022Article
- Identifying high-risk areas for dog-mediated rabies using Bayesian spatial regression.One health (Amsterdam, Netherlands) · 2022Article
- Modeling COVID-19 transmission between age groups in the United States considering virus mutations, vaccinations, and reinfection.Scientific reports · 2022Article
- COVID-19 transmission in cities.European economic review · 2022Article
- Mathematical modeling to study the impact of immigration on the dynamics of the COVID-19 pandemic: A case study for Venezuela.Spatial and spatio-temporal epidemiology · 2022Article
- Optimising the impact of COVID-19 vaccination on mortality and hospitalisations using an individual additive risk measuring approach based on a risk adjustment scheme.The European journal of health economics : HEPAC : health economics in prevention and care · 2022Article
- Mutation induced infection waves in diseases like COVID-19.Scientific reports · 2022Article
- Reconstruction of a large-scale outbreak of SARS-CoV-2 infection in Iceland informs vaccination strategies.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Present hopes to conquer the Covid-19 epidemic are largely based on the expectation of a rapid availability of vaccines. However, once vaccine production starts, it will probably take time before there is enough vaccine for everyone, evoking the question how to distribute it best. While present vaccination guidelines largely focus on individual-based factors, i.e. on the question to whom vaccines should be provided first, e.g. to risk groups or to individuals with a strong social-mixing tendency, here we ask if a strategic spatiotemporal distribution of vaccines, e.g. to prioritize certain cities, can help to increase the overall survival rate of a population subject to an epidemic disease. To this end, we propose a strategy for the distribution of vaccines in time and space, which sequentially prioritizes regions with the most new cases of infection during a certain time frame and compare it with the standard practice of distributing vaccines demographically. Using a simple statistical model we find that, for a locally well-mixed population, the proposed strategy strongly reduces the number of deaths (by about a factor of two for basic reproduction numbers of [Formula: see text] and by about 35% for [Formula: see text]). The proposed vaccine distribution strategy establishes the idea that prioritizing individuals not only regarding individual factors, such as their risk of spreading the disease, but also according to the region in which they live can help saving lives. The suggested vaccine distribution strategy can be tested in more detailed models in the future and might inspire discussions regarding the importance of spatiotemporal distribution rules for vaccination guidelines.
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