Grauer, Jens ; Löwen, Hartmut ; Liebchen, Benno (2022)
Strategic spatiotemporal vaccine distribution increases the survival rate in an infectious disease like Covid-19.
In: Scientific Reports, 2022, 10
doi: 10.26083/tuprints-00021091
Artikel, Zweitveröffentlichung, Verlagsversion
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
Kurzbeschreibung (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 R₀∼1.5−4 and by about 35% for R₀∼1). 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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Grauer, Jens ; Löwen, Hartmut ; Liebchen, Benno |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Strategic spatiotemporal vaccine distribution increases the survival rate in an infectious disease like Covid-19 |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Verlag: | Springer Nature |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Scientific Reports |
| Jahrgang/Volume einer Zeitschrift: | 10 |
| Kollation: | 10 Seiten |
| DOI: | 10.26083/tuprints-00021091 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/21091 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung aus gefördertem Golden Open Access |
| Kurzbeschreibung (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 R₀∼1.5−4 and by about 35% for R₀∼1). 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. |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-210911 |
| Zusätzliche Informationen: | The source code of the model has been deposited in a recognized public source code repository (Zenodo, http://doi.org/10.5281/zenodo.4122012) Supplementary movie: https://doi.org/10.1038/s41598-020-78447-3 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 500 Naturwissenschaften und Mathematik > 530 Physik |
| Fachbereich(e)/-gebiet(e): | 05 Fachbereich Physik 05 Fachbereich Physik > Institut für Physik Kondensierter Materie (IPKM) 05 Fachbereich Physik > Institut für Physik Kondensierter Materie (IPKM) > Theorie weicher Materie |
| Hinterlegungsdatum: | 05 Apr 2022 13:14 |
| Letzte Änderung: | 06 Apr 2022 09:23 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Strategic spatiotemporal vaccine distribution increases the survival rate in an infectious disease like Covid-19. (deposited 05 Apr 2022 13:14) [Gegenwärtig angezeigt]
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