Substantial Impact of Post Vaccination Contacts on Cumulative Infections during Viral Epidemics
Background: The start of 2021 will be marked by a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic.
Methods: A deterministic model of epidemic evolution is analyzed, with 7 compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections.
Results: When an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host-host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%.
Conclusions: Mathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can affect the course of an epidemic. Given the relatively short window between inoculation and the acquisition of immunity, these results might merit consideration for an immediate, practical public health response.
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2020 |
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| Enthalten in: |
medRxiv : the preprint server for health sciences - (2020) vom: 24. Dez. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Rochman, Nash D [VerfasserIn] |
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| Links: |
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| Themen: |
Compartment model |
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Date Revised 03.04.2024 published: Electronic UpdateIn: F1000Res. 2021 Apr 23;10:315. - PMID 34504684 Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2020.12.19.20248554 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM31962210X |
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| 500 | |a Date Revised 03.04.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a UpdateIn: F1000Res. 2021 Apr 23;10:315. - PMID 34504684 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Background: The start of 2021 will be marked by a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic | ||
| 520 | |a Methods: A deterministic model of epidemic evolution is analyzed, with 7 compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections | ||
| 520 | |a Results: When an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host-host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20% | ||
| 520 | |a Conclusions: Mathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can affect the course of an epidemic. Given the relatively short window between inoculation and the acquisition of immunity, these results might merit consideration for an immediate, practical public health response | ||
| 650 | 4 | |a Preprint | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Vaccine Escape | |
| 650 | 4 | |a Vaccine Resistance | |
| 650 | 4 | |a compartment model | |
| 700 | 1 | |a Wolf, Yuri I |e verfasserin |4 aut | |
| 700 | 1 | |a Koonin, Eugene V |e verfasserin |4 aut | |
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