A Vaccination Simulator for COVID-19: Effective and Sterilizing Immunization Cases
Abstract Accurate modeling provides a means by which a complex problem can be examined for informed decision-making. We present a particle-based SEIR epidemic simulator as a tool to assess the impact of vaccination strategies on viral propagation and to model both sterilizing and effective immunization outcomes. The simulator includes modules to support contact tracing of the interactions amongst individuals as well as epidemiological testing of the general population. The simulator particles are distinguished by age, thus enabling a more accurate representation of the rates of infection and mortality in accordance with differential demographic susceptibilities and medical outcomes. Moreover, thanks to the age differentiation of particles, the vaccination can be simulated based on the age group descending order or randomly across all age groups. The simulator can be calibrated by region of interest and variable vaccination strategies (i.e. random or prioritized by age) so as to enable locality-sensitive virus mitigation policy measures and resource allocation. The results described, based on the experience of the province of Lecco, Italy, indicate that the tool can be used to evaluate vaccination strategies in a way that incorporates local circumstances of viral propagation and demographic susceptibilities. Further, the simulator accounts for modeling the distinction between sterilizing immunization, in which immunized people are no longer contagious, and that of effective immunization, in which symptoms and mortality outcomes are diminished but individuals can still transmit the virus. The sterilizing-age-based vaccination scenario results in the least number of deaths compared to other scenarios. Furthermore, the results show that the vaccination of the most vulnerable portion of the population should be prioritized for the effective immunization case. As the vaccination rate increases, the mortality gap between the scenarios shrinks..
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Preprint| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
bioRxiv.org - (2021) vom: 15. Dez. Zur Gesamtaufnahme - year:2021 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Karabay, Aknur [VerfasserIn] |
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| Links: |
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| doi: |
10.1101/2021.03.28.21254468 |
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| PPN (Katalog-ID): |
XBI02029025X |
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| 520 | |a Abstract Accurate modeling provides a means by which a complex problem can be examined for informed decision-making. We present a particle-based SEIR epidemic simulator as a tool to assess the impact of vaccination strategies on viral propagation and to model both sterilizing and effective immunization outcomes. The simulator includes modules to support contact tracing of the interactions amongst individuals as well as epidemiological testing of the general population. The simulator particles are distinguished by age, thus enabling a more accurate representation of the rates of infection and mortality in accordance with differential demographic susceptibilities and medical outcomes. Moreover, thanks to the age differentiation of particles, the vaccination can be simulated based on the age group descending order or randomly across all age groups. The simulator can be calibrated by region of interest and variable vaccination strategies (i.e. random or prioritized by age) so as to enable locality-sensitive virus mitigation policy measures and resource allocation. The results described, based on the experience of the province of Lecco, Italy, indicate that the tool can be used to evaluate vaccination strategies in a way that incorporates local circumstances of viral propagation and demographic susceptibilities. Further, the simulator accounts for modeling the distinction between sterilizing immunization, in which immunized people are no longer contagious, and that of effective immunization, in which symptoms and mortality outcomes are diminished but individuals can still transmit the virus. The sterilizing-age-based vaccination scenario results in the least number of deaths compared to other scenarios. Furthermore, the results show that the vaccination of the most vulnerable portion of the population should be prioritized for the effective immunization case. As the vaccination rate increases, the mortality gap between the scenarios shrinks. | ||
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