COVID-19 Vaccination Strategies Considering Hesitancy Using Particle-Based Epidemic Simulation
Abstract Vaccine hesitancy is one of the critical factors in achieving herd immunity and suppressing the COVID-19 epidemic. Many countries face this as an acute public health issue that diminishes the efficacy of their vaccination campaigns. Epidemic modeling and simulation can be used to predict the effects of different vaccination strategies. In this work, we present an open-source particle-based COVID-19 simulator with a vaccination module capable of taking into account the vaccine hesitancy of the population. To demonstrate the efficacy of the simulator, we conducted extensive simulations for the province of Lecco, Italy. The results indicate that the combination of both high vaccination rate and low hesitancy leads to faster epidemic suppression..
Medienart: |
Preprint |
---|
Erscheinungsjahr: |
2021 |
---|---|
Erschienen: |
2021 |
Enthalten in: |
bioRxiv.org - (2021) vom: 30. Sept. Zur Gesamtaufnahme - year:2021 |
---|
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Karabay, Aknur [VerfasserIn] |
---|
Links: |
Volltext [kostenfrei] |
---|
doi: |
10.1101/2021.09.26.21264153 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
XBI032674902 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | XBI032674902 | ||
003 | DE-627 | ||
005 | 20230429082626.0 | ||
007 | cr uuu---uuuuu | ||
008 | 210929s2021 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1101/2021.09.26.21264153 |2 doi | |
035 | |a (DE-627)XBI032674902 | ||
035 | |a (biorXiv)10.1101/2021.09.26.21264153 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | |a 570 |q DE-84 | |
100 | 1 | |a Karabay, Aknur |e verfasserin |4 aut | |
245 | 1 | 0 | |a COVID-19 Vaccination Strategies Considering Hesitancy Using Particle-Based Epidemic Simulation |
264 | 1 | |c 2021 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Abstract Vaccine hesitancy is one of the critical factors in achieving herd immunity and suppressing the COVID-19 epidemic. Many countries face this as an acute public health issue that diminishes the efficacy of their vaccination campaigns. Epidemic modeling and simulation can be used to predict the effects of different vaccination strategies. In this work, we present an open-source particle-based COVID-19 simulator with a vaccination module capable of taking into account the vaccine hesitancy of the population. To demonstrate the efficacy of the simulator, we conducted extensive simulations for the province of Lecco, Italy. The results indicate that the combination of both high vaccination rate and low hesitancy leads to faster epidemic suppression. | ||
700 | 1 | |a Kuzdeuov, Askat |e verfasserin |4 aut | |
700 | 1 | |a Varol, Huseyin Atakan |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2021) vom: 30. Sept. |
773 | 1 | 8 | |g year:2021 |g day:30 |g month:09 |
856 | 4 | 0 | |u http://dx.doi.org/10.1101/2021.09.26.21264153 |z kostenfrei |3 Volltext |
912 | |a GBV_XBI | ||
912 | |a SSG-OLC-PHA | ||
951 | |a AR | ||
952 | |j 2021 |b 30 |c 09 | ||
953 | |2 045F |a 570 |