TY - JOUR
T1 - Evaluation of vaccination strategies for the metropolitan area of Madrid via agent-based simulation
AU - Singh, David E.
AU - Olmedo Luceron, Carmen
AU - Limia Sanchez, Aurora
AU - Guzman Merino, Miguel
AU - Duran Gonzalez, Christian
AU - Delgado-Sanz, Concepcion
AU - Gomez-Barroso, Diana
AU - Carretero, Jesus
AU - Marinescu, Maria Cristina
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2022/12/9
Y1 - 2022/12/9
N2 - Objective We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. Materials and methods The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator - including the vaccination model - is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million. Results The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation. Conclusion The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities.
AB - Objective We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. Materials and methods The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator - including the vaccination model - is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million. Results The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation. Conclusion The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities.
KW - COVID-19
KW - Epidemiology
KW - Health policy
KW - HEALTH SERVICES ADMINISTRATION & MANAGEMENT
KW - Public health
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UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_univeritat_ramon_llull&SrcAuth=WosAPI&KeyUT=WOS:000901531900037&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1136/bmjopen-2022-065937
DO - 10.1136/bmjopen-2022-065937
M3 - Article
C2 - 36600331
AN - SCOPUS:85144488322
SN - 2044-6055
VL - 12
JO - BMJ open
JF - BMJ open
IS - 12
M1 - e065937
ER -
