@article{adc6f54224e640bd9fe90102335a5e90,
title = "Predicting the Effects of Waning Vaccine Immunity Against COVID-19 through High-Resolution Agent-Based Modeling",
abstract = "The potential waning of the vaccination immunity to COVID-19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near-complete restoration of normalcy. Should also testing be relaxed, a resurgent COVID-19 wave in winter 2021/2022 might be witnessed. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. A projected study with an outlook of 6 months explores the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent-based model tuned on a medium-sized US town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid-spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to the continuously evolving nature of the pandemic. This study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed.",
keywords = "COVID-19, agent-based model, epidemiology, urban science, vaccination",
author = "Agnieszka Truszkowska and Lorenzo Zino and Sachit Butail and Emanuele Caroppo and Jiang, {Zhong Ping} and Alessandro Rizzo and Maurizio Porfiri",
note = "Funding Information: The authors would like to acknowledge Maya Fayed and Sihan (Silvia) Wei for updating the town database, identifying part of the new model parameters, and introducing the code for the out-of-town non-essential locations. The work of A.T. and M.P. was partially supported by National Science Foundation (CMMI-1561134 and CMMI-2027990). The work of E.C., Z.-P.J., and A.R. was partially supported by National Science Foundation (CMMI-2027990). The work of S.B. was partially supported by National Science Foundation (CMMI-2027988). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding Information: The authors would like to acknowledge Maya Fayed and Sihan (Silvia) Wei for updating the town database, identifying part of the new model parameters, and introducing the code for the out‐of‐town non‐essential locations. The work of A.T. and M.P. was partially supported by National Science Foundation (CMMI‐1561134 and CMMI‐2027990). The work of E.C., Z.‐P.J., and A.R. was partially supported by National Science Foundation (CMMI‐2027990). The work of S.B. was partially supported by National Science Foundation (CMMI‐2027988). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2022 Wiley-VCH GmbH.",
year = "2022",
month = jun,
doi = "10.1002/adts.202100521",
language = "English (US)",
volume = "5",
journal = "Advanced Theory and Simulations",
issn = "2513-0390",
publisher = "Wiley-VCH Verlag",
number = "6",
}