TY - JOUR
T1 - High-Resolution Agent-Based Modeling of COVID-19 Spreading in a Small Town
AU - Truszkowska, Agnieszka
AU - Behring, Brandon
AU - Hasanyan, Jalil
AU - Zino, Lorenzo
AU - Butail, Sachit
AU - Caroppo, Emanuele
AU - Jiang, Zhong Ping
AU - Rizzo, Alessandro
AU - Porfiri, Maurizio
N1 - Publisher Copyright:
© 2021 Wiley-VCH GmbH
PY - 2021/3
Y1 - 2021/3
N2 - Amid the ongoing COVID-19 pandemic, public health authorities and the general population are striving to achieve a balance between safety and normalcy. Ever changing conditions call for the development of theory and simulation tools to finely describe multiple strata of society while supporting the evaluation of “what-if” scenarios. Particularly important is to assess the effectiveness of potential testing approaches and vaccination strategies. Here, an agent-based modeling platform is proposed to simulate the spreading of COVID-19 in small towns and cities, with a single-individual resolution. The platform is validated on real data from New Rochelle, NY—one of the first outbreaks registered in the United States. Supported by expert knowledge and informed by reported data, the model incorporates detailed elements of the spreading within a statistically realistic population. Along with pertinent functionality such as testing, treatment, and vaccination options, the model accounts for the burden of other illnesses with symptoms similar to COVID-19. Unique to the model is the possibility to explore different testing approaches—in hospitals or drive-through facilities—and vaccination strategies that could prioritize vulnerable groups. Decision-making by public authorities could benefit from the model, for its fine-grain resolution, open-source nature, and wide range of features.
AB - Amid the ongoing COVID-19 pandemic, public health authorities and the general population are striving to achieve a balance between safety and normalcy. Ever changing conditions call for the development of theory and simulation tools to finely describe multiple strata of society while supporting the evaluation of “what-if” scenarios. Particularly important is to assess the effectiveness of potential testing approaches and vaccination strategies. Here, an agent-based modeling platform is proposed to simulate the spreading of COVID-19 in small towns and cities, with a single-individual resolution. The platform is validated on real data from New Rochelle, NY—one of the first outbreaks registered in the United States. Supported by expert knowledge and informed by reported data, the model incorporates detailed elements of the spreading within a statistically realistic population. Along with pertinent functionality such as testing, treatment, and vaccination options, the model accounts for the burden of other illnesses with symptoms similar to COVID-19. Unique to the model is the possibility to explore different testing approaches—in hospitals or drive-through facilities—and vaccination strategies that could prioritize vulnerable groups. Decision-making by public authorities could benefit from the model, for its fine-grain resolution, open-source nature, and wide range of features.
KW - COVID-19
KW - agent-based models
KW - epidemiology
KW - vaccination
UR - http://www.scopus.com/inward/record.url?scp=85100155710&partnerID=8YFLogxK
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U2 - 10.1002/adts.202000277
DO - 10.1002/adts.202000277
M3 - Article
AN - SCOPUS:85100155710
SN - 2513-0390
VL - 4
JO - Advanced Theory and Simulations
JF - Advanced Theory and Simulations
IS - 3
M1 - 2000277
ER -