Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway
The Mumbai Suburban Railways, \emph{locals}, are a key transit infrastructure of the city and is crucial for resuming normal economic activity. To reduce disease transmission, policymakers can enforce reduced crowding and mandate wearing of masks. \emph{Cohorting} -- forming groups of travelers that...
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Main Authors | , , , , , , , , , , , , |
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Format | Journal Article |
Language | English |
Published |
23.12.2020
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Subjects | |
Online Access | Get full text |
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Summary: | The Mumbai Suburban Railways, \emph{locals}, are a key transit infrastructure
of the city and is crucial for resuming normal economic activity. To reduce
disease transmission, policymakers can enforce reduced crowding and mandate
wearing of masks. \emph{Cohorting} -- forming groups of travelers that always
travel together, is an additional policy to reduce disease transmission on
\textit{locals} without severe restrictions. Cohorting allows us to: ($i$) form
traveler bubbles, thereby decreasing the number of distinct interactions over
time; ($ii$) potentially quarantine an entire cohort if a single case is
detected, making contact tracing more efficient, and ($iii$) target cohorts for
testing and early detection of symptomatic as well as asymptomatic cases.
Studying impact of cohorts using compartmental models is challenging because of
the ensuing representational complexity. Agent-based models provide a natural
way to represent cohorts along with the representation of the cohort members
with the larger social network. This paper describes a novel multi-scale
agent-based model to study the impact of cohorting strategies on COVID-19
dynamics in Mumbai. We achieve this by modeling the Mumbai urban region using a
detailed agent-based model comprising of 12.4 million agents. Individual
cohorts and their inter-cohort interactions as they travel on locals are
modeled using local mean field approximations. The resulting multi-scale model
in conjunction with a detailed disease transmission and intervention simulator
is used to assess various cohorting strategies. The results provide a
quantitative trade-off between cohort size and its impact on disease dynamics
and well being. The results show that cohorts can provide significant benefit
in terms of reduced transmission without significantly impacting ridership and
or economic \& social activity. |
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DOI: | 10.48550/arxiv.2012.12839 |