Abstract: Assessing the interplay between travel
patterns and SARS‑CoV‑2 outbreak in realistic
urban setting
Rohan Patil1†
, Raviraj Dave 2†
, Harsh Patel 1
, Viraj M. Shah3
, Deep Chakrabarti4 and Udit Bhatia2*
Abstract
Background: The dense social contact networks and high mobility in congested
urban areas facilitate the rapid transmission of infectious diseases. Typical mechanis-
tic epidemiological models are either based on uniform mixing with ad-hoc contact
processes or need real-time or archived population mobility data to simulate the social
networks. However, the rapid and global transmission of the novel coronavirus (SARS-
CoV-2) has led to unprecedented lockdowns at global and regional scales, leaving the
archived datasets to limited use.
Findings: While it is often hypothesized that population density is a significant driver
in disease propagation, the disparate disease trajectories and infection rates exhibited
by the different cities with comparable densities require a high-resolution description
of the disease and its drivers. In this study, we explore the impact of creation of con-
tainment zones on travel patterns within the city. Further, we use a dynamical network-
based infectious disease model to understand the key drivers of disease spread at
sub-kilometer scales demonstrated in the city of Ahmedabad, India, which has been
classified as a SARS-CoV-2 hotspot. We find that in addition to the contact network
and population density, road connectivity patterns and ease of transit are strongly
correlated with the rate of transmission of the disease. Given the limited access to
real-time traffic data during lockdowns, we generate road connectivity networks using
open-source imageries and travel patterns from open-source surveys and government
reports. Within the proposed framework, we then analyze the relative merits of social
distancing, enforced lockdowns, and enhanced testing and quarantining mitigating
the disease spread.
Scope: Our results suggest that the declaration of micro-containment zones within
the city with high road network density combined with enhanced testing can help in
containing the outbreaks until clinical interventions become available.
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