ArticleApplied network science2021
Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting.
Article in Applied network science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 2 citations in OpenAlex.
- TVISARS-CoV-2: a multicriteria index and urban dynamics in Minas Gerais, Brazil.Revista de saude publica · 2026Article
- Characterising protective immune responses to SARS-CoV-2 in urban and rural Malawi between February 2021 and April 2022.Scientific reports · 2025Article
- Strategies and Trends in COVID-19 Vaccination Delivery: What We Learn and What We May Use for the Future.Vaccines · 2023Article
- Assessing the transmissibility of epidemics involving epidemic zoning.BMC infectious diseases · 2023Article
- Quantitative Framework for Establishing Low-Risk Inter-District Travel Corridors During COVID-19.Transportation research record · 2023Article
- Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.Progress in planning · 2023Article
- Spatial networks and the spread of COVID-19: results and policy implications from Germany.Jahrbuch fur Regionalwissenschaftt = Review of regional research · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe dense social contact networks and high mobility in congested urban areas facilitate the rapid transmission of infectious diseases. Typical mechanistic 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.
findingsWhile 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 containment 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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.