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Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting
BACKGROUND: The 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 mobi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803387/ https://www.ncbi.nlm.nih.gov/pubmed/33457497 http://dx.doi.org/10.1007/s41109-020-00346-3 |
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author | Patil, Rohan Dave, Raviraj Patel, Harsh Shah, Viraj M. Chakrabarti, Deep Bhatia, Udit |
author_facet | Patil, Rohan Dave, Raviraj Patel, Harsh Shah, Viraj M. Chakrabarti, Deep Bhatia, Udit |
author_sort | Patil, Rohan |
collection | PubMed |
description | BACKGROUND: The 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. 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 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. |
format | Online Article Text |
id | pubmed-7803387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78033872021-01-13 Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting Patil, Rohan Dave, Raviraj Patel, Harsh Shah, Viraj M. Chakrabarti, Deep Bhatia, Udit Appl Netw Sci Research BACKGROUND: The 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. 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 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. Springer International Publishing 2021-01-13 2021 /pmc/articles/PMC7803387/ /pubmed/33457497 http://dx.doi.org/10.1007/s41109-020-00346-3 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Patil, Rohan Dave, Raviraj Patel, Harsh Shah, Viraj M. Chakrabarti, Deep Bhatia, Udit Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title | Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title_full | Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title_fullStr | Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title_full_unstemmed | Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title_short | Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting |
title_sort | assessing the interplay between travel patterns and sars-cov-2 outbreak in realistic urban setting |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803387/ https://www.ncbi.nlm.nih.gov/pubmed/33457497 http://dx.doi.org/10.1007/s41109-020-00346-3 |
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