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The duration of travel impacts the spatial dynamics of infectious diseases

Humans can impact the spatial transmission dynamics of infectious diseases by introducing pathogens into susceptible environments. The rate at which this occurs depends in part on human-mobility patterns. Increasingly, mobile-phone usage data are used to quantify human mobility and investigate the i...

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Autores principales: Giles, John R., zu Erbach-Schoenberg, Elisabeth, Tatem, Andrew J., Gardner, Lauren, Bjørnstad, Ottar N., Metcalf, C. J. E., Wesolowski, Amy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486699/
https://www.ncbi.nlm.nih.gov/pubmed/32839329
http://dx.doi.org/10.1073/pnas.1922663117
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author Giles, John R.
zu Erbach-Schoenberg, Elisabeth
Tatem, Andrew J.
Gardner, Lauren
Bjørnstad, Ottar N.
Metcalf, C. J. E.
Wesolowski, Amy
author_facet Giles, John R.
zu Erbach-Schoenberg, Elisabeth
Tatem, Andrew J.
Gardner, Lauren
Bjørnstad, Ottar N.
Metcalf, C. J. E.
Wesolowski, Amy
author_sort Giles, John R.
collection PubMed
description Humans can impact the spatial transmission dynamics of infectious diseases by introducing pathogens into susceptible environments. The rate at which this occurs depends in part on human-mobility patterns. Increasingly, mobile-phone usage data are used to quantify human mobility and investigate the impact on disease dynamics. Although the number of trips between locations and the duration of those trips could both affect infectious-disease dynamics, there has been limited work to quantify and model the duration of travel in the context of disease transmission. Using mobility data inferred from mobile-phone calling records in Namibia, we calculated both the number of trips between districts and the duration of these trips from 2010 to 2014. We fit hierarchical Bayesian models to these data to describe both the mean trip number and duration. Results indicate that trip duration is positively related to trip distance, but negatively related to the destination population density. The highest volume of trips and shortest trip durations were among high-density districts, whereas trips among low-density districts had lower volume with longer duration. We also analyzed the impact of including trip duration in spatial-transmission models for a range of pathogens and introduction locations. We found that inclusion of trip duration generally delays the rate of introduction, regardless of pathogen, and that the variance and uncertainty around spatial spread increases proportionally with pathogen-generation time. These results enhance our understanding of disease-dispersal dynamics driven by human mobility, which has potential to elucidate optimal spatial and temporal scales for epidemic interventions.
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spelling pubmed-74866992020-09-23 The duration of travel impacts the spatial dynamics of infectious diseases Giles, John R. zu Erbach-Schoenberg, Elisabeth Tatem, Andrew J. Gardner, Lauren Bjørnstad, Ottar N. Metcalf, C. J. E. Wesolowski, Amy Proc Natl Acad Sci U S A Biological Sciences Humans can impact the spatial transmission dynamics of infectious diseases by introducing pathogens into susceptible environments. The rate at which this occurs depends in part on human-mobility patterns. Increasingly, mobile-phone usage data are used to quantify human mobility and investigate the impact on disease dynamics. Although the number of trips between locations and the duration of those trips could both affect infectious-disease dynamics, there has been limited work to quantify and model the duration of travel in the context of disease transmission. Using mobility data inferred from mobile-phone calling records in Namibia, we calculated both the number of trips between districts and the duration of these trips from 2010 to 2014. We fit hierarchical Bayesian models to these data to describe both the mean trip number and duration. Results indicate that trip duration is positively related to trip distance, but negatively related to the destination population density. The highest volume of trips and shortest trip durations were among high-density districts, whereas trips among low-density districts had lower volume with longer duration. We also analyzed the impact of including trip duration in spatial-transmission models for a range of pathogens and introduction locations. We found that inclusion of trip duration generally delays the rate of introduction, regardless of pathogen, and that the variance and uncertainty around spatial spread increases proportionally with pathogen-generation time. These results enhance our understanding of disease-dispersal dynamics driven by human mobility, which has potential to elucidate optimal spatial and temporal scales for epidemic interventions. National Academy of Sciences 2020-09-08 2020-08-24 /pmc/articles/PMC7486699/ /pubmed/32839329 http://dx.doi.org/10.1073/pnas.1922663117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Giles, John R.
zu Erbach-Schoenberg, Elisabeth
Tatem, Andrew J.
Gardner, Lauren
Bjørnstad, Ottar N.
Metcalf, C. J. E.
Wesolowski, Amy
The duration of travel impacts the spatial dynamics of infectious diseases
title The duration of travel impacts the spatial dynamics of infectious diseases
title_full The duration of travel impacts the spatial dynamics of infectious diseases
title_fullStr The duration of travel impacts the spatial dynamics of infectious diseases
title_full_unstemmed The duration of travel impacts the spatial dynamics of infectious diseases
title_short The duration of travel impacts the spatial dynamics of infectious diseases
title_sort duration of travel impacts the spatial dynamics of infectious diseases
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486699/
https://www.ncbi.nlm.nih.gov/pubmed/32839329
http://dx.doi.org/10.1073/pnas.1922663117
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