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Theory and data for simulating fine-scale human movement in an urban environment

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations i...

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Autores principales: Perkins, T. Alex, Garcia, Andres J., Paz-Soldán, Valerie A., Stoddard, Steven T., Reiner, Robert C., Vazquez-Prokopec, Gonzalo, Bisanzio, Donal, Morrison, Amy C., Halsey, Eric S., Kochel, Tadeusz J., Smith, David L., Kitron, Uriel, Scott, Thomas W., Tatem, Andrew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4233749/
https://www.ncbi.nlm.nih.gov/pubmed/25142528
http://dx.doi.org/10.1098/rsif.2014.0642
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author Perkins, T. Alex
Garcia, Andres J.
Paz-Soldán, Valerie A.
Stoddard, Steven T.
Reiner, Robert C.
Vazquez-Prokopec, Gonzalo
Bisanzio, Donal
Morrison, Amy C.
Halsey, Eric S.
Kochel, Tadeusz J.
Smith, David L.
Kitron, Uriel
Scott, Thomas W.
Tatem, Andrew J.
author_facet Perkins, T. Alex
Garcia, Andres J.
Paz-Soldán, Valerie A.
Stoddard, Steven T.
Reiner, Robert C.
Vazquez-Prokopec, Gonzalo
Bisanzio, Donal
Morrison, Amy C.
Halsey, Eric S.
Kochel, Tadeusz J.
Smith, David L.
Kitron, Uriel
Scott, Thomas W.
Tatem, Andrew J.
author_sort Perkins, T. Alex
collection PubMed
description Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.
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spelling pubmed-42337492014-11-24 Theory and data for simulating fine-scale human movement in an urban environment Perkins, T. Alex Garcia, Andres J. Paz-Soldán, Valerie A. Stoddard, Steven T. Reiner, Robert C. Vazquez-Prokopec, Gonzalo Bisanzio, Donal Morrison, Amy C. Halsey, Eric S. Kochel, Tadeusz J. Smith, David L. Kitron, Uriel Scott, Thomas W. Tatem, Andrew J. J R Soc Interface Research Articles Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it. The Royal Society 2014-10-06 /pmc/articles/PMC4233749/ /pubmed/25142528 http://dx.doi.org/10.1098/rsif.2014.0642 Text en http://creativecommons.org/licenses/by/4.0/ © 2014 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Research Articles
Perkins, T. Alex
Garcia, Andres J.
Paz-Soldán, Valerie A.
Stoddard, Steven T.
Reiner, Robert C.
Vazquez-Prokopec, Gonzalo
Bisanzio, Donal
Morrison, Amy C.
Halsey, Eric S.
Kochel, Tadeusz J.
Smith, David L.
Kitron, Uriel
Scott, Thomas W.
Tatem, Andrew J.
Theory and data for simulating fine-scale human movement in an urban environment
title Theory and data for simulating fine-scale human movement in an urban environment
title_full Theory and data for simulating fine-scale human movement in an urban environment
title_fullStr Theory and data for simulating fine-scale human movement in an urban environment
title_full_unstemmed Theory and data for simulating fine-scale human movement in an urban environment
title_short Theory and data for simulating fine-scale human movement in an urban environment
title_sort theory and data for simulating fine-scale human movement in an urban environment
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4233749/
https://www.ncbi.nlm.nih.gov/pubmed/25142528
http://dx.doi.org/10.1098/rsif.2014.0642
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