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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2014
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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. |
format | Online Article Text |
id | pubmed-4233749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
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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