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Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia
In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Mac...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451810/ https://www.ncbi.nlm.nih.gov/pubmed/28573009 http://dx.doi.org/10.1098/rsos.170046 |
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author | Searle, Kelly M. Lubinda, Jailos Hamapumbu, Harry Shields, Timothy M. Curriero, Frank C. Smith, David L. Thuma, Philip E. Moss, William J. |
author_facet | Searle, Kelly M. Lubinda, Jailos Hamapumbu, Harry Shields, Timothy M. Curriero, Frank C. Smith, David L. Thuma, Philip E. Moss, William J. |
author_sort | Searle, Kelly M. |
collection | PubMed |
description | In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, was selected to carry a GPS data logger for one month from October 2013 to August 2014. Density maps and activity space plots were created to evaluate seasonal movement patterns. Time spent outside the household compound during anopheline biting times, and time spent in malaria high- and low-risk areas, were calculated. There was evidence of seasonal movement patterns, with increased long-distance movement during the dry season. A median of 10.6% (interquartile range (IQR): 5.8–23.8) of time was spent away from the household, which decreased during anopheline biting times to 5.6% (IQR: 1.7–14.9). The per cent of time spent in malaria high-risk areas for participants residing in high-risk areas ranged from 83.2% to 100%, but ranged from only 0.0% to 36.7% for participants residing in low-risk areas. Interventions targeted at the household may be more effective because of restricted movement during the rainy season, with limited movement between high- and low-risk areas. |
format | Online Article Text |
id | pubmed-5451810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-54518102017-06-01 Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia Searle, Kelly M. Lubinda, Jailos Hamapumbu, Harry Shields, Timothy M. Curriero, Frank C. Smith, David L. Thuma, Philip E. Moss, William J. R Soc Open Sci Biology (Whole Organism) In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, was selected to carry a GPS data logger for one month from October 2013 to August 2014. Density maps and activity space plots were created to evaluate seasonal movement patterns. Time spent outside the household compound during anopheline biting times, and time spent in malaria high- and low-risk areas, were calculated. There was evidence of seasonal movement patterns, with increased long-distance movement during the dry season. A median of 10.6% (interquartile range (IQR): 5.8–23.8) of time was spent away from the household, which decreased during anopheline biting times to 5.6% (IQR: 1.7–14.9). The per cent of time spent in malaria high-risk areas for participants residing in high-risk areas ranged from 83.2% to 100%, but ranged from only 0.0% to 36.7% for participants residing in low-risk areas. Interventions targeted at the household may be more effective because of restricted movement during the rainy season, with limited movement between high- and low-risk areas. The Royal Society Publishing 2017-05-03 /pmc/articles/PMC5451810/ /pubmed/28573009 http://dx.doi.org/10.1098/rsos.170046 Text en © 2017 The Authors. http://creativecommons.org/licenses/by/4.0/ 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 | Biology (Whole Organism) Searle, Kelly M. Lubinda, Jailos Hamapumbu, Harry Shields, Timothy M. Curriero, Frank C. Smith, David L. Thuma, Philip E. Moss, William J. Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title | Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title_full | Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title_fullStr | Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title_full_unstemmed | Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title_short | Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia |
title_sort | characterizing and quantifying human movement patterns using gps data loggers in an area approaching malaria elimination in rural southern zambia |
topic | Biology (Whole Organism) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451810/ https://www.ncbi.nlm.nih.gov/pubmed/28573009 http://dx.doi.org/10.1098/rsos.170046 |
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