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Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore

Singapore experienced its first Zika virus (ZIKV) cluster in August 2016. To understand the implication of human movement on disease spread, a retrospective study was conducted using aggregated and anonymized mobile phone data to examine movement from the cluster to identify areas of possible transm...

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Autores principales: Rajarethinam, Jayanthi, Ong, Janet, Lim, Shi-Hui, Tay, Yu-Heng, Bounliphone, Wacha, Chong, Chee-Seng, Yap, Grace, Ng, Lee-Ching
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427696/
https://www.ncbi.nlm.nih.gov/pubmed/30841598
http://dx.doi.org/10.3390/ijerph16050808
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author Rajarethinam, Jayanthi
Ong, Janet
Lim, Shi-Hui
Tay, Yu-Heng
Bounliphone, Wacha
Chong, Chee-Seng
Yap, Grace
Ng, Lee-Ching
author_facet Rajarethinam, Jayanthi
Ong, Janet
Lim, Shi-Hui
Tay, Yu-Heng
Bounliphone, Wacha
Chong, Chee-Seng
Yap, Grace
Ng, Lee-Ching
author_sort Rajarethinam, Jayanthi
collection PubMed
description Singapore experienced its first Zika virus (ZIKV) cluster in August 2016. To understand the implication of human movement on disease spread, a retrospective study was conducted using aggregated and anonymized mobile phone data to examine movement from the cluster to identify areas of possible transmission. An origin–destination model was developed based on the movement of three groups of individuals: (i) construction workers, (ii) residents and (iii) visitors out of the cluster locality to other parts of the island. The odds ratio of ZIKV cases in a hexagon visited by an individual from the cluster, independent of the group of individuals, is 3.20 (95% CI: 2.65–3.87, p-value < 0.05), reflecting a higher count of ZIKV cases when there is a movement into a hexagon from the cluster locality. A comparison of independent ROC curves tested the statistical significance of the difference between the areas under the curves of the three groups of individuals. Visitors (difference in AUC = 0.119) and residents (difference in AUC = 0.124) have a significantly larger difference in area under the curve compared to the construction workers (p-value < 0.05). This study supports the proof of concept of using mobile phone data to approximate population movement, thus identifying areas at risk of disease transmission.
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spelling pubmed-64276962019-04-10 Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore Rajarethinam, Jayanthi Ong, Janet Lim, Shi-Hui Tay, Yu-Heng Bounliphone, Wacha Chong, Chee-Seng Yap, Grace Ng, Lee-Ching Int J Environ Res Public Health Article Singapore experienced its first Zika virus (ZIKV) cluster in August 2016. To understand the implication of human movement on disease spread, a retrospective study was conducted using aggregated and anonymized mobile phone data to examine movement from the cluster to identify areas of possible transmission. An origin–destination model was developed based on the movement of three groups of individuals: (i) construction workers, (ii) residents and (iii) visitors out of the cluster locality to other parts of the island. The odds ratio of ZIKV cases in a hexagon visited by an individual from the cluster, independent of the group of individuals, is 3.20 (95% CI: 2.65–3.87, p-value < 0.05), reflecting a higher count of ZIKV cases when there is a movement into a hexagon from the cluster locality. A comparison of independent ROC curves tested the statistical significance of the difference between the areas under the curves of the three groups of individuals. Visitors (difference in AUC = 0.119) and residents (difference in AUC = 0.124) have a significantly larger difference in area under the curve compared to the construction workers (p-value < 0.05). This study supports the proof of concept of using mobile phone data to approximate population movement, thus identifying areas at risk of disease transmission. MDPI 2019-03-05 2019-03 /pmc/articles/PMC6427696/ /pubmed/30841598 http://dx.doi.org/10.3390/ijerph16050808 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rajarethinam, Jayanthi
Ong, Janet
Lim, Shi-Hui
Tay, Yu-Heng
Bounliphone, Wacha
Chong, Chee-Seng
Yap, Grace
Ng, Lee-Ching
Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title_full Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title_fullStr Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title_full_unstemmed Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title_short Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore
title_sort using human movement data to identify potential areas of zika transmission: case study of the largest zika cluster in singapore
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427696/
https://www.ncbi.nlm.nih.gov/pubmed/30841598
http://dx.doi.org/10.3390/ijerph16050808
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