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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Main Authors: Rajarethinam, Jayanthi, Ong, Janet, Lim, Shi-Hui, Tay, Yu-Heng, Bounliphone, Wacha, Chong, Chee-Seng, Yap, Grace, Ng, Lee-Ching
Other Authors: School of Biological Sciences
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/105757
http://hdl.handle.net/10220/48745
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1057572023-02-28T17:06:29Z 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 School of Biological Sciences Zika DRNTU::Science::Biological sciences Human Movement 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. Published version 2019-06-14T02:12:33Z 2019-12-06T21:57:22Z 2019-06-14T02:12:33Z 2019-12-06T21:57:22Z 2019 Journal Article Rajarethinam, J., Ong, J., Lim, S.-H., Tay, Y.-H., Bounliphone, W., Chong, C.-S., . . . Ng, L.-C. (2019). Using human movement data to identify potential areas of Zika transmission : case study of the largest Zika cluster in Singapore. International Journal of Environmental Research and Public Health, 16(5), 808-. doi:10.3390/ijerph16050808 1661-7827 https://hdl.handle.net/10356/105757 http://hdl.handle.net/10220/48745 10.3390/ijerph16050808 en International Journal of Environmental Research and Public Health © 2019 The Author(s). 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/). 13 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Zika
DRNTU::Science::Biological sciences
Human Movement
spellingShingle Zika
DRNTU::Science::Biological sciences
Human Movement
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
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.
author2 School of Biological Sciences
author_facet School of Biological Sciences
Rajarethinam, Jayanthi
Ong, Janet
Lim, Shi-Hui
Tay, Yu-Heng
Bounliphone, Wacha
Chong, Chee-Seng
Yap, Grace
Ng, Lee-Ching
format Article
author Rajarethinam, Jayanthi
Ong, Janet
Lim, Shi-Hui
Tay, Yu-Heng
Bounliphone, Wacha
Chong, Chee-Seng
Yap, Grace
Ng, Lee-Ching
author_sort Rajarethinam, Jayanthi
title 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_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_sort using human movement data to identify potential areas of zika transmission : case study of the largest zika cluster in singapore
publishDate 2019
url https://hdl.handle.net/10356/105757
http://hdl.handle.net/10220/48745
_version_ 1759858365005037568