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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Bibliographic Details
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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Summary: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.