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Open AccessArticle

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

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Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
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Starhub Limited, 67 Ubi Avenue 1, #05-01 StarHub Green, Singapore 408942, Singapore
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Environmental Public Health Operations, National Environment Agency, 40 Scotts Road, #13-00 Environment Building, Singapore 228231, Singapore
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School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
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Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(5), 808; https://doi.org/10.3390/ijerph16050808
Received: 10 January 2019 / Revised: 22 February 2019 / Accepted: 1 March 2019 / Published: 5 March 2019
(This article belongs to the Special Issue Mosquito-Borne Disease)
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. View Full-Text
Keywords: zika; human movement; mobile phone data; disease transmission; risk zika; human movement; mobile phone data; disease transmission; risk
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Rajarethinam, J.; Ong, J.; Lim, S.-H.; Tay, Y.-H.; Bounliphone, W.; Chong, C.-S.; Yap, G.; Ng, L.-C. Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore. Int. J. Environ. Res. Public Health 2019, 16, 808.

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