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

Jayanthi Rajarethinam, Janet Ong, Shi-Hui Lim, Yu-Heng Tay, Wacha Bounliphone, Chee-Seng Chong, Grace Yap and Lee-Ching Ng
Additional contact information
Jayanthi Rajarethinam: Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
Janet Ong: Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
Shi-Hui Lim: Starhub Limited, 67 Ubi Avenue 1, #05-01 StarHub Green, Singapore 408942, Singapore
Yu-Heng Tay: Starhub Limited, 67 Ubi Avenue 1, #05-01 StarHub Green, Singapore 408942, Singapore
Wacha Bounliphone: Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
Chee-Seng Chong: Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
Grace Yap: Environmental Public Health Operations, National Environment Agency, 40 Scotts Road, #13-00 Environment Building, Singapore 228231, Singapore
Lee-Ching Ng: Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore

IJERPH, 2019, vol. 16, issue 5, 1-13

Abstract: 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.

Keywords: zika; human movement; mobile phone data; disease transmission; risk (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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