ArticleJournal of the Royal Society, Interface2019
Inferring who-infected-whom-where in the 2016 Zika outbreak in Singapore-a spatio-temporal model.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions.Journal of the Royal Society, Interface · 2021Pooled it
- Non-household environments make a major contribution to dengue transmission: implications for vector control.Royal Society open science · 2025Article
- Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China.International journal of environmental research and public health · 2022Article
- Using phylogenetics to infer HIV-1 transmission direction between known transmission pairs.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Coupling spatial statistics with social network analysis to estimate distinct risk areas of disease circulation to improve risk-based surveillance.Transboundary and emerging diseases · 2022Article
- Impact of sars-cov-2 interventions on dengue transmission.PLoS neglected tropical diseases · 2020Article
- Explicit characterization of human population connectivity reveals long run persistence of interregional dengue shocks.Journal of the Royal Society, Interface · 2020Article
- Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever.International journal of environmental research and public health · 2019Article
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Singapore experienced its first known Zika outbreak in 2016. Given the lack of herd immunity, the suitability of the climate for pathogen transmission, and the year-round presence of the vector- Aedes aegypti-Zika had the potential to become endemic, like dengue. Guillain-Barré syndrome and microcephaly are severe complications associated elsewhere with Zika and the risk of these complications makes understanding its spread imperative. We investigated the spatio-temporal spread of locally transmitted Zika in Singapore and assessed the relevance of non-residential transmission of Zika virus infections, by inferring the possible infection tree (i.e. who-infected-whom-where) and comparing inferences using geographically resolved data on cases' home, their work, or their home and work. We developed a spatio-temporal model using time of onset and both addresses of the Zika-confirmed cases between July and September 2016 to estimate the infection tree using Bayesian data augmentation. Workplaces were involved in a considerable fraction (64.2%) of infections, and homes and workplaces may be distant relative to the scale of transmission, allowing ambulant infected persons may act as the 'vector' infecting distant parts of the country. Contact tracing is a challenge for mosquito-borne diseases, but inferring the geographically structured transmission tree sheds light on the spatial transmission of Zika to immunologically naive regions of the country.
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