ArticleEpidemiology and infection2018
Travel distance and human movement predict paths of emergence and spatial spread of chikungunya in Thailand.
Article in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.BMC infectious diseases · 2023Pooled it
- Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions.Journal of the Royal Society, Interface · 2021Pooled it
- Detection of and Early Genomic Insights into Chikungunya Virus, Bolivia, 2025.Emerging infectious diseases · 2026Article
- Impact of COVID-19 Vaccination in Thailand: Averted Deaths and Severe Infections Across Age Groups.Tropical medicine and infectious disease · 2024Article
- Statistical modeling for identifying chikungunya high-risk areas of two large-scale outbreaks in Thailand's southernmost provinces.Scientific reports · 2023Article
- Behavioral-biological surveillance of emerging infectious diseases among a dynamic cohort in Thailand.BMC infectious diseases · 2022Article
- Countries at risk of importation of chikungunya virus cases from Southern Thailand: A modeling study.Infectious Disease Modelling · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Human movement contributes to the probability that pathogens will be introduced to new geographic locations. Here we investigate the impact of human movement on the spatial spread of Chikungunya virus (CHIKV) in Southern Thailand during a recent re-emergence. We hypothesised that human movement, population density, the presence of habitat conducive to vectors, rainfall and temperature affect the transmission of CHIKV and the spatiotemporal pattern of cases seen during the emergence. We fit metapopulation transmission models to CHIKV incidence data. The dates at which incidence in each of 151 districts in Southern Thailand exceeded specified thresholds were the target of model fits. We confronted multiple alternative models to determine which factors were most influential in the spatial spread. We considered multiple measures of spatial distance between districts and adjacency networks and also looked for evidence of long-distance translocation (LDT) events. The best fit model included driving-distance between districts, human movement, rubber plantation area and three LDT events. This work has important implications for predicting the spatial spread and targeting resources for control in future CHIKV emergences. Our modelling framework could also be adapted to other disease systems where population mobility may drive the spatial advance of outbreaks.
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