Aidan Findlater1, Rahim Moineddin2, Dylan Kain3, Juan Yang4, Xiling Wang4, Shengjie Lai5, Kamran Khan6, Isaac I Bogoch7. 1. Department of Medicine, McMaster University, Hamilton, Canada. 2. Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada. 3. Department of Medicine, University of Toronto, Toronto, Canada. 4. School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, 130 Dong'An Road, Shanghai, 200032, China. 5. School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, 130 Dong'An Road, Shanghai, 200032, China; WorldPop, Department of Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ, UK; Flowminder Foundation, Roslagsgatan 17, SE-11355, Stockholm, Sweden. 6. Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Department of Medicine, University of Toronto, Toronto, Canada. 7. Department of Medicine, University of Toronto, Toronto, Canada; Divisions of General Internal Medicine and Infectious Diseases, University Health Network, Toronto, Canada. Electronic address: isaac.bogoch@uhn.ca.
Abstract
BACKGROUND: Dengue virus importation from abroad is still the main driver of dengue incidence in China. Using global flight data to model importation may improve our understanding and prediction of dengue virus importation and onward transmission. METHODS: A retrospective analysis was performed of surveillance cases of dengue infections imported to China and volume of air traffic to China for the years 2005 through 2014, inclusive. The data were aggregated by year, destination province, and source country. Descriptive statistics were calculated, and a random effects negative binomial model was created to predict the number of imported cases based on the volume of travelers from dengue-endemic countries. RESULTS: There were 1,822 cases of imported dengue infections over the study period. Most imported cases are from a small number of high-incidence countries with a large volume of travel to China, most notably Myanmar (22% of cases). The number of imported cases of dengue infections increased by 5.9% for every 10% increase in travel volume from dengue-endemic countries. CONCLUSION: Patterns of air travel have a measurable impact on the importation of dengue to China. Modelling dengue importation risk may be a useful strategy to direct public health surveillance and interventions.
BACKGROUND:Dengue virus importation from abroad is still the main driver of dengue incidence in China. Using global flight data to model importation may improve our understanding and prediction of dengue virus importation and onward transmission. METHODS: A retrospective analysis was performed of surveillance cases of dengue infections imported to China and volume of air traffic to China for the years 2005 through 2014, inclusive. The data were aggregated by year, destination province, and source country. Descriptive statistics were calculated, and a random effects negative binomial model was created to predict the number of imported cases based on the volume of travelers from dengue-endemic countries. RESULTS: There were 1,822 cases of imported dengue infections over the study period. Most imported cases are from a small number of high-incidence countries with a large volume of travel to China, most notably Myanmar (22% of cases). The number of imported cases of dengue infections increased by 5.9% for every 10% increase in travel volume from dengue-endemic countries. CONCLUSION: Patterns of air travel have a measurable impact on the importation of dengue to China. Modelling dengue importation risk may be a useful strategy to direct public health surveillance and interventions.
Authors: Donald Salami; César Capinha; Maria do Rosário Oliveira Martins; Carla Alexandra Sousa Journal: PLoS One Date: 2020-03-12 Impact factor: 3.240
Authors: Xiaobo Liu; Keke Liu; Yujuan Yue; Haixia Wu; Shu Yang; Yuhong Guo; Dongsheng Ren; Ning Zhao; Jun Yang; Qiyong Liu Journal: Front Public Health Date: 2021-01-18