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利用航空旅行数据预测登革热输入中国:一项建模研究。

The use of air travel data for predicting dengue importation to China: A modelling study.

机构信息

Department of Medicine, McMaster University, Hamilton, Canada.

Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada.

出版信息

Travel Med Infect Dis. 2019 Sep-Oct;31:101446. doi: 10.1016/j.tmaid.2019.07.002. Epub 2019 Jul 5.

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.

摘要

背景

登革热病毒从国外输入仍是中国登革热发病的主要驱动因素。利用全球航班数据来建立输入模型可能有助于我们更好地理解和预测登革热病毒的输入和传播。

方法

对 2005 年至 2014 年期间输入中国的登革热感染监测病例和到中国的航空客流量进行回顾性分析。数据按年份、目的地省份和来源国进行汇总。计算描述性统计数据,并建立随机效应负二项模型,根据来自登革热流行国家的旅行者数量来预测输入病例数。

结果

在研究期间,共有 1822 例输入性登革热感染病例。大多数输入性病例来自少数高发病率国家,这些国家到中国的旅行量很大,其中最显著的是缅甸(占病例的 22%)。来自登革热流行国家的旅行量每增加 10%,输入性登革热感染病例就会增加 5.9%。

结论

航空旅行模式对中国输入登革热具有可衡量的影响。建立登革热输入风险模型可能是指导公共卫生监测和干预的有效策略。

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