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模拟人类流动性、土地利用和气候因素对斯里兰卡登革热疫情爆发的相对作用。

Modeling the relative role of human mobility, land-use and climate factors on dengue outbreak emergence in Sri Lanka.

作者信息

Zhang Ying, Riera Jefferson, Ostrow Kayla, Siddiqui Sauleh, de Silva Harendra, Sarkar Sahotra, Fernando Lakkumar, Gardner Lauren

机构信息

Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA.

出版信息

BMC Infect Dis. 2020 Sep 3;20(1):649. doi: 10.1186/s12879-020-05369-w.

Abstract

BACKGROUND

More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission.

METHODS

We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1 km × 1 km spatial resolution and a weekly temporal resolution.

RESULTS

Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions.

CONCLUSIONS

Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.

摘要

背景

2016年至2017年不到7个月的时间里,全国报告了8万多例登革热病例,其中包括215例死亡,与2010 - 2016年的平均报告病例数相比,报告病例数增加了四倍。位于西部省份的尼甘布地区是该国登革热病例数最多的地区,也是我们研究的重点区域,我们旨在捕捉登革热传播的时空动态。

方法

我们提出了一个统计建模框架,以评估2016 - 2017年斯里兰卡尼甘布地区登革热疫情的时空动态,该动态是人类流动、土地利用和气候模式的函数。分析以1公里×1公里的空间分辨率和每周的时间分辨率进行。

结果

我们的结果表明,与土地利用或气候变量相比,人类流动是本地疫情聚集的更强指标。最低日气温被确定为该地区登革热病例最具影响力的气候变量;在所考虑的土地利用模式中,城市地区被发现最容易发生登革热疫情,其次是积水地区,然后是沿海地区。结果表明在不同空间分辨率下都具有稳健性。

结论

我们的研究强调了利用出行数据在区域内进行病媒控制的潜在价值。除了说明登革热疫情各种潜在风险因素之间的相对关系外,我们的研究结果还可用于告知一个区域内登革热新病例可能在何时何地发生,从而有助于更有效和创新地规划疾病监测和病媒控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6853/7469426/e43b46858d21/12879_2020_5369_Fig1_HTML.jpg

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