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西尼罗河病毒在四个欧洲国家的生态:库蚊丰度动态与天气关系的实证模型。

Ecology of West Nile virus across four European countries: empirical modelling of the Culex pipiens abundance dynamics as a function of weather.

机构信息

University of Twente, Faculty of Geo-Information Science and Earth Observation, PO, Box 217 7500 AE, Enschede, the Netherlands.

EID Mediterranee, 165 Avenue Paul Rimbaud, 34184, Montpellier, France.

出版信息

Parasit Vectors. 2017 Oct 26;10(1):524. doi: 10.1186/s13071-017-2484-y.

Abstract

BACKGROUND

Culex pipiens is the major vector of West Nile virus in Europe, and is causing frequent outbreaks throughout the southern part of the continent. Proper empirical modelling of the population dynamics of this species can help in understanding West Nile virus epidemiology, optimizing vector surveillance and mosquito control efforts. But modelling results may differ from place to place. In this study we look at which type of models and weather variables can be consistently used across different locations.

METHODS

Weekly mosquito trap collections from eight functional units located in France, Greece, Italy and Serbia for several years were combined. Additionally, rainfall, relative humidity and temperature were recorded. Correlations between lagged weather conditions and Cx. pipiens dynamics were analysed. Also seasonal autoregressive integrated moving-average (SARIMA) models were fitted to describe the temporal dynamics of Cx. pipiens and to check whether the weather variables could improve these models.

RESULTS

Correlations were strongest between mean temperatures at short time lags, followed by relative humidity, most likely due to collinearity. Precipitation alone had weak correlations and inconsistent patterns across sites. SARIMA models could also make reasonable predictions, especially when longer time series of Cx. pipiens observations are available.

CONCLUSIONS

Average temperature was a consistently good predictor across sites. When only short time series (~ < 4 years) of observations are available, average temperature can therefore be used to model Cx. pipiens dynamics. When longer time series (~ > 4 years) are available, SARIMAs can provide better statistical descriptions of Cx. pipiens dynamics, without the need for further weather variables. This suggests that density dependence is also an important determinant of Cx. pipiens dynamics.

摘要

背景

库蚊是欧洲西尼罗河病毒的主要传播媒介,在该大陆南部地区频繁引发疫情。对该物种种群动态进行适当的经验建模有助于了解西尼罗河病毒的流行病学,优化媒介监测和蚊虫控制工作。但建模结果可能因地点而异。在这项研究中,我们研究了哪些类型的模型和气象变量可以在不同地点一致使用。

方法

将来自法国、希腊、意大利和塞尔维亚的 8 个功能单元的每周蚊虫诱捕器收集数据进行了组合,这些数据已连续收集多年。此外,还记录了降雨量、相对湿度和温度。分析了滞后气象条件与库蚊动态之间的相关性。还拟合了季节性自回归综合移动平均(SARIMA)模型,以描述库蚊的时间动态,并检查气象变量是否可以改进这些模型。

结果

在短时间滞后下,平均温度之间的相关性最强,其次是相对湿度,这很可能是由于共线性。降水单独的相关性较弱,且在不同地点的模式不一致。SARIMA 模型也可以做出合理的预测,尤其是在库蚊观测的时间序列较长时。

结论

平均温度是跨站点的一致良好预测因子。当只有较短的观测时间序列(约<4 年)可用时,平均温度可用于模拟库蚊的动态。当可用的时间序列较长(>4 年)时,SARIMAs 可以提供更好的库蚊动态统计描述,而无需其他气象变量。这表明密度依赖性也是库蚊动态的重要决定因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9508/5657042/dd9153a962e5/13071_2017_2484_Fig1_HTML.jpg

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