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推断斯里兰卡科伦坡地区伊蚊的遗传参数,确定登革热感染风险。

Determining dengue infection risk in the Colombo district of Sri Lanka by inferencing the genetic parameters of Aedes mosquitoes.

机构信息

Research & Development Centre for Mathematical Modeling, Department of Mathematics, Faculty of Science, University of Colombo, 00030, Colombo, Sri Lanka.

International Center for the Advancement of Research and Education (I·CARE), Texas Biomedical Research Institute, San Antonio, 78227, TX, USA.

出版信息

BMC Infect Dis. 2024 Sep 9;24(1):944. doi: 10.1186/s12879-024-09878-w.

Abstract

BACKGROUND

For decades, dengue has posed a significant threat as a viral infectious disease, affecting numerous human lives globally, particularly in tropical regions, yet no cure has been discovered. The genetic trait of vector competence in Aedes mosquitoes, which facilitates dengue transmission, is difficult to measure and highly sensitive to environmental changes.

METHODS

In this study we attempt, for the first time in a non-laboratory setting, to quantify the vector competence of Aedes mosquitoes assuming its homogeneity across both species; aegypti and albopictus and across the four Dengue serotypes. Estimating vector competence in relation to varying rainfall patterns was focused in this study to showcase the changes in this vector trait with respect to environmental variables. We quantify it using an existing mathematical model originally developed for malaria in a Bayesian inferencing setup. We conducted this study in the Colombo district of Sri Lanka where the highest number of human populations are threatened with dengue. Colombo district experiences continuous favorable temperature and humidity levels throughout the year creating ideal conditions for Aedes mosquitoes to thrive and transmit the Dengue disease. Therefore we only used the highly variable and seasonal rainfall as the primary environmental variable as it significantly influences the number of breeding sites and thereby impacting the population dynamics of Aedes.

RESULTS

Our research successfully deduced vector competence values for the four identified seasons based on Monsoon rainfalls experienced in Colombo within a year. We used dengue data from 2009 - 2022 to infer the estimates. These estimated values have been corroborated through experimental studies documented in the literature, thereby validating the malaria model to estimate vector competence for dengue disease.

CONCLUSION

Our research findings conclude that environmental conditions can amplify vector competence within specific seasons, categorized by their environmental attributes. Additionally, the deduced vector competence offers compelling evidence that it impacts disease transmission, irrespective of geographical location, climate, or environmental factors.

摘要

背景

几十年来,登革热一直是一种严重的病毒性传染病,对全球许多人的生命构成威胁,尤其是在热带地区,但目前仍未找到治愈方法。登革热传播的载体能力的遗传特征在埃及伊蚊中很难衡量,而且对环境变化高度敏感。

方法

本研究首次在非实验室环境中尝试量化登革热病毒载体能力,假设其在两种物种(埃及伊蚊和白纹伊蚊)和四种登革热血清型中具有均一性。本研究集中研究与不同降雨模式相关的载体能力,以展示该载体特性随环境变量的变化。我们使用一个现有的数学模型来量化它,该模型最初是为疟疾在贝叶斯推理设置中开发的。我们在斯里兰卡的科伦坡地区进行了这项研究,那里的人口最多受到登革热的威胁。科伦坡地区全年持续保持有利的温度和湿度水平,为埃及伊蚊的繁殖和传播登革热疾病创造了理想的条件。因此,我们仅将高度变化和季节性降雨作为主要环境变量,因为它显著影响繁殖地的数量,从而影响埃及伊蚊的种群动态。

结果

我们的研究成功地根据科伦坡一年中经历的季风降雨,推导出了四个确定季节的载体能力值。我们使用了 2009 年至 2022 年的登革热数据来推断估计值。这些估计值通过文献中记录的实验研究得到了证实,从而验证了疟疾模型来估计登革热疾病的载体能力。

结论

我们的研究结果表明,环境条件可以在特定季节放大载体能力,这些季节根据其环境属性进行分类。此外,推断出的载体能力提供了令人信服的证据,表明它会影响疾病的传播,而不论地理位置、气候或环境因素如何。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/98e4/11385510/a97b23cff7d9/12879_2024_9878_Fig1_HTML.jpg

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