Characterising the intensity of insecticide resistance: A novel framework for analysis of intensity bioassay data

IF 1.7 Q3 PARASITOLOGY
Mara D. Kont , Ben Lambert , Antoine Sanou , Jessica Williams , Hilary Ranson , Geraldine M. Foster , Rosemary S. Lees , Thomas S. Churcher
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Abstract

Insecticide resistance is a growing problem that risks harming the progress made by vector control tools in reducing the malaria burden globally. New methods for quantifying the extent of resistance in wild populations are urgently needed to guide deployment of interventions to improve disease control. Intensity bioassays measure mosquito mortality at a range of insecticide doses and characterise phenotypic resistance in regions where resistance is already detected. These data are increasingly being collected but tend to exhibit high measurement error and there is a lack of formal guidelines on how they should be analysed or compared. This paper introduces a novel Bayesian framework for analysing intensity bioassay data, which uses a flexible statistical model able to capture a wide variety of relationships between mortality and insecticide dose. By accounting for background mortality of mosquitoes, our approach minimises the impact of this source of measurement noise resulting in more precise quantification of resistance. It outputs a range of metrics for describing the intensity and variability in resistance within the sample and quantifies the level of measurement error in the assay. The functionality is illustrated with data from laboratory-reared mosquitoes to show how the lethal dose varies within and between different strains. The framework can also be used to formally test hypotheses by explicitly considering the high heterogeneity seen in these types of data in field samples. Here we show that the intensity of resistance (as measured by the median lethal dose (LC50) of insecticide) increases over 7 years in mosquitoes from one village in Burkina Faso but remains constant in another. This work showcases the benefits of statistically rigorous analysis of insecticide bioassay data and highlights the additional information available from this and other dose-response data.

Abstract Image

表征杀虫剂抗性强度:强度生物测定数据分析的新框架
杀虫剂耐药性是一个日益严重的问题,有可能损害病媒控制工具在全球减轻疟疾负担方面取得的进展。迫切需要量化野生种群耐药性程度的新方法来指导干预措施的部署,以改善疾病控制。强度生物测定法测量一系列杀虫剂剂量下蚊子的死亡率,并表征已经检测到耐药性的地区的表型耐药性。这些数据越来越多地被收集,但往往表现出很高的测量误差,并且缺乏关于如何分析或比较这些数据的正式指南。本文介绍了一种用于分析强度生物测定数据的新贝叶斯框架,该框架使用了一个灵活的统计模型,能够捕捉死亡率和杀虫剂剂量之间的各种关系。通过考虑蚊子的背景死亡率,我们的方法将这种测量噪声源的影响降至最低,从而实现更精确的耐药性量化。它输出一系列指标,用于描述样本中耐药性的强度和可变性,并量化分析中的测量误差水平。该功能通过实验室饲养的蚊子的数据进行了说明,以显示不同菌株内和不同菌株之间的致死剂量是如何变化的。该框架还可用于通过明确考虑现场样本中这些类型数据的高度异质性来正式检验假设。在这里,我们发现布基纳法索一个村庄的蚊子的抵抗强度(以杀虫剂的中位致死剂量(LC50)衡量)在7年内增加,但在另一个村庄保持不变。这项工作展示了对杀虫剂生物测定数据进行严格统计分析的好处,并强调了从这一数据和其他剂量反应数据中获得的额外信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.60
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0.00%
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