Department of Environmental Health & Ecological Sciences, Ifakara Health Institute, Ifakara, Tanzania.
Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK.
Parasit Vectors. 2022 Aug 17;15(1):293. doi: 10.1186/s13071-022-05403-7.
Improved methods for sampling outdoor-biting mosquitoes are urgently needed to improve surveillance of vector-borne diseases. Such tools could potentially replace the human landing catch (HLC), which, despite being the most direct option for measuring human exposures, raises significant ethical and logistical concerns. Several alternatives are under development, but detailed evaluation still requires common frameworks for calibration relative to HLC. The aim of this study was to develop and validate a statistical framework for predicting human-biting rates from different exposure-free alternatives.
We obtained mosquito abundance data (Anopheles arabiensis, Anopheles funestus and Culex spp.) from a year-long Tanzanian study comparing six outdoor traps [Suna Trap (SUN), BG Sentinel (BGS), M-Trap (MTR), M-Trap + CDC (MTRC), Ifakara Tent Trap-C (ITT-C) and Mosquito Magnet-X Trap (MMX)] and HLC. Generalised linear models were developed within a Bayesian framework to investigate associations between the traps and HLC, taking intra- and inter-specific density dependence into account. The best model was used to create a calibration tool for predicting HLC-equivalents.
For An. arabiensis, SUN catches had the strongest correlation with HLC (R = 19.4), followed by BGS (R = 17.2) and MTRC (R = 13.1) catches. The least correlated catch was MMX (R = 2.5). For An. funestus, BGS had the strongest correlation with the HLC (R = 53.4), followed by MTRC (R = 37.4) and MTR (R = 37.4). For Culex mosquitoes, the traps most highly correlated with the HLC were MTR (R = 45.4) and MTRC (R = 44.2). Density dependence, both between and within species, influenced the performance of only BGS traps. An interactive Shiny App calibration tool was developed for this and similar applications.
We successfully developed a calibration tool to assess the performance of different traps for assessing outdoor-biting risk, and established a valuable framework for estimating human exposures based on the trap catches. The performance of candidate traps varied between mosquito taxa; thus, there was no single optimum. Although all the traps tested underestimated the HLC-derived exposures, it was possible to mathematically define their representativeness of the true biting risk, with or without density dependence. The results of this study emphasise the need to aim for a consistent and representative sampling approach, as opposed to simply seeking traps that catch the most mosquitoes.
为了改善对媒介传播疾病的监测，迫切需要改进户外叮咬蚊子的采样方法。此类工具可能替代人体捕获法（HLC），尽管这是测量人类接触的最直接选择，但存在重大的伦理和后勤问题。目前正在开发几种替代方法，但详细评估仍需要相对于 HLC 进行校准的通用框架。本研究旨在开发和验证一种从不同无接触暴露替代方法预测人类叮咬率的统计框架。
我们从坦桑尼亚进行的一项为期一年的研究中获得了蚊子丰度数据（按蚊属阿拉伯亚种、按蚊属冈比亚亚种和库蚊属），该研究比较了六种户外诱捕器[Suna 诱捕器（SUN）、BG 哨兵诱捕器（BGS）、M-诱捕器（MTR）、M-诱捕器+CDC 诱捕器（MTRC）、Ifakara 帐篷诱捕器-C（ITT-C）和 Mosquito Magnet-X 诱捕器（MMX）]和 HLC。在贝叶斯框架内开发了广义线性模型，以研究诱捕器与 HLC 之间的关联，同时考虑了种内和种间密度依赖性。使用最佳模型创建了一个校准工具，用于预测 HLC 等效值。
对于按蚊属阿拉伯亚种，SUN 的捕获量与 HLC 的相关性最强（R=19.4），其次是 BGS（R=17.2）和 MTRC（R=13.1）的捕获量。相关性最低的捕获量是 MMX（R=2.5）。对于按蚊属冈比亚亚种，BGS 与 HLC 的相关性最强（R=53.4），其次是 MTRC（R=37.4）和 MTR（R=37.4）。对于库蚊属，与 HLC 相关性最高的诱捕器是 MTR（R=45.4）和 MTRC（R=44.2）。种内和种间的密度依赖性仅影响 BGS 诱捕器的性能。为此和类似应用开发了一个交互式闪亮应用程序校准工具。
我们成功开发了一种校准工具，用于评估不同诱捕器评估户外叮咬风险的性能，并建立了一个基于诱捕器捕获量估计人类暴露的有价值框架。候选诱捕器的性能因蚊子分类群而异；因此，没有单一的最佳选择。尽管所有测试的诱捕器都低估了 HLC 衍生的暴露量，但可以通过数学方法定义它们与真实叮咬风险的代表性，无论是否存在密度依赖性。本研究的结果强调了需要采用一致和有代表性的采样方法，而不是仅仅寻求捕获最多蚊子的诱捕器。
