Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, L3 5QA, Liverpool, UK.
Malar J. 2021 Jan 7;20(1):24. doi: 10.1186/s12936-020-03546-5.
Advances in digitized video-tracking and behavioural analysis have enabled accurate recording and quantification of mosquito flight and host-seeking behaviours, facilitating development of individual (agent) based models at much finer spatial scales than previously possible.
Quantified behavioural parameters were used to create a novel virtual testing model, capable of accurately simulating indoor flight behaviour by a virtual population of host-seeking mosquitoes as they interact with and respond to simulated stimuli from a human-occupied bed net. The model is described, including base mosquito behaviour, state transitions, environmental representation and host stimulus representation.
In the absence of a bed net and human host bait, flight distribution of the model population was relatively uniform throughout the arena. Introducing an unbaited untreated bed net induced a change in distribution with an increase in landing events on the net surface, predominantly on the sides of the net. Adding the presence of a simulated human bait dramatically impacted flight distribution patterns, exploratory foraging and, the number and distribution of landing positions on the net, which were determined largely by the orientation of the human within. The model replicates experimental results with free-flying living mosquitoes at human-occupied bed nets, where contact occurs predominantly on the top surface of the net. This accuracy is important as it quantifies exposure to the lethal insecticide residues that may be unique to the net roof (or theoretically any other surface). Number of net contacts and height of contacts decreased with increasing attractant dispersal noise.
Results generated by the model are an accurate representation of actual mosquito behaviour recorded at and around a human-occupied bed net in untreated and insecticide-treated nets. This fine-grained model is highly flexible and has significant potential for in silico screening of novel bed net designs, potentially reducing time and cost and accelerating the deployment of new and more effective tools for protecting against malaria in sub-Saharan Africa.
数字化视频跟踪和行为分析的进步使准确记录和量化蚊子的飞行和寻找宿主行为成为可能，这使得在比以往更精细的空间尺度上开发基于个体（剂）的模型成为可能。
量化的行为参数被用于创建一个新的虚拟测试模型，该模型能够通过虚拟的寻找宿主的蚊子群体准确模拟室内飞行行为，这些蚊子与模拟的人类占据的蚊帐中的刺激相互作用并做出反应。该模型的描述包括基础蚊子行为、状态转换、环境表示和宿主刺激表示。
在没有蚊帐和人类宿主诱饵的情况下，模型种群的飞行分布在整个竞技场中相对均匀。引入一个未诱饵处理的蚊帐会导致分布发生变化，增加在网表面上的着陆事件，主要是在网的侧面。添加模拟人类诱饵的存在会极大地影响飞行分布模式、探索性觅食以及网的着陆位置的数量和分布，这些主要由人类在网内的方向决定。该模型复制了在有人居住的蚊帐中自由飞行的活体蚊子的实验结果，在这些实验中接触主要发生在网的顶部表面。这种准确性很重要，因为它量化了接触到可能是网顶特有的（或者理论上任何其他表面）致死杀虫剂残留的情况。网接触次数和接触高度随着引诱剂扩散噪声的增加而减少。
模型生成的结果准确地反映了在未经处理和经过杀虫剂处理的蚊帐中以及在有人居住的蚊帐周围实际蚊子行为的记录。这种细粒度的模型具有很高的灵活性，对于新型蚊帐设计的计算机筛选具有重要潜力，可能会减少时间和成本，并加速在撒哈拉以南非洲地区部署新的、更有效的疟疾防护工具。
